importance of technology in education research paper

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• Published: 12 February 2024

Education reform and change driven by digital technology: a bibliometric study from a global perspective

• Chengliang Wang 1 ,
• Xiaojiao Chen 1 ,
• Teng Yu   ORCID: orcid.org/0000-0001-5198-7261 2 , 3 ,
• Yidan Liu 1 , 4 &
• Yuhui Jing 1  

Humanities and Social Sciences Communications volume  11 , Article number:  256 ( 2024 ) Cite this article

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• Development studies
• Science, technology and society

Amidst the global digital transformation of educational institutions, digital technology has emerged as a significant area of interest among scholars. Such technologies have played an instrumental role in enhancing learner performance and improving the effectiveness of teaching and learning. These digital technologies also ensure the sustainability and stability of education during the epidemic. Despite this, a dearth of systematic reviews exists regarding the current state of digital technology application in education. To address this gap, this study utilized the Web of Science Core Collection as a data source (specifically selecting the high-quality SSCI and SCIE) and implemented a topic search by setting keywords, yielding 1849 initial publications. Furthermore, following the PRISMA guidelines, we refined the selection to 588 high-quality articles. Using software tools such as CiteSpace, VOSviewer, and Charticulator, we reviewed these 588 publications to identify core authors (such as Selwyn, Henderson, Edwards), highly productive countries/regions (England, Australia, USA), key institutions (Monash University, Australian Catholic University), and crucial journals in the field ( Education and Information Technologies , Computers & Education , British Journal of Educational Technology ). Evolutionary analysis reveals four developmental periods in the research field of digital technology education application: the embryonic period, the preliminary development period, the key exploration, and the acceleration period of change. The study highlights the dual influence of technological factors and historical context on the research topic. Technology is a key factor in enabling education to transform and upgrade, and the context of the times is an important driving force in promoting the adoption of new technologies in the education system and the transformation and upgrading of education. Additionally, the study identifies three frontier hotspots in the field: physical education, digital transformation, and professional development under the promotion of digital technology. This study presents a clear framework for digital technology application in education, which can serve as a valuable reference for researchers and educational practitioners concerned with digital technology education application in theory and practice.

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Introduction.

Digital technology has become an essential component of modern education, facilitating the extension of temporal and spatial boundaries and enriching the pedagogical contexts (Selwyn and Facer, 2014 ). The advent of mobile communication technology has enabled learning through social media platforms (Szeto et al. 2015 ; Pires et al. 2022 ), while the advancement of augmented reality technology has disrupted traditional conceptions of learning environments and spaces (Perez-Sanagustin et al., 2014 ; Kyza and Georgiou, 2018 ). A wide range of digital technologies has enabled learning to become a norm in various settings, including the workplace (Sjöberg and Holmgren, 2021 ), home (Nazare et al. 2022 ), and online communities (Tang and Lam, 2014 ). Education is no longer limited to fixed locations and schedules, but has permeated all aspects of life, allowing learning to continue at any time and any place (Camilleri and Camilleri, 2016 ; Selwyn and Facer, 2014 ).

The advent of digital technology has led to the creation of several informal learning environments (Greenhow and Lewin, 2015 ) that exhibit divergent form, function, features, and patterns in comparison to conventional learning environments (Nygren et al. 2019 ). Consequently, the associated teaching and learning processes, as well as the strategies for the creation, dissemination, and acquisition of learning resources, have undergone a complete overhaul. The ensuing transformations have posed a myriad of novel issues, such as the optimal structuring of teaching methods by instructors and the adoption of appropriate learning strategies by students in the new digital technology environment. Consequently, an examination of the principles that underpin effective teaching and learning in this environment is a topic of significant interest to numerous scholars engaged in digital technology education research.

Over the course of the last two decades, digital technology has made significant strides in the field of education, notably in extending education time and space and creating novel educational contexts with sustainability. Despite research attempts to consolidate the application of digital technology in education, previous studies have only focused on specific aspects of digital technology, such as Pinto and Leite’s ( 2020 ) investigation into digital technology in higher education and Mustapha et al.’s ( 2021 ) examination of the role and value of digital technology in education during the pandemic. While these studies have provided valuable insights into the practical applications of digital technology in particular educational domains, they have not comprehensively explored the macro-mechanisms and internal logic of digital technology implementation in education. Additionally, these studies were conducted over a relatively brief period, making it challenging to gain a comprehensive understanding of the macro-dynamics and evolutionary process of digital technology in education. Some studies have provided an overview of digital education from an educational perspective but lack a precise understanding of technological advancement and change (Yang et al. 2022 ). Therefore, this study seeks to employ a systematic scientific approach to collate relevant research from 2000 to 2022, comprehend the internal logic and development trends of digital technology in education, and grasp the outstanding contribution of digital technology in promoting the sustainability of education in time and space. In summary, this study aims to address the following questions:

RQ1: Since the turn of the century, what is the productivity distribution of the field of digital technology education application research in terms of authorship, country/region, institutional and journal level?

RQ2: What is the development trend of research on the application of digital technology in education in the past two decades?

RQ3: What are the current frontiers of research on the application of digital technology in education?

Literature review

Although the term “digital technology” has become ubiquitous, a unified definition has yet to be agreed upon by scholars. Because the meaning of the word digital technology is closely related to the specific context. Within the educational research domain, Selwyn’s ( 2016 ) definition is widely favored by scholars (Pinto and Leite, 2020 ). Selwyn ( 2016 ) provides a comprehensive view of various concrete digital technologies and their applications in education through ten specific cases, such as immediate feedback in classes, orchestrating teaching, and community learning. Through these specific application scenarios, Selwyn ( 2016 ) argues that digital technology encompasses technologies associated with digital devices, including but not limited to tablets, smartphones, computers, and social media platforms (such as Facebook and YouTube). Furthermore, Further, the behavior of accessing the internet at any location through portable devices can be taken as an extension of the behavior of applying digital technology.

The evolving nature of digital technology has significant implications in the field of education. In the 1890s, the focus of digital technology in education was on comprehending the nuances of digital space, digital culture, and educational methodologies, with its connotations aligned more towards the idea of e-learning. The advent and subsequent widespread usage of mobile devices since the dawn of the new millennium have been instrumental in the rapid expansion of the concept of digital technology. Notably, mobile learning devices such as smartphones and tablets, along with social media platforms, have become integral components of digital technology (Conole and Alevizou, 2010 ; Batista et al. 2016 ). In recent times, the burgeoning application of AI technology in the education sector has played a vital role in enriching the digital technology lexicon (Banerjee et al. 2021 ). ChatGPT, for instance, is identified as a novel educational technology that has immense potential to revolutionize future education (Rospigliosi, 2023 ; Arif, Munaf and Ul-Haque, 2023 ).

Pinto and Leite ( 2020 ) conducted a comprehensive macroscopic survey of the use of digital technologies in the education sector and identified three distinct categories, namely technologies for assessment and feedback, mobile technologies, and Information Communication Technologies (ICT). This classification criterion is both macroscopic and highly condensed. In light of the established concept definitions of digital technology in the educational research literature, this study has adopted the characterizations of digital technology proposed by Selwyn ( 2016 ) and Pinto and Leite ( 2020 ) as crucial criteria for analysis and research inclusion. Specifically, this criterion encompasses several distinct types of digital technologies, including Information and Communication Technologies (ICT), Mobile tools, eXtended Reality (XR) Technologies, Assessment and Feedback systems, Learning Management Systems (LMS), Publish and Share tools, Collaborative systems, Social media, Interpersonal Communication tools, and Content Aggregation tools.

Methodology and materials

Research method: bibliometric.

The research on econometric properties has been present in various aspects of human production and life, yet systematic scientific theoretical guidance has been lacking, resulting in disorganization. In 1969, British scholar Pritchard ( 1969 ) proposed “bibliometrics,” which subsequently emerged as an independent discipline in scientific quantification research. Initially, Pritchard defined bibliometrics as “the application of mathematical and statistical methods to books and other media of communication,” however, the definition was not entirely rigorous. To remedy this, Hawkins ( 2001 ) expanded Pritchard’s definition to “the quantitative analysis of the bibliographic features of a body of literature.” De Bellis further clarified the objectives of bibliometrics, stating that it aims to analyze and identify patterns in literature, such as the most productive authors, institutions, countries, and journals in scientific disciplines, trends in literary production over time, and collaboration networks (De Bellis, 2009 ). According to Garfield ( 2006 ), bibliometric research enables the examination of the history and structure of a field, the flow of information within the field, the impact of journals, and the citation status of publications over a longer time scale. All of these definitions illustrate the unique role of bibliometrics as a research method for evaluating specific research fields.

This study uses CiteSpace, VOSviewer, and Charticulator to analyze data and create visualizations. Each of these three tools has its own strengths and can complement each other. CiteSpace and VOSviewer use set theory and probability theory to provide various visualization views in fields such as keywords, co-occurrence, and co-authors. They are easy to use and produce visually appealing graphics (Chen, 2006 ; van Eck and Waltman, 2009 ) and are currently the two most widely used bibliometric tools in the field of visualization (Pan et al. 2018 ). In this study, VOSviewer provided the data necessary for the Performance Analysis; Charticulator was then used to redraw using the tabular data exported from VOSviewer (for creating the chord diagram of country collaboration); this was to complement the mapping process, while CiteSpace was primarily utilized to generate keyword maps and conduct burst word analysis.

Data retrieval

This study selected documents from the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) in the Web of Science Core Collection as the data source, for the following reasons:

(1) The Web of Science Core Collection, as a high-quality digital literature resource database, has been widely accepted by many researchers and is currently considered the most suitable database for bibliometric analysis (Jing et al. 2023a ). Compared to other databases, Web of Science provides more comprehensive data information (Chen et al. 2022a ), and also provides data formats suitable for analysis using VOSviewer and CiteSpace (Gaviria-Marin et al. 2019 ).

(2) The application of digital technology in the field of education is an interdisciplinary research topic, involving technical knowledge literature belonging to the natural sciences and education-related literature belonging to the social sciences. Therefore, it is necessary to select Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) as the sources of research data, ensuring the comprehensiveness of data while ensuring the reliability and persuasiveness of bibliometric research (Hwang and Tsai, 2011 ; Wang et al. 2022 ).

After establishing the source of research data, it is necessary to determine a retrieval strategy (Jing et al. 2023b ). The choice of a retrieval strategy should consider a balance between the breadth and precision of the search formula. That is to say, it should encompass all the literature pertaining to the research topic while excluding irrelevant documents as much as possible. In light of this, this study has set a retrieval strategy informed by multiple related papers (Mustapha et al. 2021 ; Luo et al. 2021 ). The research by Mustapha et al. ( 2021 ) guided us in selecting keywords (“digital” AND “technolog*”) to target digital technology, while Luo et al. ( 2021 ) informed the selection of terms (such as “instruct*,” “teach*,” and “education”) to establish links with the field of education. Then, based on the current application of digital technology in the educational domain and the scope of selection criteria, we constructed the final retrieval strategy. Following the general patterns of past research (Jing et al. 2023a , 2023b ), we conducted a specific screening using the topic search (Topics, TS) function in Web of Science. For the specific criteria used in the screening for this study, please refer to Table 1 .

Literature screening

Literature acquired through keyword searches may contain ostensibly related yet actually unrelated works. Therefore, to ensure the close relevance of literature included in the analysis to the research topic, it is often necessary to perform a manual screening process to identify the final literature to be analyzed, subsequent to completing the initial literature search.

The manual screening process consists of two steps. Initially, irrelevant literature is weeded out based on the title and abstract, with two members of the research team involved in this phase. This stage lasted about one week, resulting in 1106 articles being retained. Subsequently, a comprehensive review of the full text is conducted to accurately identify the literature required for the study. To carry out the second phase of manual screening effectively and scientifically, and to minimize the potential for researcher bias, the research team established the inclusion criteria presented in Table 2 . Three members were engaged in this phase, which took approximately 2 weeks, culminating in the retention of 588 articles after meticulous screening. The entire screening process is depicted in Fig. 1 , adhering to the PRISMA guidelines (Page et al. 2021 ).

The process of obtaining and filtering the necessary literature data for research.

Data standardization

Nguyen and Hallinger ( 2020 ) pointed out that raw data extracted from scientific databases often contains multiple expressions of the same term, and not addressing these synonymous expressions could affect research results in bibliometric analysis. For instance, in the original data, the author list may include “Tsai, C. C.” and “Tsai, C.-C.”, while the keyword list may include “professional-development” and “professional development,” which often require merging. Therefore, before analyzing the selected literature, a data disambiguation process is necessary to standardize the data (Strotmann and Zhao, 2012 ; Van Eck and Waltman, 2019 ). This study adopted the data standardization process proposed by Taskin and Al ( 2019 ), mainly including the following standardization operations:

Firstly, the author and source fields in the data are corrected and standardized to differentiate authors with similar names.

Secondly, the study checks whether the journals to which the literature belongs have been renamed in the past over 20 years, so as to avoid the influence of periodical name change on the analysis results.

Finally, the keyword field is standardized by unifying parts of speech and singular/plural forms of keywords, which can help eliminate redundant entries in the knowledge graph.

Performance analysis (RQ1)

This section offers a thorough and detailed analysis of the state of research in the field of digital technology education. By utilizing descriptive statistics and visual maps, it provides a comprehensive overview of the development trends, authors, countries, institutions, and journal distribution within the field. The insights presented in this section are of great significance in advancing our understanding of the current state of research in this field and identifying areas for further investigation. The use of visual aids to display inter-country cooperation and the evolution of the field adds to the clarity and coherence of the analysis.

Time trend of the publications

To understand a research field, it is first necessary to understand the most basic quantitative information, among which the change in the number of publications per year best reflects the development trend of a research field. Figure 2 shows the distribution of publication dates.

Time trend of the publications on application of digital technology in education.

From the Fig. 2 , it can be seen that the development of this field over the past over 20 years can be roughly divided into three stages. The first stage was from 2000 to 2007, during which the number of publications was relatively low. Due to various factors such as technological maturity, the academic community did not pay widespread attention to the role of digital technology in expanding the scope of teaching and learning. The second stage was from 2008 to 2019, during which the overall number of publications showed an upward trend, and the development of the field entered an accelerated period, attracting more and more scholars’ attention. The third stage was from 2020 to 2022, during which the number of publications stabilized at around 100. During this period, the impact of the pandemic led to a large number of scholars focusing on the role of digital technology in education during the pandemic, and research on the application of digital technology in education became a core topic in social science research.

Analysis of authors

An analysis of the author’s publication volume provides information about the representative scholars and core research strengths of a research area. Table 3 presents information on the core authors in adaptive learning research, including name, publication number, and average number of citations per article (based on the analysis and statistics from VOSviewer).

Variations in research foci among scholars abound. Within the field of digital technology education application research over the past two decades, Neil Selwyn stands as the most productive author, having published 15 papers garnering a total of 1027 citations, resulting in an average of 68.47 citations per paper. As a Professor at the Faculty of Education at Monash University, Selwyn concentrates on exploring the application of digital technology in higher education contexts (Selwyn et al. 2021 ), as well as related products in higher education such as Coursera, edX, and Udacity MOOC platforms (Bulfin et al. 2014 ). Selwyn’s contributions to the educational sociology perspective include extensive research on the impact of digital technology on education, highlighting the spatiotemporal extension of educational processes and practices through technological means as the greatest value of educational technology (Selwyn, 2012 ; Selwyn and Facer, 2014 ). In addition, he provides a blueprint for the development of future schools in 2030 based on the present impact of digital technology on education (Selwyn et al. 2019 ). The second most productive author in this field, Henderson, also offers significant contributions to the understanding of the important value of digital technology in education, specifically in the higher education setting, with a focus on the impact of the pandemic (Henderson et al. 2015 ; Cohen et al. 2022 ). In contrast, Edwards’ research interests focus on early childhood education, particularly the application of digital technology in this context (Edwards, 2013 ; Bird and Edwards, 2015 ). Additionally, on the technical level, Edwards also mainly prefers digital game technology, because it is a digital technology that children are relatively easy to accept (Edwards, 2015 ).

Analysis of countries/regions and organization

The present study aimed to ascertain the leading countries in digital technology education application research by analyzing 75 countries related to 558 works of literature. Table 4 depicts the top ten countries that have contributed significantly to this field in terms of publication count (based on the analysis and statistics from VOSviewer). Our analysis of Table 4 data shows that England emerged as the most influential country/region, with 92 published papers and 2401 citations. Australia and the United States secured the second and third ranks, respectively, with 90 papers (2187 citations) and 70 papers (1331 citations) published. Geographically, most of the countries featured in the top ten publication volumes are situated in Australia, North America, and Europe, with China being the only exception. Notably, all these countries, except China, belong to the group of developed nations, suggesting that economic strength is a prerequisite for fostering research in the digital technology education application field.

This study presents a visual representation of the publication output and cooperation relationships among different countries in the field of digital technology education application research. Specifically, a chord diagram is employed to display the top 30 countries in terms of publication output, as depicted in Fig. 3 . The chord diagram is composed of nodes and chords, where the nodes are positioned as scattered points along the circumference, and the length of each node corresponds to the publication output, with longer lengths indicating higher publication output. The chords, on the other hand, represent the cooperation relationships between any two countries, and are weighted based on the degree of closeness of the cooperation, with wider chords indicating closer cooperation. Through the analysis of the cooperation relationships, the findings suggest that the main publishing countries in this field are engaged in cooperative relationships with each other, indicating a relatively high level of international academic exchange and research internationalization.

In the diagram, nodes are scattered along the circumference of a circle, with the length of each node representing the volume of publications. The weighted arcs connecting any two points on the circle are known as chords, representing the collaborative relationship between the two, with the width of the arc indicating the closeness of the collaboration.

Further analyzing Fig. 3 , we can extract more valuable information, enabling a deeper understanding of the connections between countries in the research field of digital technology in educational applications. It is evident that certain countries, such as the United States, China, and England, display thicker connections, indicating robust collaborative relationships in terms of productivity. These thicker lines signify substantial mutual contributions and shared objectives in certain sectors or fields, highlighting the interconnectedness and global integration in these areas. By delving deeper, we can also explore potential future collaboration opportunities through the chord diagram, identifying possible partners to propel research and development in this field. In essence, the chord diagram successfully encapsulates and conveys the multi-dimensionality of global productivity and cooperation, allowing for a comprehensive understanding of the intricate inter-country relationships and networks in a global context, providing valuable guidance and insights for future research and collaborations.

An in-depth examination of the publishing institutions is provided in Table 5 , showcasing the foremost 10 institutions ranked by their publication volume. Notably, Monash University and Australian Catholic University, situated in Australia, have recorded the most prolific publications within the digital technology education application realm, with 22 and 10 publications respectively. Moreover, the University of Oslo from Norway is featured among the top 10 publishing institutions, with an impressive average citation count of 64 per publication. It is worth highlighting that six institutions based in the United Kingdom were also ranked within the top 10 publishing institutions, signifying their leading position in this area of research.

Analysis of journals

Journals are the main carriers for publishing high-quality papers. Some scholars point out that the two key factors to measure the influence of journals in the specified field are the number of articles published and the number of citations. The more papers published in a magazine and the more citations, the greater its influence (Dzikowski, 2018 ). Therefore, this study utilized VOSviewer to statistically analyze the top 10 journals with the most publications in the field of digital technology in education and calculated the average citations per article (see Table 6 ).

Based on Table 6 , it is apparent that the highest number of articles in the domain of digital technology in education research were published in Education and Information Technologies (47 articles), Computers & Education (34 articles), and British Journal of Educational Technology (32 articles), indicating a higher article output compared to other journals. This underscores the fact that these three journals concentrate more on the application of digital technology in education. Furthermore, several other journals, such as Technology Pedagogy and Education and Sustainability, have published more than 15 articles in this domain. Sustainability represents the open access movement, which has notably facilitated research progress in this field, indicating that the development of open access journals in recent years has had a significant impact. Although there is still considerable disagreement among scholars on the optimal approach to achieve open access, the notion that research outcomes should be accessible to all is widely recognized (Huang et al. 2020 ). On further analysis of the research fields to which these journals belong, except for Sustainability, it is evident that they all pertain to educational technology, thus providing a qualitative definition of the research area of digital technology education from the perspective of journals.

Temporal keyword analysis: thematic evolution (RQ2)

The evolution of research themes is a dynamic process, and previous studies have attempted to present the developmental trajectory of fields by drawing keyword networks in phases (Kumar et al. 2021 ; Chen et al. 2022b ). To understand the shifts in research topics across different periods, this study follows past research and, based on the significant changes in the research field and corresponding technological advancements during the outlined periods, divides the timeline into four stages (the first stage from January 2000 to December 2005, the second stage from January 2006 to December 2011, the third stage from January 2012 to December 2017; and the fourth stage from January 2018 to December 2022). The division into these four stages was determined through a combination of bibliometric analysis and literature review, which presented a clear trajectory of the field’s development. The research analyzes the keyword networks for each time period (as there are only three articles in the first stage, it was not possible to generate an appropriate keyword co-occurrence map, hence only the keyword co-occurrence maps from the second to the fourth stages are provided), to understand the evolutionary track of the digital technology education application research field over time.

2000.1–2005.12: germination period

From January 2000 to December 2005, digital technology education application research was in its infancy. Only three studies focused on digital technology, all of which were related to computers. Due to the popularity of computers, the home became a new learning environment, highlighting the important role of digital technology in expanding the scope of learning spaces (Sutherland et al. 2000 ). In specific disciplines and contexts, digital technology was first favored in medical clinical practice, becoming an important tool for supporting the learning of clinical knowledge and practice (Tegtmeyer et al. 2001 ; Durfee et al. 2003 ).

2006.1–2011.12: initial development period

Between January 2006 and December 2011, it was the initial development period of digital technology education research. Significant growth was observed in research related to digital technology, and discussions and theoretical analyses about “digital natives” emerged. During this phase, scholars focused on the debate about “how to use digital technology reasonably” and “whether current educational models and school curriculum design need to be adjusted on a large scale” (Bennett and Maton, 2010 ; Selwyn, 2009 ; Margaryan et al. 2011 ). These theoretical and speculative arguments provided a unique perspective on the impact of cognitive digital technology on education and teaching. As can be seen from the vocabulary such as “rethinking”, “disruptive pedagogy”, and “attitude” in Fig. 4 , many scholars joined the calm reflection and analysis under the trend of digital technology (Laurillard, 2008 ; Vratulis et al. 2011 ). During this phase, technology was still undergoing dramatic changes. The development of mobile technology had already caught the attention of many scholars (Wong et al. 2011 ), but digital technology represented by computers was still very active (Selwyn et al. 2011 ). The change in technological form would inevitably lead to educational transformation. Collins and Halverson ( 2010 ) summarized the prospects and challenges of using digital technology for learning and educational practices, believing that digital technology would bring a disruptive revolution to the education field and bring about a new educational system. In addition, the term “teacher education” in Fig. 4 reflects the impact of digital technology development on teachers. The rapid development of technology has widened the generation gap between teachers and students. To ensure smooth communication between teachers and students, teachers must keep up with the trend of technological development and establish a lifelong learning concept (Donnison, 2009 ).

In the diagram, each node represents a keyword, with the size of the node indicating the frequency of occurrence of the keyword. The connections represent the co-occurrence relationships between keywords, with a higher frequency of co-occurrence resulting in tighter connections.

2012.1–2017.12: critical exploration period

During the period spanning January 2012 to December 2017, the application of digital technology in education research underwent a significant exploration phase. As can be seen from Fig. 5 , different from the previous stage, the specific elements of specific digital technology have started to increase significantly, including the enrichment of technological contexts, the greater variety of research methods, and the diversification of learning modes. Moreover, the temporal and spatial dimensions of the learning environment were further de-emphasized, as noted in previous literature (Za et al. 2014 ). Given the rapidly accelerating pace of technological development, the education system in the digital era is in urgent need of collaborative evolution and reconstruction, as argued by Davis, Eickelmann, and Zaka ( 2013 ).

In the domain of digital technology, social media has garnered substantial scholarly attention as a promising avenue for learning, as noted by Pasquini and Evangelopoulos ( 2016 ). The implementation of social media in education presents several benefits, including the liberation of education from the restrictions of physical distance and time, as well as the erasure of conventional educational boundaries. The user-generated content (UGC) model in social media has emerged as a crucial source for knowledge creation and distribution, with the widespread adoption of mobile devices. Moreover, social networks have become an integral component of ubiquitous learning environments (Hwang et al. 2013 ). The utilization of social media allows individuals to function as both knowledge producers and recipients, which leads to a blurring of the conventional roles of learners and teachers. On mobile platforms, the roles of learners and teachers are not fixed, but instead interchangeable.

In terms of research methodology, the prevalence of empirical studies with survey designs in the field of educational technology during this period is evident from the vocabulary used, such as “achievement,” “acceptance,” “attitude,” and “ict.” in Fig. 5 . These studies aim to understand learners’ willingness to adopt and attitudes towards new technologies, and some seek to investigate the impact of digital technologies on learning outcomes through quasi-experimental designs (Domínguez et al. 2013 ). Among these empirical studies, mobile learning emerged as a hot topic, and this is not surprising. First, the advantages of mobile learning environments over traditional ones have been empirically demonstrated (Hwang et al. 2013 ). Second, learners born around the turn of the century have been heavily influenced by digital technologies and have developed their own learning styles that are more open to mobile devices as a means of learning. Consequently, analyzing mobile learning as a relatively novel mode of learning has become an important issue for scholars in the field of educational technology.

The intervention of technology has led to the emergence of several novel learning modes, with the blended learning model being the most representative one in the current phase. Blended learning, a novel concept introduced in the information age, emphasizes the integration of the benefits of traditional learning methods and online learning. This learning mode not only highlights the prominent role of teachers in guiding, inspiring, and monitoring the learning process but also underlines the importance of learners’ initiative, enthusiasm, and creativity in the learning process. Despite being an early conceptualization, blended learning’s meaning has been expanded by the widespread use of mobile technology and social media in education. The implementation of new technologies, particularly mobile devices, has resulted in the transformation of curriculum design and increased flexibility and autonomy in students’ learning processes (Trujillo Maza et al. 2016 ), rekindling scholarly attention to this learning mode. However, some scholars have raised concerns about the potential drawbacks of the blended learning model, such as its significant impact on the traditional teaching system, the lack of systematic coping strategies and relevant policies in several schools and regions (Moskal et al. 2013 ).

2018.1–2022.12: accelerated transformation period

The period spanning from January 2018 to December 2022 witnessed a rapid transformation in the application of digital technology in education research. The field of digital technology education research reached a peak period of publication, largely influenced by factors such as the COVID-19 pandemic (Yu et al. 2023 ). Research during this period was built upon the achievements, attitudes, and social media of the previous phase, and included more elements that reflect the characteristics of this research field, such as digital literacy, digital competence, and professional development, as depicted in Fig. 6 . Alongside this, scholars’ expectations for the value of digital technology have expanded, and the pursuit of improving learning efficiency and performance is no longer the sole focus. Some research now aims to cultivate learners’ motivation and enhance their self-efficacy by applying digital technology in a reasonable manner, as demonstrated by recent studies (Beardsley et al. 2021 ; Creely et al. 2021 ).

The COVID-19 pandemic has emerged as a crucial backdrop for the digital technology’s role in sustaining global education, as highlighted by recent scholarly research (Zhou et al. 2022 ; Pan and Zhang, 2020 ; Mo et al. 2022 ). The online learning environment, which is supported by digital technology, has become the primary battleground for global education (Yu, 2022 ). This social context has led to various studies being conducted, with some scholars positing that the pandemic has impacted the traditional teaching order while also expanding learning possibilities in terms of patterns and forms (Alabdulaziz, 2021 ). Furthermore, the pandemic has acted as a catalyst for teacher teaching and technological innovation, and this viewpoint has been empirically substantiated (Moorhouse and Wong, 2021 ). Additionally, some scholars believe that the pandemic’s push is a crucial driving force for the digital transformation of the education system, serving as an essential mechanism for overcoming the system’s inertia (Romero et al. 2021 ).

The rapid outbreak of the pandemic posed a challenge to the large-scale implementation of digital technologies, which was influenced by a complex interplay of subjective and objective factors. Objective constraints included the lack of infrastructure in some regions to support digital technologies, while subjective obstacles included psychological resistance among certain students and teachers (Moorhouse, 2021 ). These factors greatly impacted the progress of online learning during the pandemic. Additionally, Timotheou et al. ( 2023 ) conducted a comprehensive systematic review of existing research on digital technology use during the pandemic, highlighting the critical role played by various factors such as learners’ and teachers’ digital skills, teachers’ personal attributes and professional development, school leadership and management, and administration in facilitating the digitalization and transformation of schools.

The current stage of research is characterized by the pivotal term “digital literacy,” denoting a growing interest in learners’ attitudes and adoption of emerging technologies. Initially, the term “literacy” was restricted to fundamental abilities and knowledge associated with books and print materials (McMillan, 1996 ). However, with the swift advancement of computers and digital technology, there have been various attempts to broaden the scope of literacy beyond its traditional meaning, including game literacy (Buckingham and Burn, 2007 ), information literacy (Eisenberg, 2008 ), and media literacy (Turin and Friesem, 2020 ). Similarly, digital literacy has emerged as a crucial concept, and Gilster and Glister ( 1997 ) were the first to introduce this concept, referring to the proficiency in utilizing technology and processing digital information in academic, professional, and daily life settings. In practical educational settings, learners who possess higher digital literacy often exhibit an aptitude for quickly mastering digital devices and applying them intelligently to education and teaching (Yu, 2022 ).

The utilization of digital technology in education has undergone significant changes over the past two decades, and has been a crucial driver of educational reform with each new technological revolution. The impact of these changes on the underlying logic of digital technology education applications has been noticeable. From computer technology to more recent developments such as virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), the acceleration in digital technology development has been ongoing. Educational reforms spurred by digital technology development continue to be dynamic, as each new digital innovation presents new possibilities and models for teaching practice. This is especially relevant in the post-pandemic era, where the importance of technological progress in supporting teaching cannot be overstated (Mughal et al. 2022 ). Existing digital technologies have already greatly expanded the dimensions of education in both time and space, while future digital technologies aim to expand learners’ perceptions. Researchers have highlighted the potential of integrated technology and immersive technology in the development of the educational metaverse, which is highly anticipated to create a new dimension for the teaching and learning environment, foster a new value system for the discipline of educational technology, and more effectively and efficiently achieve the grand educational blueprint of the United Nations’ Sustainable Development Goals (Zhang et al. 2022 ; Li and Yu, 2023 ).

Hotspot evolution analysis (RQ3)

The examination of keyword evolution reveals a consistent trend in the advancement of digital technology education application research. The emergence and transformation of keywords serve as indicators of the varying research interests in this field. Thus, the utilization of the burst detection function available in CiteSpace allowed for the identification of the top 10 burst words that exhibited a high level of burst strength. This outcome is illustrated in Table 7 .

According to the results presented in Table 7 , the explosive terminology within the realm of digital technology education research has exhibited a concentration mainly between the years 2018 and 2022. Prior to this time frame, the emerging keywords were limited to “information technology” and “computer”. Notably, among them, computer, as an emergent keyword, has always had a high explosive intensity from 2008 to 2018, which reflects the important position of computer in digital technology and is the main carrier of many digital technologies such as Learning Management Systems (LMS) and Assessment and Feedback systems (Barlovits et al. 2022 ).

Since 2018, an increasing number of research studies have focused on evaluating the capabilities of learners to accept, apply, and comprehend digital technologies. As indicated by the use of terms such as “digital literacy” and “digital skill,” the assessment of learners’ digital literacy has become a critical task. Scholarly efforts have been directed towards the development of literacy assessment tools and the implementation of empirical assessments. Furthermore, enhancing the digital literacy of both learners and educators has garnered significant attention. (Nagle, 2018 ; Yu, 2022 ). Simultaneously, given the widespread use of various digital technologies in different formal and informal learning settings, promoting learners’ digital skills has become a crucial objective for contemporary schools (Nygren et al. 2019 ; Forde and OBrien, 2022 ).

Since 2020, the field of applied research on digital technology education has witnessed the emergence of three new hotspots, all of which have been affected to some extent by the pandemic. Firstly, digital technology has been widely applied in physical education, which is one of the subjects that has been severely affected by the pandemic (Parris et al. 2022 ; Jiang and Ning, 2022 ). Secondly, digital transformation has become an important measure for most schools, especially higher education institutions, to cope with the impact of the pandemic globally (García-Morales et al. 2021 ). Although the concept of digital transformation was proposed earlier, the COVID-19 pandemic has greatly accelerated this transformation process. Educational institutions must carefully redesign their educational products to face this new situation, providing timely digital learning methods, environments, tools, and support systems that have far-reaching impacts on modern society (Krishnamurthy, 2020 ; Salas-Pilco et al. 2022 ). Moreover, the professional development of teachers has become a key mission of educational institutions in the post-pandemic era. Teachers need to have a certain level of digital literacy and be familiar with the tools and online teaching resources used in online teaching, which has become a research hotspot today. Organizing digital skills training for teachers to cope with the application of emerging technologies in education is an important issue for teacher professional development and lifelong learning (Garzón-Artacho et al. 2021 ). As the main organizers and practitioners of emergency remote teaching (ERT) during the pandemic, teachers must put cognitive effort into their professional development to ensure effective implementation of ERT (Romero-Hall and Jaramillo Cherrez, 2022 ).

The burst word “digital transformation” reveals that we are in the midst of an ongoing digital technology revolution. With the emergence of innovative digital technologies such as ChatGPT and Microsoft 365 Copilot, technology trends will continue to evolve, albeit unpredictably. While the impact of these advancements on school education remains uncertain, it is anticipated that the widespread integration of technology will significantly affect the current education system. Rejecting emerging technologies without careful consideration is unwise. Like any revolution, the technological revolution in the education field has both positive and negative aspects. Detractors argue that digital technology disrupts learning and memory (Baron, 2021 ) or causes learners to become addicted and distracted from learning (Selwyn and Aagaard, 2020 ). On the other hand, the prudent use of digital technology in education offers a glimpse of a golden age of open learning. Educational leaders and practitioners have the opportunity to leverage cutting-edge digital technologies to address current educational challenges and develop a rational path for the sustainable and healthy growth of education.

Discussion on performance analysis (RQ1)

The field of digital technology education application research has experienced substantial growth since the turn of the century, a phenomenon that is quantifiably apparent through an analysis of authorship, country/region contributions, and institutional engagement. This expansion reflects the increased integration of digital technologies in educational settings and the heightened scholarly interest in understanding and optimizing their use.

Discussion on authorship productivity in digital technology education research

The authorship distribution within digital technology education research is indicative of the field’s intellectual structure and depth. A primary figure in this domain is Neil Selwyn, whose substantial citation rate underscores the profound impact of his work. His focus on the implications of digital technology in higher education and educational sociology has proven to be seminal. Selwyn’s research trajectory, especially the exploration of spatiotemporal extensions of education through technology, provides valuable insights into the multifaceted role of digital tools in learning processes (Selwyn et al. 2019 ).

Other notable contributors, like Henderson and Edwards, present diversified research interests, such as the impact of digital technologies during the pandemic and their application in early childhood education, respectively. Their varied focuses highlight the breadth of digital technology education research, encompassing pedagogical innovation, technological adaptation, and policy development.

Discussion on country/region-level productivity and collaboration

At the country/region level, the United Kingdom, specifically England, emerges as a leading contributor with 92 published papers and a significant citation count. This is closely followed by Australia and the United States, indicating a strong English-speaking research axis. Such geographical concentration of scholarly output often correlates with investment in research and development, technological infrastructure, and the prevalence of higher education institutions engaging in cutting-edge research.

China’s notable inclusion as the only non-Western country among the top contributors to the field suggests a growing research capacity and interest in digital technology in education. However, the lower average citation per paper for China could reflect emerging engagement or different research focuses that may not yet have achieved the same international recognition as Western counterparts.

The chord diagram analysis furthers this understanding, revealing dense interconnections between countries like the United States, China, and England, which indicates robust collaborations. Such collaborations are fundamental in addressing global educational challenges and shaping international research agendas.

Discussion on institutional-level contributions to digital technology education

Institutional productivity in digital technology education research reveals a constellation of universities driving the field forward. Monash University and the Australian Catholic University have the highest publication output, signaling Australia’s significant role in advancing digital education research. The University of Oslo’s remarkable average citation count per publication indicates influential research contributions, potentially reflecting high-quality studies that resonate with the broader academic community.

The strong showing of UK institutions, including the University of London, The Open University, and the University of Cambridge, reinforces the UK’s prominence in this research field. Such institutions are often at the forefront of pedagogical innovation, benefiting from established research cultures and funding mechanisms that support sustained inquiry into digital education.

Discussion on journal publication analysis

An examination of journal outputs offers a lens into the communicative channels of the field’s knowledge base. Journals such as Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology not only serve as the primary disseminators of research findings but also as indicators of research quality and relevance. The impact factor (IF) serves as a proxy for the quality and influence of these journals within the academic community.

The high citation counts for articles published in Computers & Education suggest that research disseminated through this medium has a wide-reaching impact and is of particular interest to the field. This is further evidenced by its significant IF of 11.182, indicating that the journal is a pivotal platform for seminal work in the application of digital technology in education.

The authorship, regional, and institutional productivity in the field of digital technology education application research collectively narrate the evolution of this domain since the turn of the century. The prominence of certain authors and countries underscores the importance of socioeconomic factors and existing academic infrastructure in fostering research productivity. Meanwhile, the centrality of specific journals as outlets for high-impact research emphasizes the role of academic publishing in shaping the research landscape.

As the field continues to grow, future research may benefit from leveraging the collaborative networks that have been elucidated through this analysis, perhaps focusing on underrepresented regions to broaden the scope and diversity of research. Furthermore, the stabilization of publication numbers in recent years invites a deeper exploration into potential plateaus in research trends or saturation in certain sub-fields, signaling an opportunity for novel inquiries and methodological innovations.

Discussion on the evolutionary trends (RQ2)

The evolution of the research field concerning the application of digital technology in education over the past two decades is a story of convergence, diversification, and transformation, shaped by rapid technological advancements and shifting educational paradigms.

At the turn of the century, the inception of digital technology in education was largely exploratory, with a focus on how emerging computer technologies could be harnessed to enhance traditional learning environments. Research from this early period was primarily descriptive, reflecting on the potential and challenges of incorporating digital tools into the educational setting. This phase was critical in establishing the fundamental discourse that would guide subsequent research, as it set the stage for understanding the scope and impact of digital technology in learning spaces (Wang et al. 2023 ).

As the first decade progressed, the narrative expanded to encompass the pedagogical implications of digital technologies. This was a period of conceptual debates, where terms like “digital natives” and “disruptive pedagogy” entered the academic lexicon, underscoring the growing acknowledgment of digital technology as a transformative force within education (Bennett and Maton, 2010 ). During this time, the research began to reflect a more nuanced understanding of the integration of technology, considering not only its potential to change where and how learning occurred but also its implications for educational equity and access.

In the second decade, with the maturation of internet connectivity and mobile technology, the focus of research shifted from theoretical speculations to empirical investigations. The proliferation of digital devices and the ubiquity of social media influenced how learners interacted with information and each other, prompting a surge in studies that sought to measure the impact of these tools on learning outcomes. The digital divide and issues related to digital literacy became central concerns, as scholars explored the varying capacities of students and educators to engage with technology effectively.

Throughout this period, there was an increasing emphasis on the individualization of learning experiences, facilitated by adaptive technologies that could cater to the unique needs and pacing of learners (Jing et al. 2023a ). This individualization was coupled with a growing recognition of the importance of collaborative learning, both online and offline, and the role of digital tools in supporting these processes. Blended learning models, which combined face-to-face instruction with online resources, emerged as a significant trend, advocating for a balance between traditional pedagogies and innovative digital strategies.

The later years, particularly marked by the COVID-19 pandemic, accelerated the necessity for digital technology in education, transforming it from a supplementary tool to an essential platform for delivering education globally (Mo et al. 2022 ; Mustapha et al. 2021 ). This era brought about an unprecedented focus on online learning environments, distance education, and virtual classrooms. Research became more granular, examining not just the pedagogical effectiveness of digital tools, but also their role in maintaining continuity of education during crises, their impact on teacher and student well-being, and their implications for the future of educational policy and infrastructure.

Across these two decades, the research field has seen a shift from examining digital technology as an external addition to the educational process, to viewing it as an integral component of curriculum design, instructional strategies, and even assessment methods. The emergent themes have broadened from a narrow focus on specific tools or platforms to include wider considerations such as data privacy, ethical use of technology, and the environmental impact of digital tools.

Moreover, the field has moved from considering the application of digital technology in education as a primarily cognitive endeavor to recognizing its role in facilitating socio-emotional learning, digital citizenship, and global competencies. Researchers have increasingly turned their attention to the ways in which technology can support collaborative skills, cultural understanding, and ethical reasoning within diverse student populations.

In summary, the past over twenty years in the research field of digital technology applications in education have been characterized by a progression from foundational inquiries to complex analyses of digital integration. This evolution has mirrored the trajectory of technology itself, from a facilitative tool to a pervasive ecosystem defining contemporary educational experiences. As we look to the future, the field is poised to delve into the implications of emerging technologies like AI, AR, and VR, and their potential to redefine the educational landscape even further. This ongoing metamorphosis suggests that the application of digital technology in education will continue to be a rich area of inquiry, demanding continual adaptation and forward-thinking from educators and researchers alike.

Discussion on the study of research hotspots (RQ3)

The analysis of keyword evolution in digital technology education application research elucidates the current frontiers in the field, reflecting a trajectory that is in tandem with the rapidly advancing digital age. This landscape is sculpted by emergent technological innovations and shaped by the demands of an increasingly digital society.

Interdisciplinary integration and pedagogical transformation

One of the frontiers identified from recent keyword bursts includes the integration of digital technology into diverse educational contexts, particularly noted with the keyword “physical education.” The digitalization of disciplines traditionally characterized by physical presence illustrates the pervasive reach of technology and signifies a push towards interdisciplinary integration where technology is not only a facilitator but also a transformative agent. This integration challenges educators to reconceptualize curriculum delivery to accommodate digital tools that can enhance or simulate the physical aspects of learning.

Digital literacy and skills acquisition

Another pivotal frontier is the focus on “digital literacy” and “digital skill”, which has intensified in recent years. This suggests a shift from mere access to technology towards a comprehensive understanding and utilization of digital tools. In this realm, the emphasis is not only on the ability to use technology but also on critical thinking, problem-solving, and the ethical use of digital resources (Yu, 2022 ). The acquisition of digital literacy is no longer an additive skill but a fundamental aspect of modern education, essential for navigating and contributing to the digital world.

Educational digital transformation

The keyword “digital transformation” marks a significant research frontier, emphasizing the systemic changes that education institutions must undergo to align with the digital era (Romero et al. 2021 ). This transformation includes the redesigning of learning environments, pedagogical strategies, and assessment methods to harness digital technology’s full potential. Research in this area explores the complexity of institutional change, addressing the infrastructural, cultural, and policy adjustments needed for a seamless digital transition.

Engagement and participation

Further exploration into “engagement” and “participation” underscores the importance of student-centered learning environments that are mediated by technology. The current frontiers examine how digital platforms can foster collaboration, inclusivity, and active learning, potentially leading to more meaningful and personalized educational experiences. Here, the use of technology seeks to support the emotional and cognitive aspects of learning, moving beyond the transactional view of education to one that is relational and interactive.

Professional development and teacher readiness

As the field evolves, “professional development” emerges as a crucial area, particularly in light of the pandemic which necessitated emergency remote teaching. The need for teacher readiness in a digital age is a pressing frontier, with research focusing on the competencies required for educators to effectively integrate technology into their teaching practices. This includes familiarity with digital tools, pedagogical innovation, and an ongoing commitment to personal and professional growth in the digital domain.

Pandemic as a catalyst

The recent pandemic has acted as a catalyst for accelerated research and application in this field, particularly in the domains of “digital transformation,” “professional development,” and “physical education.” This period has been a litmus test for the resilience and adaptability of educational systems to continue their operations in an emergency. Research has thus been directed at understanding how digital technologies can support not only continuity but also enhance the quality and reach of education in such contexts.

Ethical and societal considerations

The frontier of digital technology in education is also expanding to consider broader ethical and societal implications. This includes issues of digital equity, data privacy, and the sociocultural impact of technology on learning communities. The research explores how educational technology can be leveraged to address inequities and create more equitable learning opportunities for all students, regardless of their socioeconomic background.

Innovation and emerging technologies

Looking forward, the frontiers are set to be influenced by ongoing and future technological innovations, such as artificial intelligence (AI) (Wu and Yu, 2023 ; Chen et al. 2022a ). The exploration into how these technologies can be integrated into educational practices to create immersive and adaptive learning experiences represents a bold new chapter for the field.

In conclusion, the current frontiers of research on the application of digital technology in education are multifaceted and dynamic. They reflect an overarching movement towards deeper integration of technology in educational systems and pedagogical practices, where the goals are not only to facilitate learning but to redefine it. As these frontiers continue to expand and evolve, they will shape the educational landscape, requiring a concerted effort from researchers, educators, policymakers, and technologists to navigate the challenges and harness the opportunities presented by the digital revolution in education.

Conclusions and future research

Conclusions.

The utilization of digital technology in education is a research area that cuts across multiple technical and educational domains and continues to experience dynamic growth due to the continuous progress of technology. In this study, a systematic review of this field was conducted through bibliometric techniques to examine its development trajectory. The primary focus of the review was to investigate the leading contributors, productive national institutions, significant publications, and evolving development patterns. The study’s quantitative analysis resulted in several key conclusions that shed light on this research field’s current state and future prospects.

(1) The research field of digital technology education applications has entered a stage of rapid development, particularly in recent years due to the impact of the pandemic, resulting in a peak of publications. Within this field, several key authors (Selwyn, Henderson, Edwards, etc.) and countries/regions (England, Australia, USA, etc.) have emerged, who have made significant contributions. International exchanges in this field have become frequent, with a high degree of internationalization in academic research. Higher education institutions in the UK and Australia are the core productive forces in this field at the institutional level.

(2) Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology are notable journals that publish research related to digital technology education applications. These journals are affiliated with the research field of educational technology and provide effective communication platforms for sharing digital technology education applications.

(3) Over the past two decades, research on digital technology education applications has progressed from its early stages of budding, initial development, and critical exploration to accelerated transformation, and it is currently approaching maturity. Technological progress and changes in the times have been key driving forces for educational transformation and innovation, and both have played important roles in promoting the continuous development of education.

(4) Influenced by the pandemic, three emerging frontiers have emerged in current research on digital technology education applications, which are physical education, digital transformation, and professional development under the promotion of digital technology. These frontier research hotspots reflect the core issues that the education system faces when encountering new technologies. The evolution of research hotspots shows that technology breakthroughs in education’s original boundaries of time and space create new challenges. The continuous self-renewal of education is achieved by solving one hotspot problem after another.

The present study offers significant practical implications for scholars and practitioners in the field of digital technology education applications. Firstly, it presents a well-defined framework of the existing research in this area, serving as a comprehensive guide for new entrants to the field and shedding light on the developmental trajectory of this research domain. Secondly, the study identifies several contemporary research hotspots, thus offering a valuable decision-making resource for scholars aiming to explore potential research directions. Thirdly, the study undertakes an exhaustive analysis of published literature to identify core journals in the field of digital technology education applications, with Sustainability being identified as a promising open access journal that publishes extensively on this topic. This finding can potentially facilitate scholars in selecting appropriate journals for their research outputs.

Limitation and future research

Influenced by some objective factors, this study also has some limitations. First of all, the bibliometrics analysis software has high standards for data. In order to ensure the quality and integrity of the collected data, the research only selects the periodical papers in SCIE and SSCI indexes, which are the core collection of Web of Science database, and excludes other databases, conference papers, editorials and other publications, which may ignore some scientific research and original opinions in the field of digital technology education and application research. In addition, although this study used professional software to carry out bibliometric analysis and obtained more objective quantitative data, the analysis and interpretation of data will inevitably have a certain subjective color, and the influence of subjectivity on data analysis cannot be completely avoided. As such, future research endeavors will broaden the scope of literature screening and proactively engage scholars in the field to gain objective and state-of-the-art insights, while minimizing the adverse impact of personal subjectivity on research analysis.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/F9QMHY

Alabdulaziz MS (2021) COVID-19 and the use of digital technology in mathematics education. Educ Inf Technol 26(6):7609–7633. https://doi.org/10.1007/s10639-021-10602-3

Arif TB, Munaf U, Ul-Haque I (2023) The future of medical education and research: is ChatGPT a blessing or blight in disguise? Med Educ Online 28. https://doi.org/10.1080/10872981.2023.2181052

Banerjee M, Chiew D, Patel KT, Johns I, Chappell D, Linton N, Cole GD, Francis DP, Szram J, Ross J, Zaman S (2021) The impact of artificial intelligence on clinical education: perceptions of postgraduate trainee doctors in London (UK) and recommendations for trainers. BMC Med Educ 21. https://doi.org/10.1186/s12909-021-02870-x

Barlovits S, Caldeira A, Fesakis G, Jablonski S, Koutsomanoli Filippaki D, Lázaro C, Ludwig M, Mammana MF, Moura A, Oehler DXK, Recio T, Taranto E, Volika S(2022) Adaptive, synchronous, and mobile online education: developing the ASYMPTOTE learning environment. Mathematics 10:1628. https://doi.org/10.3390/math10101628

Article   Google Scholar  

Baron NS(2021) Know what? How digital technologies undermine learning and remembering J Pragmat 175:27–37. https://doi.org/10.1016/j.pragma.2021.01.011

Batista J, Morais NS, Ramos F (2016) Researching the use of communication technologies in higher education institutions in Portugal. https://doi.org/10.4018/978-1-5225-0571-6.ch057

Beardsley M, Albó L, Aragón P, Hernández-Leo D (2021) Emergency education effects on teacher abilities and motivation to use digital technologies. Br J Educ Technol 52. https://doi.org/10.1111/bjet.13101

Bennett S, Maton K(2010) Beyond the “digital natives” debate: towards a more nuanced understanding of students’ technology experiences J Comput Assist Learn 26:321–331. https://doi.org/10.1111/j.1365-2729.2010.00360.x

Buckingham D, Burn A (2007) Game literacy in theory and practice 16:323–349

Google Scholar  

Bulfin S, Pangrazio L, Selwyn N (2014) Making “MOOCs”: the construction of a new digital higher education within news media discourse. In: The International Review of Research in Open and Distributed Learning 15. https://doi.org/10.19173/irrodl.v15i5.1856

Camilleri MA, Camilleri AC(2016) Digital learning resources and ubiquitous technologies in education Technol Knowl Learn 22:65–82. https://doi.org/10.1007/s10758-016-9287-7

Chen C(2006) CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature J Am Soc Inf Sci Technol 57:359–377. https://doi.org/10.1002/asi.20317

Chen J, Dai J, Zhu K, Xu L(2022) Effects of extended reality on language learning: a meta-analysis Front Psychol 13:1016519. https://doi.org/10.3389/fpsyg.2022.1016519

Article   PubMed   PubMed Central   Google Scholar  

Chen J, Wang CL, Tang Y (2022b) Knowledge mapping of volunteer motivation: a bibliometric analysis and cross-cultural comparative study. Front Psychol 13. https://doi.org/10.3389/fpsyg.2022.883150

Cohen A, Soffer T, Henderson M(2022) Students’ use of technology and their perceptions of its usefulness in higher education: International comparison J Comput Assist Learn 38(5):1321–1331. https://doi.org/10.1111/jcal.12678

Collins A, Halverson R(2010) The second educational revolution: rethinking education in the age of technology J Comput Assist Learn 26:18–27. https://doi.org/10.1111/j.1365-2729.2009.00339.x

Conole G, Alevizou P (2010) A literature review of the use of Web 2.0 tools in higher education. Walton Hall, Milton Keynes, UK: the Open University, retrieved 17 February

Creely E, Henriksen D, Crawford R, Henderson M(2021) Exploring creative risk-taking and productive failure in classroom practice. A case study of the perceived self-efficacy and agency of teachers at one school Think Ski Creat 42:100951. https://doi.org/10.1016/j.tsc.2021.100951

Davis N, Eickelmann B, Zaka P(2013) Restructuring of educational systems in the digital age from a co-evolutionary perspective J Comput Assist Learn 29:438–450. https://doi.org/10.1111/jcal.12032

De Belli N (2009) Bibliometrics and citation analysis: from the science citation index to cybermetrics, Scarecrow Press. https://doi.org/10.1111/jcal.12032

Domínguez A, Saenz-de-Navarrete J, de-Marcos L, Fernández-Sanz L, Pagés C, Martínez-Herráiz JJ(2013) Gamifying learning experiences: practical implications and outcomes Comput Educ 63:380–392. https://doi.org/10.1016/j.compedu.2012.12.020

Donnison S (2009) Discourses in conflict: the relationship between Gen Y pre-service teachers, digital technologies and lifelong learning. Australasian J Educ Technol 25. https://doi.org/10.14742/ajet.1138

Durfee SM, Jain S, Shaffer K (2003) Incorporating electronic media into medical student education. Acad Radiol 10:205–210. https://doi.org/10.1016/s1076-6332(03)80046-6

Dzikowski P(2018) A bibliometric analysis of born global firms J Bus Res 85:281–294. https://doi.org/10.1016/j.jbusres.2017.12.054

van Eck NJ, Waltman L(2009) Software survey: VOSviewer, a computer program for bibliometric mapping Scientometrics 84:523–538 https://doi.org/10.1007/s11192-009-0146-3

Edwards S(2013) Digital play in the early years: a contextual response to the problem of integrating technologies and play-based pedagogies in the early childhood curriculum Eur Early Child Educ Res J 21:199–212. https://doi.org/10.1080/1350293x.2013.789190

Edwards S(2015) New concepts of play and the problem of technology, digital media and popular-culture integration with play-based learning in early childhood education Technol Pedagogy Educ 25:513–532 https://doi.org/10.1080/1475939x.2015.1108929

Article   MathSciNet   Google Scholar  

Eisenberg MB(2008) Information literacy: essential skills for the information age DESIDOC J Libr Inf Technol 28:39–47. https://doi.org/10.14429/djlit.28.2.166

Forde C, OBrien A (2022) A literature review of barriers and opportunities presented by digitally enhanced practical skill teaching and learning in health science education. Med Educ Online 27. https://doi.org/10.1080/10872981.2022.2068210

García-Morales VJ, Garrido-Moreno A, Martín-Rojas R (2021) The transformation of higher education after the COVID disruption: emerging challenges in an online learning scenario. Front Psychol 12. https://doi.org/10.3389/fpsyg.2021.616059

Garfield E(2006) The history and meaning of the journal impact factor JAMA 295:90. https://doi.org/10.1001/jama.295.1.90

Article   PubMed   Google Scholar  

Garzón-Artacho E, Sola-Martínez T, Romero-Rodríguez JM, Gómez-García G(2021) Teachers’ perceptions of digital competence at the lifelong learning stage Heliyon 7:e07513. https://doi.org/10.1016/j.heliyon.2021.e07513

Gaviria-Marin M, Merigó JM, Baier-Fuentes H(2019) Knowledge management: a global examination based on bibliometric analysis Technol Forecast Soc Change 140:194–220. https://doi.org/10.1016/j.techfore.2018.07.006

Gilster P, Glister P (1997) Digital literacy. Wiley Computer Pub, New York

Greenhow C, Lewin C(2015) Social media and education: reconceptualizing the boundaries of formal and informal learning Learn Media Technol 41:6–30. https://doi.org/10.1080/17439884.2015.1064954

Hawkins DT(2001) Bibliometrics of electronic journals in information science Infor Res 7(1):7–1. http://informationr.net/ir/7-1/paper120.html

Henderson M, Selwyn N, Finger G, Aston R(2015) Students’ everyday engagement with digital technology in university: exploring patterns of use and “usefulness J High Educ Policy Manag 37:308–319 https://doi.org/10.1080/1360080x.2015.1034424

Huang CK, Neylon C, Hosking R, Montgomery L, Wilson KS, Ozaygen A, Brookes-Kenworthy C (2020) Evaluating the impact of open access policies on research institutions. eLife 9. https://doi.org/10.7554/elife.57067

Hwang GJ, Tsai CC(2011) Research trends in mobile and ubiquitous learning: a review of publications in selected journals from 2001 to 2010 Br J Educ Technol 42:E65–E70. https://doi.org/10.1111/j.1467-8535.2011.01183.x

Hwang GJ, Wu PH, Zhuang YY, Huang YM(2013) Effects of the inquiry-based mobile learning model on the cognitive load and learning achievement of students Interact Learn Environ 21:338–354. https://doi.org/10.1080/10494820.2011.575789

Jiang S, Ning CF (2022) Interactive communication in the process of physical education: are social media contributing to the improvement of physical training performance. Universal Access Inf Soc, 1–10. https://doi.org/10.1007/s10209-022-00911-w

Jing Y, Zhao L, Zhu KK, Wang H, Wang CL, Xia Q(2023) Research landscape of adaptive learning in education: a bibliometric study on research publications from 2000 to 2022 Sustainability 15:3115–3115. https://doi.org/10.3390/su15043115

Jing Y, Wang CL, Chen Y, Wang H, Yu T, Shadiev R (2023b) Bibliometric mapping techniques in educational technology research: a systematic literature review. Educ Inf Technol 1–29. https://doi.org/10.1007/s10639-023-12178-6

Krishnamurthy S (2020) The future of business education: a commentary in the shadow of the Covid-19 pandemic. J Bus Res. https://doi.org/10.1016/j.jbusres.2020.05.034

Kumar S, Lim WM, Pandey N, Christopher Westland J (2021) 20 years of electronic commerce research. Electron Commer Res 21:1–40

Kyza EA, Georgiou Y(2018) Scaffolding augmented reality inquiry learning: the design and investigation of the TraceReaders location-based, augmented reality platform Interact Learn Environ 27:211–225. https://doi.org/10.1080/10494820.2018.1458039

Laurillard D(2008) Technology enhanced learning as a tool for pedagogical innovation J Philos Educ 42:521–533. https://doi.org/10.1111/j.1467-9752.2008.00658.x

Li M, Yu Z (2023) A systematic review on the metaverse-based blended English learning. Front Psychol 13. https://doi.org/10.3389/fpsyg.2022.1087508

Luo H, Li G, Feng Q, Yang Y, Zuo M (2021) Virtual reality in K-12 and higher education: a systematic review of the literature from 2000 to 2019. J Comput Assist Learn. https://doi.org/10.1111/jcal.12538

Margaryan A, Littlejohn A, Vojt G(2011) Are digital natives a myth or reality? University students’ use of digital technologies Comput Educ 56:429–440. https://doi.org/10.1016/j.compedu.2010.09.004

McMillan S(1996) Literacy and computer literacy: definitions and comparisons Comput Educ 27:161–170. https://doi.org/10.1016/s0360-1315(96)00026-7

Mo CY, Wang CL, Dai J, Jin P (2022) Video playback speed influence on learning effect from the perspective of personalized adaptive learning: a study based on cognitive load theory. Front Psychology 13. https://doi.org/10.3389/fpsyg.2022.839982

Moorhouse BL (2021) Beginning teaching during COVID-19: newly qualified Hong Kong teachers’ preparedness for online teaching. Educ Stud 1–17. https://doi.org/10.1080/03055698.2021.1964939

Moorhouse BL, Wong KM (2021) The COVID-19 Pandemic as a catalyst for teacher pedagogical and technological innovation and development: teachers’ perspectives. Asia Pac J Educ 1–16. https://doi.org/10.1080/02188791.2021.1988511

Moskal P, Dziuban C, Hartman J (2013) Blended learning: a dangerous idea? Internet High Educ 18:15–23

Mughal MY, Andleeb N, Khurram AFA, Ali MY, Aslam MS, Saleem MN (2022) Perceptions of teaching-learning force about Metaverse for education: a qualitative study. J. Positive School Psychol 6:1738–1745

Mustapha I, Thuy Van N, Shahverdi M, Qureshi MI, Khan N (2021) Effectiveness of digital technology in education during COVID-19 pandemic. a bibliometric analysis. Int J Interact Mob Technol 15:136

Nagle J (2018) Twitter, cyber-violence, and the need for a critical social media literacy in teacher education: a review of the literature. Teach Teach Education 76:86–94

Nazare J, Woolf A, Sysoev I, Ballinger S, Saveski M, Walker M, Roy D (2022) Technology-assisted coaching can increase engagement with learning technology at home and caregivers’ awareness of it. Comput Educ 188:104565

Nguyen UP, Hallinger P (2020) Assessing the distinctive contributions of simulation & gaming to the literature, 1970-2019: a bibliometric review. Simul Gaming 104687812094156. https://doi.org/10.1177/1046878120941569

Nygren H, Nissinen K, Hämäläinen R, Wever B(2019) Lifelong learning: formal, non-formal and informal learning in the context of the use of problem-solving skills in technology-rich environments Br J Educ Technol 50:1759–1770. https://doi.org/10.1111/bjet.12807

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Moher D (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg 88:105906

Pan SL, Zhang S(2020) From fighting COVID-19 pandemic to tackling sustainable development goals: an opportunity for responsible information systems research Int J Inf Manage 55:102196. https://doi.org/10.1016/j.ijinfomgt.2020.102196

Pan X, Yan E, Cui M, Hua W(2018) Examining the usage, citation, and diffusion patterns of bibliometric mapping software: a comparative study of three tools J Informetr 12:481–493. https://doi.org/10.1016/j.joi.2018.03.005

Parris Z, Cale L, Harris J, Casey A (2022) Physical activity for health, covid-19 and social media: what, where and why?. Movimento, 28. https://doi.org/10.22456/1982-8918.122533

Pasquini LA, Evangelopoulos N (2016) Sociotechnical stewardship in higher education: a field study of social media policy documents. J Comput High Educ 29:218–239

Pérez-Sanagustín M, Hernández-Leo D, Santos P, Delgado Kloos C, Blat J(2014) Augmenting reality and formality of informal and non-formal settings to enhance blended learning IEEE Trans Learn Technol 7:118–131. https://doi.org/10.1109/TLT.2014.2312719

Pinto M, Leite C (2020) Digital technologies in support of students learning in Higher Education: literature review. Digital Education Review 343–360. https://doi.org/10.1344/der.2020.37.343-360

Pires F, Masanet MJ, Tomasena JM, Scolari CA(2022) Learning with YouTube: beyond formal and informal through new actors, strategies and affordances Convergence 28(3):838–853. https://doi.org/10.1177/1354856521102054

Pritchard A (1969) Statistical bibliography or bibliometrics 25:348

Romero M, Romeu T, Guitert M, Baztán P (2021) Digital transformation in higher education: the UOC case. In ICERI2021 Proceedings (pp. 6695–6703). IATED https://doi.org/10.21125/iceri.2021.1512

Romero-Hall E, Jaramillo Cherrez N (2022) Teaching in times of disruption: faculty digital literacy in higher education during the COVID-19 pandemic. Innovations in Education and Teaching International 1–11. https://doi.org/10.1080/14703297.2022.2030782

Rospigliosi PA(2023) Artificial intelligence in teaching and learning: what questions should we ask of ChatGPT? Interactive Learning Environments 31:1–3. https://doi.org/10.1080/10494820.2023.2180191

Salas-Pilco SZ, Yang Y, Zhang Z(2022) Student engagement in online learning in Latin American higher education during the COVID-19 pandemic: a systematic review. Br J Educ Technol 53(3):593–619. https://doi.org/10.1111/bjet.13190

Selwyn N(2009) The digital native-myth and reality In Aslib proceedings 61(4):364–379. https://doi.org/10.1108/00012530910973776

Selwyn N(2012) Making sense of young people, education and digital technology: the role of sociological theory Oxford Review of Education 38:81–96. https://doi.org/10.1080/03054985.2011.577949

Selwyn N, Facer K(2014) The sociology of education and digital technology: past, present and future Oxford Rev Educ 40:482–496. https://doi.org/10.1080/03054985.2014.933005

Selwyn N, Banaji S, Hadjithoma-Garstka C, Clark W(2011) Providing a platform for parents? Exploring the nature of parental engagement with school Learning Platforms J Comput Assist Learn 27:314–323. https://doi.org/10.1111/j.1365-2729.2011.00428.x

Selwyn N, Aagaard J (2020) Banning mobile phones from classrooms-an opportunity to advance understandings of technology addiction, distraction and cyberbullying. Br J Educ Technol 52. https://doi.org/10.1111/bjet.12943

Selwyn N, O’Neill C, Smith G, Andrejevic M, Gu X (2021) A necessary evil? The rise of online exam proctoring in Australian universities. Media Int Austr 1329878X2110058. https://doi.org/10.1177/1329878x211005862

Selwyn N, Pangrazio L, Nemorin S, Perrotta C (2019) What might the school of 2030 be like? An exercise in social science fiction. Learn, Media Technol 1–17. https://doi.org/10.1080/17439884.2020.1694944

Selwyn, N (2016) What works and why?* Understanding successful technology enabled learning within institutional contexts 2016 Final report Appendices (Part B). Monash University Griffith University

Sjöberg D, Holmgren R (2021) Informal workplace learning in swedish police education-a teacher perspective. Vocations and Learning. https://doi.org/10.1007/s12186-021-09267-3

Strotmann A, Zhao D (2012) Author name disambiguation: what difference does it make in author-based citation analysis? J Am Soc Inf Sci Technol 63:1820–1833

Article   CAS   Google Scholar  

Sutherland R, Facer K, Furlong R, Furlong J(2000) A new environment for education? The computer in the home. Comput Educ 34:195–212. https://doi.org/10.1016/s0360-1315(99)00045-7

Szeto E, Cheng AY-N, Hong J-C(2015) Learning with social media: how do preservice teachers integrate YouTube and Social Media in teaching? Asia-Pac Educ Res 25:35–44. https://doi.org/10.1007/s40299-015-0230-9

Tang E, Lam C(2014) Building an effective online learning community (OLC) in blog-based teaching portfolios Int High Educ 20:79–85. https://doi.org/10.1016/j.iheduc.2012.12.002

Taskin Z, Al U(2019) Natural language processing applications in library and information science Online Inf Rev 43:676–690. https://doi.org/10.1108/oir-07-2018-0217

Tegtmeyer K, Ibsen L, Goldstein B(2001) Computer-assisted learning in critical care: from ENIAC to HAL Crit Care Med 29:N177–N182. https://doi.org/10.1097/00003246-200108001-00006

Article   CAS   PubMed   Google Scholar  

Timotheou S, Miliou O, Dimitriadis Y, Sobrino SV, Giannoutsou N, Cachia R, Moné AM, Ioannou A(2023) Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: a literature review. Educ Inf Technol 28(6):6695–6726. https://doi.org/10.1007/s10639-022-11431-8

Trujillo Maza EM, Gómez Lozano MT, Cardozo Alarcón AC, Moreno Zuluaga L, Gamba Fadul M (2016) Blended learning supported by digital technology and competency-based medical education: a case study of the social medicine course at the Universidad de los Andes, Colombia. Int J Educ Technol High Educ 13. https://doi.org/10.1186/s41239-016-0027-9

Turin O, Friesem Y(2020) Is that media literacy?: Israeli and US media scholars’ perceptions of the field J Media Lit Educ 12:132–144. https://doi.org/10.1007/s11192-009-0146-3

Van Eck NJ, Waltman L (2019) VOSviewer manual. Universiteit Leiden

Vratulis V, Clarke T, Hoban G, Erickson G(2011) Additive and disruptive pedagogies: the use of slowmation as an example of digital technology implementation Teach Teach Educ 27:1179–1188. https://doi.org/10.1016/j.tate.2011.06.004

Wang CL, Dai J, Xu LJ (2022) Big data and data mining in education: a bibliometrics study from 2010 to 2022. In 2022 7th International Conference on Cloud Computing and Big Data Analytics ( ICCCBDA ) (pp. 507-512). IEEE. https://doi.org/10.1109/icccbda55098.2022.9778874

Wang CL, Dai J, Zhu KK, Yu T, Gu XQ (2023) Understanding the continuance intention of college students toward new E-learning spaces based on an integrated model of the TAM and TTF. Int J Hum-Comput Int 1–14. https://doi.org/10.1080/10447318.2023.2291609

Wong L-H, Boticki I, Sun J, Looi C-K(2011) Improving the scaffolds of a mobile-assisted Chinese character forming game via a design-based research cycle Comput Hum Behav 27:1783–1793. https://doi.org/10.1016/j.chb.2011.03.005

Wu R, Yu Z (2023) Do AI chatbots improve students learning outcomes? Evidence from a meta-analysis. Br J Educ Technol. https://doi.org/10.1111/bjet.13334

Yang D, Zhou J, Shi D, Pan Q, Wang D, Chen X, Liu J (2022) Research status, hotspots, and evolutionary trends of global digital education via knowledge graph analysis. Sustainability 14:15157–15157. https://doi.org/10.3390/su142215157

Yu T, Dai J, Wang CL (2023) Adoption of blended learning: Chinese university students’ perspectives. Humanit Soc Sci Commun 10:390. https://doi.org/10.3390/su142215157

Yu Z (2022) Sustaining student roles, digital literacy, learning achievements, and motivation in online learning environments during the COVID-19 pandemic. Sustainability 14:4388. https://doi.org/10.3390/su14084388

Za S, Spagnoletti P, North-Samardzic A(2014) Organisational learning as an emerging process: the generative role of digital tools in informal learning practices Br J Educ Technol 45:1023–1035. https://doi.org/10.1111/bjet.12211

Zhang X, Chen Y, Hu L, Wang Y (2022) The metaverse in education: definition, framework, features, potential applications, challenges, and future research topics. Front Psychol 13:1016300. https://doi.org/10.3389/fpsyg.2022.1016300

Zhou M, Dzingirai C, Hove K, Chitata T, Mugandani R (2022) Adoption, use and enhancement of virtual learning during COVID-19. Education and Information Technologies. https://doi.org/10.1007/s10639-022-10985-x

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This research was supported by the Zhejiang Provincial Social Science Planning Project, “Mechanisms and Pathways for Empowering Classroom Teaching through Learning Spaces under the Strategy of High-Quality Education Development”, the 2022 National Social Science Foundation Education Youth Project “Research on the Strategy of Creating Learning Space Value and Empowering Classroom Teaching under the background of ‘Double Reduction’” (Grant No. CCA220319) and the National College Student Innovation and Entrepreneurship Training Program of China (Grant No. 202310337023).

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Wang, C., Chen, X., Yu, T. et al. Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11 , 256 (2024). https://doi.org/10.1057/s41599-024-02717-y

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Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review

Stella timotheou.

1 CYENS Center of Excellence & Cyprus University of Technology (Cyprus Interaction Lab), Cyprus, CYENS Center of Excellence & Cyprus University of Technology, Nicosia-Limassol, Cyprus

Ourania Miliou

Yiannis dimitriadis.

2 Universidad de Valladolid (UVA), Spain, Valladolid, Spain

Sara Villagrá Sobrino

Nikoleta giannoutsou, romina cachia.

3 JRC - Joint Research Centre of the European Commission, Seville, Spain

Alejandra Martínez Monés

Andri ioannou, associated data.

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Digital technologies have brought changes to the nature and scope of education and led education systems worldwide to adopt strategies and policies for ICT integration. The latter brought about issues regarding the quality of teaching and learning with ICTs, especially concerning the understanding, adaptation, and design of the education systems in accordance with current technological trends. These issues were emphasized during the recent COVID-19 pandemic that accelerated the use of digital technologies in education, generating questions regarding digitalization in schools. Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses. Such results have engendered the need for schools to learn and build upon the experience to enhance their digital capacity and preparedness, increase their digitalization levels, and achieve a successful digital transformation. Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem, there is a need to show how these impacts are interconnected and identify the factors that can encourage an effective and efficient change in the school environments. For this purpose, we conducted a non-systematic literature review. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors that affect the schools’ digital capacity and digital transformation. The findings suggest that ICT integration in schools impacts more than just students’ performance; it affects several other school-related aspects and stakeholders, too. Furthermore, various factors affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the digital transformation process. The study results shed light on how ICTs can positively contribute to the digital transformation of schools and which factors should be considered for schools to achieve effective and efficient change.

Introduction

Digital technologies have brought changes to the nature and scope of education. Versatile and disruptive technological innovations, such as smart devices, the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR) and virtual reality (VR), blockchain, and software applications have opened up new opportunities for advancing teaching and learning (Gaol & Prasolova-Førland, 2021 ; OECD, 2021 ). Hence, in recent years, education systems worldwide have increased their investment in the integration of information and communication technology (ICT) (Fernández-Gutiérrez et al., 2020 ; Lawrence & Tar, 2018 ) and prioritized their educational agendas to adapt strategies or policies around ICT integration (European Commission, 2019 ). The latter brought about issues regarding the quality of teaching and learning with ICTs (Bates, 2015 ), especially concerning the understanding, adaptation, and design of education systems in accordance with current technological trends (Balyer & Öz, 2018 ). Studies have shown that despite the investment made in the integration of technology in schools, the results have not been promising, and the intended outcomes have not yet been achieved (Delgado et al., 2015 ; Lawrence & Tar, 2018 ). These issues were exacerbated during the COVID-19 pandemic, which forced teaching across education levels to move online (Daniel, 2020 ). Online teaching accelerated the use of digital technologies generating questions regarding the process, the nature, the extent, and the effectiveness of digitalization in schools (Cachia et al., 2021 ; König et al., 2020 ). Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses (Blaskó et al., 2021 ; Di Pietro et al, 2020 ). Such results have engendered the need for schools to learn and build upon the experience in order to enhance their digital capacity (European Commission, 2020 ) and increase their digitalization levels (Costa et al., 2021 ). Digitalization offers possibilities for fundamental improvement in schools (OECD, 2021 ; Rott & Marouane, 2018 ) and touches many aspects of a school’s development (Delcker & Ifenthaler, 2021 ) . However, it is a complex process that requires large-scale transformative changes beyond the technical aspects of technology and infrastructure (Pettersson, 2021 ). Namely, digitalization refers to “ a series of deep and coordinated culture, workforce, and technology shifts and operating models ” (Brooks & McCormack, 2020 , p. 3) that brings cultural, organizational, and operational change through the integration of digital technologies (JISC, 2020 ). A successful digital transformation requires that schools increase their digital capacity levels, establishing the necessary “ culture, policies, infrastructure as well as digital competence of students and staff to support the effective integration of technology in teaching and learning practices ” (Costa et al, 2021 , p.163).

Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem (Eng, 2005 ), there is a need to show how the different elements of the impact are interconnected and to identify the factors that can encourage an effective and efficient change in the school environment. To address the issues outlined above, we formulated the following research questions:

a) What is the impact of digital technologies on education?

b) Which factors might affect a school’s digital capacity and transformation?

In the present investigation, we conducted a non-systematic literature review of publications pertaining to the impact of digital technologies on education and the factors that affect a school’s digital capacity and transformation. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors which affect the schools’ digital capacity and digital transformation.

Methodology

The non-systematic literature review presented herein covers the main theories and research published over the past 17 years on the topic. It is based on meta-analyses and review papers found in scholarly, peer-reviewed content databases and other key studies and reports related to the concepts studied (e.g., digitalization, digital capacity) from professional and international bodies (e.g., the OECD). We searched the Scopus database, which indexes various online journals in the education sector with an international scope, to collect peer-reviewed academic papers. Furthermore, we used an all-inclusive Google Scholar search to include relevant key terms or to include studies found in the reference list of the peer-reviewed papers, and other key studies and reports related to the concepts studied by professional and international bodies. Lastly, we gathered sources from the Publications Office of the European Union ( https://op.europa.eu/en/home ); namely, documents that refer to policies related to digital transformation in education.

Regarding search terms, we first searched resources on the impact of digital technologies on education by performing the following search queries: “impact” OR “effects” AND “digital technologies” AND “education”, “impact” OR “effects” AND “ICT” AND “education”. We further refined our results by adding the terms “meta-analysis” and “review” or by adjusting the search options based on the features of each database to avoid collecting individual studies that would provide limited contributions to a particular domain. We relied on meta-analyses and review studies as these consider the findings of multiple studies to offer a more comprehensive view of the research in a given area (Schuele & Justice, 2006 ). Specifically, meta-analysis studies provided quantitative evidence based on statistically verifiable results regarding the impact of educational interventions that integrate digital technologies in school classrooms (Higgins et al., 2012 ; Tolani-Brown et al., 2011 ).

However, quantitative data does not offer explanations for the challenges or difficulties experienced during ICT integration in learning and teaching (Tolani-Brown et al., 2011 ). To fill this gap, we analyzed literature reviews and gathered in-depth qualitative evidence of the benefits and implications of technology integration in schools. In the analysis presented herein, we also included policy documents and reports from professional and international bodies and governmental reports, which offered useful explanations of the key concepts of this study and provided recent evidence on digital capacity and transformation in education along with policy recommendations. The inclusion and exclusion criteria that were considered in this study are presented in Table ​ Table1 1 .

Inclusion and exclusion criteria for the selection of resources on the impact of digital technologies on education

To ensure a reliable extraction of information from each study and assist the research synthesis we selected the study characteristics of interest (impact) and constructed coding forms. First, an overview of the synthesis was provided by the principal investigator who described the processes of coding, data entry, and data management. The coders followed the same set of instructions but worked independently. To ensure a common understanding of the process between coders, a sample of ten studies was tested. The results were compared, and the discrepancies were identified and resolved. Additionally, to ensure an efficient coding process, all coders participated in group meetings to discuss additions, deletions, and modifications (Stock, 1994 ). Due to the methodological diversity of the studied documents we began to synthesize the literature review findings based on similar study designs. Specifically, most of the meta-analysis studies were grouped in one category due to the quantitative nature of the measured impact. These studies tended to refer to student achievement (Hattie et al., 2014 ). Then, we organized the themes of the qualitative studies in several impact categories. Lastly, we synthesized both review and meta-analysis data across the categories. In order to establish a collective understanding of the concept of impact, we referred to a previous impact study by Balanskat ( 2009 ) which investigated the impact of technology in primary schools. In this context, the impact had a more specific ICT-related meaning and was described as “ a significant influence or effect of ICT on the measured or perceived quality of (parts of) education ” (Balanskat, 2009 , p. 9). In the study presented herein, the main impacts are in relation to learning and learners, teaching, and teachers, as well as other key stakeholders who are directly or indirectly connected to the school unit.

The study’s results identified multiple dimensions of the impact of digital technologies on students’ knowledge, skills, and attitudes; on equality, inclusion, and social integration; on teachers’ professional and teaching practices; and on other school-related aspects and stakeholders. The data analysis indicated various factors that might affect the schools’ digital capacity and transformation, such as digital competencies, the teachers’ personal characteristics and professional development, as well as the school’s leadership and management, administration, infrastructure, etc. The impacts and factors found in the literature review are presented below.

Impacts of digital technologies on students’ knowledge, skills, attitudes, and emotions

The impact of ICT use on students’ knowledge, skills, and attitudes has been investigated early in the literature. Eng ( 2005 ) found a small positive effect between ICT use and students' learning. Specifically, the author reported that access to computer-assisted instruction (CAI) programs in simulation or tutorial modes—used to supplement rather than substitute instruction – could enhance student learning. The author reported studies showing that teachers acknowledged the benefits of ICT on pupils with special educational needs; however, the impact of ICT on students' attainment was unclear. Balanskat et al. ( 2006 ) found a statistically significant positive association between ICT use and higher student achievement in primary and secondary education. The authors also reported improvements in the performance of low-achieving pupils. The use of ICT resulted in further positive gains for students, namely increased attention, engagement, motivation, communication and process skills, teamwork, and gains related to their behaviour towards learning. Evidence from qualitative studies showed that teachers, students, and parents recognized the positive impact of ICT on students' learning regardless of their competence level (strong/weak students). Punie et al. ( 2006 ) documented studies that showed positive results of ICT-based learning for supporting low-achieving pupils and young people with complex lives outside the education system. Liao et al. ( 2007 ) reported moderate positive effects of computer application instruction (CAI, computer simulations, and web-based learning) over traditional instruction on primary school student's achievement. Similarly, Tamim et al. ( 2011 ) reported small to moderate positive effects between the use of computer technology (CAI, ICT, simulations, computer-based instruction, digital and hypermedia) and student achievement in formal face-to-face classrooms compared to classrooms that did not use technology. Jewitt et al., ( 2011 ) found that the use of learning platforms (LPs) (virtual learning environments, management information systems, communication technologies, and information- and resource-sharing technologies) in schools allowed primary and secondary students to access a wider variety of quality learning resources, engage in independent and personalized learning, and conduct self- and peer-review; LPs also provide opportunities for teacher assessment and feedback. Similar findings were reported by Fu ( 2013 ), who documented a list of benefits and opportunities of ICT use. According to the author, the use of ICTs helps students access digital information and course content effectively and efficiently, supports student-centered and self-directed learning, as well as the development of a creative learning environment where more opportunities for critical thinking skills are offered, and promotes collaborative learning in a distance-learning environment. Higgins et al. ( 2012 ) found consistent but small positive associations between the use of technology and learning outcomes of school-age learners (5–18-year-olds) in studies linking the provision and use of technology with attainment. Additionally, Chauhan ( 2017 ) reported a medium positive effect of technology on the learning effectiveness of primary school students compared to students who followed traditional learning instruction.

The rise of mobile technologies and hardware devices instigated investigations into their impact on teaching and learning. Sung et al. ( 2016 ) reported a moderate effect on students' performance from the use of mobile devices in the classroom compared to the use of desktop computers or the non-use of mobile devices. Schmid et al. ( 2014 ) reported medium–low to low positive effects of technology integration (e.g., CAI, ICTs) in the classroom on students' achievement and attitude compared to not using technology or using technology to varying degrees. Tamim et al. ( 2015 ) found a low statistically significant effect of the use of tablets and other smart devices in educational contexts on students' achievement outcomes. The authors suggested that tablets offered additional advantages to students; namely, they reported improvements in students’ notetaking, organizational and communication skills, and creativity. Zheng et al. ( 2016 ) reported a small positive effect of one-to-one laptop programs on students’ academic achievement across subject areas. Additional reported benefits included student-centered, individualized, and project-based learning enhanced learner engagement and enthusiasm. Additionally, the authors found that students using one-to-one laptop programs tended to use technology more frequently than in non-laptop classrooms, and as a result, they developed a range of skills (e.g., information skills, media skills, technology skills, organizational skills). Haßler et al. ( 2016 ) found that most interventions that included the use of tablets across the curriculum reported positive learning outcomes. However, from 23 studies, five reported no differences, and two reported a negative effect on students' learning outcomes. Similar results were indicated by Kalati and Kim ( 2022 ) who investigated the effect of touchscreen technologies on young students’ learning. Specifically, from 53 studies, 34 advocated positive effects of touchscreen devices on children’s learning, 17 obtained mixed findings and two studies reported negative effects.

More recently, approaches that refer to the impact of gamification with the use of digital technologies on teaching and learning were also explored. A review by Pan et al. ( 2022 ) that examined the role of learning games in fostering mathematics education in K-12 settings, reported that gameplay improved students’ performance. Integration of digital games in teaching was also found as a promising pedagogical practice in STEM education that could lead to increased learning gains (Martinez et al., 2022 ; Wang et al., 2022 ). However, although Talan et al. ( 2020 ) reported a medium effect of the use of educational games (both digital and non-digital) on academic achievement, the effect of non-digital games was higher.

Over the last two years, the effects of more advanced technologies on teaching and learning were also investigated. Garzón and Acevedo ( 2019 ) found that AR applications had a medium effect on students' learning outcomes compared to traditional lectures. Similarly, Garzón et al. ( 2020 ) showed that AR had a medium impact on students' learning gains. VR applications integrated into various subjects were also found to have a moderate effect on students’ learning compared to control conditions (traditional classes, e.g., lectures, textbooks, and multimedia use, e.g., images, videos, animation, CAI) (Chen et al., 2022b ). Villena-Taranilla et al. ( 2022 ) noted the moderate effect of VR technologies on students’ learning when these were applied in STEM disciplines. In the same meta-analysis, Villena-Taranilla et al. ( 2022 ) highlighted the role of immersive VR, since its effect on students’ learning was greater (at a high level) across educational levels (K-6) compared to semi-immersive and non-immersive integrations. In another meta-analysis study, the effect size of the immersive VR was small and significantly differentiated across educational levels (Coban et al., 2022 ). The impact of AI on education was investigated by Su and Yang ( 2022 ) and Su et al. ( 2022 ), who showed that this technology significantly improved students’ understanding of AI computer science and machine learning concepts.

It is worth noting that the vast majority of studies referred to learning gains in specific subjects. Specifically, several studies examined the impact of digital technologies on students’ literacy skills and reported positive effects on language learning (Balanskat et al., 2006 ; Grgurović et al., 2013 ; Friedel et al., 2013 ; Zheng et al., 2016 ; Chen et al., 2022b ; Savva et al., 2022 ). Also, several studies documented positive effects on specific language learning areas, namely foreign language learning (Kao, 2014 ), writing (Higgins et al., 2012 ; Wen & Walters, 2022 ; Zheng et al., 2016 ), as well as reading and comprehension (Cheung & Slavin, 2011 ; Liao et al., 2007 ; Schwabe et al., 2022 ). ICTs were also found to have a positive impact on students' performance in STEM (science, technology, engineering, and mathematics) disciplines (Arztmann et al., 2022 ; Bado, 2022 ; Villena-Taranilla et al., 2022 ; Wang et al., 2022 ). Specifically, a number of studies reported positive impacts on students’ achievement in mathematics (Balanskat et al., 2006 ; Hillmayr et al., 2020 ; Li & Ma, 2010 ; Pan et al., 2022 ; Ran et al., 2022 ; Verschaffel et al., 2019 ; Zheng et al., 2016 ). Furthermore, studies documented positive effects of ICTs on science learning (Balanskat et al., 2006 ; Liao et al., 2007 ; Zheng et al., 2016 ; Hillmayr et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ; Lei et al., 2022a ). Çelik ( 2022 ) also noted that computer simulations can help students understand learning concepts related to science. Furthermore, some studies documented that the use of ICTs had a positive impact on students’ achievement in other subjects, such as geography, history, music, and arts (Chauhan, 2017 ; Condie & Munro, 2007 ), and design and technology (Balanskat et al., 2006 ).

More specific positive learning gains were reported in a number of skills, e.g., problem-solving skills and pattern exploration skills (Higgins et al., 2012 ), metacognitive learning outcomes (Verschaffel et al., 2019 ), literacy skills, computational thinking skills, emotion control skills, and collaborative inquiry skills (Lu et al., 2022 ; Su & Yang, 2022 ; Su et al., 2022 ). Additionally, several investigations have reported benefits from the use of ICT on students’ creativity (Fielding & Murcia, 2022 ; Liu et al., 2022 ; Quah & Ng, 2022 ). Lastly, digital technologies were also found to be beneficial for enhancing students’ lifelong learning skills (Haleem et al., 2022 ).

Apart from gaining knowledge and skills, studies also reported improvement in motivation and interest in mathematics (Higgins et. al., 2019 ; Fadda et al., 2022 ) and increased positive achievement emotions towards several subjects during interventions using educational games (Lei et al., 2022a ). Chen et al. ( 2022a ) also reported a small but positive effect of digital health approaches in bullying and cyberbullying interventions with K-12 students, demonstrating that technology-based approaches can help reduce bullying and related consequences by providing emotional support, empowerment, and change of attitude. In their meta-review study, Su et al. ( 2022 ) also documented that AI technologies effectively strengthened students’ attitudes towards learning. In another meta-analysis, Arztmann et al. ( 2022 ) reported positive effects of digital games on motivation and behaviour towards STEM subjects.

Impacts of digital technologies on equality, inclusion and social integration

Although most of the reviewed studies focused on the impact of ICTs on students’ knowledge, skills, and attitudes, reports were also made on other aspects in the school context, such as equality, inclusion, and social integration. Condie and Munro ( 2007 ) documented research interventions investigating how ICT can support pupils with additional or special educational needs. While those interventions were relatively small scale and mostly based on qualitative data, their findings indicated that the use of ICTs enabled the development of communication, participation, and self-esteem. A recent meta-analysis (Baragash et al., 2022 ) with 119 participants with different disabilities, reported a significant overall effect size of AR on their functional skills acquisition. Koh’s meta-analysis ( 2022 ) also revealed that students with intellectual and developmental disabilities improved their competence and performance when they used digital games in the lessons.

Istenic Starcic and Bagon ( 2014 ) found that the role of ICT in inclusion and the design of pedagogical and technological interventions was not sufficiently explored in educational interventions with people with special needs; however, some benefits of ICT use were found in students’ social integration. The issue of gender and technology use was mentioned in a small number of studies. Zheng et al. ( 2016 ) reported a statistically significant positive interaction between one-to-one laptop programs and gender. Specifically, the results showed that girls and boys alike benefitted from the laptop program, but the effect on girls’ achievement was smaller than that on boys’. Along the same lines, Arztmann et al. ( 2022 ) reported no difference in the impact of game-based learning between boys and girls, arguing that boys and girls equally benefited from game-based interventions in STEM domains. However, results from a systematic review by Cussó-Calabuig et al. ( 2018 ) found limited and low-quality evidence on the effects of intensive use of computers on gender differences in computer anxiety, self-efficacy, and self-confidence. Based on their view, intensive use of computers can reduce gender differences in some areas and not in others, depending on contextual and implementation factors.

Impacts of digital technologies on teachers’ professional and teaching practices

Various research studies have explored the impact of ICT on teachers’ instructional practices and student assessment. Friedel et al. ( 2013 ) found that the use of mobile devices by students enabled teachers to successfully deliver content (e.g., mobile serious games), provide scaffolding, and facilitate synchronous collaborative learning. The integration of digital games in teaching and learning activities also gave teachers the opportunity to study and apply various pedagogical practices (Bado, 2022 ). Specifically, Bado ( 2022 ) found that teachers who implemented instructional activities in three stages (pre-game, game, and post-game) maximized students’ learning outcomes and engagement. For instance, during the pre-game stage, teachers focused on lectures and gameplay training, at the game stage teachers provided scaffolding on content, addressed technical issues, and managed the classroom activities. During the post-game stage, teachers organized activities for debriefing to ensure that the gameplay had indeed enhanced students’ learning outcomes.

Furthermore, ICT can increase efficiency in lesson planning and preparation by offering possibilities for a more collaborative approach among teachers. The sharing of curriculum plans and the analysis of students’ data led to clearer target settings and improvements in reporting to parents (Balanskat et al., 2006 ).

Additionally, the use and application of digital technologies in teaching and learning were found to enhance teachers’ digital competence. Balanskat et al. ( 2006 ) documented studies that revealed that the use of digital technologies in education had a positive effect on teachers’ basic ICT skills. The greatest impact was found on teachers with enough experience in integrating ICTs in their teaching and/or who had recently participated in development courses for the pedagogical use of technologies in teaching. Punie et al. ( 2006 ) reported that the provision of fully equipped multimedia portable computers and the development of online teacher communities had positive impacts on teachers’ confidence and competence in the use of ICTs.

Moreover, online assessment via ICTs benefits instruction. In particular, online assessments support the digitalization of students’ work and related logistics, allow teachers to gather immediate feedback and readjust to new objectives, and support the improvement of the technical quality of tests by providing more accurate results. Additionally, the capabilities of ICTs (e.g., interactive media, simulations) create new potential methods of testing specific skills, such as problem-solving and problem-processing skills, meta-cognitive skills, creativity and communication skills, and the ability to work productively in groups (Punie et al., 2006 ).

Impacts of digital technologies on other school-related aspects and stakeholders

There is evidence that the effective use of ICTs and the data transmission offered by broadband connections help improve administration (Balanskat et al., 2006 ). Specifically, ICTs have been found to provide better management systems to schools that have data gathering procedures in place. Condie and Munro ( 2007 ) reported impacts from the use of ICTs in schools in the following areas: attendance monitoring, assessment records, reporting to parents, financial management, creation of repositories for learning resources, and sharing of information amongst staff. Such data can be used strategically for self-evaluation and monitoring purposes which in turn can result in school improvements. Additionally, they reported that online access to other people with similar roles helped to reduce headteachers’ isolation by offering them opportunities to share insights into the use of ICT in learning and teaching and how it could be used to support school improvement. Furthermore, ICTs provided more efficient and successful examination management procedures, namely less time-consuming reporting processes compared to paper-based examinations and smooth communications between schools and examination authorities through electronic data exchange (Punie et al., 2006 ).

Zheng et al. ( 2016 ) reported that the use of ICTs improved home-school relationships. Additionally, Escueta et al. ( 2017 ) reported several ICT programs that had improved the flow of information from the school to parents. Particularly, they documented that the use of ICTs (learning management systems, emails, dedicated websites, mobile phones) allowed for personalized and customized information exchange between schools and parents, such as attendance records, upcoming class assignments, school events, and students’ grades, which generated positive results on students’ learning outcomes and attainment. Such information exchange between schools and families prompted parents to encourage their children to put more effort into their schoolwork.

The above findings suggest that the impact of ICT integration in schools goes beyond students’ performance in school subjects. Specifically, it affects a number of school-related aspects, such as equality and social integration, professional and teaching practices, and diverse stakeholders. In Table ​ Table2, 2 , we summarize the different impacts of digital technologies on school stakeholders based on the literature review, while in Table ​ Table3 3 we organized the tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript.

The impact of digital technologies on schools’ stakeholders based on the literature review

Tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript

Additionally, based on the results of the literature review, there are many types of digital technologies with different affordances (see, for example, studies on VR vs Immersive VR), which evolve over time (e.g. starting from CAIs in 2005 to Augmented and Virtual reality 2020). Furthermore, these technologies are linked to different pedagogies and policy initiatives, which are critical factors in the study of impact. Table ​ Table3 3 summarizes the different tools and practices that have been used to examine the impact of digital technologies on education since 2005 based on the review results.

Factors that affect the integration of digital technologies

Although the analysis of the literature review demonstrated different impacts of the use of digital technology on education, several authors highlighted the importance of various factors, besides the technology itself, that affect this impact. For example, Liao et al. ( 2007 ) suggested that future studies should carefully investigate which factors contribute to positive outcomes by clarifying the exact relationship between computer applications and learning. Additionally, Haßler et al., ( 2016 ) suggested that the neutral findings regarding the impact of tablets on students learning outcomes in some of the studies included in their review should encourage educators, school leaders, and school officials to further investigate the potential of such devices in teaching and learning. Several other researchers suggested that a number of variables play a significant role in the impact of ICTs on students’ learning that could be attributed to the school context, teaching practices and professional development, the curriculum, and learners’ characteristics (Underwood, 2009 ; Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Tang et al., 2022 ).

Digital competencies

One of the most common challenges reported in studies that utilized digital tools in the classroom was the lack of students’ skills on how to use them. Fu ( 2013 ) found that students’ lack of technical skills is a barrier to the effective use of ICT in the classroom. Tamim et al. ( 2015 ) reported that students faced challenges when using tablets and smart mobile devices, associated with the technical issues or expertise needed for their use and the distracting nature of the devices and highlighted the need for teachers’ professional development. Higgins et al. ( 2012 ) reported that skills training about the use of digital technologies is essential for learners to fully exploit the benefits of instruction.

Delgado et al. ( 2015 ), meanwhile, reported studies that showed a strong positive association between teachers’ computer skills and students’ use of computers. Teachers’ lack of ICT skills and familiarization with technologies can become a constraint to the effective use of technology in the classroom (Balanskat et al., 2006 ; Delgado et al., 2015 ).

It is worth noting that the way teachers are introduced to ICTs affects the impact of digital technologies on education. Previous studies have shown that teachers may avoid using digital technologies due to limited digital skills (Balanskat, 2006 ), or they prefer applying “safe” technologies, namely technologies that their own teachers used and with which they are familiar (Condie & Munro, 2007 ). In this regard, the provision of digital skills training and exposure to new digital tools might encourage teachers to apply various technologies in their lessons (Condie & Munro, 2007 ). Apart from digital competence, technical support in the school setting has also been shown to affect teachers’ use of technology in their classrooms (Delgado et al., 2015 ). Ferrari et al. ( 2011 ) found that while teachers’ use of ICT is high, 75% stated that they needed more institutional support and a shift in the mindset of educational actors to achieve more innovative teaching practices. The provision of support can reduce time and effort as well as cognitive constraints, which could cause limited ICT integration in the school lessons by teachers (Escueta et al., 2017 ).

Teachers’ personal characteristics, training approaches, and professional development

Teachers’ personal characteristics and professional development affect the impact of digital technologies on education. Specifically, Cheok and Wong ( 2015 ) found that teachers’ personal characteristics (e.g., anxiety, self-efficacy) are associated with their satisfaction and engagement with technology. Bingimlas ( 2009 ) reported that lack of confidence, resistance to change, and negative attitudes in using new technologies in teaching are significant determinants of teachers’ levels of engagement in ICT. The same author reported that the provision of technical support, motivation support (e.g., awards, sufficient time for planning), and training on how technologies can benefit teaching and learning can eliminate the above barriers to ICT integration. Archer et al. ( 2014 ) found that comfort levels in using technology are an important predictor of technology integration and argued that it is essential to provide teachers with appropriate training and ongoing support until they are comfortable with using ICTs in the classroom. Hillmayr et al. ( 2020 ) documented that training teachers on ICT had an important effecton students’ learning.

According to Balanskat et al. ( 2006 ), the impact of ICTs on students’ learning is highly dependent on the teachers’ capacity to efficiently exploit their application for pedagogical purposes. Results obtained from the Teaching and Learning International Survey (TALIS) (OECD, 2021 ) revealed that although schools are open to innovative practices and have the capacity to adopt them, only 39% of teachers in the European Union reported that they are well or very well prepared to use digital technologies for teaching. Li and Ma ( 2010 ) and Hardman ( 2019 ) showed that the positive effect of technology on students’ achievement depends on the pedagogical practices used by teachers. Schmid et al. ( 2014 ) reported that learning was best supported when students were engaged in active, meaningful activities with the use of technological tools that provided cognitive support. Tamim et al. ( 2015 ) compared two different pedagogical uses of tablets and found a significant moderate effect when the devices were used in a student-centered context and approach rather than within teacher-led environments. Similarly, Garzón and Acevedo ( 2019 ) and Garzón et al. ( 2020 ) reported that the positive results from the integration of AR applications could be attributed to the existence of different variables which could influence AR interventions (e.g., pedagogical approach, learning environment, and duration of the intervention). Additionally, Garzón et al. ( 2020 ) suggested that the pedagogical resources that teachers used to complement their lectures and the pedagogical approaches they applied were crucial to the effective integration of AR on students’ learning gains. Garzón and Acevedo ( 2019 ) also emphasized that the success of a technology-enhanced intervention is based on both the technology per se and its characteristics and on the pedagogical strategies teachers choose to implement. For instance, their results indicated that the collaborative learning approach had the highest impact on students’ learning gains among other approaches (e.g., inquiry-based learning, situated learning, or project-based learning). Ran et al. ( 2022 ) also found that the use of technology to design collaborative and communicative environments showed the largest moderator effects among the other approaches.

Hattie ( 2008 ) reported that the effective use of computers is associated with training teachers in using computers as a teaching and learning tool. Zheng et al. ( 2016 ) noted that in addition to the strategies teachers adopt in teaching, ongoing professional development is also vital in ensuring the success of technology implementation programs. Sung et al. ( 2016 ) found that research on the use of mobile devices to support learning tends to report that the insufficient preparation of teachers is a major obstacle in implementing effective mobile learning programs in schools. Friedel et al. ( 2013 ) found that providing training and support to teachers increased the positive impact of the interventions on students’ learning gains. Trucano ( 2005 ) argued that positive impacts occur when digital technologies are used to enhance teachers’ existing pedagogical philosophies. Higgins et al. ( 2012 ) found that the types of technologies used and how they are used could also affect students’ learning. The authors suggested that training and professional development of teachers that focuses on the effective pedagogical use of technology to support teaching and learning is an important component of successful instructional approaches (Higgins et al., 2012 ). Archer et al. ( 2014 ) found that studies that reported ICT interventions during which teachers received training and support had moderate positive effects on students’ learning outcomes, which were significantly higher than studies where little or no detail about training and support was mentioned. Fu ( 2013 ) reported that the lack of teachers’ knowledge and skills on the technical and instructional aspects of ICT use in the classroom, in-service training, pedagogy support, technical and financial support, as well as the lack of teachers’ motivation and encouragement to integrate ICT on their teaching were significant barriers to the integration of ICT in education.

School leadership and management

Management and leadership are important cornerstones in the digital transformation process (Pihir et al., 2018 ). Zheng et al. ( 2016 ) documented leadership among the factors positively affecting the successful implementation of technology integration in schools. Strong leadership, strategic planning, and systematic integration of digital technologies are prerequisites for the digital transformation of education systems (Ređep, 2021 ). Management and leadership play a significant role in formulating policies that are translated into practice and ensure that developments in ICT become embedded into the life of the school and in the experiences of staff and pupils (Condie & Munro, 2007 ). Policy support and leadership must include the provision of an overall vision for the use of digital technologies in education, guidance for students and parents, logistical support, as well as teacher training (Conrads et al., 2017 ). Unless there is a commitment throughout the school, with accountability for progress at key points, it is unlikely for ICT integration to be sustained or become part of the culture (Condie & Munro, 2007 ). To achieve this, principals need to adopt and promote a whole-institution strategy and build a strong mutual support system that enables the school’s technological maturity (European Commission, 2019 ). In this context, school culture plays an essential role in shaping the mindsets and beliefs of school actors towards successful technology integration. Condie and Munro ( 2007 ) emphasized the importance of the principal’s enthusiasm and work as a source of inspiration for the school staff and the students to cultivate a culture of innovation and establish sustainable digital change. Specifically, school leaders need to create conditions in which the school staff is empowered to experiment and take risks with technology (Elkordy & Lovinelli, 2020 ).

In order for leaders to achieve the above, it is important to develop capacities for learning and leading, advocating professional learning, and creating support systems and structures (European Commission, 2019 ). Digital technology integration in education systems can be challenging and leadership needs guidance to achieve it. Such guidance can be introduced through the adoption of new methods and techniques in strategic planning for the integration of digital technologies (Ređep, 2021 ). Even though the role of leaders is vital, the relevant training offered to them has so far been inadequate. Specifically, only a third of the education systems in Europe have put in place national strategies that explicitly refer to the training of school principals (European Commission, 2019 , p. 16).

Connectivity, infrastructure, and government and other support

The effective integration of digital technologies across levels of education presupposes the development of infrastructure, the provision of digital content, and the selection of proper resources (Voogt et al., 2013 ). Particularly, a high-quality broadband connection in the school increases the quality and quantity of educational activities. There is evidence that ICT increases and formalizes cooperative planning between teachers and cooperation with managers, which in turn has a positive impact on teaching practices (Balanskat et al., 2006 ). Additionally, ICT resources, including software and hardware, increase the likelihood of teachers integrating technology into the curriculum to enhance their teaching practices (Delgado et al., 2015 ). For example, Zheng et al. ( 2016 ) found that the use of one-on-one laptop programs resulted in positive changes in teaching and learning, which would not have been accomplished without the infrastructure and technical support provided to teachers. Delgado et al. ( 2015 ) reported that limited access to technology (insufficient computers, peripherals, and software) and lack of technical support are important barriers to ICT integration. Access to infrastructure refers not only to the availability of technology in a school but also to the provision of a proper amount and the right types of technology in locations where teachers and students can use them. Effective technical support is a central element of the whole-school strategy for ICT (Underwood, 2009 ). Bingimlas ( 2009 ) reported that lack of technical support in the classroom and whole-school resources (e.g., failing to connect to the Internet, printers not printing, malfunctioning computers, and working on old computers) are significant barriers that discourage the use of ICT by teachers. Moreover, poor quality and inadequate hardware maintenance, and unsuitable educational software may discourage teachers from using ICTs (Balanskat et al., 2006 ; Bingimlas, 2009 ).

Government support can also impact the integration of ICTs in teaching. Specifically, Balanskat et al. ( 2006 ) reported that government interventions and training programs increased teachers’ enthusiasm and positive attitudes towards ICT and led to the routine use of embedded ICT.

Lastly, another important factor affecting digital transformation is the development and quality assurance of digital learning resources. Such resources can be support textbooks and related materials or resources that focus on specific subjects or parts of the curriculum. Policies on the provision of digital learning resources are essential for schools and can be achieved through various actions. For example, some countries are financing web portals that become repositories, enabling teachers to share resources or create their own. Additionally, they may offer e-learning opportunities or other services linked to digital education. In other cases, specific agencies of projects have also been set up to develop digital resources (Eurydice, 2019 ).

Administration and digital data management

The digital transformation of schools involves organizational improvements at the level of internal workflows, communication between the different stakeholders, and potential for collaboration. Vuorikari et al. ( 2020 ) presented evidence that digital technologies supported the automation of administrative practices in schools and reduced the administration’s workload. There is evidence that digital data affects the production of knowledge about schools and has the power to transform how schooling takes place. Specifically, Sellar ( 2015 ) reported that data infrastructure in education is developing due to the demand for “ information about student outcomes, teacher quality, school performance, and adult skills, associated with policy efforts to increase human capital and productivity practices ” (p. 771). In this regard, practices, such as datafication which refers to the “ translation of information about all kinds of things and processes into quantified formats” have become essential for decision-making based on accountability reports about the school’s quality. The data could be turned into deep insights about education or training incorporating ICTs. For example, measuring students’ online engagement with the learning material and drawing meaningful conclusions can allow teachers to improve their educational interventions (Vuorikari et al., 2020 ).

Students’ socioeconomic background and family support

Research show that the active engagement of parents in the school and their support for the school’s work can make a difference to their children’s attitudes towards learning and, as a result, their achievement (Hattie, 2008 ). In recent years, digital technologies have been used for more effective communication between school and family (Escueta et al., 2017 ). The European Commission ( 2020 ) presented data from a Eurostat survey regarding the use of computers by students during the pandemic. The data showed that younger pupils needed additional support and guidance from parents and the challenges were greater for families in which parents had lower levels of education and little to no digital skills.

In this regard, the socio-economic background of the learners and their socio-cultural environment also affect educational achievements (Punie et al., 2006 ). Trucano documented that the use of computers at home positively influenced students’ confidence and resulted in more frequent use at school, compared to students who had no home access (Trucano, 2005 ). In this sense, the socio-economic background affects the access to computers at home (OECD, 2015 ) which in turn influences the experience of ICT, an important factor for school achievement (Punie et al., 2006 ; Underwood, 2009 ). Furthermore, parents from different socio-economic backgrounds may have different abilities and availability to support their children in their learning process (Di Pietro et al., 2020 ).

Schools’ socioeconomic context and emergency situations

The socio-economic context of the school is closely related to a school’s digital transformation. For example, schools in disadvantaged, rural, or deprived areas are likely to lack the digital capacity and infrastructure required to adapt to the use of digital technologies during emergency periods, such as the COVID-19 pandemic (Di Pietro et al., 2020 ). Data collected from school principals confirmed that in several countries, there is a rural/urban divide in connectivity (OECD, 2015 ).

Emergency periods also affect the digitalization of schools. The COVID-19 pandemic led to the closure of schools and forced them to seek appropriate and connective ways to keep working on the curriculum (Di Pietro et al., 2020 ). The sudden large-scale shift to distance and online teaching and learning also presented challenges around quality and equity in education, such as the risk of increased inequalities in learning, digital, and social, as well as teachers facing difficulties coping with this demanding situation (European Commission, 2020 ).

Looking at the findings of the above studies, we can conclude that the impact of digital technologies on education is influenced by various actors and touches many aspects of the school ecosystem. Figure  1 summarizes the factors affecting the digital technologies’ impact on school stakeholders based on the findings from the literature review.

Factors that affect the impact of ICTs on education

The findings revealed that the use of digital technologies in education affects a variety of actors within a school’s ecosystem. First, we observed that as technologies evolve, so does the interest of the research community to apply them to school settings. Figure  2 summarizes the trends identified in current research around the impact of digital technologies on schools’ digital capacity and transformation as found in the present study. Starting as early as 2005, when computers, simulations, and interactive boards were the most commonly applied tools in school interventions (e.g., Eng, 2005 ; Liao et al., 2007 ; Moran et al., 2008 ; Tamim et al., 2011 ), moving towards the use of learning platforms (Jewitt et al., 2011 ), then to the use of mobile devices and digital games (e.g., Tamim et al., 2015 ; Sung et al., 2016 ; Talan et al., 2020 ), as well as e-books (e.g., Savva et al., 2022 ), to the more recent advanced technologies, such as AR and VR applications (e.g., Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ), or robotics and AI (e.g., Su & Yang, 2022 ; Su et al., 2022 ). As this evolution shows, digital technologies are a concept in flux with different affordances and characteristics. Additionally, from an instructional perspective, there has been a growing interest in different modes and models of content delivery such as online, blended, and hybrid modes (e.g., Cheok & Wong, 2015 ; Kazu & Yalçin, 2022 ; Ulum, 2022 ). This is an indication that the value of technologies to support teaching and learning as well as other school-related practices is increasingly recognized by the research and school community. The impact results from the literature review indicate that ICT integration on students’ learning outcomes has effects that are small (Coban et al., 2022 ; Eng, 2005 ; Higgins et al., 2012 ; Schmid et al., 2014 ; Tamim et al., 2015 ; Zheng et al., 2016 ) to moderate (Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Liao et al., 2007 ; Sung et al., 2016 ; Talan et al., 2020 ; Wen & Walters, 2022 ). That said, a number of recent studies have reported high effect sizes (e.g., Kazu & Yalçin, 2022 ).

Current work and trends in the study of the impact of digital technologies on schools’ digital capacity

Based on these findings, several authors have suggested that the impact of technology on education depends on several variables and not on the technology per se (Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Lei et al., 2022a ). While the impact of ICTs on student achievement has been thoroughly investigated by researchers, other aspects related to school life that are also affected by ICTs, such as equality, inclusion, and social integration have received less attention. Further analysis of the literature review has revealed a greater investment in ICT interventions to support learning and teaching in the core subjects of literacy and STEM disciplines, especially mathematics, and science. These were the most common subjects studied in the reviewed papers often drawing on national testing results, while studies that investigated other subject areas, such as social studies, were limited (Chauhan, 2017 ; Condie & Munro, 2007 ). As such, research is still lacking impact studies that focus on the effects of ICTs on a range of curriculum subjects.

The qualitative research provided additional information about the impact of digital technologies on education, documenting positive effects and giving more details about implications, recommendations, and future research directions. Specifically, the findings regarding the role of ICTs in supporting learning highlight the importance of teachers’ instructional practice and the learning context in the use of technologies and consequently their impact on instruction (Çelik, 2022 ; Schmid et al., 2014 ; Tamim et al., 2015 ). The review also provided useful insights regarding the various factors that affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the transformation process. Specifically, these factors include a) digital competencies; b) teachers’ personal characteristics and professional development; c) school leadership and management; d) connectivity, infrastructure, and government support; e) administration and data management practices; f) students’ socio-economic background and family support and g) the socioeconomic context of the school and emergency situations. It is worth noting that we observed factors that affect the integration of ICTs in education but may also be affected by it. For example, the frequent use of ICTs and the use of laptops by students for instructional purposes positively affect the development of digital competencies (Zheng et al., 2016 ) and at the same time, the digital competencies affect the use of ICTs (Fu, 2013 ; Higgins et al., 2012 ). As a result, the impact of digital technologies should be explored more as an enabler of desirable and new practices and not merely as a catalyst that improves the output of the education process i.e. namely student attainment.

Conclusions

Digital technologies offer immense potential for fundamental improvement in schools. However, investment in ICT infrastructure and professional development to improve school education are yet to provide fruitful results. Digital transformation is a complex process that requires large-scale transformative changes that presuppose digital capacity and preparedness. To achieve such changes, all actors within the school’s ecosystem need to share a common vision regarding the integration of ICTs in education and work towards achieving this goal. Our literature review, which synthesized quantitative and qualitative data from a list of meta-analyses and review studies, provided useful insights into the impact of ICTs on different school stakeholders and showed that the impact of digital technologies touches upon many different aspects of school life, which are often overlooked when the focus is on student achievement as the final output of education. Furthermore, the concept of digital technologies is a concept in flux as technologies are not only different among them calling for different uses in the educational practice but they also change through time. Additionally, we opened a forum for discussion regarding the factors that affect a school’s digital capacity and transformation. We hope that our study will inform policy, practice, and research and result in a paradigm shift towards more holistic approaches in impact and assessment studies.

Study limitations and future directions

We presented a review of the study of digital technologies' impact on education and factors influencing schools’ digital capacity and transformation. The study results were based on a non-systematic literature review grounded on the acquisition of documentation in specific databases. Future studies should investigate more databases to corroborate and enhance our results. Moreover, search queries could be enhanced with key terms that could provide additional insights about the integration of ICTs in education, such as “policies and strategies for ICT integration in education”. Also, the study drew information from meta-analyses and literature reviews to acquire evidence about the effects of ICT integration in schools. Such evidence was mostly based on the general conclusions of the studies. It is worth mentioning that, we located individual studies which showed different, such as negative or neutral results. Thus, further insights are needed about the impact of ICTs on education and the factors influencing the impact. Furthermore, the nature of the studies included in meta-analyses and reviews is different as they are based on different research methodologies and data gathering processes. For instance, in a meta-analysis, the impact among the studies investigated is measured in a particular way, depending on policy or research targets (e.g., results from national examinations, pre-/post-tests). Meanwhile, in literature reviews, qualitative studies offer additional insights and detail based on self-reports and research opinions on several different aspects and stakeholders who could affect and be affected by ICT integration. As a result, it was challenging to draw causal relationships between so many interrelating variables.

Despite the challenges mentioned above, this study envisaged examining school units as ecosystems that consist of several actors by bringing together several variables from different research epistemologies to provide an understanding of the integration of ICTs. However, the use of other tools and methodologies and models for evaluation of the impact of digital technologies on education could give more detailed data and more accurate results. For instance, self-reflection tools, like SELFIE—developed on the DigCompOrg framework- (Kampylis et al., 2015 ; Bocconi & Lightfoot, 2021 ) can help capture a school’s digital capacity and better assess the impact of ICTs on education. Furthermore, the development of a theory of change could be a good approach for documenting the impact of digital technologies on education. Specifically, theories of change are models used for the evaluation of interventions and their impact; they are developed to describe how interventions will work and give the desired outcomes (Mayne, 2015 ). Theory of change as a methodological approach has also been used by researchers to develop models for evaluation in the field of education (e.g., Aromatario et al., 2019 ; Chapman & Sammons, 2013 ; De Silva et al., 2014 ).

We also propose that future studies aim at similar investigations by applying more holistic approaches for impact assessment that can provide in-depth data about the impact of digital technologies on education. For instance, future studies could focus on different research questions about the technologies that are used during the interventions or the way the implementation takes place (e.g., What methodologies are used for documenting impact? How are experimental studies implemented? How can teachers be taken into account and trained on the technology and its functions? What are the elements of an appropriate and successful implementation? How is the whole intervention designed? On which learning theories is the technology implementation based?).

Future research could also focus on assessing the impact of digital technologies on various other subjects since there is a scarcity of research related to particular subjects, such as geography, history, arts, music, and design and technology. More research should also be done about the impact of ICTs on skills, emotions, and attitudes, and on equality, inclusion, social interaction, and special needs education. There is also a need for more research about the impact of ICTs on administration, management, digitalization, and home-school relationships. Additionally, although new forms of teaching and learning with the use of ICTs (e.g., blended, hybrid, and online learning) have initiated several investigations in mainstream classrooms, only a few studies have measured their impact on students’ learning. Additionally, our review did not document any study about the impact of flipped classrooms on K-12 education. Regarding teaching and learning approaches, it is worth noting that studies referred to STEM or STEAM did not investigate the impact of STEM/STEAM as an interdisciplinary approach to learning but only investigated the impact of ICTs on learning in each domain as a separate subject (science, technology, engineering, arts, mathematics). Hence, we propose future research to also investigate the impact of the STEM/STEAM approach on education. The impact of emerging technologies on education, such as AR, VR, robotics, and AI has also been investigated recently, but more work needs to be done.

Finally, we propose that future studies could focus on the way in which specific factors, e.g., infrastructure and government support, school leadership and management, students’ and teachers’ digital competencies, approaches teachers utilize in the teaching and learning (e.g., blended, online and hybrid learning, flipped classrooms, STEM/STEAM approach, project-based learning, inquiry-based learning), affect the impact of digital technologies on education. We hope that future studies will give detailed insights into the concept of schools’ digital transformation through further investigation of impacts and factors which influence digital capacity and transformation based on the results and the recommendations of the present study.

Acknowledgements

This project has received funding under Grant Agreement No Ref Ares (2021) 339036 7483039 as well as funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. The UVa co-authors would like also to acknowledge funding from the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science and Innovation, under project grant PID2020-112584RB-C32.

Data availability statement

Declarations.

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• Archer K, Savage R, Sanghera-Sidhu S, Wood E, Gottardo A, Chen V. Examining the effectiveness of technology use in classrooms: A tertiary meta-analysis. Computers & Education. 2014; 78 :140–149. doi: 10.1016/j.compedu.2014.06.001. [ CrossRef ] [ Google Scholar ]
• Aromatario O, Van Hoye A, Vuillemin A, Foucaut AM, Pommier J, Cambon L. Using theory of change to develop an intervention theory for designing and evaluating behavior change SDApps for healthy eating and physical exercise: The OCAPREV theory. BMC Public Health. 2019; 19 (1):1–12. doi: 10.1186/s12889-019-7828-4. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Arztmann, M., Hornstra, L., Jeuring, J., & Kester, L. (2022). Effects of games in STEM education: A meta-analysis on the moderating role of student background characteristics. Studies in Science Education , 1-37. 10.1080/03057267.2022.2057732
• Bado N. Game-based learning pedagogy: A review of the literature. Interactive Learning Environments. 2022; 30 (5):936–948. doi: 10.1080/10494820.2019.1683587. [ CrossRef ] [ Google Scholar ]
• Balanskat, A. (2009). Study of the impact of technology in primary schools – Synthesis Report. Empirica and European Schoolnet. Retrieved 30 June 2022 from: https://erte.dge.mec.pt/sites/default/files/Recursos/Estudos/synthesis_report_steps_en.pdf
• Balanskat, A. (2006). The ICT Impact Report: A review of studies of ICT impact on schools in Europe, European Schoolnet. Retrieved 30 June 2022 from:  https://en.unesco.org/icted/content/ict-impact-report-review-studies-ict-impact-schools-europe
• Balanskat, A., Blamire, R., & Kefala, S. (2006). The ICT impact report.  European Schoolnet . Retrieved from: http://colccti.colfinder.org/sites/default/files/ict_impact_report_0.pdf
• Balyer, A., & Öz, Ö. (2018). Academicians’ views on digital transformation in education. International Online Journal of Education and Teaching (IOJET), 5 (4), 809–830. Retrieved 30 June 2022 from  http://iojet.org/index.php/IOJET/article/view/441/295
• Baragash RS, Al-Samarraie H, Moody L, Zaqout F. Augmented reality and functional skills acquisition among individuals with special needs: A meta-analysis of group design studies. Journal of Special Education Technology. 2022; 37 (1):74–81. doi: 10.1177/0162643420910413. [ CrossRef ] [ Google Scholar ]
• Bates, A. W. (2015). Teaching in a digital age: Guidelines for designing teaching and learning . Open Educational Resources Collection . 6. Retrieved 30 June 2022 from: https://irl.umsl.edu/oer/6
• Bingimlas KA. Barriers to the successful integration of ICT in teaching and learning environments: A review of the literature. Eurasia Journal of Mathematics, Science and Technology Education. 2009; 5 (3):235–245. doi: 10.12973/ejmste/75275. [ CrossRef ] [ Google Scholar ]
• Blaskó Z, Costa PD, Schnepf SV. Learning losses and educational inequalities in Europe: Mapping the potential consequences of the COVID-19 crisis. Journal of European Social Policy. 2022; 32 (4):361–375. doi: 10.1177/09589287221091687. [ CrossRef ] [ Google Scholar ]
• Bocconi S, Lightfoot M. Scaling up and integrating the selfie tool for schools' digital capacity in education and training systems: Methodology and lessons learnt. European Training Foundation. 2021 doi: 10.2816/907029,JRC123936. [ CrossRef ] [ Google Scholar ]
• Brooks, D. C., & McCormack, M. (2020). Driving Digital Transformation in Higher Education . Retrieved 30 June 2022 from: https://library.educause.edu/-/media/files/library/2020/6/dx2020.pdf?la=en&hash=28FB8C377B59AFB1855C225BBA8E3CFBB0A271DA
• Cachia, R., Chaudron, S., Di Gioia, R., Velicu, A., & Vuorikari, R. (2021). Emergency remote schooling during COVID-19, a closer look at European families. Retrieved 30 June 2022 from  https://publications.jrc.ec.europa.eu/repository/handle/JRC125787
• Çelik B. The effects of computer simulations on students’ science process skills: Literature review. Canadian Journal of Educational and Social Studies. 2022; 2 (1):16–28. doi: 10.53103/cjess.v2i1.17. [ CrossRef ] [ Google Scholar ]
• Chapman, C., & Sammons, P. (2013). School Self-Evaluation for School Improvement: What Works and Why? . CfBT Education Trust. 60 Queens Road, Reading, RG1 4BS, England.
• Chauhan S. A meta-analysis of the impact of technology on learning effectiveness of elementary students. Computers & Education. 2017; 105 :14–30. doi: 10.1016/j.compedu.2016.11.005. [ CrossRef ] [ Google Scholar ]
• Chen, Q., Chan, K. L., Guo, S., Chen, M., Lo, C. K. M., & Ip, P. (2022a). Effectiveness of digital health interventions in reducing bullying and cyberbullying: a meta-analysis. Trauma, Violence, & Abuse , 15248380221082090. 10.1177/15248380221082090 [ PubMed ]
• Chen B, Wang Y, Wang L. The effects of virtual reality-assisted language learning: A meta-analysis. Sustainability. 2022; 14 (6):3147. doi: 10.3390/su14063147. [ CrossRef ] [ Google Scholar ]
• Cheok ML, Wong SL. Predictors of e-learning satisfaction in teaching and learning for school teachers: A literature review. International Journal of Instruction. 2015; 8 (1):75–90. doi: 10.12973/iji.2015.816a. [ CrossRef ] [ Google Scholar ]
• Cheung, A. C., & Slavin, R. E. (2011). The Effectiveness of Education Technology for Enhancing Reading Achievement: A Meta-Analysis. Center for Research and reform in Education .
• Coban, M., Bolat, Y. I., & Goksu, I. (2022). The potential of immersive virtual reality to enhance learning: A meta-analysis. Educational Research Review , 100452. 10.1016/j.edurev.2022.100452
• Condie, R., & Munro, R. K. (2007). The impact of ICT in schools-a landscape review. Retrieved 30 June 2022 from: https://oei.org.ar/ibertic/evaluacion/sites/default/files/biblioteca/33_impact_ict_in_schools.pdf
• Conrads, J., Rasmussen, M., Winters, N., Geniet, A., Langer, L., (2017). Digital Education Policies in Europe and Beyond: Key Design Principles for More Effective Policies. Redecker, C., P. Kampylis, M. Bacigalupo, Y. Punie (ed.), EUR 29000 EN, Publications Office of the European Union, Luxembourg, 10.2760/462941
• Costa P, Castaño-Muñoz J, Kampylis P. Capturing schools’ digital capacity: Psychometric analyses of the SELFIE self-reflection tool. Computers & Education. 2021; 162 :104080. doi: 10.1016/j.compedu.2020.104080. [ CrossRef ] [ Google Scholar ]
• Cussó-Calabuig R, Farran XC, Bosch-Capblanch X. Effects of intensive use of computers in secondary school on gender differences in attitudes towards ICT: A systematic review. Education and Information Technologies. 2018; 23 (5):2111–2139. doi: 10.1007/s10639-018-9706-6. [ CrossRef ] [ Google Scholar ]
• Daniel SJ. Education and the COVID-19 pandemic. Prospects. 2020; 49 (1):91–96. doi: 10.1007/s11125-020-09464-3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Delcker J, Ifenthaler D. Teachers’ perspective on school development at German vocational schools during the Covid-19 pandemic. Technology, Pedagogy and Education. 2021; 30 (1):125–139. doi: 10.1080/1475939X.2020.1857826. [ CrossRef ] [ Google Scholar ]
• Delgado, A., Wardlow, L., O’Malley, K., & McKnight, K. (2015). Educational technology: A review of the integration, resources, and effectiveness of technology in K-12 classrooms. Journal of Information Technology Education Research , 14, 397. Retrieved 30 June 2022 from  http://www.jite.org/documents/Vol14/JITEv14ResearchP397-416Delgado1829.pdf
• De Silva MJ, Breuer E, Lee L, Asher L, Chowdhary N, Lund C, Patel V. Theory of change: A theory-driven approach to enhance the Medical Research Council's framework for complex interventions. Trials. 2014; 15 (1):1–13. doi: 10.1186/1745-6215-15-267. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Di Pietro G, Biagi F, Costa P, Karpiński Z, Mazza J. The likely impact of COVID-19 on education: Reflections based on the existing literature and recent international datasets. Publications Office of the European Union; 2020. [ Google Scholar ]
• Elkordy A, Lovinelli J. Competencies, Culture, and Change: A Model for Digital Transformation in K12 Educational Contexts. In: Ifenthaler D, Hofhues S, Egloffstein M, Helbig C, editors. Digital Transformation of Learning Organizations. Springer; 2020. pp. 203–219. [ Google Scholar ]
• Eng TS. The impact of ICT on learning: A review of research. International Education Journal. 2005; 6 (5):635–650. [ Google Scholar ]
• European Commission. (2020). Digital Education Action Plan 2021 – 2027. Resetting education and training for the digital age. Retrieved 30 June 2022 from  https://ec.europa.eu/education/sites/default/files/document-library-docs/deap-communication-sept2020_en.pdf
• European Commission. (2019). 2 nd survey of schools: ICT in education. Objective 1: Benchmark progress in ICT in schools . Retrieved 30 June 2022 from: https://data.europa.eu/euodp/data/storage/f/2019-03-19T084831/FinalreportObjective1-BenchmarkprogressinICTinschools.pdf
• Eurydice. (2019). Digital Education at School in Europe , Luxembourg: Publications Office of the European Union. Retrieved 30 June 2022 from: https://eacea.ec.europa.eu/national-policies/eurydice/content/digital-education-school-europe_en
• Escueta, M., Quan, V., Nickow, A. J., & Oreopoulos, P. (2017). Education technology: An evidence-based review. Retrieved 30 June 2022 from  https://ssrn.com/abstract=3031695
• Fadda D, Pellegrini M, Vivanet G, Zandonella Callegher C. Effects of digital games on student motivation in mathematics: A meta-analysis in K-12. Journal of Computer Assisted Learning. 2022; 38 (1):304–325. doi: 10.1111/jcal.12618. [ CrossRef ] [ Google Scholar ]
• Fernández-Gutiérrez M, Gimenez G, Calero J. Is the use of ICT in education leading to higher student outcomes? Analysis from the Spanish Autonomous Communities. Computers & Education. 2020; 157 :103969. doi: 10.1016/j.compedu.2020.103969. [ CrossRef ] [ Google Scholar ]
• Ferrari, A., Cachia, R., & Punie, Y. (2011). Educational change through technology: A challenge for obligatory schooling in Europe. Lecture Notes in Computer Science , 6964 , 97–110. Retrieved 30 June 2022  https://link.springer.com/content/pdf/10.1007/978-3-642-23985-4.pdf
• Fielding, K., & Murcia, K. (2022). Research linking digital technologies to young children’s creativity: An interpretive framework and systematic review. Issues in Educational Research , 32 (1), 105–125. Retrieved 30 June 2022 from  http://www.iier.org.au/iier32/fielding-abs.html
• Friedel, H., Bos, B., Lee, K., & Smith, S. (2013). The impact of mobile handheld digital devices on student learning: A literature review with meta-analysis. In Society for Information Technology & Teacher Education International Conference (pp. 3708–3717). Association for the Advancement of Computing in Education (AACE).
• Fu JS. ICT in education: A critical literature review and its implications. International Journal of Education and Development Using Information and Communication Technology (IJEDICT) 2013; 9 (1):112–125. [ Google Scholar ]
• Gaol FL, Prasolova-Førland E. Special section editorial: The frontiers of augmented and mixed reality in all levels of education. Education and Information Technologies. 2022; 27 (1):611–623. doi: 10.1007/s10639-021-10746-2. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Garzón J, Acevedo J. Meta-analysis of the impact of Augmented Reality on students’ learning gains. Educational Research Review. 2019; 27 :244–260. doi: 10.1016/j.edurev.2019.04.001. [ CrossRef ] [ Google Scholar ]
• Garzón, J., Baldiris, S., Gutiérrez, J., & Pavón, J. (2020). How do pedagogical approaches affect the impact of augmented reality on education? A meta-analysis and research synthesis. Educational Research Review , 100334. 10.1016/j.edurev.2020.100334
• Grgurović M, Chapelle CA, Shelley MC. A meta-analysis of effectiveness studies on computer technology-supported language learning. ReCALL. 2013; 25 (2):165–198. doi: 10.1017/S0958344013000013. [ CrossRef ] [ Google Scholar ]
• Haßler B, Major L, Hennessy S. Tablet use in schools: A critical review of the evidence for learning outcomes. Journal of Computer Assisted Learning. 2016; 32 (2):139–156. doi: 10.1111/jcal.12123. [ CrossRef ] [ Google Scholar ]
• Haleem A, Javaid M, Qadri MA, Suman R. Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers. 2022; 3 :275–285. doi: 10.1016/j.susoc.2022.05.004. [ CrossRef ] [ Google Scholar ]
• Hardman J. Towards a pedagogical model of teaching with ICTs for mathematics attainment in primary school: A review of studies 2008–2018. Heliyon. 2019; 5 (5):e01726. doi: 10.1016/j.heliyon.2019.e01726. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hattie J, Rogers HJ, Swaminathan H. The role of meta-analysis in educational research. In: Reid AD, Hart P, Peters MA, editors. A companion to research in education. Springer; 2014. pp. 197–207. [ Google Scholar ]
• Hattie J. Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge. 2008 doi: 10.4324/9780203887332. [ CrossRef ] [ Google Scholar ]
• Higgins S, Xiao Z, Katsipataki M. The impact of digital technology on learning: A summary for the education endowment foundation. Education Endowment Foundation and Durham University; 2012. [ Google Scholar ]
• Higgins, K., Huscroft-D’Angelo, J., & Crawford, L. (2019). Effects of technology in mathematics on achievement, motivation, and attitude: A meta-analysis. Journal of Educational Computing Research , 57(2), 283-319.
• Hillmayr D, Ziernwald L, Reinhold F, Hofer SI, Reiss KM. The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education. 2020; 153 (1038):97. doi: 10.1016/j.compedu.2020.103897. [ CrossRef ] [ Google Scholar ]
• Istenic Starcic A, Bagon S. ICT-supported learning for inclusion of people with special needs: Review of seven educational technology journals, 1970–2011. British Journal of Educational Technology. 2014; 45 (2):202–230. doi: 10.1111/bjet.12086. [ CrossRef ] [ Google Scholar ]
• Jewitt C, Clark W, Hadjithoma-Garstka C. The use of learning platforms to organise learning in English primary and secondary schools. Learning, Media and Technology. 2011; 36 (4):335–348. doi: 10.1080/17439884.2011.621955. [ CrossRef ] [ Google Scholar ]
• JISC. (2020). What is digital transformation?.  Retrieved 30 June 2022 from: https://www.jisc.ac.uk/guides/digital-strategy-framework-for-university-leaders/what-is-digital-transformation
• Kalati, A. T., & Kim, M. S. (2022). What is the effect of touchscreen technology on young children’s learning?: A systematic review. Education and Information Technologies , 1-19. 10.1007/s10639-021-10816-5
• Kalemkuş, J., & Kalemkuş, F. (2022). Effect of the use of augmented reality applications on academic achievement of student in science education: Meta-analysis review. Interactive Learning Environments , 1-18. 10.1080/10494820.2022.2027458
• Kao C-W. The effects of digital game-based learning task in English as a foreign language contexts: A meta-analysis. Education Journal. 2014; 42 (2):113–141. [ Google Scholar ]
• Kampylis P, Punie Y, Devine J. Promoting effective digital-age learning - a European framework for digitally competent educational organisations. JRC Technical Reports. 2015 doi: 10.2791/54070. [ CrossRef ] [ Google Scholar ]
• Kazu IY, Yalçin CK. Investigation of the effectiveness of hybrid learning on academic achievement: A meta-analysis study. International Journal of Progressive Education. 2022; 18 (1):249–265. doi: 10.29329/ijpe.2022.426.14. [ CrossRef ] [ Google Scholar ]
• Koh C. A qualitative meta-analysis on the use of serious games to support learners with intellectual and developmental disabilities: What we know, what we need to know and what we can do. International Journal of Disability, Development and Education. 2022; 69 (3):919–950. doi: 10.1080/1034912X.2020.1746245. [ CrossRef ] [ Google Scholar ]
• König J, Jäger-Biela DJ, Glutsch N. Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education. 2020; 43 (4):608–622. doi: 10.1080/02619768.2020.1809650. [ CrossRef ] [ Google Scholar ]
• Lawrence JE, Tar UA. Factors that influence teachers’ adoption and integration of ICT in teaching/learning process. Educational Media International. 2018; 55 (1):79–105. doi: 10.1080/09523987.2018.1439712. [ CrossRef ] [ Google Scholar ]
• Lee, S., Kuo, L. J., Xu, Z., & Hu, X. (2020). The effects of technology-integrated classroom instruction on K-12 English language learners’ literacy development: A meta-analysis. Computer Assisted Language Learning , 1-32. 10.1080/09588221.2020.1774612
• Lei, H., Chiu, M. M., Wang, D., Wang, C., & Xie, T. (2022a). Effects of game-based learning on students’ achievement in science: a meta-analysis. Journal of Educational Computing Research . 10.1177/07356331211064543
• Lei H, Wang C, Chiu MM, Chen S. Do educational games affect students' achievement emotions? Evidence from a meta-analysis. Journal of Computer Assisted Learning. 2022; 38 (4):946–959. doi: 10.1111/jcal.12664. [ CrossRef ] [ Google Scholar ]
• Liao YKC, Chang HW, Chen YW. Effects of computer application on elementary school student's achievement: A meta-analysis of students in Taiwan. Computers in the Schools. 2007; 24 (3–4):43–64. doi: 10.1300/J025v24n03_04. [ CrossRef ] [ Google Scholar ]
• Li Q, Ma X. A meta-analysis of the effects of computer technology on school students’ mathematics learning. Educational Psychology Review. 2010; 22 (3):215–243. doi: 10.1007/s10648-010-9125-8. [ CrossRef ] [ Google Scholar ]
• Liu, M., Pang, W., Guo, J., & Zhang, Y. (2022). A meta-analysis of the effect of multimedia technology on creative performance. Education and Information Technologies , 1-28. 10.1007/s10639-022-10981-1
• Lu Z, Chiu MM, Cui Y, Mao W, Lei H. Effects of game-based learning on students’ computational thinking: A meta-analysis. Journal of Educational Computing Research. 2022 doi: 10.1177/07356331221100740. [ CrossRef ] [ Google Scholar ]
• Martinez L, Gimenes M, Lambert E. Entertainment video games for academic learning: A systematic review. Journal of Educational Computing Research. 2022 doi: 10.1177/07356331211053848. [ CrossRef ] [ Google Scholar ]
• Mayne J. Useful theory of change models. Canadian Journal of Program Evaluation. 2015; 30 (2):119–142. doi: 10.3138/cjpe.230. [ CrossRef ] [ Google Scholar ]
• Moran J, Ferdig RE, Pearson PD, Wardrop J, Blomeyer RL., Jr Technology and reading performance in the middle-school grades: A meta-analysis with recommendations for policy and practice. Journal of Literacy Research. 2008; 40 (1):6–58. doi: 10.1080/10862960802070483. [ CrossRef ] [ Google Scholar ]
• OECD. (2015). Students, Computers and Learning: Making the Connection . PISA, OECD Publishing, Paris. Retrieved from: 10.1787/9789264239555-en
• OECD. (2021). OECD Digital Education Outlook 2021: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots. Retrieved from: https://www.oecd-ilibrary.org/education/oecd-digital-education-outlook-2021_589b283f-en
• Pan Y, Ke F, Xu X. A systematic review of the role of learning games in fostering mathematics education in K-12 settings. Educational Research Review. 2022; 36 :100448. doi: 10.1016/j.edurev.2022.100448. [ CrossRef ] [ Google Scholar ]
• Pettersson F. Understanding digitalization and educational change in school by means of activity theory and the levels of learning concept. Education and Information Technologies. 2021; 26 (1):187–204. doi: 10.1007/s10639-020-10239-8. [ CrossRef ] [ Google Scholar ]
• Pihir, I., Tomičić-Pupek, K., & Furjan, M. T. (2018). Digital transformation insights and trends. In Central European Conference on Information and Intelligent Systems (pp. 141–149). Faculty of Organization and Informatics Varazdin. Retrieved 30 June 2022 from https://www.proquest.com/conference-papers-proceedings/digital-transformation-insights-trends/docview/2125639934/se-2
• Punie, Y., Zinnbauer, D., & Cabrera, M. (2006). A review of the impact of ICT on learning. Working Paper prepared for DG EAC. Retrieved 30 June 2022 from: http://www.eurosfaire.prd.fr/7pc/doc/1224678677_jrc47246n.pdf
• Quah CY, Ng KH. A systematic literature review on digital storytelling authoring tool in education: January 2010 to January 2020. International Journal of Human-Computer Interaction. 2022; 38 (9):851–867. doi: 10.1080/10447318.2021.1972608. [ CrossRef ] [ Google Scholar ]
• Ran H, Kim NJ, Secada WG. A meta-analysis on the effects of technology's functions and roles on students' mathematics achievement in K-12 classrooms. Journal of computer assisted learning. 2022; 38 (1):258–284. doi: 10.1111/jcal.12611. [ CrossRef ] [ Google Scholar ]
• Ređep, N. B. (2021). Comparative overview of the digital preparedness of education systems in selected CEE countries. Center for Policy Studies. CEU Democracy Institute .
• Rott, B., & Marouane, C. (2018). Digitalization in schools–organization, collaboration and communication. In Digital Marketplaces Unleashed (pp. 113–124). Springer, Berlin, Heidelberg.
• Savva M, Higgins S, Beckmann N. Meta-analysis examining the effects of electronic storybooks on language and literacy outcomes for children in grades Pre-K to grade 2. Journal of Computer Assisted Learning. 2022; 38 (2):526–564. doi: 10.1111/jcal.12623. [ CrossRef ] [ Google Scholar ]
• Schmid RF, Bernard RM, Borokhovski E, Tamim RM, Abrami PC, Surkes MA, Wade CA, Woods J. The effects of technology use in postsecondary education: A meta-analysis of classroom applications. Computers & Education. 2014; 72 :271–291. doi: 10.1016/j.compedu.2013.11.002. [ CrossRef ] [ Google Scholar ]
• Schuele CM, Justice LM. The importance of effect sizes in the interpretation of research: Primer on research: Part 3. The ASHA Leader. 2006; 11 (10):14–27. doi: 10.1044/leader.FTR4.11102006.14. [ CrossRef ] [ Google Scholar ]
• Schwabe, A., Lind, F., Kosch, L., & Boomgaarden, H. G. (2022). No negative effects of reading on screen on comprehension of narrative texts compared to print: A meta-analysis. Media Psychology , 1-18. 10.1080/15213269.2022.2070216
• Sellar S. Data infrastructure: a review of expanding accountability systems and large-scale assessments in education. Discourse: Studies in the Cultural Politics of Education. 2015; 36 (5):765–777. doi: 10.1080/01596306.2014.931117. [ CrossRef ] [ Google Scholar ]
• Stock WA. Systematic coding for research synthesis. In: Cooper H, Hedges LV, editors. The handbook of research synthesis, 236. Russel Sage; 1994. pp. 125–138. [ Google Scholar ]
• Su, J., Zhong, Y., & Ng, D. T. K. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence , 100065. 10.1016/j.caeai.2022.100065
• Su J, Yang W. Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence. 2022; 3 :100049. doi: 10.1016/j.caeai.2022.100049. [ CrossRef ] [ Google Scholar ]
• Sung YT, Chang KE, Liu TC. The effects of integrating mobile devices with teaching and learning on students' learning performance: A meta-analysis and research synthesis. Computers & Education. 2016; 94 :252–275. doi: 10.1016/j.compedu.2015.11.008. [ CrossRef ] [ Google Scholar ]
• Talan T, Doğan Y, Batdı V. Efficiency of digital and non-digital educational games: A comparative meta-analysis and a meta-thematic analysis. Journal of Research on Technology in Education. 2020; 52 (4):474–514. doi: 10.1080/15391523.2020.1743798. [ CrossRef ] [ Google Scholar ]
• Tamim, R. M., Bernard, R. M., Borokhovski, E., Abrami, P. C., & Schmid, R. F. (2011). What forty years of research says about the impact of technology on learning: A second-order meta-analysis and validation study. Review of Educational research, 81 (1), 4–28. Retrieved 30 June 2022 from 10.3102/0034654310393361
• Tamim, R. M., Borokhovski, E., Pickup, D., Bernard, R. M., & El Saadi, L. (2015). Tablets for teaching and learning: A systematic review and meta-analysis. Commonwealth of Learning. Retrieved from: http://oasis.col.org/bitstream/handle/11599/1012/2015_Tamim-et-al_Tablets-for-Teaching-and-Learning.pdf
• Tang C, Mao S, Xing Z, Naumann S. Improving student creativity through digital technology products: A literature review. Thinking Skills and Creativity. 2022; 44 :101032. doi: 10.1016/j.tsc.2022.101032. [ CrossRef ] [ Google Scholar ]
• Tolani-Brown, N., McCormac, M., & Zimmermann, R. (2011). An analysis of the research and impact of ICT in education in developing country contexts. In ICTs and sustainable solutions for the digital divide: Theory and perspectives (pp. 218–242). IGI Global.
• Trucano, M. (2005). Knowledge Maps: ICTs in Education. Washington, DC: info Dev / World Bank. Retrieved 30 June 2022 from  https://files.eric.ed.gov/fulltext/ED496513.pdf
• Ulum H. The effects of online education on academic success: A meta-analysis study. Education and Information Technologies. 2022; 27 (1):429–450. doi: 10.1007/s10639-021-10740-8. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Underwood, J. D. (2009). The impact of digital technology: A review of the evidence of the impact of digital technologies on formal education. Retrieved 30 June 2022 from: http://dera.ioe.ac.uk/id/eprint/10491
• Verschaffel, L., Depaepe, F., & Mevarech, Z. (2019). Learning Mathematics in metacognitively oriented ICT-Based learning environments: A systematic review of the literature. Education Research International , 2019 . 10.1155/2019/3402035
• Villena-Taranilla R, Tirado-Olivares S, Cózar-Gutiérrez R, González-Calero JA. Effects of virtual reality on learning outcomes in K-6 education: A meta-analysis. Educational Research Review. 2022; 35 :100434. doi: 10.1016/j.edurev.2022.100434. [ CrossRef ] [ Google Scholar ]
• Voogt J, Knezek G, Cox M, Knezek D, ten Brummelhuis A. Under which conditions does ICT have a positive effect on teaching and learning? A call to action. Journal of Computer Assisted Learning. 2013; 29 (1):4–14. doi: 10.1111/j.1365-2729.2011.00453.x. [ CrossRef ] [ Google Scholar ]
• Vuorikari, R., Punie, Y., & Cabrera, M. (2020). Emerging technologies and the teaching profession: Ethical and pedagogical considerations based on near-future scenarios  (No. JRC120183). Joint Research Centre. Retrieved 30 June 2022 from: https://publications.jrc.ec.europa.eu/repository/handle/JRC120183
• Wang LH, Chen B, Hwang GJ, Guan JQ, Wang YQ. Effects of digital game-based STEM education on students’ learning achievement: A meta-analysis. International Journal of STEM Education. 2022; 9 (1):1–13. doi: 10.1186/s40594-022-00344-0. [ CrossRef ] [ Google Scholar ]
• Wen X, Walters SM. The impact of technology on students’ writing performances in elementary classrooms: A meta-analysis. Computers and Education Open. 2022; 3 :100082. doi: 10.1016/j.caeo.2022.100082. [ CrossRef ] [ Google Scholar ]
• Zheng B, Warschauer M, Lin CH, Chang C. Learning in one-to-one laptop environments: A meta-analysis and research synthesis. Review of Educational Research. 2016; 86 (4):1052–1084. doi: 10.3102/0034654316628645. [ CrossRef ] [ Google Scholar ]

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IMPORTANCE OF TECHNOLOGY IN EDUCATION

In the 21 st century the use of technology in teaching learning process is an important aspect which cannot be ignored at any level. Laptops, Tablets, i Pads, Smart phones are being extensively used for imparting education in place of Books and Notebooks. Now a day's Internet is used for searching the desired information and content. We prefer Internet searching about any information instead of searching in library. We are in an Era, where the information is at our finger tips with one click. This is only and only possible with the help of technology which is inseparable part of our life. Technology has completely transformed our lives and Teaching learning Process is no exception to it. How we can think about the Education without technology? This is indeed not possible at all. The Teachers, Educators and Policy Makers also recognized the importance of developing technological skills in the students so that they can be better Global Citizens. The impact of technology on Teaching Learning process is very significant and its contribution can never be ignored. The technology has completely changed the

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Engaging students in higher education with educational technology

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• Mikkel Godsk   ORCID: orcid.org/0000-0002-8332-2712 1 &
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There is a widespread agenda of improving teaching and learning in higher education by engaging students with educational technology. Based on a large-scale literature review, the article presents 61 specific, research-based recommendations for realising the engagement potential of eight types of educational technologies in higher education. These recommendations can be used, for example, by educators to incorporate specific, available educational technologies into their teaching or as an educational development method to enhance particular forms of student engagement. Based on the evidence, the article points out that some educational technologies have a more documented and sometimes also broader potential to engage the students behaviourally, affectively, and/or cognitively than others and that this likely is related to the extent the technology supports structure, active learning, communication, interaction, and activities on the higher levels on the learning taxonomies.

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1 Introduction

The use of digital educational technology is not a new phenomenon in higher education and gained traction in the early ‘70s in the form of telecourses and the ‘80s in the form of computer-assisted learning and online learning (Garrison, 1985 ). In recent years, technology has received significant attention as a means to support distance education during the COVID-19 pandemic (Abu Talib et al., 2021 ) and as a disruptor of traditional teaching, learning, and assessment forms with the advent of generative artificial intelligence (GenAI) tools such as ChatGPT, Google Gemini, and Dall-E (Farrelly & Baker, 2023 ; Godsk & Elving, 2024 ). Studies show that educational technology has the potential for improving learning outcomes, motivation, engagement, and pass rates (Garrison & Kanuka, 2004 ; Price & Kirkwood, 2011 ; Schindler et al., 2017 ), as well as the business potential for reducing costs, increasing intakes, and increasing student retention (Daniel et al., 2009 ). In higher education in Europe and English-speaking countries, student engagement is often linked to the students’ experience, satisfaction, and learning outcomes, which is why there is a widespread desire to benefit from the technology’s potential to engage students (Payne, 2019 ; Schindler et al., 2017 ). Despite the evidence and interest, universities are struggling to make effective and systematic use of technology to support student engagement (Henrie et al., 2015b ). This may be due to limited systematic evidence on how to engage students with specific educational technologies in terms of practical, concrete recommendations or guidelines, which can be directly applied by educators in their lesson planning or connection with Learning Design processes (Henrie et al., 2015b ; Schindler et al., 2017 ).

1.1 The concept of student engagement and educational technology

The concept of “student engagement” has significantly evolved and expanded within educational research and higher education. Unlike traditional views that mainly focus on observable behaviours and indicators of involvement in educational activities, such as attendance and participation, recent studies adopt broader conceptualisations, analysing how students behave, feel, and think in the context of teaching and learning (Bond et al., 2020 ; Fredricks et al., 2004 ; Henrie et al., 2015a ). This includes aspects like the general student experience and the resultant institutional reputation (Trowler, 2010 ; Wimpenny & Savin-Baden, 2013 ), viewing student engagement as an interconnected and psychosocial process influenced by personal and contextual factors (Kahu, 2013 ), “force-fields” (i.e., driving/resisting forces) for and against intrinsic and extrinsic motivation (Payne, 2019 ), or as described through three dimensions of engagement: behavioural, affective/emotional, and cognitive (Fredricks et al., 2004 ; Newmann et al., 1992 ). These dimensions are sometimes supplemented by additional dimensions such as “the will to succeed” (Kahu, 2013 ), social-behavioural engagement in the context of group work (Linnenbrink-Garcia et al., 2011 ), and student agency (Reeve & Tseng, 2011 ), which other researchers consider unnecessary, as they believe the three existing dimensions already adequately capture these aspects of student engagement (Kahu, 2013 ). These varied conceptualisations also reflect a broader debate between narrow, “mainstream”, and broad, holistic views of student engagement. The narrow view often restricts engagement to specific, measurable behaviours within classroom settings related to an effective learning process (Henrie et al., 2015b ; Zepke, 2015 ), whereas the more broad and holistic view considers engagement as encompassing a wide range of student activities, interactions, and emotions both within and beyond academic environments that contribute to a richer learning experience (Bond et al., 2020 ; Fredricks et al., 2004 ; Henrie et al., 2015b ; Zepke, 2015 ).

In addition, educational technology can involve students in teaching activities that were previously inconceivable (e.g., in virtual reality, simulations, online self-test quizzes, and GenAI-based formative feedback) (Kirkwood & Price, 2014 ; Puentedura, 2010 ; Godsk & Elving, 2024 ) and engagement can be expressed in ways and with indicators that could not previously be observed without technology (Bond & Bedenlier, 2019 ; Fredricks et al., 2004 ). This underscores the importance of not limiting focus to readily observable indicators of student engagement or confining the understanding to just one indicator, as both approaches risk overly simplifying the potential for student engagement. Such narrow focus may also overlook other forms of engagement that are indirectly related or cannot be observed without technology.

In other words, both the general desire to improve students’ learning experiences by engaging them with educational technology and the potential of the technology to engage in numerous ways that are not necessarily observable but interconnected (Payne, 2019 ) advocate for a need to adopt a broad conceptualisation of student engagement. One of the broad and widely used conceptualisations is based on Fredricks et al. ( 2004 ) and Newmann et al.’s ( 1992 ) three perspectives on student engagement and defined by Bond et al. ( 2020 ) in the context of higher education as: “The energy and effort that students employ within their learning community, observable via any number of behavioural, cognitive or affective indicators across a continuum.” (Bond et al., 2020 , p. 2). This conceptualisation extends the narrow behavioural perspective by adding affective and cognitive dimensions, including how students feel and think about their learning experiences, which may significantly affect their engagement (Fredricks et al., 2004 ). “Behavioural engagement” is typically indicated by participation, interaction, involvement, achievement, confidence, and study habits; “affective engagement” or “emotional engagement” is often indicated by positive interaction, enjoyment, attitude, motivation, and enthusiasm; and “cognitive engagement” is typically indicated by peer learning, deep learning, self-regulated learning, positive self-perception, and critical thinking (Bond et al., 2020 ; Fredricks et al., 2004 ). This breadth of Fredricks et al. ( 2004 )’s conceptualisation of student engagement, along with Bond et al. ( 2020 )’s extensive and thorough list of indicators based on a large-scale review related to the three dimensions of engagement, therefore provides a coherent and practical framework for mapping studies of educational technologies and their use to actual engagement types, including the broader, holistic views of student engagement. Although no direct relationship between introducing specific educational technologies and student engagement in higher education has been established (Schindler et al., 2017 ; see also Pickering & Swinnerton, 2019 ), studies show that technology in education does influence student engagement and that more research is needed to understand the potential of specific educational technologies and how to benefit from them (Bond & Bedenlier, 2019 ; Clark, 1994 ; Lillejord et al., 2018 ) and thus ultimately meet the widespread desire to promote student engagement with educational technology. This leads to the following research question:

How to engage students with educational technology in higher education?

A systematic literature review guided by the PRISMA process and utilising the inclusion and exclusion criteria in Table  1 was conducted to answer this question. The PRISMA process involved four steps: (1) searching for, screening and identifying relevant studies based on abstracts; (2) screening of and excluding studies that were not relevant based on full-text; (3) assessment of eligibility based on full-text; and (4) selection (‘inclusion’), coding, and analysis of the relevant studies in the final synthesis (see 6. for details). The analysis was based on a deductive and inductive coding of the studies according to educational technology, subject area, educational level, modality, type of student engagement, research method, and aim (Khan et al., 2003 ; Littell et al., 2008 ; Moher et al., 2009 ); and supplemented with follow-up searches (“Round 2”) on the identified types of educational technologies in step 4 (see details in 6. and Godsk et al, 2021 ). Fredricks et al.’s ( 2004 ) conceptualisation of student engagement as comprising three perspectives — behavioural, affective (emotional), and cognitive engagement — as well as Bond et al. ( 2020 )’s identification of 55 specific indicators related to these dimensions, served as the basis for the coding of the engagement type (see Bond et al., 2020 , Additional file 2). In Round 1, the searches were limited to empirical studies from OECD countries from 2013 onwards for maximum comparability of the educational contexts regarding teaching tradition, educational regulations, including GDPR, and the available technologies. In Round 2, there were no exclusion criteria related to country or resource type as long as the resource was scientifically robust and directly or indirectly based on empirical data. However, only resources that included firsthand empirical data were included as the basis of the synthesis and recommendations, while, for example, systematic reviews and reports were used for perspective and discussion.

In the first round, 2,154 articles were screened, and 112 empirical studies were included in the synthesis. The 112 studies document a positive or negative engagement potential of educational technology related to eight major clusters of educational technologies, hereafter referred to as “types”: (1) learning management systems, (2) discussion forums and weblogs, (3) audience response systems and tablets, (4) online quizzes, (5) social media, (6) video and audio, (7) games and gamification, and (8) virtual reality and simulation. In addition, only eight eligible studies addressed diverse technologies that did not fall within these eight types of technologies (i.e., digital curation tools, e-portfolios, peer feedback tools, haptic devices (except virtual and augmented reality), digital magazines, open badges, word clouds, and diverse or non-specified mobile technologies), thereby constituting an insufficient basis to conclude on their engagement potential and thus excluded from the article. In the second round, the eight identified types of technology were used to search more specifically for the engagement potential of each respective technology. This resulted in screening 618 new articles, of which 60 ended up being added, bringing the total number of studies and other publications included in the article to 196 (see Table  2 and Appendix  for details). The second round of searches validated and expanded the already identified recommendations, but only eight new recommendations were identified, suggesting that the list was already saturated.

The coding revealed that a wide range of subject areas were represented, including the social sciences, comprising psychology and business; natural and technical sciences; humanities; and health sciences, as well as a representation of first-year, other undergraduate, and postgraduate teaching. The coding also revealed that most included studies were based on qualitative case studies or quantitative quasi-experimental research methods involving pre- and post-studies or a control group receiving conventional teaching, analysing differences in students’ test results, activity level, perceived engagement, or attitude. However, despite the wide representation of subject areas and levels and the thorough research, it is difficult to generalise findings from these kinds of studies from various contexts. Thus, the findings and recommendations in this article build on the heterogeneity principle (Patton, 2015 ) that any common finding that emerges from a great variation suggests a potentially more general pattern and forms the basis for the recommendations for each technology collected in Table  2 .

The included studies show that educational technology can engage students in higher education behaviourally, affectively, and cognitively. However, the studies also show that this potential depends on the context, how the technology is pedagogically and didactically integrated into teaching practice, and that the potential type of engagement varies between the specific educational technologies (Vercellotti, 2018 ). The findings for actualising the engagement potential of the eight types of educational technologies are further unfolded in the following sections and Table  2 .

3.1 Learning Management Systems

Learning Management Systems (LMS) is a collective term for web-based learning platforms for developing, distributing, delivering, and administrating educational materials and activities via the Internet (Weller, 2007 ). 99% of higher education institutions have at least one platform available, of which Canvas, Blackboard, Brightspace, and Moodle are currently the most widespread (Dahlstrom & Bichsel, 2014 ). Clark et al. ( 2016 ) demonstrate that an LMS can lead to increased engagement, better student-educator interaction, and improved learning when used to structure flipped classrooms with online video lessons supplemented by face-to-face activities. Zanjani et al. ( 2017 ) also note that engagement is generally strengthened by simple structure and navigation and a manageable number of links and tools that students can customise according to their needs and preferences. Furthermore, Karaksha et al. ( 2013 ) highlight that it is relevant to remind students of the available digital tools to increase their use and engagement potential. Vercellotti ( 2018 ) compares students’ learning outcomes in online and face-to-face teaching and finds that how the technology is utilised to support an active learning pedagogy plays a crucial role, while Osman ( 2022 ) finds that combining synchronous and asynchronous activities in the LMS enhances students’ interaction and engagement and ultimately their satisfaction. Orcutt and Dringus ( 2017 ) highlight how educators’ online presence and passion for teaching influence the students’ intellectual curiosity. Wdowik ( 2014 ) highlights the opportunities to support more interaction and collaboration between educator and students, as well as among students, using the video conferencing tool in the LMS.

Another potential of LMSs is linked to their tools for tracking students’ activities, progress, and submissions (Veluvali & Surisetti, 2022 ). Lawrence et al. ( 2019 ) point out how learning analytics can promote desired study behaviour and increase behavioural engagement by identifying and assisting students at a low academic level or close to dropping out through reminders, links to resources, or other support for task completion. The study also emphasises the need to explicitly communicate expectations for online students and prepare them for online activities (Pepple, 2022 ). The tools to monitor students’ progression also influence their retention through continuous summative assessment and peer feedback, and students can monitor their learning. This can be done, for example, through the educator’s feedback on activities and tasks submitted on the e-learning platform (Holmes, 2018 ) or via peer assessment activities, where students anonymously assess each other’s activities and assignments (Mirmotahari et al., 2019 ; Sullivan & Watson, 2015 ).

3.2 Discussion forums and weblogs

Discussion forums and weblogs are typically used for asynchronous activities in which students and the educator discuss and develop ideas related to the course content and form using threaded discussions, text, and possibly multimedia independently of time and place. Most LMSs have a built-in discussion forum that the educator typically manages, whereas weblogs are often managed by the students individually. Research on this technology, in general, focuses primarily on how the technology can be used to train writing, critical thinking, reflection, and argumentation, social constructivist online teaching and peer learning, “scaffolding” (Arend, 2009 ; Dalsgaard & Paulsen, 2009 ; MacKnight, 2000 ; Salmon, 2000 ; Szabo & Schwartz, 2011 ), and how students can be activated in their learning processes (Balaji & Chakrabarti, 2010 ; Dennen, 2005 ). The included studies show that it is essential that the educator outlines the code of conduct as well as provides short, precise instructions. Additionally, open questions at an appropriate academic level that can encourage all students to participate and discussions where students can apply existing experiences or relate them to their lives can be stimulating. Likewise, the peer aspect of online discussions can contribute to developing students’ professional identity and sense of belonging, thereby increasing their participation (Willis et al, 2013 ). In addition, audiovisual media can make discussions more authentic for the students (Douglas et al., 2020 ; Harvey et al., 2018 ; Kebble, 2017 ; Page et al., 2020 ). Stimulating questions can, for example, be formulated based on Bloom’s taxonomy (Badenhorst & Mather, 2014 ; Shaw & Irwin, 2017 ), and students’ participation can be strengthened by providing exemplars of “quality discussions” (Kebble, 2017 ). It is also effective to let the discussion be based on questions and topics that are engaging for students, such as relevant cases and real situations, and that invite students to share different opinions and develop personal perspectives through reflection questions (Buelow et al., 2018 ; Fukuzawa & Boyd, 2016 ). Another important factor is the educator’s visible and active participation in the discussion forum, which can consist of relevant contributions related to the issues the students are discussing (Collins et al., 2019 ; Mokoena, 2013 ; Mooney et al., 2014 ) or guide and point out relevant teaching materials that students can work with (Fukuzawa & Boyd, 2016 ). It also has a positive effect on engagement if students are assigned roles that frame their active participation in the discussion (Mooney et al., 2014 ; Truhlar et al., 2018 ), there is a requirement to use a specific argumentation model (Oh & Kim, 2016 ), or the students’ participation is assessed according to well-defined criteria (Kebble, 2017 ; Wyatt, 2021 ). Truhlar et al. ( 2018 ) highlight that activities in which students summarise discussions stimulate higher-order thinking. Discussions with many participants and repetitive and extensive posts are experienced as frustrating, so large groups should consider this (Fukuzawa & Boyd, 2016 ; Kebble, 2017 ). Concerning weblogs in formal settings, Sharma and Tietjen ( 2016 ) demonstrate a similar effect on education, indicating that the technology is viable for supporting both students’ collaboration and meaning-making.

3.3 Audience response systems

Audience response systems and devices (ARS) are a collective term for a range of software and hardware-based technologies that allow students to participate in activities such as polls or ask questions and provide answers interactively during lectures using their computer, tablet, mobile phone, or a so-called clicker. The majority of studies find that activities involving audience response systems enhance student engagement (Çakir, 2020 ; Fischer et al., 2015 ; Funnell, 2017 ; Habel & Stubbs, 2014 ; Han & Finkelstein, 2013 ; Jozwiak, 2015 ; Kay & LeSage, 2009 ; Remón et al., 2017 ; Sawang et al., 2017 ; Shaw et al., 2015 ; Sun et al., 2014 ), and a comprehensive literature review from 2009 highlights the technology’s potential to particularly increase behavioural and cognitive engagement (Kay & LeSage, 2009 ). Shaw et al. ( 2015 ) and Lim’s ( 2017 ) studies demonstrate that digital polls with questions and answers foster a sense of cohesion between the educator and students, which is not typically experienced in large classes. The technology also provides educators with insights into students’ learning outcomes for continuous feedback and addressing their questions (McKenzie & Ziemann, 2020 ; Remón et al., 2017 ; Robson & Basse, 2018 ; Yilmaz, 2017 ) and allows students to pause the classroom if they needed more time (Dong et al., 2017 ). Polls should ideally be academically challenging (Sawang et al., 2017 ), preferably combined with group activities (Jozwiak, 2015 ) or plenary discussions in the class (Robson & Basse, 2018 ; Sawang et al., 2017 ), and ideally allow students to respond anonymously (Heaslip et al., 2014 : Remón et al., 2017 ). Notably, the opportunity to discuss the reasoning behind poll responses is crucial (Habel & Stubbs, 2014 ; Steadman, 2015 ; see also “Peer Instruction,” Crouch & Mazur, 2001 , and Thomas et al., 2017 ). It can also enhance engagement if students formulate questions themselves (Song et al., 2017 ) or if the question is open-ended, controversial, or requires ethical consideration or higher-order thinking (Campbell & Monk, 2015 ; Steadman, 2015 ; Wood & Shirazi, 2020 ). Finally, the technology can support students’ mutual dialogue through a “backchannel,” where students can discuss ongoing teaching, leading to higher student satisfaction, higher grades, and more frequent use of class content (Neustifter et al., 2016 ).

3.4 Online quizzes

In online quizzes, students can answer questions related to the subject matter. Online quizzes differ from audience response stems by being fully online and, typically, asynchronous so that they can be used and reused regardless of time and place. The activities contribute to students’ understanding and deep learning and consolidate what has been learned (Argyriou et al., 2022 ; Browne, 2019 ; Russell et al., 2016 ). Students appreciate the flexible access, the options to revisit the quizzes, and the ability to do the quizzes at their own pace (Browne, 2019 ). When quizzes are used regularly for providing feedback, it promotes students’ engagement (Browne, 2019 ; Holmes, 2015 ; Lee & Harris, 2018 ; McKenzie et al., 2013 ) and is an effective mechanism for incentivising student completion of preparatory work (Cann, 2016 ; Cook & Babon, 2017 ; Cossu et al., 2022 ). It is important to use various quiz question types (Browne, 2019 ) and provide the students with specific feedback so that they can monitor and self-regulate their studying and progression (Evans et al., 2021 ; Thomas et al., 2017 ). Combining quizzes with group activities promotes students’ engagement and learning outcomes (Balta & Awedh, 2017 ) and supports collaborative learning.

3.5 Social media

Social media is a collective term for web-based social networks where users can socialise, communicate, and share files and other information. Social media is typically not an institutionalised learning technology but often plays a role in students’ social interaction and their informal digital learning environment (frequently referred to as “personal learning environment,” PLE, see also Caviglia et al., 2018 ) or as part of the curriculum (see Delello et al., 2015 ; Megele, 2015 ). Overall, studies indicate that increased interaction and collaboration opportunities offered by the social media in terms of their flexibility and the ability to incorporate external resources contribute to enhanced motivation and interest in teaching (Camus et al., 2016 ; Cooper & Naatus, 2014 ; Chugh & Ruhi, 2018 ; Delello et al., 2015 ; Evans, 2014 ; Glowatz & Bofin, 2014 ; Graham, 2014 ; Gregory et al., 2016 ; Kent, 2013 ; Northey et al., 2015 ; Scott & Stanway, 2015 ; Sharma & Tietjen, 2016 ). Students prefer Facebook and Twitter (now “X”) over discussion forums in LMSs, as they are perceived as more accessible than the LMSs’ discussion forums (Kent, 2013 ) and are more familiar (Clements, 2015 ). However, other studies suggest that familiarity with Facebook does not guarantee its use for study purposes (Dyson et al., 2015 ; Gregory et al., 2016 ). Similarly, Cooke ( 2017 ) points out a risk that students may lose interest in the specific social media and, as a result, its value as a supplementary tool for supporting discussions if the platform is their primary learning platform and its use is mandatory (Cooke, 2017 ). Both Camus et al. ( 2016 ) and Kent ( 2013 ) note that the use of Facebook resulted in more dialogue compared to the institutionalised LMS, and Evans ( 2014 ), Tiernan ( 2014 ), and Pallas et al. ( 2019 ) find that social media can also contribute to increasing student collaboration, creating an inclusive atmosphere that increases the participation of “quiet” students and supporting deep learning (Megele, 2015 ). However, if assessment is involved, it is important to be explicit about expectations and criteria (O’Brien & Freund, 2018 ). Similarly, Barber et al. ( 2015 ) show that a “Digital Moments” course helped create meaningful online learning communities among the students. Kent ( 2013 ) also points to a different perception and use of social media and LMS. LMS is associated with formal learning, while social media is more often used for practical questions and informal collaboration. Several studies describe different ways Twitter has been used: as a channel for questions to the instructor during class (Kunka, 2020 ; Tiernan, 2014 ; Prestridge, 2014 ), as a discussion forum between students and possibly external participants (Bender, 2021 ; Dragseth, 2020 ; Megele, 2015 ), and as a channel for students to share academic examples (Prestridge, 2014 ). Diug et al. ( 2016 ) demonstrate that Twitter gave students a sense of increased access to their educators while supporting their collaboration.

3.6 Video, audio, and multimedia

Video, audio, and multimedia are used here as a broad term for synchronous and asynchronous, audiovisual and digital multimedia, such as video presentations of course content and feedback on assignments, video recordings from field trips, and video assignments, produced by both the educator, students, or external providers. Video can be used, for example, to “flip” the teaching, allowing students to watch video lectures at home, creating more time for in-class dialogue (Noetel et al., 2021 ; Willis et al., 2018 ), appealing to multiple sensory channels simultaneously (Mayer, 2008 ), and supporting more authentic communication compared to written communication (Henderson & Phillips, 2015 ; McCarthy, 2015 ; Noetel et al., 2021 ; Oh & Kim, 2016 ). Activities where students produce audio can enhance their engagement, provided they have the equipment and skills to create them (Bolliger & Armier, 2013 ). In addition, student-produced audio materials can have a socialising effect on teaching due to their authenticity and personal touch, offering variation compared to traditional written assignments (Barber et al., 2015 ; Bolliger & Armier, 2013 ). Similarly, audio and video feedback from the educator is perceived as more personal and information-rich than written feedback (Cavaleri et al., 2019 ; Pearson, 2018 ; Rasi & Vuojärvi, 2018 ; Seery, 2015 ; Zhan, 2023 ) as well as video conferences can make the educator more visible and “accessible” than in face-to-face teaching (Gleason & Greenhow, 2017 ; Ng, 2018 ; Wdowik, 2014 ), thus creating a closer connection and being perceived as more personal (Steele et al., 2018 ). Educator feedback on video is often revisited and used in later assignments (Speicher & Stollhans, 2015 ). Several studies document a generally positive attitude towards video lectures and instructions among students, providing greater flexibility and allowing more independence in the learning process compared to face-to-face teaching (O’Callaghan et al., 2017 ; Gnaur & Hüttel, 2014 ; Lin et al., 2017 ; Lupinski & Kaufman, 2023 ; Scagnoli et al., 2019 ; Seery, 2015 ; Speicher & Stollhans, 2015 ). Scagnoli et al. ( 2019 ) conclude that the more video lectures students watch, the more positively they perceive the medium. However, they also emphasise the importance of familiarity with and experience using video for learning purposes, students’ academic level (postgraduate students are more positive than undergraduates), and how well the video lectures are integrated into the course. In addition, Brame ( 2016 ) stresses the importance of minimising students’ cognitive load when watching the videos — a parallel theme to research on “attention span,” which ambiguously indicates various durations students can maintain concentration depending on the context, teaching format, subject matter, and the students’ characteristics (Bradbury, 2016 ; Hartley & Davies, 1978 ). However, there are also studies highlighting the risk of a more superficial learning approach (Francescucci & Rohani, 2019 ; Trenholm et al., 2019 ), lower learning outcomes (Roberts, 2015 ), lower attendance in class (O’Callaghan et al., 2017 ), and lower engagement with video lectures where in particular the low-performing students are at risk (Murphy & Stewart, 2015 ). Lin et al. ( 2017 ) point out that students found concrete, instructional videos for laboratory work more useful and essential for their learning than video lectures of a generally more conceptual nature. However, the longer the videos are, the fewer students will watch them to the end (Lin et al., 2017 ). Video combined with other activities such as quizzes, small assignments, group work, or individual feedback positively impacts student engagement (Brame, 2016 ; Gnaur & Hüttel, 2014 ; Jozwiak, 2015 ; Paiva et al., 2017 ). In addition, student-produced video and audio for learning and assessment purposes may also positively impact students’ learning experience and contribute to the development of their communication, knowledge construction, and teamwork skills (Arsenis et al., 2022 ; Mathany & Dodd, 2018 ; Morena et al., 2019 ), for example, in the form of digital storytelling, which can also contribute to developing social and cultural competencies (Grant & Bolin, 2016 ; Ribiero, 2016 ; Yousuf & Conlan, 2018 ).

3.7 Games and gamification

Games and gamification as educational technology involve activities with various forms of game elements such as leaderboards, points, badges, or other forms of rewards or competition. The technology distinguishes itself from online quizzes by extensively using entertainment and possible competitive elements to motivate students’ participation and learning (Educause Learning Initiative, 2011 ). Subhash and Cudney ( 2018 ) find in their review that the elements mentioned above increase, in particular, the students’ attitude, level of participation, motivation, and performance. However, several studies also highlight the importance of authenticity and its relation to reality. Edmonds and Smith ( 2017 ) find that mobile learning games can engage students if they involve interactive investigations of phenomena with fellow students and involve them as designers of similar games. Similarly, Buckley and Doyle ( 2016 ) find that involving games with real-world dilemmas and decisions increases student engagement. However, it is important to note that students who are already gamers are more positive towards games in education than other students (Davis et al., 2018 ). Bawa ( 2019 ), Plump and LaRosa ( 2017 ), and Holbrey ( 2020 ) find that the game-inspired polling tool Kahoot can increase student engagement and participation in education if used for students to play together in groups against other groups, collaboratively create quizzes for other groups based on the curriculum, and this subsequently forms the basis for discussion among the students. Viswanathan and Radhakrishnan ( 2018 ) document in this context that students find it engaging to be co-developers of a game and that it supports their critical thinking. The combination of games and collaboration is also highlighted by Christopoulos et al. ( 2018 ), who, in their study, emphasise the importance of both the interaction among students and the function of the game. For example, individual games that test students’ knowledge will only be engaging for a few students (Christopoulos et al., 2018 ).

3.8 Virtual reality and simulation

Virtual reality (VR) and simulation are computer-generated simulations of an environment where educators and students can interact via a computer or, for example, through a dedicated headset (Makransky & Petersen, 2019 ). Studies indicate a general increase in engagement, especially due to the sense of presence (Cavanaugh et al., 2023 ; Chulkov & Wang, 2020 ; Papanastasiou et al., 2019 ; Rafiq et al., 2022 ), the simulated first-hand experiences that would have been impossible in the real world (Di Natale et al., 2020 ) for instance, interacting with three-dimensional virtual molecular phenomena (Elford et al., 2021 ), doing virtual field trips in Google Earth (McDaniel, 2022 ), use virtual microscopes for manipulation of online images (Herodotou et al., 2020 ) and provide variation for the students in the learning process (Hayes et al., 2021 ). However, opinions on the technology may be divided, and reservations among students often stem from a lack of experience and comfort in participating and interacting in VR (Francescucci & Foster, 2013 ). Francescucci and Foster ( 2013 ) and Makransky and Lilleholt ( 2018 ) find it essential to ensure that students have a high level of autonomy through a sense of control and active learning when using the technology, while others find it important that educators have the qualifications to use VR for learning purposes, give time for students to get familiar with the technology and have access to support in initial phases (Nesenbergs et al., 2020 ; Pellas et al., 2021 ). Luo et al. ( 2021 ) find that activities in VR can benefit from being combined with non-VR activities, including group or educator debriefings related to the VR activities. Pellas and Kazanidis ( 2015 ) found significantly positive learning outcomes and engagement results for teaching conducted solely in Second Life, compared to combined Second Life and face-to-face teaching. Matthew & Butler’s ( 2017 ) study showed that video from Second Life was suitable for simulating authentic problems, positively influencing students’ engagement and learning outcomes. Similarly, Sobocan and Klemenc-Ketis ( 2017 ) document that virtual patients in teaching for diagnosis and medical practice are perceived as beneficial due to the increased opportunities for skill training. Likewise, a positive effect on student engagement is demonstrated in simulations. Pallas et al. ( 2019 ) identify how simulations can increase students’ online interaction and reflection, including involving otherwise quiet students. Irby et al. ( 2018 ) and Marques et al. ( 2014 ) point out that virtual laboratories can be just as engaging as working in a physical laboratory and, in some situations, primarily introductory modules, completely replace face-to-face laboratory work.

4 Discussion

Overall, the included studies document the potential of educational technology to engage students in higher education behaviourally, affectively, and cognitively, which is dependent on the context, integration, and the specific educational technology as well as the specific technology’s support for structure, active learning, communication, and interaction between students and/or educators (Fig.  1 , further developed from Schindler et al., 2017 ). Furthermore, the synthesis indicates that each of the eight technologies has the potential to support all three forms of engagement, of which some are more well-documented than others and that they are interconnected.

Overview of the potential of educational technology for student engagement

Across 64 studies, the impact on students’ behavioural engagement is documented, particularly in the context of LMSs, discussion forums, audience response systems, online quizzes, social media, video and audio, and virtual reality and simulations. The studies document that technologies suitable for conveying curriculum content, creating structure, providing assessment tasks, and facilitating interaction and active learning effectively support students’ behavioural engagement. The interaction between students and content, educators, and peers is crucial for behavioural engagement (McCallum et al., 2015 ) as well as a course organisation with clear learning goals, logical course structures, recurring activities, and regular interactions with peers and educators contribute to behavioural engagement, satisfaction, and learning (Gray & DiLoreto, 2016 ; Gross et al., 2015 ; Porcaro et al., 2016 ; Ravenscroft & Luhanga, 2018 ; Ravishankar et al., 2018 ). Thus, this also shows how structure influences students’ affective engagement. Muir et al. ( 2019 ) highlight the importance of assessment tasks, workload, work-life balance, assignment quality, and educator presence. While online activities can enhance retention and engagement (Callahan, 2016 ), Dumford & Miller, ( 2018 ) note a link between students’ preferences and experience with online learning. Studies emphasise the flexibility of access to online teaching materials, with video lectures freeing up time for more engaging in-class activities (Steen-Utheim & Foldnes, 2018 ).

The impact of technology on students’ affective engagement is highly linked to how it influences the communication and interaction between students and educators, as documented in 59 studies. Communication tools within the LMS, discussion forums for peer learning, social media, competitive game elements, VR and simulations, and other audiovisual media can play a key role in this context. In general, technologies facilitating multi-faceted communication and interaction and educator involvement are often effective for affective engagement (Vayre & Vonthron, 2017 ). Educator presence, social support, figurative language, and effective facilitation are pivotal factors in online settings (Dixson et al., 2017 ; O’Shea et al., 2015 ; Orcutt & Dringus, 2017 ; Yates et al., 2014 ). Nevertheless, students’ low technological skills can negatively impact their affective engagement (Butz et al., 2016 ; Vayre & Vonthron, 2017 ), and some students may prefer using technologies they are already familiar with (del Barrio-Garcia et al., 2015 ). While students generally have experience with and a positive attitude towards technology in education, they may lack the skills to use technology in their academic work (Kim et al., 2019 ). Technology and online teaching can also hinder students’ involvement in the informal, implicit aspects of academic work (Selwyn, 2016 ).

The cognitive engagement is documented in 46 studies and notably supported by technologies such as audio and video, virtual reality and simulations, and audience response systems used to facilitate active and flexible student involvement in high taxonomic learning activities, such as collaboration, problem-solving, reflection, authentic exploration, and hypothesis testing. Flexible technology access supports self-directed learning, motivating students to engage actively (Mello, 2016 ; Mihret et al., 2017 ). McGuinness and Fulton ( 2019 ) illustrate the value of online tutorials as a flexible supplement to in-class teaching, aiding students in self-paced learning. Mihret et al.’s ( 2017 ) case-based teaching, combined with online discussions and ongoing e-portfolio assessment, enhances self-directed learning compared to face-to-face participation. However, high flexibility may negatively impact affective engagement due to the self-discipline required (McCallum et al., 2015 ). The technology may also support adaptive learning involving diagnostic quizzes, individual materials, formative tests, lectures, and summative tests that enhance satisfaction, performance, and cognitive engagement, as McKenzie et al. ( 2013 ) and Pourdana ( 2022 ) demonstrated. Technology supporting pedagogical strategies, like Baum’s ( 2013 ) guided inquiry, blends short video lectures and self-organised problem-solving, proving less confusing than traditional teaching. Gibbings et al. ( 2015 ) highlight the role of technology in providing authentic online activities and fostering communication, collaboration, and personal development despite geographical distances. Activities that challenge students’ understanding of societal issues, entertaining elements, and connections to past experiences also enhance cognitive and affective engagement (Buelow et al., 2018 ; O’Shea et al., 2015 ).

4.1 Breadth and Interconnectedness

When looking across the three types of engagement, there is no clear pattern in which technologies that engage students in more than one way. However, as also stressed by Payne ( 2019 ) and Fredricks et al. ( 2004 ), engagement is often interconnected, and indicators can be ambiguous. This interconnectedness is notably evident from the 25 included studies on specific technologies and background studies that document the technology’s potential to engage students in multiple ways simultaneously as well as from the studies that investigate the impact of technology-enhanced learning designs in education (e.g., Gray & DiLoreto, 2016 ; Gross et al., 2015 ; Porcaro et al., 2016 ; Ravenscroft & Luhanga, 2018 ; Ravishankar et al., 2018 ). Audience response systems and video, audio, and multimedia appeared most frequently in the studies of specific technologies, with seven and five studies, respectively, and three studies demonstrated a potential to support all three types of engagement simultaneously (Chulkov & Wang, 2020 , on VR, and Christopoulos et al., 2018 , on games and gamification; and Neustifter et al., 2016 , on audience response systems). The varying documented breadth may be due to a narrow focus of the individual studies, but it may also suggest a diverse potential to support student engagement more broadly. Furthermore, it may indicate that it often does not make sense to talk about a specific type of engagement potential as they are often interconnected and/or prerequisites for each other, just as important indicators can be overlooked. For example, Bond et al. ( 2020 ) categorise “confidence” as a (direct) indicator of affective engagement as well as an (indirect) indicator of behavioural engagement. The rationale is that the students’ confidence with the technology is manifested in their constructive behaviour. Likewise, cognitive engagement can manifest as self-regulated behaviour or simple memorisation (Fredricks et al., 2004 ).

Overall, the conceptual framework of student engagement by Fredricks et al. ( 2004 ) and the indicators provided by Bond et al. ( 2020 ) are useful for capturing a broad spectrum of the concept. This includes both observable behaviours, traditionally associated with narrow understandings of student engagement and the broader understandings, where student engagement is linked to experience, satisfaction, learning outcomes, and various affective and cognitive factors. This broader conceptualisation also addresses the additional dimensions proposed by Kahu ( 2013 ), Linnenbrink-Garcia et al. ( 2011 ), and Reeve and Tseng ( 2011 ). Furthermore, these frameworks accommodate indicators that may be overlooked without technology. For example, the use of technology allows for the observation of student engagement in online peer feedback activities (Mirmotahari et al., 2019 ) and supports self-regulated behaviours through online quizzes that enable students to monitor their progress and receive automated feedback (Evans et al., 2021 ; McKenzie et al., 2013 ; Thomas et al., 2017 ). However, the results suggest that one should place little importance on the actual classification but rather consider whether a given indicator may point to multiple types of engagement and be connected to other indicators.

4.2 How to Engage Students with Educational Technology in Higher Education?

The answer to the research question depends on the type of engagement one wishes to support, available technologies, and the specific context and educator competencies. For instance, to increase students’ behavioural engagement, educators may utilise technologies that provide structure and support active content delivery, such as LMSs, ARSs, and online quizzes, and follow the provided recommendations (Table  2 ). Those aiming to increase students’ affective engagement can benefit from technologies supporting student interaction, like discussion forums, social media, and games. Educators wanting to support students’ cognitive engagement can use simulations to aid students in authentic exploration of a given topic, have the students produce their own video, or facilitate structured online discussions. If there is a need to engage students behaviourally, affectively, and/or cognitively at the same time, it is relevant to consider technologies with a documented, broad engagement potential. However, if the educational technology is already provided, the recommendations provided (Table  2 ) can increase the chances of engaging students with the respective technology.

4.3 Limitations

The study in this article has revealed limitations related to the concept of student engagement and an inherent limitation associated with the research methods of the available studies.

The term “engagement” is ambiguous in English and may refer to attending something in a broad sense (Payne, 2019 ) or, in a narrow sense, referring to student behaviour in class (Zepke, 2015 ). Conversely, studies may deal with student engagement without necessarily using the term. A similar limitation is seen in the naming of educational technologies, which are often referred to by the name of the software or hardware and not necessarily by the type of technology, which is why it is easy to overlook relevant studies with a traditional protocol-driven search strategy based on keywords.

In addition, the study confirmed that engagement can be interconnected and indicators can be ambiguous. This is not a problem per se in realising the technology’s engagement potential but rather a problem in analysing studies that investigate and document a narrow engagement potential. Thus, further validation and mapping of the interconnectedness of Bond et al. ( 2020 )'s indicators would be useful.

Finally, there is a limitation that relates to the nature of the available studies, which are often characterised by qualitative case and quasi-experimental studies and other research methodologies in which it is difficult to distinguish the cause of the effect from other factors such as the novelty effect (McKechnie, 2008 ), the redesign of teaching that the introduction of technology entails (Kirkwood & Price, 2014 ), and the context (Schindler et al., 2017 ) and thus also to generalise findings. This calls for more research on the significance of the teaching context, including course design, course delivery, and other contextual factors.

5 Conclusion and implications

The article has identified the potential of educational technology to support students’ behavioural, affective, and cognitive engagement, along with a series of specific recommendations on how to realise this potential. These recommendations can be used, for example, by educators to incorporate specific, available educational technologies into their teaching or as an educational development method to enhance particular forms of student engagement. Educators and educational developers can use these recommendations to qualify the use of educational technology for student engagement in higher education. While the studies highlight various engagement potentials of educational technology, the synthesis also revealed that whether this potential is realised is dependent on the context, integration, the specific technology, and the educator’s competencies in teaching with technology (see also Orcutt & Dringus, 2017 , and Schindler et al., 2017 ). Furthermore, the synthesis also shows that all included technologies can support all three kinds of engagement, that engagement is often interconnected, and that technologies may vary in how broad their engagement potential is. Therefore, the recommendations should be viewed for what they are — practical guidelines derived from what was effective in another context — and should always be adjusted based on what is possible and relevant in the given situation. One cannot expect a specific effect on learning outcomes or student engagement simply by introducing a specific educational technology, and only few studies investigate aspects such as the importance of context, the role of the educator, how students interact, and what happens in the actual learning process (e.g., Bertheussen & Myrland, 2016 ; Butz et al., 2016 ; Evans, 2014 ; Steen-Utheim & Foldnes, 2018 ; Vercellotti, 2018 ). This calls for more research on the influence of course context and delivery on student engagement.

The synthesis also revealed that many aspects that determine whether the potential is realised are recognisable from traditional face-to-face teaching. For example, the educator’s active role as a facilitator of learning, active involvement of students, and consideration for students and their needs are crucial, as well as the technical support, feedback, authenticity, and learning environment. This is not surprising but important to remember when designing and delivering technology-enhanced, blended, and online learning. Careful considerations should be made for both the design and delivery of teaching: What is the purpose of educational technology, what potential does this technology hold for student engagement, and what determines whether this potential is realised? Thus, if all forms of engagement are to be supported by technology, the educator must have competencies in structuring, developing, and delivering technology-enhanced teaching, as well as taking the possibilities, engagement broadness, and limitations of the technology into account. Furthermore, the educator must be able to communicate and involve students in an activating way in high-taxonomic learning activities, as well as support students’ communication and interaction through suitable technology.

Data availability

The review is based on published research and other publicly available resources. A search protocol can be obtained from the authors upon reasonable request.

Abu Talib, M., Bettayeb, A. M., & Omer, R. I. (2021). Analytical study on the impact of technology in higher education during the age of COVID-19: Systematic literature review. Education and Information Technologies, 26 , 6719–6746. https://doi.org/10.1007/s10639-021-10507-1

Article   Google Scholar  

Arend, B. (2009). Encouraging critical thinking in online threaded discussions. Journal of Educators Online, 6 (1), n1. https://doi.org/10.9743/JEO.2009.1.1

Argyriou, P., Benamar, K., & Nikolajeva, M. (2022). What to Blend? Exploring the relationship between student engagement and academic achievement via a blended learning approach. Psychology Learning & Teaching, 21 (2), 126–137. https://doi.org/10.1177/14757257221091512

Arsenis, P., Flores, M., & Petropoulou, D. (2022). Enhancing graduate employability skills and student engagement through group video assessment. Assessment & Evaluation in Higher Education, 47 (2), 245–258. https://doi.org/10.1080/02602938.2021.1897086

Badenhorst, C., & Mather, C. (2014). Blogging geographies. Journal of Geography in Higher Education, 38 (2), 193–207. https://doi.org/10.1080/03098265.2014.908276

Balaji, M. S., & Chakrabarti, D. (2010). Student interactions in online discussion forum: Empirical research from ‘media richness theory’ perspective. Journal of Interactive Online Learning , 9 (1), 1-22.

Balta, N., & Awedh, M. H. (2017). The effect of student collaboration in solving physics problems using an online interactive response system. European Journal of Educational Research, 6 (3), 385–394. https://doi.org/10.12973/eu-jer.6.3.385

Barber, W., King, S., & Buchanan, S. (2015). Problem based learning and authentic assessment in digital pedagogy: Embracing the role of collaborative communities. Electronic Journal of e-Learning, 13 (2), 59–67.

Google Scholar  

Baum, E. J. (2013). Augmenting guided-inquiry learning with a blended classroom approach. Journal of College Science Teaching, 42 (6), 27–33.

Bawa, P. (2019). Using Kahoot to Inspire. Journal of Educational Technology Systems, 47 (3), 373–390. https://doi.org/10.1177/0047239518804173

Bender, R. M. (2021). From snaps to maps: Using literature, mobile applications, and mapping software to design an engaging L2 curriculum. Hispania, 104 (4), 557–570. https://doi.org/10.1353/hpn.2021.0126

Bertheussen, B. A., & Myrland, Ø. (2016). Relation between academic performance and students’ engagement in digital learning activities. Journal of Education for Business, 91 (3), 125–131. https://doi.org/10.1080/08832323.2016.1140113

Bolliger, D. U., & Armier, D. D., Jr. (2013). Active learning in the online environment: The integration of student-generated audio files. Active Learning in Higher Education, 14 (3), 201–211. https://doi.org/10.1177/1469787413498032

Bond, M., & Bedenlier, S. (2019). Facilitating student engagement through educational technology: Towards a conceptual framework. Journal of Interactive Media in Education, 2019 (1). Retrieved July 28, 2024, from https://jime.open.ac.uk/articles/10.5334/jime.528/

Bond, M., Buntins, K., Bedenlier, S., Zawacki-Richter, O., & Kerres, M. (2020). Mapping research in student engagement and educational technology in higher education: A systematic evidence map. International Journal of Educational Technology in Higher Education, 17 , 1–30. https://doi.org/10.1186/s41239-019-0176-8

Bradbury, N. A. (2016). Attention span during lectures: 8 seconds, 10 minutes, or more? Advances in Physiology Education, 40 (4). https://doi.org/10.1152/advan.00109.2016

Brame, C. J. (2016). Effective educational videos: Principles and guidelines for maximizing student learning from video content. CBE—Life Sciences Education, 15 (4), es6. https://doi.org/10.1187/cbe.16-03-0125

Browne, C. J. (2019). Assessing the engagement rates and satisfaction levels of various clinical health science student sub-groups using supplementary eLearning resources in an introductory anatomy and physiology unit. Health Education, 119 (1), 2–17. https://doi.org/10.1108/HE-04-2018-0020

Buckley, P., & Doyle, E. (2016). Gamification and Student Motivation. Interactive Learning Environments, 24 (6), 1162–1175. https://doi.org/10.1080/10494820.2014.964263

Buelow, J. R., Barry, T., & Rich, L. E. (2018). Supporting learning engagement with online students. Online Learning, 22 (4), 313–340. https://doi.org/10.24059/olj.v22i4.1384

Butz, N. T., Stupnisky, R. H., Pekrun, R., Jensen, J. L., & Harsell, S. M. (2016). The impact of emotions on student achievement in synchronous hybrid business and public administration programs: A longitudinal test of control-value theory. Decision Sciences Journal of Innovative Education, 14 (4), 441–474. https://doi.org/10.1111/dsji.12110

Çakir, A. M. K. (2020). Engaging students with questions: Attitudes towards using student response systems in higher education. Journal of Learning and Teaching in Digital Age, 5 (1), 24–34.

MathSciNet   Google Scholar  

Callahan, J. T. (2016). Assessing online homework in first-semester Calculus. PRIMUS, 26 (6), 545–556. https://doi.org/10.1080/10511970.2015.1128501

Campbell, C., & Monk, S. (2015). Introducing a learner response system to pre-service education students: Increasing student engagement. Active Learning in Higher Education, 16 (1), 25–36. https://doi.org/10.1177/1469787414558981

Camus, M., Hurt, N. E., Larson, L. R., & Prevost, L. (2016). Facebook as an online teaching tool: Effects on student participation, learning, and overall course performance. College Teaching, 64 (2), 84–94. https://doi.org/10.1080/87567555.2015.1099093

Cann, A. J. (2016). Increasing student engagement with practical classes through online pre-lab quizzes. Journal of Biological Education, 50 (1), 101–112. https://doi.org/10.1080/00219266.2014.986182

Cavaleri, M., Kawaguchi, S., Di Biase, B., & Power, C. (2019). How recorded audio-visual feedback can improve academic language support. Journal of University Teaching & Learning Practice, 16 (4). https://doi.org/10.53761/1.16.4.6

Cavanaugh, G., Condry, H. M., Afable, C. F., Morris, M., De, S., Madison, H. E., & Weiner, M. (2023). Immersive learning and participatory engagement: Connecting in the online classroom through virtual reality. International Journal of Distance Education Technologies (IJDET), 21 (1), 1–19. https://doi.org/10.4018/IJDET.317364

Caviglia, F., Dalsgaard, C., Davidsen, J., & Ryberg, T. (2018). Studerendes digitale læringsmiljøer: læringsplatform eller medieøkologi? Tidsskriftet Læring og Medier (LOM), 10 (18). https://doi.org/10.7146/lom.v10i18.96928

Christopoulos, A., Conrad, M., & Shukla, M. (2018). Interaction with educational games in hybrid virtual worlds. Journal of Educational Technology Systems, 46 (4), 385–413. https://doi.org/10.1177/0047239518757986

Chugh, R., & Ruhi, U. (2018). Social media in higher education: A literature review of facebook. Education and Information Technologies, 23 (2), 605–616. https://doi.org/10.1007/s10639-017-9621-2

Chulkov, D., & Wang, X. (2020). The educational value of simulation as a teaching strategy in a finance course. e-Journal of Business Education and Scholarship of Teaching, 14 (1), 40–56.

Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Development, 42 (2), 21–29. https://doi.org/10.1007/BF02299088

Clark, R. M., Besterfield-Sacre, M., Budny, D., Bursic, K. M., Clark, W. W., Norman, B. A., Parker, R. S., Patzer, I. I., & Slaughter, W. S. (2016). Flipping engineering courses: A school wide initiative. Advances in Engineering Education, 5 (3), 1–39.

Clements, J. C. (2015). Using facebook to enhance independent student engagement: A case study of first-year undergraduates. Higher Education Studies, 5 (4), 131–146. https://doi.org/10.5539/hes.v5n4p131

Cooke, S. (2017). Social teaching: Student perspectives on the inclusion of social media in higher education. Education and Information Technologies, 22 (1), 255–269. https://doi.org/10.1007/s10639-015-9444-y

Collins, K., Groff, S., Mathena, C., & Kupczynski, L. (2019). Asynchronous video and the development of instructor social presence and student engagement. Turkish Online Journal of Distance Education, 20 (1), 53–70. https://doi.org/10.17718/tojde.522378

Cook, B. R., & Babon, A. (2017). Active learning through online quizzes: Better learning and less (busy) work. Journal of Geography in Higher Education, 41 (1), 24–38. https://doi.org/10.1080/03098265.2016.1185772

Cooper, B., & Naatus, M. K. (2014). LinkedIn as a learning tool in business education. American Journal of Business Education (AJBE), 7 (4), 299–306. https://doi.org/10.19030/ajbe.v7i4.8815

Cossu, R., Awidi, I., & Nagy, J. (2022). Can we use online technology to rejig the traditional laboratory experience to improve student engagement? Higher Education Pedagogies, 7 (1), 1–19. https://doi.org/10.1080/23752696.2022.2068155

Crouch, C. H., & Mazur, E. (2001). Peer instruction: Ten years of experience and results. American Journal of Physics, 69 (9), 970–977. https://doi.org/10.1119/1.1374249

Dahlstrom, E., & Bichsel, J. (2014). ECAR study of undergraduate students and information technology, 2014 . Educause. Retrieved July 28, 2024, from https://library.educause.edu/~/media/files/library/2014/10/ers1406-pdf.pdf?la=en

Dalsgaard, C., & Paulsen, M. F. (2009). Transparency in cooperative online education. International Review of Research in Open and Distributed Learning , 10 (3). https://doi.org/10.19173/irrodl.v10i3.671

Daniel, J., Kanwar, A., & Uvalić-Trumbić, S. (2009). Breaking higher education’s iron triangle: Access, cost, and quality. Change: The Magazine of Higher Learning, 41 (2), 30–35. https://doi.org/10.3200/CHNG.41.2.30-35

Davis, K., Sridharan, H., Koepke, L., Singh, S., & Boiko, R. (2018). Learning and engagement in a gamified course: Investigating the effects of student characteristics. Journal of Computer Assisted Learning, 34 (5), 492–503. https://doi.org/10.1111/jcal.12254

Del Barrio-Garcia, S., Arquero, J. L., & Romero-Frías, E. (2015). Personal learning environments acceptance model: The role of need for cognition, e-learning satisfaction and students’ perceptions. Journal of Educational Technology & Society, 18 (3), 129–141.

Delello, J. A., McWhorter, R. R., & Camp, K. M. (2015). Using social media as a tool for learning: A multi-disciplinary study. International Journal on E-Learning, 14 (2), 163–180.

Dennen, V. P. (2005). From message posting to learning dialogues: Factors affecting learner participation in asynchronous discussion. Distance Education, 26 (1), 127–148. https://doi.org/10.1080/01587910500081376

Di Natale, A. F., Repetto, C., Riva, G., & Villani, D. (2020). Immersive virtual reality in K-12 and higher education: A 10‐year systematic review of empirical research. British Journal of Educational Technology, 51 (6), 2006–2033. https://doi.org/10.1111/bjet.13030

Diug, B., Kendal, E., & Ilic, D. (2016). Evaluating the use of twitter as a tool to increase engagement in medical education. Education for Health, 29 (3), 223–230. https://doi.org/10.4103/1357-6283.204216

Dixson, M. D., Greenwell, M. R., Rogers-Stacy, C., Weister, T., & Lauer, S. (2017). Nonverbal immediacy behaviors and online student engagement: Bringing past instructional research into the present virtual classroom. Communication Education, 66 (1), 37–53. https://doi.org/10.1080/03634523.2016.1209222

Dong, J. J., Hwang, W. Y., Shadiev, R., & Chen, G. Y. (2017). Pausing the classroom lecture: The use of clickers to facilitate student engagement. Active Learning in Higher Education, 18 (2), 157–172. https://doi.org/10.1177/1469787417707617

Douglas, T., James, A., Earwaker, L., Mather, C., & Murray, S. (2020). Online discussion boards: Improving practice and student engagement by harnessing facilitator perceptions. Journal of University Teaching & Learning Practice, 17 (3). https://doi.org/10.53761/1.17.3.7

Dragseth, M. R. (2020). Building student engagement through social media. Journal of Political Science Education, 16 (2), 243–256. https://doi.org/10.1080/15512169.2018.155042

Dumford, A. D., & Miller, A. L. (2018). Online learning in higher education: Exploring advantages and disadvantages for engagement. Journal of Computing in Higher Education, 30 (3), 452–465. https://doi.org/10.1007/s12528-018-9179-z

Dyson, B., Vickers, K., Turtle, J., Cowan, S., & Tassone, A. (2015). Evaluating the use of Facebook to increase student engagement and understanding in lecture-based classes. Higher Education, 69 (2), 303–313. https://doi.org/10.1007/s10734-014-9776-3

Edmonds, R., & Smith, S. (2017). From playing to designing: Enhancing educational experiences with location-based mobile learning games. Australasian Journal of Educational Technology, 33 (6), 41–53. https://doi.org/10.14742/ajet.3583

Educause Learning Initiative. (2011). Seven things you should know about gamification. Educause. Retrieved July 28, 2024 from: https://library.educause.edu/-/media/files/library/2011/8/eli7075-pdf.pdf

Elford, D., Lancaster, S. J., & Jones, G. A. (2021). Stereoisomers, not stereo enigmas: A stereochemistry escape activity incorporating augmented and immersive virtual reality. Journal of Chemical Education, 98 (5), 1691–1704. https://doi.org/10.1021/acs.jchemed.0c01283

Evans, C. (2014). Twitter for teaching: Can social media be used to enhance the process of learning? British Journal of Educational Technology, 45 (5), 902–915. https://doi.org/10.1111/bjet.12099

Evans, T., Kensington-Miller, B., & Novak, J. (2021). Effectiveness, efficiency, engagement: Mapping the impact of pre-lecture quizzes on educational exchange. Australasian Journal of Educational Technology, 37 (1), 163–177. https://doi.org/10.14742/ajet.6258

Farrelly, T., & Baker, N. (2023). Generative artificial intelligence: Implications and considerations for higher education practice. Education Sciences, 13 (11). https://doi.org/10.3390/educsci13111109

Fischer, C. M., Hoffman, M. S., Casey, N. C., & Cox, M. P. (2015). Software-based student response systems: An interdisciplinary initiative. Journal of Learning in Higher Education, 11 (2), 33–39.

Francescucci, A., & Foster, M. (2013). The VIRI (virtual, interactive, Real-Time, Instructor-Led) Classroom: The impact of blended synchronous online courses on student performance, engagement, and satisfaction. Canadian Journal of Higher Education, 43 (3), 78–91.

Francescucci, A., & Rohani, L. (2019). Exclusively synchronous online (VIRI) learning: The impact on student performance and engagement outcomes. Journal of Marketing Education, 41 (1), 60–69. https://doi.org/10.1177/0273475318818864

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74 (1), 59–109. https://doi.org/10.3102/00346543074001059

Fukuzawa, S., & Boyd, C. (2016). Student engagement in a large classroom: Using technology to generate a hybridized problem-based learning experience in a large first year undergraduate class. Canadian Journal for the Scholarship of Teaching and Learning, 7 (1), 1–17. https://doi.org/10.5206/cjsotl-rcacea.2016.1.7

Funnell, P. (2017). Using audience response systems to enhance student engagement and learning in information literacy teaching. Journal of Information Literacy , 11 (2). https://doi.org/10.11645/11.2.2238

Garrison, D. R. (1985). Three generations of technological innovations in distance education. Distance Education, 6 (2), 235–241. https://doi.org/10.1080/0158791850060208

Garrison, D. R., & Kanuka, H. (2004). Blended learning: Uncovering its transformative potential in higher education. The Internet and Higher Education, 7 (2), 95–105. https://doi.org/10.1016/j.iheduc.2004.02.001

Gibbings, P., Lidstone, J., & Bruce, C. (2015). Students’ experience of problem-based learning in virtual space. Higher Education Research and Development, 34 (1), 74–88. https://doi.org/10.1080/07294360.2014.934327

Gleason, B., & Greenhow, C. (2017). Hybrid learning in higher education: The potential of teaching and learning with robot-mediated communication. Online Learning, 21 (4), 159–176. https://doi.org/10.24059/olj.v21i4.1276

Glowatz, M., & Bofin, L. (2014). Enhancing student engagement through social media. A school of business case study. EAI Endorsed Transactions on e-Learning , 1 (4). https://doi.org/10.4108/el.1.4.e4

Godsk, M., & Elving, P.R. (2024). ChatGPT for Learning in Higher Education: Benefits, Downsides, and Implications. Journal of Interactive Learning Research, 35 (1), 31-69. Waynesville, NC: Association for the Advancement of Computing in Education (AACE). Retrieved July 28, 2024 from https://www.learntechlib.org/primary/p/222471/

Godsk, M., Kristiansen, B., & Møller, K. L. (2021). Digital læringsteknologis potentiale for studerendes engagement. Pædagogisk indblik 12. DPU. Aarhus University Press. Retrieved July 28, 2024 from https://unipress.dk/media/18273/12-digital-laeringsteknologis-potentiale-for-studerendes-engagement.pdf

Gnaur, D., & Hüttel, H. (2014). How a flipped learning environment affects learning in a course on theoretical computer science. Advances in Web-Based Learning – ICWL 2014 (pp. 219–228). Springer International Publishing. https://doi.org/10.1007/978-3-319-09635-3_25

Chapter   Google Scholar  

Graham, M. (2014). Social media as a tool for increased student participation and engagement outside the classroom in higher education. Journal of Perspectives in Applied Academic Practice, 2 (3), 16. https://doi.org/10.14297/jpaap.v2i3.113

Grant, N. S., & Bolin, B. L. (2016). Digital storytelling: A method for engaging students and increasing cultural competency. Journal of Effective Teaching, 16 (3), 44–61.

Gray, J. A., & DiLoreto, M. (2016). The effects of student engagement, student satisfaction, and perceived learning in online learning environments. International Journal of Educational Leadership Preparation, 11 (1), 1–20.

Greenhalgh, T., & Peacock, R. (2005). Effectiveness and efficiency of search methods in systematic reviews of complex evidence: Audit of primary sources. Bmj, 331 (7524), 1064–1065. https://doi.org/10.1136/bmj.38636.593461.68

Gregory, P. L., Gregory, K. M., & Eddy, E. R. (2016). Factors contributing to student engagement in an instructional facebook group for undergraduate mathematics. Journal of Computers in Mathematics and Science Teaching, 35 (3), 249–268.

Gross, B., Marinari, M., Hoffman, M., DeSimone, K., & Burke, P. (2015). Flipped @ SBU: Student satisfaction and the college classroom. Educational Research Quarterly, 39 (2), 36–52.

Habel, C., & Stubbs, M. (2014). Mobile phone voting for participation and engagement in a large compulsory law course. Association for learning technology journal. Research in Learning Technology, 22 , 1–15. https://doi.org/10.3402/rlt.v22.19537

Han, J. H., & Finkelstein, A. (2013). Understanding the effects of professors’ pedagogical development with clicker assessment and feedback technologies and the impact on students’ engagement and learning in higher education. Computers & Education, 65 (2013), 64–76. https://doi.org/10.1016/j.compedu.2013.02.002

Hartley, J., & Davies, I. K. (1978). Note-taking: A critical review. Programmed Learning and Educational Technology, 15 (3), 207–224. https://doi.org/10.1080/0033039780150305

Harvey, T., Carlson, J., Struck, M., & Moroz, K. (2018). Feeling real: Social presence within online discussions. Distance Learning, 15 (4), 13–27.

Hayes, A., Daughrity, L. A., & Meng, N. (2021). Approaches to integrate virtual reality into K-16 lesson plans: An introduction for teachers. TechTrends, 65 , 394–401. https://doi.org/10.1007/s11528-020-00572-7

Heaslip, G., Donovan, P., & Cullen, J. G. (2014). Student response systems and learner engagement in large classes. Active Learning in Higher Education, 15 (1), 11–24. https://doi.org/10.1177/1469787413514648

Henderson, M., & Phillips, M. (2015). Video-based feedback on student assessment: Scarily personal. Australasian Journal of Educational Technology, 31 (1), 51–66. https://doi.org/10.14742/ajet.1878

Henrie, C. R., Bodily, R., Manwaring, K. C., & Graham, C. R. (2015a). Exploring intensive longitudinal measures of student engagement in blended learning. International Review of Research in Open and Distributed Learning, 16 (3), 131–155. https://doi.org/10.19173/irrodl.v16i3.2015

Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015b). Measuring student engagement in technology-mediated learning: A review. Computers & Education, 90 , 36–53. https://doi.org/10.1016/j.compedu.2015.09.005

Herodotou, C., Muirhead, D. K., Aristeidou, M., Hole, M. J., Kelley, S., Scanlon, E., & Duffy, M. (2020). Blended and online learning: A comparative study of virtual microscopy in higher education. Interactive Learning Environments, 28 (6), 713–728. https://doi.org/10.1080/10494820.2018.1552874

Holbrey, C. E. (2020). Kahoot! Using a game-based approach to blended learning to support effective learning environments and student engagement in traditional lecture theatres. Technology Pedagogy and Education, 29 (2), 191–202. https://doi.org/10.1080/1475939X.2020.1737568

Holmes, N. (2015). Student perceptions of their learning and engagement in response to the Use of a continuous E-Assessment in an undergraduate module. Assessment & Evaluation in Higher Education, 40 (1), 1–14. https://doi.org/10.1080/02602938.2014.881978

Holmes, N. (2018). Engaging with assessment: Increasing student engagement through continuous assessment. Active Learning in Higher Education, 19 (1), 23–34. https://doi.org/10.1177/1469787417723230

Irby, S. M., Borda, E. J., & Haupt, J. (2018). Effects of implementing a hybrid wet lab and online module lab curriculum into a general chemistry course: Impacts on student performance and engagement with the chemistry triplet. Journal of Chemical Education, 95 (2), 224–232. https://doi.org/10.1021/acs.jchemed.7b00642

Jozwiak, J. (2015). Helping students to succeed in general education political science courses? Online assignments and in-class activities. International Journal of Teaching and Learning in Higher Education, 27 (3), 393–406.

Kahu, E. R. (2013). Framing student engagement in higher education. Studies in Higher Education, 38 (5), 758–773. https://doi.org/10.1080/03075079.2011.598505

Karaksha, A., Grant, G., Anoopkumar-Dukie, S., Nirthanan, S. N., & Davey, A. K. (2013). Student engagement in pharmacology courses using online learning tools. American Journal of Pharmaceutical Education, 77 (6). https://doi.org/10.5688/ajpe776125

Kay, R. H., & LeSage, A. (2009). Examining the benefits and challenges of using audience response systems: A review of the literature. Computers & Education, 53 (3), 819–827. https://doi.org/10.1016/j.compedu.2009.05.001

Kebble, P. G. (2017). Assessing online asynchronous communication strategies designed to enhance large student cohort engagement and foster a community of learning. Journal of Education and Training Studies, 5 (8), 92–100. https://doi.org/10.11114/jets.v5i8.2539

Kent, M. (2013). Changing the conversation: Facebook as a venue for online class discussion in higher education. Journal of Online Learning and Teaching, 9 (4), 546–565.

Khan, K. S., Kunz, R., Kleijnen, J., & Antes, G. (2003). Five steps to conducting a systematic review. Journal of the Royal Society of Medicine, 96 (3), 118–121. https://doi.org/10.1177/014107680309600304

Kim, H. J., Hong, A. J., & Song, H. D. (2019). The roles of academic engagement and digital readiness in students’ achievements in university e-learning environments: Revista De Universidad Y Sociedad Del Conocimiento. International Journal of Educational Technology in Higher Education, 16 (1), 1–18. https://doi.org/10.1186/s41239-019-0152-3

Kirkwood, A., & Price, L. (2014). Technology-enhanced learning and teaching in higher education: What is ‘enhanced’ and how do we know? A critical literature review. Learning Media and Technology, 39 (1), 6–36. https://doi.org/10.1080/17439884.2013.770404

Kunka, B. A. (2020). Twitter in higher education: increasing student engagement. Educational Media International, 57 (4), 316–331. https://doi.org/10.1080/09523987.2020.1848508

Lawrence, J., Brown, A., Redmond, P., & Basson, M. (2019). Engaging the disengaged: Exploring the use of course-specific learning analytics and nudging to enhance online student engagement. Student Success, 10 (2), 47–58. https://doi.org/10.5204/ssj.v10i2.1295

Lee, E., & Harris, R. (2018). The effects of online glossary quizzes and student autonomy on domain vocabulary learning in business law. Journal of Computing in Higher Education, 30 (2), 326–343. https://doi.org/10.1007/s12528-018-9183-3

Lillejord, S., Børte, K., Nesje, K., & Ruud, E. (2018). Learning and teaching with technology in higher education–a systematic review (Vol. 2, pp. 40–64). Knowledge Centre for Education.

Lim, W. N. (2017). Improving student engagement in higher education through mobile-based interactive teaching model using socrative. In 2017 IEEE Global Engineering Education Conference (EDUCON) (pp. 404–412). IEEE.

Lin, S. Y., Aiken, J. M., Seaton, D. T., Douglas, S. S., Greco, E. F., Thoms, B. D., & Schatz, M. F. (2017). Exploring physics students’ engagement with online instructional videos in an introductory mechanics course. Physical Review Physics Education Research, 13 (2), 020138–020131. https://doi.org/10.1103/PhysRevPhysEducRes.13.020138

Linnenbrink-Garcia, L., Rogat, T. K., & Koskey, K. L. (2011). Affect and engagement during small group instruction. Contemporary Educational Psychology, 36 (1), 13–24. https://doi.org/10.1016/j.cedpsych.2010.09.001

Littell, J. H., Corcoran, J., & Pillai, V. (2008). Systematic reviews and meta-analysis. Oxford University Press . https://doi.org/10.1093/acprof:oso/9780195326543.001.0001

Luo, H., Li, G., Feng, Q., Yang, Y., & Zuo, M. (2021). Virtual reality in K-12 and higher education: A systematic review of the literature from 2000 to 2019. Journal of Computer Assisted Learning, 37 (3), 887–901. https://doi.org/10.1111/jcal.12538

Lupinski, K., & Kaufman, M. (2023). Exploring student perceptions, Engagement, and satisfaction with instructor made videos in online courses. International Journal on E-Learning , 43–73. Retrieved July 28, 2024, from https://www.learntechlib.org/primary/p/219870/ . Association for the Advancement of Computing in Education (AACE).

MacKnight, C. B. (2000). Teaching critical thinking through online discussions. Educause Quarterly, 23 (4), 38–41.

Makransky, G., & Lilleholt, L. (2018). A structural equation modelling investigation of the emotional value of immersive virtual reality in education. Educational Technology Research and Development, 66 (5), 1141–1164. https://doi.org/10.1007/s11423-018-9581-2

Makransky, G., & Petersen, G. B. (2019). Investigating the process of learning with desktop virtual reality: A structural equation modeling approach. Computers & Education, 134 , 15–30.

Marques, M. A., Viegas, M. C., Costa-Lobo, M. C., Fidalgo, A. V., Alves, G. R., Rocha, J. S., & Gustavsson, I. (2014). How remote labs impact on course outcomes: Various practices using VISIR. IEEE Transactions on Education, 57 (3), 151–159.

Mathany, C., & Dodd, J. (2018). Student-generated interview podcasts: An assignment template. Collected Essays on Learning and Teaching . https://doi.org/10.22329/celt.v11i0.4971

Matthew, A., & Butler, D. (2017). Narrative, Machinima and cognitive realism: Constructing an authentic real-world learning experience for law students. Australasian Journal of Educational Technology, 33 (1), 148–162. https://doi.org/10.14742/ajet.2846

Mayer, R. E. (2008). Applying the science of learning: Evidence-based principles for the design of multimedia instruction. American Psychologist, 63 (8). https://doi.org/10.1037/0003-066X.63.8.760

McCallum, S., Schultz, J., Sellke, K., & Spartz, J. (2015). An examination of the flipped classroom approach on college student academic involvement. International Journal of Teaching and Learning in Higher Education, 27 (1), 42–55.

McCarthy, J. (2015). Evaluating written, audio and video feedback in higher education summative assessment tasks. Issues in Educational Research, 25 (2), 153–169.

McDaniel, P. N. (2022). Teaching, learning, and exploring the geography of North America with virtual globes and geovisual narratives. Journal of Geography, 121 (4), 125–140. https://doi.org/10.1080/00221341.2022.2119597

McGuinness, C., & Fulton, C. (2019). Digital literacy in higher education: A case study of student engagement with e-Tutorials using blended learning. Journal of Information Technology Education: Innovations in Practice, 18 , 1–28. https://doi.org/10.28945/4190

McKechnie, L. E. F. (2008). Reactivity. In L. M. Given (Ed.), The SAGE Encyclopedia of Qualitative Research Methods . SAGE Publications, Inc.

McKenzie, M., & Ziemann, M. (2020). Assessment of the web-based audience response system socrative for biomedical science revision classes. International Journal of Educational Research Open, 1 ,. https://doi.org/10.1016/j.ijedro.2020.100008

McKenzie, W. A., Perini, E., Rohlf, V., Toukhsati, S., Conduit, R., & Sanson, G. (2013). A blended learning lecture delivery model for large and diverse undergraduate cohorts. Computers & Education, 64 , 116–126. https://doi.org/10.1016/j.compedu.2013.01.009

Megele, C. (2015). eABLE: Embedding social media in academic curriculum as a learning and assessment strategy to enhance students learning and E-Professionalism. Innovations in Education and Teaching International, 52 (4), 414–425. https://doi.org/10.1080/14703297.2014.890951

Mello, L. V. (2016). Fostering postgraduate student engagement: Online resources supporting self-directed learning in a diverse cohort. Research in Learning Technology, 24 , 1–16. https://doi.org/10.3402/rlt.v24.29366

Mihret, D. G., Abayadeera, N., Watty, K., & McKay, J. (2017). Teaching auditing using cases in an online learning environment: The role of ePortfolio Assessment. Accounting Education, 26 (4), 335–357. https://doi.org/10.1080/09639284.2017.1292466

Mirmotahari, O., Berg, Y., Fremstad, E., & Damsa, C. (2019). Student engagement by employing student peer reviews with criteria-based assessment. In IEEE Global Engineering Education Conference (EDUCON) (pp. 1152–1157). Dubai, United Arab Emirates. https://doi.org/10.1109/EDUCON.2019.8725174

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., Prisma Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS med, 6 (7), e1000097. https://doi.org/10.1136/bmj.b2535

Mokoena, S. (2013). Engagement with and participation in online discussion forums. Turkish Online Journal of Educational Technology-TOJET, 12 (2), 97–105.

Mooney, M., Southard, S., & Burton, C. H. (2014). Shifting from obligatory discourse to rich dialogue: Promoting student interaction in asynchronous threaded discussion postings. Online Journal of Distance Learning Administration, 17 (1), 1–12.

Morena, M. A., Smith, S., & Talbert, R. (2019). Video made the calculus star. Primus, 29 (1), 43–55. https://doi.org/10.1080/10511970.2017.1396568

Muir, T., Milthorpe, N., Stone, C., Dyment, J., Freeman, E., & Hopwood, B. (2019). Chronicling engagement: Students’ experience of online learning over time. Distance Education, 40 (2), 262–277. https://doi.org/10.1080/01587919.2019.1600367

Murphy, C. A., & Stewart, J. C. (2015). The impact of online or F2F lecture choice on student achievement and engagement in a large lecture-based science course: Closing the gap. Online Learning, 19 (3), 91–110. https://doi.org/10.24059/olj.v19i3.536

Nesenbergs, K., Abolins, V., Ormanis, J., & Mednis, A. (2020). Use of augmented and virtual reality in remote higher education: A systematic umbrella review. Education Sciences, 11 (1). https://doi.org/10.3390/educsci11010008

Neustifter, R., Kukkonen, T., Coulter, C., & Landry, S. (2016). Introducing backchannel technology into a large undergraduate course. Canadian Journal of Learning and Technology, 42 (1), 1–22.

Newmann, F. M., Wehlage, G. G., & Lamborn, S. D. (1992). The significance and sources of student engagement. In F. Newmann (Ed.), Student engagement and achievement in American secondary schools (pp. 11–39). Teachers College Press.

Ng, K. (2018). Implementation of new communication tools to an online chemistry course. Journal of Educators Online, 15 (1), 1–6. https://doi.org/10.9743/JEO2018.15.1.8

Noetel, M., Griffith, S., Delaney, O., Sanders, T., Parker, P., del Pozo Cruz, B., & Lonsdale, C. (2021). Video improves learning in higher education: A systematic review. Review of Educational Research, 91 (2), 204–236. https://doi.org/10.3102/0034654321990713

Northey, G., Bucic, T., Chylinski, M., & Govind, R. (2015). Increasing student engagement using asynchronous learning. Journal of Marketing Education, 37 (3), 171–180. https://doi.org/10.1177/0273475315589814

O’Brien, M., & Freund, K. (2018). Lessons learned from introducing social media use in undergraduate economics research. International Journal of Education and Development Using ICT , 14 (1). https://www.learntechlib.org/p/183552/

O’Callaghan, F. V., Neumann, D. L., Jones, L., & Creed, P. A. (2017). The use of lecture recordings in higher education: A review of institutional, student, and lecturer issues. Education and Information Technologies, 22 , 399–415. https://doi.org/10.1007/s10639-015-9451-z

O’Shea, S. E., Stone, C., & Delahunty, J. (2015). I ‘Feel’ like I am at University even though I am online. Exploring how students narrate their engagement with higher education institutions in an online learning environment. Distance Education, 36 (1), 41–58. https://doi.org/10.1080/01587919.2015.1019970

Oh, E. G., & Kim, H. S. (2016). Understanding cognitive engagement in online discussion: Use of a scaffolded, audio-based argumentation activity. International Review of Research in Open and Distributed Learning, 17 (5), 28–48. https://doi.org/10.19173/irrodl.v17i5.2456

Orcutt, J. M., & Dringus, L. P. (2017). Beyond being there: Practices that establish presence, engage students and influence intellectual curiosity in a structured online learning environment. Online Learning, 21 (3), 15–35. https://doi.org/10.24059/olj.v21i3.1231

Osman, S. Z. M. (2022). Combining synchronous and asynchronous learning: Student satisfaction with online learning using learning management systems. Journal of Education and E-Learning Research, 9 (3), 147–154. https://doi.org/10.20448/jeelr.v9i3.4103

Page, L., Hullett, E. M., & Boysen, S. (2020). Are you a robot? Revitalizing online learning and discussion boards for today’s modern learner. The Journal of Continuing Higher Education, 68 (2), 128–136. https://doi.org/10.1080/07377363.2020.1745048

Paiva, R. C., Ferreira, M. S., & Frade, M. M. (2017). Intelligent tutorial system based on personalized system of instruction to teach or remind mathematical concepts. Journal of Computer Assisted Learning, 33 (4), 370–381. https://doi.org/10.1111/jcal.12186

Pallas, J., Eidenfalk, J., & Engel, S. (2019). Social networking sites and learning in international relations: The impact of platforms. Australasian Journal of Educational Technology, 35 (1), 16–27. https://doi.org/10.14742/ajet.3637

Papanastasiou, G., Drigas, A., Skianis, C., Lytras, M., & Papanastasiou, E. (2019). Virtual and augmented reality effects on K-12, higher and tertiary education students’ twenty-first century skills. Virtual Reality, 23 , 425–436. https://doi.org/10.1007/s10055-018-0363-2

Patton, M. Q. (2015). Qualitative designs and data collection (4th ed.). Sage Publications.

Payne, L. (2019). Student engagement: Three models for its investigation. Journal of Further and Higher Education, 43 (5), 641–657. https://doi.org/10.1080/0309877X.2017.1391186

Pearson, J. (2018). Engaging practical students through audio feedback. Practitioner Research in Higher Education, 11 (1), 87–94.

Pellas, N., & Kazanidis, I. (2015). On the value of second life for students’ engagement in blended and online courses: A comparative study from the higher education in Greece. Education and Information Technologies, 20 (3), 445–466. https://doi.org/10.1007/s10639-013-9294-4

Pellas, N., Mystakidis, S., & Kazanidis, I. (2021). Immersive virtual reality in K-12 and higher education: A systematic review of the last decade scientific literature. Virtual Reality, 25 (3), 835–861. https://doi.org/10.1007/s10639-013-9294-4

Pepple, D. G. (2022). An ecological perspective of student engagement through digital technology: Practical application and implications. British Educational Research Journal, 48 (6), 1216–1231.  https://doi.org/10.1002/berj.3823

Pickering, J. D., & Swinnerton, B. J. (2019). Exploring the dimensions of medical student engagement with technology-enhanced learning resources and assessing the impact on assessment outcomes. Anatomical Sciences Education, 12 (2), 117–128. https://doi.org/10.1002/ase.1810

Plump, C. M., & LaRosa, J. (2017). Using Kahoot! In the classroom to create engagement and active learning: A game-based technology solution for eLearning novices. Management Teaching Review, 2 (2), 151–158. https://doi.org/10.1177/2379298116689783

Porcaro, P. A., Jackson, D. E., McLaughlin, P. M., & O’Malley, C. J. (2016). Curriculum design of a flipped classroom to enhance haematology learning. Journal of Science Education and Technology, 25 (3), 345–357. https://doi.org/10.1007/s10956-015-9599-8

Pourdana, N. (2022). Impacts of computer-assisted diagnostic assessment on sustainability of L2 learners’ collaborative writing improvement and their engagement modes. Asian-Pacific Journal of Second and Foreign Language Education, 7 (1), 11. https://doi.org/10.1186/s40862-022-00139-4

Prestridge, S. (2014). A focus on students’ Use of Twitter – their interactions with each other, content and interface. Active Learning in Higher Education, 15 (2), 101–115. https://doi.org/10.1177/1469787414527394

Price, L., & Kirkwood, A. (2011). Enhancing professional learning and teaching through technology: A synthesis of evidence-based practice among teachers in higher education. Higher Education Academy . Retrieved from: http://oro.open.ac.uk/30686/1/1_PLATP_main_report.pdf . https://doi.org/10.1080/17439884.2012.696543

Puentedura, R. (2010). SAMR and TPCK: Intro to Advanced Practice. http://hippasus.com/resources/sweden2010/SAMR_TPCK_IntroToAdvancedPractice.pdf . Accessed 30 July 2013.

Rafiq, A. A., Triyono, M. B., & Djatmiko, I. W. (2022). Enhancing student engagement in vocational education by using virtual reality. Waikato Journal of Education, 27 (3), 175–188. https://doi.org/10.15663/wje.v27i3.964

Rasi, P., & Vuojärvi, H. (2018). Toward personal and emotional connectivity in mobile higher education through asynchronous formative audio feedback. British Journal of Educational Technology, 49 (2), 292–304. https://doi.org/10.1111/bjet.12587

Ravenscroft, B., & Luhanga, U. (2018). Enhancing student engagement through an institutional blended learning initiative: A case study. Teaching & Learning Inquiry, 6 (2), 97–114. https://doi.org/10.20343/teachlearninqu.6.2.8

Ravishankar, J., Epps, J., & Ambikairajah, E. (2018). A flipped mode teaching approach for large and advanced electrical engineering courses. European Journal of Engineering Education, 43 (3), 413–426. https://doi.org/10.1080/03043797.2017.1383974

Reeve, J., & Tseng, C. M. (2011). Agency as a fourth aspect of students’ engagement during learning activities. Contemporary Educational Psychology, 36 (4), 257–267. https://doi.org/10.1016/j.cedpsych.2011.05.002

Remón, J., Sebastián, V., Romero, E., & Arauzo, J. (2017). Effect of using smartphones as clickers and tablets as digital whiteboards on students’ engagement and learning. Active Learning in Higher Education, 18 (2), 173–187. https://doi.org/10.1177/1469787417707618

Ribiero, S. P. M. (2016). Developing intercultural awareness using digital storytelling. Language and Intercultural Communication, 16 (1), 69–82. https://doi.org/10.1080/14708477.2015.1113752

Roberts, J. C. (2015). Evaluating the effectiveness of lecture capture: Lessons learned from an undergraduate political research class. Journal of Political Science Education, 11 (1), 45–60. https://doi.org/10.1080/15512169.2014.985104

Robson, D., & Basse, B. (2018). Advantages and disadvantages of an innovative tablet technology learning activity: A ten year case study in small tertiary mathematics classrooms. Journal of Information Technology Education: Innovations in Practice, 17 , 225–239. https://doi.org/10.28945/4165

Russell, J. E., Van Horne, S., Ward, A. S., Bettis, I. I. I., Sipola, E. A., Colombo, M., & Rocheford, M. K. (2016). Large lecture transformation: Adopting evidence-based practices to increase student engagement and performance in an introductory science course. Journal of Geoscience Education, 64 (1), 37–51. https://doi.org/10.5408/15-084.1

Salmon, G. (2000). E-Moderating: The key to teaching and learning online (1st ed.). Routledge.

Sawang, S., O’Connor, P., & Ali, M. (2017). IEngage: Using technology to enhance students’ engagement in a large classroom. Journal of Learning Design, 10 (1), 11–19. https://doi.org/10.5204/jld.v9i3.292

Scagnoli, N. I., Choo, J., & Tian, J. (2019). Students’ insights on the Use of video lectures in online classes. British Journal of Educational Technology, 50 (1), 399–414. https://doi.org/10.1111/bjet.12572

Schindler, L. A., Burkholder, G. J., Morad, O. A., et al. (2017). Computer-based technology and student engagement: A critical review of the literature. International Journal of Educational Technology in Higher Education, 14 (25), 1–28. https://doi.org/10.1186/s41239-017-0063-0

Scott, O. K. M., & Stanway, A. R. (2015). Tweeting the lecture: How social media can increase student engagement in higher education. Sport Management Education Journal (Human Kinetics) , 9 (2). https://doi.org/10.1123/SMEJ.2014-0038

Seery, M. K. (2015). ConfChem conference on flipped classroom: Student engagement with flipped chemistry lectures. Journal of Chemical Education, 92 (9), 1566–1567. https://doi.org/10.1021/ed500919u

Selwyn, N. (2016). Digital downsides: Exploring University Students’ negative engagements with digital technology. Teaching in Higher Education, 21 (8), 1006–1021. https://doi.org/10.1080/13562517.2016.1213229

Sharma, P., & Tietjen, P. (2016). Examining patterns of participation and meaning making in student blogs: A case study in higher education. American Journal of Distance Education, 30 (1), 2–13. https://doi.org/10.1080/08923647.2016.1119605

Shaw, C. S., & Irwin, K. C. (2017). Forum quality or quantity: What is driving student engagement online? Online Journal of Distance Learning Administration, 20 (3).

Shaw, J., Kominko, S., & Terrion, J. L. (2015). Using lecturetools to enhance student-instructor relations and student engagement in the large class. Research in Learning Technology, 23 , 1–14. https://doi.org/10.3402/rlt.v23.27197

Sobocan, M., & Klemenc-Ketis, Z. (2017). Medical students’ attitudes towards the use of virtual patients. Journal of Computer Assisted Learning, 33 (4), 393–402. https://doi.org/10.1111/jcal.12190

Song, D., Oh, E. Y., & Glazewski, K. (2017). Student-generated questioning activity in second language courses using a customized personal response system: A case study. Educational Technology Research and Development, 65 (6), 1425–1449. https://doi.org/10.1007/s11423-017-9520-7

Speicher, O., & Stollhans, S. (2015). Feedback on feedback: does it work? Proceedings of the 2015 EUROCALL Conference , Padova, Italy, (pp. 507–511). Dublin: Research-publishing.net.

Steadman, R. G. (2015). Establishing an atmosphere for critical thinking in the online classroom. Journal of Instructional Research, 4 , 3–11.

Steele, J. P., Robertson, S. N., & Mandernach, B. J. (2018). Beyond content: The value of instructor-student connections in the online classroom. Journal of the Scholarship of Teaching and Learning, 18 (4), 130–150. https://doi.org/10.14434/josotl.v18i4.23430

Steen-Utheim, A. T., & Foldnes, N. (2018). A qualitative investigation of student engagement in a flipped classroom. Teaching in Higher Education, 23 (3), 307–324. https://doi.org/10.1080/13562517.2017.1379481

Subhash, S., & Cudney, E. A. (2018). Gamified learning in higher education: A systematic review of the literature. Computers in Human Behavior, 87 , 192–206. https://doi.org/10.1016/j.chb.2018.05.028

Sullivan, D., & Watson, S. (2015). Peer assessment within hybrid and online courses: Students’ view of its potential and performance. Journal of Educational Issues, 1 (1), 1–18. https://doi.org/10.5296/jei.v1i1.7255

Sun, J. C. Y., Martinez, B., & Seli, H. (2014). Just-in-time or plenty-of-time teaching? Different electronic feedback devices and their effect on Student Engagement. Journal of Educational Technology & Society, 17 (2), 234–244.

Szabo, Z., & Schwartz, J. (2011). Learning methods for teacher education: The use of online discussions to improve critical thinking. Technology Pedagogy and Education, 20 (1), 79–94. https://doi.org/10.1080/1475939X.2010.534866

Thomas, M. P., Türkay, S., & Parker, M. (2017). Explanations and interactives improve subjective experiences in Online Courseware. International Review of Research in Open and Distributed Learning, 18 (7), 213–241. https://doi.org/10.19173/irrodl.v18i7.3076

Tiernan, P. (2014). A study of the use of twitter by students for lecture engagement and discussion. Education and Information Technologies, 19 (4), 673–690. https://doi.org/10.1007/s10639-012-9246-4

Trenholm, S., Hajek, B., Robinson, C. L., Chinnappan, M., Albrecht, A., & Ashman, H. (2019). Investigating undergraduate Mathematics learners’ cognitive engagement with recorded lecture videos. International Journal of Mathematical Education in Science and Technology, 50 (1), 3–24. https://doi.org/10.1080/0020739X.2018.1458339

Trowler, V. (2010). Student engagement literature review. The Higher Education Academy, 11 (1), 1–15.

Truhlar, A. M., Walter, M. T., & Williams, K. M. (2018). Student engagement with course content and peers in synchronous online discussions. Online Learning, 22 (4), 289–312. https://doi.org/10.24059/olj.v22i4.1389

Vayre, E., & Vonthron, A. M. (2017). Psychological Engagement of students in Distance and Online Learning: Effects of Self-Efficacy and Psychosocial processes. Journal of Educational Computing Research, 55 (2), 197–218. https://doi.org/10.1177/0735633116656849

Veluvali, P., & Surisetti, J. (2022). Learning management system for greater learner engagement in higher education—a review. Higher Education for the Future, 9 (1), 107–121. https://doi.org/10.1177/23476311211049855

Vercellotti, M. L. (2018). Do interactive learning spaces increase student achievement? A comparison of Classroom Context. Active Learning in Higher Education, 19 (3), 197–210. https://doi.org/10.1177/1469787417735606

Viswanathan, S., & Radhakrishnan, B. (2018). A novel ’Game Design’ methodology for STEM Program. International Journal of Game-Based Learning, 8 (4), 1–17.

Wdowik, S. (2014). Using a synchronous online learning environment to promote and enhance transactional engagement beyond the classroom. Campus-Wide Information Systems, 31 (4), 264–275. https://doi.org/10.1108/CWIS-10-2013-0057

Weller, M. (2007). Virtual learning environments: Using, choosing and developing your VLE . Routledge.

Book   Google Scholar  

Willis, J., Davis, K., & Chaplin, S. (2013). Sociocultural affordances of online peer Engagement. Journal of Learning Design, 6 (1), 34–45.

Willis, R., Yeigh, T., Lynch, D., Smith, R., Provost, S., Sell, K., & Turner, D. (2018). Towards a strategic blend in education: A review of the blended learning literature . Oxford Global Press.

Wimpenny, K., & Savin-Baden, M. (2013). Alienation, agency and authenticity: A synthesis of the literature on student engagement. Teaching in Higher Education, 18 (3), 311–326. https://doi.org/10.1080/13562517.2012.725223

Wood, R., & Shirazi, S. (2020). A systematic review of audience response systems for teaching and learning in higher education: The student experience. Computers & Education, 153 ,. https://doi.org/10.1016/j.compedu.2020.103896

Wyatt, B. (2021). Insights into student participation in a soil physics course during COVID-19 emergency online learning. Natural Sciences Education, 50 (1). https://doi.org/10.1002/nse2.20036

Article   MathSciNet   Google Scholar  

Yates, A., Brindley-Richards, W., & Thistoll, T. (2014). Student engagement in distance-based vocational education. Journal of Open Flexible and Distance Learning, 18 (2), 29–44. https://doi.org/10.61468/jofdl.v18i2.228

Yilmaz, O. (2017). Learner centered classroom in Science instruction: Providing feedback with technology integration. International Journal of Research in Education and Science, 3 (2), 604–613. https://doi.org/10.21890/ijres.328091

Yousuf, B., & Conlan, O. (2018). Supporting student engagement through explorable visual narratives. IEEE Transactions on Learning Technologies, 11 (3), 307–320.

Zanjani, N., Edwards, S. L., Nykvist, S., & Geva, S. (2017). The important elements of LMS design that affect user engagement with E-learning tools within LMSs in the higher education sector. Australasian Journal of Educational Technology, 33 (1), 19–31. https://doi.org/10.14742/ajet.2938

Zepke, N. (2015). Student engagement research: Thinking beyond the mainstream. Higher Education Research & Development, 34 (6), 1311–1323. https://doi.org/10.1080/07294360.2015.1024635

Zhan, Y. (2023). Beyond technology: Factors influencing the effects of teachers’ audio feedback on students’ project-based learning. Technology Pedagogy and Education, 32 (1), 91–103. https://doi.org/10.1080/1475939X.2022.2093965

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Acknowledgements

The authors would like to thank Bente Kristiansen for her contribution to screening articles in the early version of the literature review as well as Jens Laurs Kærsgaard and Birthe Aagesen for feedback on earlier versions of this article.

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The results of the initial study from 2021 and its preliminary findings have been published in a Danish e-book (Godsk et al., 2021 ). Since this publication was based on narrow searches, only included results from before COVID-19), and did not include a specific research question or similar focus, everything has been completely revised, extended, and updated. Consequently, only very few elements from this e-book can be found in this article. Therefore, we consider the submitted article to be original and not published. Engaging students in higher education with educational technology.

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Appendix: Literature search

The literature review was guided by a PRISMA process (Khan et al., 2003 ; Littell et al., 2008 ; Moher et al., 2009 ; Appendix Fig.  2 ) and follow-up hand searches. The review identified eight clusters (henceforth referred to as “types”) of educational technologies, leading to focused follow-up hand searches on each technology type. This minimised the risk of overlooking key publications due to a single protocol-driven search strategy (Greenhalgh & Peacock, 2005 ). Figure  2 provides an overview of the process.

The PRISMA flow diagram

1.1 Search procedure and identification

The search in the first PRISMA process was carried out in January 2019 in four international databases: ERIC, Education Database, Australian Education Index, and British Education Index; eight Scandinavian databases: Bibliotek.dk, Forskningsdatabasen, Libris, Swepub, DIVA Portal, Oria, Christin, and Norart; and 12 Scandinavian knowledge-producing institutions’ databases and publications (see Godsk et al., 2021 ). The search combined three concepts and their synonyms: (1) educational technology or technology-enhanced learning (the means), (2) student engagement (the effect), and (3) university or higher education (the context) (see protocol for synonyms).

The second round of searches was conducted in 2022–2023 in Google Scholar and ERIC, combining each of the identified clusters of educational technologies, the student engagement concept, and higher education. The reason for using ERIC in the second round was that it, besides being one of the most comprehensive educational databases, also indexes other kinds of publication types such as theses, books, and reports. The reason for using Google Scholar was to compensate for the low effectiveness associated with protocol-driven searches on standard electronic databases (Greenhalgh & Peacock, 2005 ).

1.2 Screening and selection

The identified articles in the first round were imported into EPPI reviewer and screened. Studies of the wrong document type, year, country, educational level, language, or focus were excluded (see Fig.  2 ; Table  1 ). During the screening of articles, however, it became clear that most publications before 2013 were dated and thus not applicable for students today due to contextual factors such as the technologies’ stage of development, ethical and legal perspectives such as GDPR and privacy, and students’ technological skills and competencies. The first round identified 135 relevant articles, of which 112 were included in the review.

The second round was less exclusive in terms of publication type. It included any kind of publication, including theses, books, and reports, as long as it was relevant to the research question, scientifically robust, and directly or indirectly based on empirical data. This round involved the screening of 618 publications and resulted in the inclusion of 60 additional articles and other publications.

1.3 Data coding and analysis

The articles included in the first round were coded and negotiated by three researchers according to subject area, educational level, modality, educational technology, conceptualisation of student engagement, and research question/aim. The first round revealed eight clusters of educational technologies: learning management systems, discussion forums and weblogs, audience response systems, online quizzes, social media, video, audio and multimedia, games and gamification, and virtual reality and simulation. The round also revealed that student engagement was often not explicitly defined, often used as a synonym for students’ participation in the teaching (i.e., a form of behavioural engagement), and often measured on a single indicator and that the three-perspective conceptualisation by Fredricks et al. ( 2004 ) and the related indicators identified by Bond, Bedenlier and others (Bond & Bedenlier, 2019 ; Bond et al., 2020 ) were utilised for analysing the data and classifying the engagement potential.

The included studies were subsequently revisited, discussed, and organised according to the engagement potential of the specific educational technology together with the findings phrased as recommendations in Table  2 . Studies that did not analyse a specific educational technology are only included in the discussion, and technologies addressed only by individual studies are excluded from the article due to the limited extent of evidence.

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Secure applications and enable frictionless access with strong MFA and more. Establish user and device trust, gain visibility into devices, and enable secure access to all apps.

Cisco Identity Services Engine (ISE)

Simplify highly secure network access control with software-defined access and automation.

Security Suites delivered by Cisco Security Cloud

Cisco User Protection Suite

Get secure access to any application, on any device, from anywhere. Defend against threats targeting users and deliver seamless access for hybrid work.

Cisco Cloud Protection Suite

Secure your apps and data with a powerful, flexible framework for a hybrid and multicloud world.

Cisco Breach Protection Suite

Secure your business by investigating, prioritizing, and resolving incidents through unified defense and contextual insights from data-backed, AI-powered security.

Customer stories and insights

Global partnerships fight to end child exploitation together.

"Marriott has long championed human rights and human trafficking awareness. Combating CSAM is an important extension of that work. The IWF provided the level of rigor we needed in a URL list, and Cisco's security technology provided the means to easily apply it."

Abbe Horswill, Director, Human Rights and Social Impact

Company: Marriott International

The NFL relies on Cisco

"From securing stadiums, broadcasts, and fans to protecting the largest live sporting event in America, the right tools and the right team are key in making sure things run smoothly, avoiding disruptions to the game, and safeguarding the data and devices that make mission-critical gameday operations possible."

Add value to security solutions

Cisco Security Enterprise Agreement

Instant savings

Experience security software buying flexibility with one easy-to-manage agreement.

Services for security

Let the experts secure your business

Get more from your investments and enable constant vigilance to protect your organization.

Sharpen your security insights

Cisco Cybersecurity Viewpoints

Set your vision to a more secure future with Cisco Cybersecurity Viewpoints. With specialized content from podcasts to industry news, you'll walk away with a deeper understanding of the trends, research, and topics in our rapidly changing world.