quantitative research on emotional intelligence

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• v.9(10); 2023 Oct
• PMC10543214

Emotional intelligence, leadership, and work teams: A hybrid literature review

Isabel coronado-maldonado.

a Department of Economy and Business Administration, Faculty of Economics and Business, University of Malaga, Malaga, Spain

María-Dolores Benítez-Márquez

b Department of Applied Economics (Statistics and Econometrics), Faculty of Economics and Business, University of Malaga, Malaga, Spain

Associated Data

An asterisk (*) marks the 104 reviewed documents in the Reference Section.

Emotional intelligence (EI) has been widely researched in different fields of knowledge. This paper reviews the literature on emotional intelligence, leadership, and teams in 104 peer-reviewed articles and reviews provided by the Web of Science and Scopus databases from 1998 to 2022. It is a hybrid or mixed review as it uses both quantitative and qualitative analysis techniques. The aims of this study are a performance analysis of the selected documents (years of publication, country, sectors, techniques used, most cited authors, authors with more publications, journals, journal quartiles, and scope of publication), as well as a co-word analysis using Atlas. ti v8. The results of the quantitative analysis indicate that the majority are empirical works. The qualitative analysis is a co-word analysis providing the following results: (i) classification of authors by major themes-categories (EI, leadership, team), (ii) classification of themes within each major theme: three subcategories in EI, 17 subcategories in leadership, and 19 subcategories in team and, lastly, (iii) classification according to the chronological development of main objectives from the most cited authors' articles we analyzed. Leadership (transformational, emergence, virtual, effective, health, effectiveness) is the major theme we studied. Our in-depth review of the articles has shown that emotionally intelligent leaders improve both behaviors and business results and have an impact on work team performance. It also highlighted a positive relationship between emotional competence and team members’ attitudes about work. The new trends focus on the impacts of COVID19, the global crisis due to the Ukraine War, working in VUCA and BANI environments, comparative studies between generations, the application of artificial intelligence and the influence of mindfulness on organizations.

1. Introduction

Emotional intelligence (EI) involves understanding others in a social context in such a way that it enables one to detect nuances in emotional reactions and use this knowledge to influence others by controlling and regulating emotions [ 1 ]. It is therefore a crucial element of the competencies that are necessary for effective leadership and teamwork performance.

Although the intelligence quotient is considered to be one of the most significant predictors of future success in life, the need for effective leadership has led researchers and scholars to seek other improvement tools. Studies such as those conducted by Goleman [ 2 ] on competency assessments show that emotional competencies account for two out of three essential skills for effective performance in a wide array of different job positions in companies around the world. Moreover, Dulewicz and Higgs [ 3 ] point out that both academics and senior management at companies are increasingly recognizing the importance of EI in effective leadership, making it necessary to address the role of EI when discussing leadership [ 4 ].

Other researchers have suggested that not only is EI essential for an individual's success within an organization but that it becomes increasingly important as said individual moves up the ranks into leadership positions [ 2 , [5] , [6] , [7] ]. Various work streams suggest that EI is relevant for effective leadership in 21st-century organizations.

Organizational roles have changed over the years. Organizations now emphasize the need for leaders to take on new roles, including coordinating and facilitating others’ behavior in the workplace. Organizations therefore need to achieve and retain a sustainable competitive advantage in order to continue to develop, paying special attention to human issues [ [8] , [9] , [10] , [11] , [12] ]. Furthermore, many employees have to work in teams in order to achieve complex organizational objectives and work groups are becoming more common in organizations [ 13 ]. It is clear that EI influences relationships within the team [ 14 ].

Some authors highlight the importance of emotional intelligence in leadership and work teams [ 15 ]. According to Lim et al. [ 16 ], literature reviews (as independent studies) provide new researchers with broader knowledge of a certain topic. Furthermore, reviews that include both conceptual and empirical studies lend them greater credibility, as well as helping to suggest important gaps in the literature and highlighting contradictory findings. The justification for this semi-systematic review [ 17 ] of emotional intelligence, leadership (in the broadest sense of the word), and work groups is that our performance and co-word analysis is more current and comprehensive, including both empirical and conceptual studies.

Furthermore, taking into account current reviews on emotional intelligence and human resources, we can cite the systematic review by Sharma and Tiwari [ 18 ]. Our research complements this study for several reasons. First, these scholars used Web of Science (WoS) and Google Scholar for their review while our review considers WoS and Scopus, which includes peer review scholar journals as Google Scholar does not index with any quality assessment. Secondly, the abovementioned authors selected literature from the last two decades (2002–2022), while our analysis is not limited to any specific years of publication, thus offering a more historical and simultaneously current view. Third, the other authors focused their attention on transformational leadership while our study encompasses all kinds of leadership. Fourth, our study includes both empirical and conceptual work while the former authors included only articles. Lastly, the other authors focused on personnel performance, which is further complemented by our approach to work groups, as we also consider other issues such as stress, harassment and worker burn-out.

This paper presents a literature review on EI, leadership, and work teams in peer-reviewed articles written in English and is divided into five sections. This introduction is followed by Section 2 , which provides details regarding definitions and assessments of EI and explores how EI relates to leadership and teams in the leading research. Section 3 describes the methodology used to conduct the review including the search strategy, document selection, and analytical techniques applied (performance analysis and co-word analysis) related to these three topics aforementioned. Section 4 shows the results for the 104 selected articles, including a chronological development of the main articles’ objectives and findings from the most cited authors. Section 5 presents conclusions and future lines of research.

At this point, we have established the following research questions.

Do all the articles from the search strategy go as in-depth into the three topics under review: EI, leadership and work teams?

In regard to performance analysis, we have considered the following research questions.

What evolution can be seen in the articles published per year from 1998 to 2022?

Which countries samples have been researched?

Which sectors are studied in the analyzed articles?

Who are the most cited authors?

Which authors have the most published articles? What is the ranking of the scientific journals that have published the analyzed articles?

What is the classification of documents by type of research design, distinguishing between conceptual and empirical, and how many are qualitative and quantitative inside? What techniques are used in the empirical quantitative and quantitative studies?

What EI assessment measures or models are applied in the analyzed documents?

Regarding co-word analysis, we propose the following questions.

Which are the main categories resulting from the co-word analysis and the authors publish in each one?

Which themes are studied in the subcategories resulting from the co-word analysis and who are the authors publish in each one?

Which research objectives have been studied and their correspondent authors?

2. Theoretical background

2.1. emotional intelligence.

The term EI is rooted in the term “social intelligence.” While Thorndike [ 19 ] defined EI as “the ability to understand people,” Gardner [ 20 ] uses this term in his multiple intelligence theory to refer to interpersonal and intrapersonal intelligence. According to Ruisel [ 1 ], EI is a type of social intelligence that is widely recognized as important in most cases. Wechsler's [ 21 ] work encouraged the study of non-cognitive intelligence, including IE, suggesting that the totality of intelligence should necessarily include a measure of cognitive and non-intellectual effects [ 22 ].

Salovey and Mayer [ 23 ] introduced the specific definition of EI and then later simplified the definition as “the ability to perceive and express emotion, assimilate emotion and thought, understand and reason with emotion, and regulate emotion in the self and others” [ 24 ] cited in McCleskey [ 25 ].

Although Goleman [ 26 ] may be regarded by some as the father of the concept of EI due to his highly acclaimed book chapter, “The Emotional and Intelligent Workplace,” it is actually an adaptation from Salovey and Mayer [ 23 ], Mayer and Salovey [ 24 ], and many other researchers who had previously conducted studies in this field. In 1997, Goleman stated that we have to manage our emotions without letting them overwhelm us, motivate ourselves to do work, to be creative, and to feel what others feel while effectively managing our emotions. Goleman [ 2 ] defines EI as “the ability to recognize our feelings and those of others, to motivate ourselves, and to handle our emotions well to have the best for ourselves and our relationships.” It is also relevant to mention the very concise definition by Martinez [ 27 ] as “an array of non-cognitive skills, capabilities, and competencies that influence a person's ability to cope with environmental demands and pressures.”

Following Mayer et al. [ 28 ], other researchers such as Barn-On [ 29 ], Goleman [ 2 ], and his colleagues complemented this concept with different types of personality traits and skills. Barn-On [ 29 ] states that EI is a set of non-cognitive abilities, competencies, and skills that influence a person's ability to successfully cope with the demands and pressures of the environment. Other studies consider EI to be a personality trait [ [30] , [31] , [32] ]. The latter academics define it as “a constellation of emotional self-perceptions located in the lower levels of personality hierarchies, measured via the trait emotional intelligence questionnaire.”

Other scientific studies that are worthy of mention bring up concepts such as emotional literacy [ 33 , 34 ]; personal literacy [ 35 ]; interpersonal intelligence [ 20 , 36 ], and socio-emotional competencies [ 37 ]. So, following Goleman's [ 2 , 38 ] definition, Boyatzis [ 39 ] considers EI in terms of competencies and skills, defining an EI competence as the ability to recognize one's own feelings as well as others' feelings. There are three such competencies: cognitive competencies, social intelligence competencies, and EI competencies.

After reviewing the theoretical perspective of EI, early studies attempted to relate EI to various variables that are not directly observed (including factor, composite, and latent variables or constructs, among others) in order to assess an individual's capacity for EI. Researchers consequently began to develop several EI models and scales [ 23 , 29 , 32 ]. Current scales generally achieve appropriate psychometric properties, although some have limitations.

Generally speaking, three different approaches have been used to evaluate EI. Mixed or trait models measure an individual's EI through questionnaires and self-reports, regarding EI as a personality trait that includes social, emotional, and organizational aspects or competencies. In contrast, ability models regard EI as the result of the ability to solve certain emotional issues, comparing these responses with pre-established scoring guidelines according to specific measures [ 40 , 41 ]. The third approach is external assessment, which involves asking someone other than the test-taker to give their opinion and assessment of how they perceive the person being evaluated. This technique involves evaluating interpersonal skills, which compliments and reaffirms the two former techniques and avoids any issues related to social desirability presented by certain individuals.

In regard to self-report measures, the theoretical conceptualization of Salovey and Mayer [ 23 ] led to the classic version of the “Trait Meta-Mood Scale-48” (TMMS-48). Later, Schutte et al. [ 32 ] produced the Schutte Self Report Inventory (SSRI) measure. Similarly, Wong and Law [ 42 ] eventually developed Wong and Law's Emotional Intelligence Scale (WLEIS) to assess perceived EI.

Other self-report measures relate to emotional, social, and occupational functions. Bar-On [ 29 ] developed the Bar-On Emotional Quotient Inventory (EQ-i) measure, which includes items intended to ensure that participants do not distort the possible consequences of social desirability [ 43 ]. Petrides and Furnham's [ 44 ] developed a measure based on the Barn-On [ 29 ] scale, defining EI as a set of personality traits, socio-emotional competencies, motivational aspects, and cognitive skills. They created the Trait Emotional Intelligence Questionnaire (TEIQue). Similarly, Goleman's base model [ 2 ], the “Emotional Competence Inventory” (ECI), initially included a series of emotional competencies. Boyatzis et al. [ 45 ] eventually reduced the dimensions of the aforementioned assessment so as to only include business-related competencies of workers and leaders. All of these versions generally have acceptable levels of consistency and, according to Extremera et al. [ 46 ], most of them have reduced versions of the measures from the original model.

Task and performance-based ability and performance measures have been developed in order to mitigate potential biases that may appear in self-reports, as one may feel that perceived EI is associated with high social desirability. The most widely used performance measure is the Mayer-Caruso-Salovey [ 28 ] Multifactor Emotional Intelligence Scale (MEIS) based on theoretical concepts developed by Mayer and Salovey [ 24 ], which generally offers a high degree of predictive ability. Mayer et al. [ 28 ] eventually proposed another version of the theoretical model, the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), which no longer includes scales with low reliability (as it did in the two former versions, v.1.1 and v.1.2).

There are various EI-related controversies. Murphy [ 47 ] and Mayer et al. [ 48 ] argue that many different constructs lead to suspicions about whether or not they are interrelated, which is detrimental to the legitimacy of the term emotional intelligence. Locke [ 49 ] criticizes the great diversity of shifting and incomprehensible definitions of EI and proposes replacing the term EI with introspective ability. In the same vein, Cherniss [ 50 ] and Conté [ 51 ] criticize the fact that existing assessment methods measure intelligence based on different conceptualizations of the term and that there's a lack of consensus among them. Conté [ 51 ] discusses whether these concepts are even comparable.

Generally, these scales have a high degree of reliability and internal consistency; however, the scales do not indicate whether they assess concepts that are already measured by other more established constructs. Mayer et al. [ 28 ] and Brackett and Mayer [ 52 ] have concluded that there is a low correlation between the MSCEIT model and the EQ-i model constructs. They raise the question of whether these models measure the same concept [ 53 ]. Rosete and Ciarrochi [ 54 ] found no significant correlations between the total score of the EI construct and any of the 16 personality factors in the ability-based MSCEIT model. Wilhelm [ 55 ] argues that, despite possible discordances, the MEIS and MSCEIT are the most comprehensive assessments of EI. He considers the MSCEIT to be the most ambitious and appropriate approach to date for the overall assessment of emotion-related abilities. Wilhelm [ 55 ] also recommended not conducting any further research on self-reports. According to Mayer et al. [ 48 ] regarding the Big Five measures, the strongest correlations between EI and the five personality dimensions only occur with the agreeableness factor. Furthermore, MEIS and MSCEIT (v.2) measures seem to correlate better with general mental ability than with self-report measures [ 51 , 56 ]. In contrast, proponents of EI measurement find it acceptable that the different measures have adequate internal consistency reliability, both in self-reports and ability reports [ 2 , 29 , 30 ].

2.2. Emotional intelligence and leadership

Since its conceptualization in the early 1990s, EI has been considered as a relevant non-observable variable associated with organizational success. It is important to note how we manifest and control emotions. Several authors [ 2 , 23 , 29 , 57 ] share multiple theoretical foundations on this issue, including: awareness of our own emotions, awareness of others’ emotions, and our understanding and ability to manage our emotions and those of others.

The importance of emotions in the workplace has led researchers to increasingly recognize that effective leadership can also have a strong emotional component, making it vital for leaders to be emotionally intelligent [ 38 ]. Consequently, effective leadership may depend heavily on a leader's ability to both proactively and reactively manage the emotions of those under them [ 58 , 59 ].

According to studies from the last few decades, it is important to study personalities and individual differences in order for leadership to be effective [ [60] , [61] , [62] ]. These studies have led to the emergence of the EI perspective, which is the ability to recognize, understand and manage one's and others' moods and emotions, as established by Salovey and Mayer [ 23 ]. Likewise, Chen et al. [ 63 ] state that EI has an impact on success in leadership positions.

Although most studies on workplace leadership address constructive forms of leadership, another aspect that has been considered recently is the importance of toxic and counterproductive work behaviors that can occur in organizations [ 64 ]. Most studies focus on employees in lower-level positions [ 65 ], while few have touched on issues that may expose people in managerial, supervisory, or leadership positions.

Supervisors' abusive behavior towards their subordinates has an adverse effect on employees’ work behavior and performance, including decreased job satisfaction and commitment to the organization [ 66 ]. Consequently, employees feel helpless and more conflicts arise regarding their roles and employee turnover [ 67 ].

The “Five Factor Model” personality studies conducted in recent years encompass personality traits such as extroversion, empathy, conscientiousness, and neuroticism. Multiple studies explore the influence of these general factors on personality dimensions, performance, and leadership at work [ 68 , 69 ].

2.3. Emotional intelligence and work teams

On an individual level, team members’ personalities, abilities, and skills play an integral role in the work team. Highly emotionally intelligent individuals can communicate effectively and empathize with others, allowing them to develop cohesive, supportive relationships [ 70 , 71 ]. Furthermore, emotionally intelligent individuals can think in an innovative manner and create an environment that supports these activities [ 72 ]. Accordingly, some studies show that EI competencies are significantly related to individual performance [ 73 ].

Because business environments experience continuous changes, leadership positions often require more than just competence to perform tasks or technical expertise [ 74 ]. Scholars have explicitly demonstrated that emotional skills are essential to a leader's performance at the executive level [ 15 ] and are becoming increasingly important as individuals move up in their organizational hierarchies [ 3 , 75 ]. Consequently, EI is a crucial element in the workplace, and companies and individuals are growing increasingly interested in balancing the rational and emotional aspects of business strategies [ 76 ]. As social and individual skills improve, so does the ability to express inner feelings toward others; EI is therefore manifested in one's effectiveness on the job [ 77 ].

Druskat and Kayes [ 78 ] suggest that a group's ability to manage itself both on a group and individual level plays a crucial role in developing social relationships, effective task processes, and overall group effectiveness. Druskat [ 79 ] and, later, Druskat and Wolff [ 80 ] proposed a model of group EI that analyzes the role of emotional disturbances in work teams, further developing and recognizing the existence of these enforced emotionally intelligent group norms. Druskat and Wheeler [ 81 ] link the degree to which a group develops these norms to team performance, considering group EI to be a “set of group norms that shapes group members' interpretation of emotion-provoking events and group members' response to that interpretation.”

As leaders have a direct influence on their employees, it is easy to see how a team leader's EI can influence the development of emotionally competent group norms in his or her team [ 82 ]. Consequently, a team leader's EI strongly impacts the work team's well-being as the work climate becomes stressed [ 83 ]. Furthermore, emotionally competent leaders perform better and are more successful [ 2 , 74 , 84 ]. The idea is to link these emotional competencies with leadership behaviors and organizational performance [ 74 , [85] , [86] , [87] ].

Since teamwork is an intrinsically social activity, emotions play an essential role in team effectiveness and affect team behavioral outcomes [ 88 ]. EI is therefore essential for effective team interaction and productivity. In parallel, recognizing and managing emotions is crucial for both individuals and work teams [ 2 , 23 , 34 , 38 , 57 , 75 , 89 ].

2.4. Current research trends

Ongoing business challenges are affecting workers for a variety of reasons, including changing organizational structures, adoption of new technologies, and working remotely. These changes are leading to major transformations in how organizations work as well as the actual space at the workplace, both of which are influenced by external factors and new trends.

One of these trends has arisen from the global crisis caused by the COVID-19 pandemic, which made it especially important to know how to manage fear and stress. This situation did not promote emotional or physical well-being in people and this imbalance was transferred to both the personal and the professional levels for all workers within an organization. The changes that have occurred in managing the workforce remain in the post-pandemic era and, therefore, must continue to be assessed, especially considering that the markets are still volatile, uncertain, complex, and ambiguous (VUCA). Likewise, the same goes for the changes brought about by the war in Ukraine, not only on an economic level, but on a personal one too [ 90 ]. In wartime conditions, ensuring economic and financial security at all social and economic levels must be considered a priority. For post-war recovery of companies with critical infrastructures in global BANI conditions, developing a new prototype of strategic management for financial and economic security will make it possible to expand the limits for applying effective security-oriented management tools. All the uncertainty caused by the uncertain future itself has a negative impact on levels of productivity, loyalty and the manifestation of leadership qualities [ 91 ].

In today's brittle, anxious, non-linear and incomprehensible (BANI) environment, emotional intelligence, leadership and work teams have changed significantly, presenting new strategies to cope with this environment. In this context, Sharma and Tiwari [ 18 ] point out that individuals who have a high level of emotional intelligence are better able to manage pressures and demands at work because they are more self-aware, according to studies by Fisher et al. [ 92 ], Hartmann et al. [ 93 ], and Wang et al. [ 94 ]. This means that BANI environments can be coped with by creating a culture of resilience in order to have rapid recovery processes in very uncertain situations. Resilience can be a skill that can be developed or learned, not only in order to cope with problems but also as a means of learning and improving workers' success rates [ 95 ]. Considered from this perspective, emotions are an integral part of human beings and therefore it is important to take into consideration people with high levels of emotional intelligence. Furthermore, these resilient skills provide individuals with psychological/emotional stability, allowing them to calmly deal with stressful situations and make effective decisions [ 96 ]. Likewise, emotional intelligence serves as a prerequisite for becoming more resilient, providing a specific pathway to career success [ 95 ].

Developing and encouraging workers' skills such as empathy, confidence, intuition, creativity and self-control is another way to increase people's ability to adapt to rapidly changing and unexpected situations. Consequently, the practice of mindfulness is positively related to the development of changes in personal and social awareness as it regulates people's emotions and behaviors. Mindfulness also has a positive influence on work engagement and performance, as well as interpersonal relationships since it increases workers' personal well-being [ 97 ]. Mindfulness also improves cognitive function, contributing to the development of emotional intelligence competencies associated with higher performance and effective leadership [ 98 ]. Similarly, the use of mindfulness at work is useful for leaders to develop emotional intelligence, social skills, and support systems within the organization [ 99 ].

Another current topic is studying the behavior of different generations (Baby Boomers, Generation X, Generation Y or Millennials, and Generation Z). Specifically, in the field of employment, there are differences between these generations. Baby boomers are likely in the process of retiring, while Generation Y may have greater project management responsibilities and Generation Z is just starting to enter the workforce. The latter generation is characterized by having short attention spans, socializing on the Internet, being impatient, innovative and creative, and they like to work individually. Generation Z is associated with being born with technology and having a good command of it, unlike Millennials who started using it later on in life [ 100 ]. Magano et al. [ 100 ] have associated Generation Z with project management competencies that have to do with strengths in emotional intelligence. Significant gaps were found in traits such as individualism; that is, less personal relationships. Some studies support the importance of sociocultural factors that influence the acceptance of technology by this specific generation, although other studies also add that additional factors such as cross-cultural, religions and regions must be taken into account [ 101 ].

Another trend is the major revolution that comes with advances in technology. In order for service companies to increase their operational efficiency, artificial intelligence is being increasingly used to improve the quality of services and customer satisfaction, such as automation techniques used by managers. In particular, techniques that use machine learning models to generate content similarly to how the human brain learns and responds to data, information and indications (generative artificial intelligence) [ 102 ]. This is the case with ChatGPT and DALL-E, which shocked us with its ability to understand complex and varied human languages, creating rich and structured responses that are very similar to how a human would respond [ 90 , 103 ]. Nevertheless, artificial intelligence continues to be more useful for technical and operational efficiency than for people-related services, which require an understanding of human behaviors, improving employee work and managing emotional tasks [ 18 ].

3. Methodology

This review would be considered semi-systematic according to Snyder [ 17 ]. Two bibliometric analysis techniques were used: a quantitative technique (performance analysis) and a qualitative technique (co-word analysis), making it a hybrid review [ 16 ]. Ordanini et al. [ 104 ] suggested choosing research with a significant impact in the field such as Web of Science, and Scopus databases as these databases includes peer review scholar journals.

The search strategy used to select articles employs the advanced search TOPIC option with the words ‘emotional intelligence,’ ‘leader*’ and ‘team’, that is, TS = (leader* AND emotional intelligence AND team). Based on the WoS core collection database, we applied the following filters: document type (articles, review articles), up to the year 2022, and language (English). The search in Scopus included the article title, abstract, and keywords with the same terms (TITLE-ABS-KEY (emotional intelligence AND leader* AND team). We then exported the complete records to Excel and merged both files, eliminating duplicates. Early access documents were not considered although they are involved in trends and other sections such as the conclusions. It is important to clarify that there may be articles of leadership in any category, not restricted only business.

Applying the search resulted in a total of 564 articles and 76 duplicates were eliminated, resulting in 488 articles. At that point we could answer the first research question.

Do all the articles resulting from the search strategy go as in-depth into the three topics under review: EI, leadership and work teams?

A manual examination by each of the authors showed that 384 articles either only made occasional references to one of the main topics (EI, leadership and team) or strayed far from the context of business organizations. Most of the studies from the final selection, 104 documents, were obtained from the WoS database, which accounted for 74 articles, or over 70% of the total publications selected and the remaining 30 articles came from the Scopus database. An asterisk (*) marks the 104 reviewed documents in the Reference Section.

The performance analysis (quantitative) provides a descriptive data analysis concerning each response of research questions from RQ2 to RQ9 displayed in the Section of results. We also mixed the performance analysis with the thematic review (qualitative) based on co-word The final selection of 104 documents was then analyzed by Atlas. ti version 8 software, which provides rigor to finding main categories, which are EI, leadership and team in the case of this study, and subcategories. The purpose of the thematic review is to find the most important research categories or themes.

4.1. Results of the performance analysis

The year of publication of the selected articles ranged from 1998 to 2022. This topic began to emerge in the literature in 1998, which makes it a relatively recent topic of interest. Interest grew in 2002, 2008, 2012, and 2020 (6%). The highest number of relevant publications were in 2017, 2018 (8%), and 2022 (7%); while the years with the lowest number of publications were prior to 2002.

The first descriptive data in this study is categorization by sample country ( Table 1 ). The majority of the sample articles are from the United States (24%), the United Kingdom (15%), China (13%), and Australia (8%). The remaining countries include a group of eight countries with less than 5% of the total, and the rest represent a small percentage of the sample. Also, less than 2%, one paper is from a 13 sample countries and ten papers are from more than one sample country.

The most noteworthy sectors ( Table 1 ) we considered include: Educational training (22%), Hospitals & Healthcare (17%), and Construction (12%).

The most frequently cited authors in both WoS and Scopus are: Schutte et al. [ 32 ], with 1796 citations, and Judge et al. [ 60 ], with 1396 citations. Carmeli [ 15 ] is also worthy of mention, with 407 citations in Scopus, although he is not mentioned in WoS ( Table 2 ).

What is the ranking of the scientific journals that have published the analyzed articles?

The analyzed articles were published in 73 different journals ( Table 2 ). The most significant number of publications corresponds to the Leadership and Organization Development Journal (10%), followed by the Journal of Managerial Psychology (5%) and Leadership Quarterly (each with 5%). The classified categories of the Journal Citation Report (JCR) in Social Science Citation Index (SSCI) are: Business, Nursing, Industrial Relations & Labor, Management, Multidisciplinary, Psychology, Psychology, Applied Psychology, Social Psychology; and the most frequent category among them is Management, followed by Applied Psychology. Related to the ranking of top thirteen journals with more than one published paper, the ranking have been abbreviated JCR-SCCI-Quartile (Q) number and are the following: JCR–SSCI–Q1 Nursing; JCR–SSCI–Q1 Industrial Relations & Labor; JCR–SSCI–Q3 Management; JCR–SSCI–Q3 Business; JCR–SSCI–Q1 Psychology; JCR–SSCI–Q4; Applied Psychology; JCR–SSCI–Q3 Social Psychology, and JCR–SSCI–Q1 Multidisciplinary.

Regarding research methods, 79% are empirical and 21% are conceptual ( Table 3 ). Out of the empirical, from 82 only two articles are qualitative and the rest are quantitative. Also, out of the quantitative, correlation analysis and regression analysis are the most used techniques (30% of the total number of techniques used in the sample); however, it is relevant that many of these papers used more than one statistical technique ( Table 3 ).

The most widely used assessment measures are the WLEIS scale (20%), the MSCEIT scale (15%), and the 5G scale (14%) ( Table 4 ).

4.2. Results of the co-word analysis of the most cited studies

This subsection includes results from the co-word analysis using the complete period 1998–2022 responding the proposed research questions.

To organize the selected studies, we considered three main categories: EI, leadership, and work teams ( Table 5 ). According to the co-word analysis, the majority of the articles (53 out of 104) fall into the EI category, accounting for 17% of the total words analyzed and 52% of the total number of articles. Leadership accounts for 8% of the total number of words analyzed and 26% of all the articles reviewed (28 out of 104). The team category represents approximately 2% of the total number of words analyzed and 5% of the total number of articles.

Which themes are studied in the subcategories resulting from the co-word analysis and the authors publish in each one?

The detailed study of co-word resulted in subcategories of EI, leadership, and work teams is included in Table 7 . Lopez-Zafra et al. [ 105 ] and Villanueva and Sanchez [ 106 ] also have emotional intelligence and leadership. Meanwhile, Ahmed et al. [ 107 ], Harrison et al. [ 108 ], Hur et al. [ 109 ], Potter et al. [ 110 ], and Schlechter and Strauss [ 111 ] concur with leadership and team. Finally, Aritzeta et al. [ 112 ], Balamohan et al. [ 113 ], and Flores et al. [ 114 ] have all three subcategories in common. Côté et al. [ 115 ], Mandell and Pherwani [ 116 ], and Judge et al. [ 60 ] only have leadership subcategories while Stubbs Koman and Wolff [ 117 ] have team subcategories ( Table 6 ).

4.3. Research objectives and findings of the most cited publications

Which research objectives are studied in the analyzed articles and their correspondent authors?

Some articles have multiple objectives, so we catalogued the articles based on their primary or most relevant objective ( Table 7 ).

One of the main contributions of this study is the classification of categories based on the research objectives of the analyzed articles in chronological order. The analysis is described in the following third-level sections.

4.3.1. Leadership types: transformational, emergence, virtual, effective, healthy, resonant, and dissonant

Dulewicz and Higgs [ 118 ] establish a positive relationship between emotional intelligence and leadership. Judge and Bono [ 119 ] conclude that relationships exist between traits of the Big Five personality model (neuroticism, extraversion, openness to experience, and agreeableness) and transformational leadership behavior. However, Shao and Webber [ 120 ] point out that the Big Five model does not appear to be as effective a predictor of transformational leadership behaviors in China as compared to samples from Judge and Bono's [ 119 ] previous studies conducted in the United States. Later, Mandell and Pherwani [ 116 ] studied managers in different industries and concluded that there is a significant relationship between EI and transformational leadership style. Scott-Halsell et al. [ 121 ] found that transformational leaders use their EI skills to employ effective leadership skills, such as good interpersonal communication and team collaboration.

Ahmed et al. [ 107 ], Polychroniou [ 122 ], Prochazka et al. [ 123 ], and Schlechter and Strauss [ 111 ] support the idea that transformational leadership mediates the relationship between EI, effectiveness, performance, and team commitment. In other results, Hur et al. [ 109 ] and Mandell and Pherwani [ 116 ] found no significant gender differences in this relationship.

Ramsey et al. [ 124 ] pointed out that leaders with high levels of cultural intelligence also exhibit high levels of transformational leadership because they can understand their own behavior. Similarly, transformational leadership increases team motivation, performance, and effectiveness-related satisfaction [ 125 ]. Furthermore, Potter et al. [ 110 ] have discovered significant positive relationships between the EI of a group of project managers working in the construction industry and the likelihood of them adopting a transformational leadership style. Doan et al. [ 126 ] later confirmed the influence of EI, the mediating role of transformational leadership, and the moderating effect of organizational commitment on the relationship between EI and project success in company leaders from various areas. Along these lines, Mysirlaki and Paraskeva [ 127 ] provide evidence that transformational leadership moderates the relationship between leaders’ EI and effectiveness in a virtual team.

In regard to effective and transformational leadership, based on the Big Five model of personality factors, Lim Leung and Bozionelos [ 128 ] concluded that extroversion was the trait most associated with the prototypical notion of an effective leader and, in turn, linked to transformational leadership traits. The results also suggest that men and women may differ in the criteria they use to evaluate leaders.

Regarding effective leadership in the context of students in business administration programs, Offerman et al. [ 129 ] found a positive relationship between emotional competence and the attitudes of team members, as well as the leader's effectiveness. Rosete and Ciarrochi [ 54 ] argue that managers with higher levels of EI tend to achieve better business results; however, the small sample size limits the conclusion. The latter authors also suggest that, in terms of managing employee performance, it is equally important for an executive to know what task to manage in order to achieve good business results as it is to know how to effectively address his or her employees. Riggio and Reichard [ 130 ] subsequently found that emotional and social skills are essential for effective leadership.

In contrast, Weinberger [ 131 ] analyzed employees of a manufacturing company and concluded that there was no relationship between a leader's EI and his or her effectiveness, which contradicts the findings of Goleman [ 2 , 38 ]. Weinberger [ 131 ] points out the redundant importance given to the relationship between EI and leadership style and effectiveness in the literature. He also indicates that such relationships do not exist and are not necessary to further understand a leader's effectiveness in an organization. Finally, he claims that the ability-based definition of EI is of little use from an organizational perspective and suggests that definitions of EI should be broader and personality-based.

The literature review by Walter et al. [ 132 ] notes that although there are controversies between the definition of EI and its measurement, empirical research on EI and effective leadership has found that EI is a crucial element for the success of leadership development projects. Similarly, Boyatzis et al. [ 133 ] studied lead engineers at a multinational manufacturing company and found that social and emotional intelligence (SEI) competencies for effectiveness significantly predict the explanatory power of SEI over general mental ability and personality.

Edelman and van Knippenberg [ 134 ] subsequently provided evidence on the mediating role of EI on leadership effectiveness, controlling for cognitive ability and the Big Five personality traits. Cavaness et al. [ 135 ] point out that understanding the importance of EI and its connection to personality dimensions provides an additional tool for leaders to be more effective and successful.

In regard to emergent leadership, Wolff et al. [ 136 ] maintain that the behavioral abilities of group task coordination and the support and development of others would predict an individual being selected as an emergent team leader. Judge et al. [ 60 ]conclude that factors of the Big Five personality model, such as neuroticism, extraversion, openness to experiential appreciation, and conscientiousness, are the most consistent constructs of leadership across study settings and emergent and effective leadership. Judge et al. [ 61 ] later studied the relationship between intelligence and leadership and established that the degree of correlation between intelligence and leadership is considerably less than previously suggested in the literature.

In particular, Côté et al. [ 115 ] confirmed that EI is positively related to emergent leadership in small groups and point out the importance of understanding emotions according to the applied contexts. They also argue that the literature on studies that control for cognitive intelligence and personality traits is rather limited. Emery [ 137 ] concluded that emotional competencies play a complementary role in emergent leadership while, the same year, Walter et al. [ 138 ] provided an innovative view regarding the connection between emotion recognition and emergent leaders. The results show that task coordination behavior is a key mediating mechanism that transfers positively into the relationship of emotion recognition and extraversion as related to task coordination.

Among the few studies that analyze emergent leadership and motivation, Hong et al. [ 139 ] examined the role of EI and motivation to lead in predicting emergent leadership. The results support the idea that motivation to lead is essential for the emergence of leaders in different environments.

In another study, Cummings et al. [ 140 ] concluded that resonant leadership moderates the impact on nurses in the case of hospital restructuring. This means that nurses working under resonant leadership have less emotional exhaustion, less somatization, and better teamwork than nurses working for dissonant leaders.

4.3.2. Leadership and emotion

In regard to the topic of leadership and emotions, Kelly and Barsade's [ 141 ] literature review shows that group emotion is the result of the combination of the affective composition of the individuals in a group and the affective context of the group itself. The authors proposed an organizational model to understand these affective influences and their impacts on group life. Pirola-Merlo et al. [ 142 ] analyzed how leaders influence the impact of affective events on team climate and performance. The findings show that potential obstacles within the organization have a negative impact on the team's work climate, although said effects can be neutralized by leaders adopting more facilitating and transforming styles.

That same year, Kellet et al. [ 143 ] established two behavioral pathways related to how an individual perceives leadership. One pathway is based on mental skills, such as task accomplishment, while the other pathway is based on emotional skills, such as empathy. Likewise, Rubin et al. [ 87 ] analyzed how leaders’ ability to recognize emotions and personality characteristics influences transformational leadership behavior performance.

4.3.3. Leadership and team conflicts, abusive-subversive leaders, and pressure-support

Ayoko et al. [ 144 ] argue that teams with less-well-defined EI environments are associated with increased task and relationship conflict as well as conflict intensity. Clarke [ 145 ] later found that emotional competence and empathy measures explain additional variance in teamwork project managers’ competencies and conflict management.

Gavin et al. [ 146 ] showed that members of an organization who experience subversive leadership are less likely to trust their leaders, to feel satisfied with their jobs, and to stay at the organization. Moreover, the level of EI mediates the level of job satisfaction for these members, but not their intention to leave the organization.

Regarding subversive leaders, Pradhan and Jena [ 147 ] found no positive relationship in the moderating role of EI between abusive supervision (an interpersonal stressor) and employees’ intention to quit. In contrast, Li et al. [ 148 ] concluded that leaders who are always supportive of employees before any pressure occurs have higher EI levels than leaders who prefer to provide support after pressure occurs.

In the case of luxury hotels, Jung and Yoon [ 149 ] analyzed emotional contagion among burned-out employees and collective commitment. These authors concluded that more emotionally contaminated employees have higher levels of burnout, and the higher the burnout, the lower the commitment to the group.

4.3.4. Leadership and work environment, leadership and interpersonal communication with team members, organizational behavior in the workplace, and leader behavior and well-being in the workplace

Although many studies attribute a positive influence on job success and well-being to EI, Zeidner et al. [ 150 ] criticize this finding, claiming that there's not enough research to support this relationship.

Ashkanasy and Daus [ 151 ] maintain that the trends have not been adequately distinguished and that EI has inappropriately been characterized as a variant of social intelligence, highlighting the relevant role of emotion in organizational behavior.

Nonetheless, recent scientific advances in the study of emotions, specifically regarding the role that emotions play in organizational behavior, are the basis of EI research. Liu et al. [ 152 ] maintain that leaders' positive emotional states are positively related to employees’ positive communication behaviors toward their managers.

4.3.5. Performance, leaders, teams, and work

Poon Teng Fatt [ 76 ] concluded that the EI competencies of a team's members effectively influence the team and its performance. Likewise, Offermann et al. [ 129 ] maintain that emotional capabilities assessed by a competency model influence both individual and team performance. Lopes et al. [ 41 ] later related EI to several job performance indicators, although the sample size limits their results. Stubbs Koman and Wolff [ 117 ] also confirm a positive relationship between team leaders' EI competencies and their team's performance. According to Chang et al. [ 153 ], both team members' average EI and emotionally intelligent leadership have a positive influence on internal confidence and team performance. These authors recommend further research to be conducted on EI and emotional management at the group level.

Considering different industries, Stein et al. [ 154 ] concluded that executives with higher levels of self-esteem and better problem management skills are more likely to create companies with higher profits. It is also vital for managers to know how to intersperse social competencies with task-specific competencies in order to achieve successful work performance.

Zhang and Fan [ 155 ] confirmed that international participation and contract type moderate the relationships between certain EI factors and project performance. These authors also confirmed that team members with high emotional competence generally enhance team success and show superior personal performance at work, which is supported by other authors [ 118 , 156 ]. Neil et al. [ 157 ] subsequently provided insights into the effective use of EI and leaders’ attitudes to benefit team cohesion and performance.

Vijayabanu and Arunkumar [ 158 ] analyzed personality traits and team performance and verified the relationship between personality traits and emotions affecting team performance. Similarly, Bartone et al. [ 159 ] assessed the influence of psychological toughness, social judgment, and the Big Five personality dimensions on leader performance at a military academy. The Big Five, extroversion, toughness, and a tendency toward social judgment predict this performance.

4.3.6. Other objectives

Carmeli [ 15 ] corroborates the importance of EI within the context of senior management in the public sector, as it increases positive work attitudes and task performance. A year later, Law et al. [ 86 ] analyzed several evaluations including supervisors' assessments of their employees' task performance, and the employees' assessments of their supervisors’ EI and job performance, as well as the performance of their peers. The results showed that peer ratings were significant predictors of job performance ratings as provided by supervisors after controlling for the Big Five personality dimensions. Law et al. [ 86 ] argue that the concept of EI differs from the concept of personality.

On another note, Espinosa et al. [ 160 ] studied project success, which was determined by evaluating the impact of emotional leadership competencies, intellectual intelligence, and management intelligence on project success according to varying degrees of complexity. They found that trust complexity moderates the relationship between EQ and project success. They investigated the moderating effect of project complexity on the relationship between project managers’ leadership competencies and their project success. The results show that EQ and MQ are correlated with project success but are moderated differently depending on the complexity.

In recent years, authors such as Fareed et al. [ 161 ], Zhang and Hao [ 162 ], and Zhang et al. [ 163 ] have tackled this issue. More specifically, Fareed et al. [ 161 ] point out that EI, project managers' intellectual competencies, and transformational leadership contribute significantly to project success. Zhang and Hao [ 162 ] have determined that a project manager's EI influences the willingness to achieve objectives in a project; that is, it has a more effective influence on leading team members (mediating team cohesion and duration in project management). Zhang et al. [ 163 ] investigated the factors influencing the relationship between project managers' EI and project performance, concluding that project managers' EI positively and significantly influences project performance.

Finally, within the context of employee innovation, Jena and Goyal [ 164 ] studied the mediating effect of person-group fit and adaptive performance on employee innovation.

5. Conclusions

This review of the selected articles indicates that the diversity of conceptualizations of EI can lead to contradictory concepts and may impair one's understanding of the construct [ [47] , [48] , [49] ]. This diversity of concepts is reflected in different measurement scales, thus raising the question of the comparability of EI measures.

Authors such as Conté [ 51 ] and Côté et al. [ 115 ] debate about the best way to measure IE. Conté [ 51 ] points out that only the ability test scores showed incremental validity over the Big Five personality traits and gender. Rosete and Ciarrochi [ 54 ] remark that the overall EI score did not correlate with any of the 16 personality factors. These results support previous research that showed that MSCEIT scores are distinguishable from personality [ 52 ]. Similarly, authors such as Brackett & Mayer [ 52 ], Matthews et al. [ 53 ], and Mayer et al. [ 28 ] found low correlations between the constructs of the MSCEIT model and the EQ-i model. Chandrapal et al. [ 165 ] argue that there could be bias in self-report tests or a limitation in their assessments.

Academics who are advocates of EI measurement accept that the different measures have adequate internal consistency reliability, both in self-reports and competence-based measures [ 2 , 29 , 30 ]. Dulewicz and Higgs [ 118 ] concluded that the construct of emotional intelligence presents validity and reliability measured through a questionnaire derived from a competence-based measure, which backs up Goleman's research [ 2 ]. Similarly, Stein et al. [ 154 ] support using the EQ-i as a functional tool in an individual's assessment and development in executive roles.

From the performance analysis of the selected documents, several conclusions are drawn. The period being studied ran from 1998 to 2022, with growing interest in the field in recent years, specifically 2017, 2018, and 2022. The countries samples more frequent are the United States and the United Kingdom. Moreover, the most widely studied industries are higher education, healthcare and hospitals, and construction.

Schutte et al. [ 32 ] and Judge et al. [ 60 ] are the most cited authors in WoS while Carmeli [ 15 ] is the most cited author in Scopus. The reviewed articles were published in 73 different scientific journals, with “Leadership and Organization Development Journal” at the top of the ranking. The top thirteen journals included with the most published papers are classified into the categories: Management (11); Applied Psychology (4); Business (2); Multidisciplinary (2); Industrial Relations & Labor (1); Nursing (1); Psychology (1); and Social Psychology (1). The most frequent category among them is Management, followed by Applied Psychology. In terms of ranking of these top journals, the most frequent ranking of these top journals belonging to Journal Citation Report-Social Sciences (JCR-SCCI) are quartile Q1 (Nursing, Business, Industrial Relations & Labor, Psychology, and Multidisciplinary) followed by Q3 (Management, Social Psychology).

Most of the studies were empirical (79%), while others were primarily conceptual (21%). The most frequently used techniques were correlation and regression analyses; however, many quantitative studies applied more than one technique. Additionally, the most frequently applied measures of emotional intelligence are the Wong-Law Emotional Intelligence Scale (20%), the Mayer-Salovey-Caruso Emotional Intelligence Test (15%), and the Five-Item General Leadership Impression Scale (14%).

The results of co-word analysis led to the conclusion that the reviewed publications mainly focus on the study of emotional intelligence followed by leadership in the section on categories.

Following is a summary of the main conclusions of the most cited academics’ research goals in the three main categories. As far as transformational leadership, conclusions support the positive influence of EI and the mediating role of transformational leadership, as well as the moderating effect of organizational commitment on the relationship between EI, performance, and project success [ 118 , 126 ].

The traits of the Big Five personality model have a positive correlation with transformational leadership behavior [ 119 ]; however, the results depend on the country where the sample is collected, as the predictor may be less significant in certain countries [ 120 ]. Some authors confirm a significant positive relationship between transformational leadership style and emotional intelligence [ 116 ]. Furthermore, Lim Leung and Bozionelos [ 128 ] analyzed transformational leadership and efficacy by applying the Big Five model of personality factors, concluding that extroversion is the trait most highly associated with effective leaders and that efficacy, in turn, is linked to transformational leadership traits.

Regarding effective leadership, the literature supports the positive relationship between emotional competence and team members' attitudes, as well as the leader's effectiveness [ 129 ]. Other authors argue that managers with higher levels of EI tend to achieve better business results. Specifically, in terms of managing employee performance, it is equally important for an executive to know what task to manage in order to achieve good business results and to effectively address their employees [ 54 ]. Emotional and social skills are also vital for effective leadership [ 130 ]. In contrast, Weinberger [ 131 ] concludes that there is no relationship between leadership effectiveness and EI.

As mentioned earlier, controversies arise between defining and measuring EI. Thus, empirical research on EI and effective leadership has established EI as crucial element for the success of leadership development projects [ 132 ]. Furthermore, there is evidence that EI mediates leadership effectiveness by controlling for cognitive ability and the Big Five personality traits [ 134 ]. Understanding the importance of EI and its connection to personality dimensions therefore provides an additional tool to make leaders more effective and successful [ 135 ].

An emerging team leader is selected primarily on the basis of behavioral skills of coordinating group tasks and supporting others [ 136 ]. Factors of the Big Five personality model are therefore the most consistent constructs of leadership across study settings and emergent and effective leadership [ 60 ]. Consequently, there is a positive correlation between EI and emergent leadership and it is important to understand emotions depending on their applied contexts [ 115 ].

Considering leadership and emotion, group emotion is the result of a combination of the affective composition of the individuals in the group and the affective context of the group itself [ 141 ]. Consequently, obstacles can have a negative impact on the team's work climate, although this impact can be neutralized by leaders adopting more facilitating and transforming styles.

Based on the authors we reviewed, in terms of performance based on a competency model, emotional capabilities were found to influence individual and/or team performance [ 41 , 77 , 87 , 88 , 118 , 130 , 142 , 152 ].

Conclusions regarding leadership and team conflicts indicate that measures of emotional intelligence and empathy explain additional variance in teamwork, project managers’ competencies, and conflict management [ 145 ]. Similarly, Ayoko et al. [ 144 ] argue that teams with less-well-defined emotional intelligence environments are associated with increased task and relationship conflict and conflict intensity. Moreover, more emotionally contaminated employees have higher levels of burnout, and the higher the burnout, the lower the commitment to the group [ 149 ].

Although there is a great deal of research attributing work success and well-being to the positive impact of EI, there is little research that supports such a relationship between leadership and the work environment [ 150 ].

It is important to address the limitations of the selected documents. Academics such as Araujo and Taylor [ 156 ] and Hur et al. [ 109 ] have established that ability measures tend to be less biased than self-report measures. The results of some studies are limited as they are based on a simulation environment using a sample of students [ 123 ]. Additionally, the use of small sample sizes [ 41 , 54 , 60 , 145 , 156 , 166 , 167 ] and data collected from convenience samples [ 122 ] make it impossible to generalize the results. Accordingly, a potential line of future research would be to analyze EI in different cultures and across different sectors [ 15 ]. Further recommendations include conducting more EI assessments based on ability measures, different models, and using mixed assessments [ 129 ].

6. Future research

The use of mindfulness is being developed on both a personal and job level as empirical evidence shows that it has a positive influence on people regulating their emotions and behaviors. Consequently, it has a positive influence on well-being, work performance, and interpersonal relationships, in addition to many other benefits. Likewise, mindfulness practice is recommended for leaders as it helps develop emotional intelligence, social skills and support within organizations [ [97] , [98] , [99] ]. The practice of mindfulness therefore favors the development of resilience and counteracts the effects of BANI and VUCA environments [ 18 , 95 ].

Intergenerational studies (Baby Boomers, Generation X, Generation Y, and Generation Z) continue to be a current topic, as there are papers from 2023 that discuss this topic but they have not been included in the period under study [ 168 ].

Artificial intelligence is among the major advances in technology that affect companies, improving service quality and customer satisfaction. Specifically, worthy of mention are machine learning models that generate content similar to how the human brain learns and responds to data [ 90 , 102 , 103 ]. However, although artificial intelligence can go beyond human abilities to solve complex problems and can generally be useful to improve the internal efficiency of companies, it is still very limited in terms of managing the emotions of employees within an organization [ 18 ].

Finally, we suggest prospective studies using different scales to measure the EI of leaders and individuals within the same organization in order to compare findings and generalize conclusions. The subject invites further research on the topic, jointly assessing the three topics reviewed, the emotional intelligence of leaders and the work team in the same organizational context. The findings could lead to an improved selection process for leaders and team members within an organization.

Acknowledgement of funding sources

The University of Malaga (Spain) funded the publication fees.

Author contribution statement

All authors listed have significantly contributed to the development and the writing of this article.

Data availability statement

Additional information.

No additional information is available for this paper.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

We are very grateful for the critical comments and helpful suggestions made by the anonymous reviewers, which have helped us to improve the paper.

Country sample and activity sectors.

Note. Percentages do not add up to 100%. (1) Brazil, Czech Republic, Denmark, Greece, Israel, Japan, Netherlands, Peru, Serbia, Singapore, South Africa, and Sweden. Each classification adds up to 100%. Source: Own elaboration.

Most cited authors and journals of the reviewed articles, ranking and categories.

Note: Social Sciences Citation Index (SSCI) and Emerging Sources Citation Index (ESCI). See the reference section, where an asterisk (*) marks the 104 reviewed articles. Note. Nº = Number of articles; % % e-share. Source: Own elaboration.

Design Research of the documents and techniques of empirical research.

Note. Nº, Number of documents o number of times the techniques have been used; Perc., Percentage. Authors are in alphabetical order in the table. Source: Own elaboration.

Methods of assessing emotional intelligence.

Classification of documents by main categories.

Note: Authors are in alphabetical order in table. An asterisk (*) marks the 104 reviewed documents in the Reference Section. Source: Own elaboration and Atlas.ti.

Subcategories: emotional intelligence, leadership, and team.

Research objectives.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• My Bibliography
• Collections
• Citation manager

Save citation to file

Email citation, add to collections.

• Create a new collection
• Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

• Search in PubMed
• Search in NLM Catalog
• Add to Search

A Meta-Analysis of the Relationship Between Emotional Intelligence and Academic Performance in Secondary Education: A Multi-Stream Comparison

Affiliations.

• 1 Department of Basic Psychology, Faculty of Psychology, University of Málaga, Málaga, Spain.
• 2 Department of Social Psychology, Faculty of Psychology, University of Jaén, Jaén, Spain.
• 3 Department of Social Psychology, Faculty of Psychology, University of Málaga, Málaga, Spain.
• PMID: 32793030
• PMCID: PMC7385306
• DOI: 10.3389/fpsyg.2020.01517

This study was a quantitative meta-analysis of empirical research on the relationship between emotional intelligence (EI) and academic performance (AP) that included the three main theoretical models of EI. We conducted a computerized literature search in the main electronic databases. Forty-four of an initial 3,210 articles met the inclusion criteria. With 49 effect sizes and a cumulative sample size of 19,861 participants, we found significant heterogeneity indices indicating a variety of results. In general, the results of this study indicated a significant effect of EI on AP ( Z ¯ = 0.26). Average association between EI and AP was higher in studies measured EI as ability ( Z ¯ = 0.31), than studies measured EI as self-report ( Z ¯ = 0.24), and self-report mixed EI ( Z ¯ = 0.26). In the educational field, this meta-analysis provides information on the specific role of EI as a function of used measures. Some practical implications are discussed.

Keywords: academic performance; emotional intelligence; instruments; meta-analysis; secondary education.

Copyright © 2020 Sánchez-Álvarez, Berrios Martos and Extremera.

PubMed Disclaimer

PRISMA flowchart for the identification,…

PRISMA flowchart for the identification, screening, and inclusion of publications in the meta-analyses.

Similar articles

• Are Effect Sizes in Emotional Intelligence Field Declining? A Meta-Meta Analysis. Gong Z, Jiao X. Gong Z, et al. Front Psychol. 2019 Jul 16;10:1655. doi: 10.3389/fpsyg.2019.01655. eCollection 2019. Front Psychol. 2019. PMID: 31379681 Free PMC article.
• Systematic review and meta-analysis: The association between emotional intelligence and subjective well-being in adolescents. Llamas-Díaz D, Cabello R, Megías-Robles A, Fernández-Berrocal P. Llamas-Díaz D, et al. J Adolesc. 2022 Oct;94(7):925-938. doi: 10.1002/jad.12075. Epub 2022 Jul 20. J Adolesc. 2022. PMID: 35860897
• Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas. Crider K, Williams J, Qi YP, Gutman J, Yeung L, Mai C, Finkelstain J, Mehta S, Pons-Duran C, Menéndez C, Moraleda C, Rogers L, Daniels K, Green P. Crider K, et al. Cochrane Database Syst Rev. 2022 Feb 1;2(2022):CD014217. doi: 10.1002/14651858.CD014217. Cochrane Database Syst Rev. 2022. PMID: 36321557 Free PMC article.
• Emotional intelligence in undergraduate medical students: a scoping review. Toriello HV, Van de Ridder JMM, Brewer P, Mavis B, Allen R, Arvidson C, Kovar-Gough I, Novak E, O'Donnell J, Osuch J, Ulrich B. Toriello HV, et al. Adv Health Sci Educ Theory Pract. 2022 Mar;27(1):167-187. doi: 10.1007/s10459-021-10079-2. Epub 2021 Oct 28. Adv Health Sci Educ Theory Pract. 2022. PMID: 34709484 Review.
• Exploring the Association between Emotional Intelligence and Academic Performance and Stress Factors among Dental Students: A Scoping Review. Jahan SS, Nerali JT, Parsa AD, Kabir R. Jahan SS, et al. Dent J (Basel). 2022 Apr 7;10(4):67. doi: 10.3390/dj10040067. Dent J (Basel). 2022. PMID: 35448061 Free PMC article. Review.
• Navigating academic performance: Unravelling the relationship between emotional intelligence, learning styles, and science and technology self-efficacy among preservice science teachers. Amponsah KD, Adu-Gyamfi K, Awoniyi FC, Commey-Mintah P. Amponsah KD, et al. Heliyon. 2024 Apr 16;10(9):e29474. doi: 10.1016/j.heliyon.2024.e29474. eCollection 2024 May 15. Heliyon. 2024. PMID: 38699017 Free PMC article.
• Impact of emotional intelligence and academic self-concept on the academic performance of educational sciences undergraduates. Ubago-Jimenez JL, Zurita-Ortega F, Ortega-Martin JL, Melguizo-Ibañez E. Ubago-Jimenez JL, et al. Heliyon. 2024 Apr 9;10(8):e29476. doi: 10.1016/j.heliyon.2024.e29476. eCollection 2024 Apr 30. Heliyon. 2024. PMID: 38644847 Free PMC article.
• Editorial: Emotional intelligence in applied settings: approaches to its theoretical model, measurement, and application. Ding C, Ramdas M, Mortillaro M. Ding C, et al. Front Psychol. 2024 Mar 7;15:1387152. doi: 10.3389/fpsyg.2024.1387152. eCollection 2024. Front Psychol. 2024. PMID: 38515968 Free PMC article. No abstract available.
• Reduced GM-WM concentration inside the Default Mode Network in individuals with high emotional intelligence and low anxiety: a data fusion mCCA+jICA approach. Grecucci A, Monachesi B, Messina I. Grecucci A, et al. Soc Cogn Affect Neurosci. 2024 Mar 4;19(1):nsae018. doi: 10.1093/scan/nsae018. Soc Cogn Affect Neurosci. 2024. PMID: 38451879 Free PMC article.
• The relationship between emotional intelligence, spiritual intelligence, and student achievement: a systematic review and meta-analysis. Zhou Z, Tavan H, Kavarizadeh F, Sarokhani M, Sayehmiri K. Zhou Z, et al. BMC Med Educ. 2024 Mar 1;24(1):217. doi: 10.1186/s12909-024-05208-5. BMC Med Educ. 2024. PMID: 38429717 Free PMC article.
• Abdo N. (2012). Academic Performance and Social/Emotional Competence in Adolescence. New York, NY: Yeshiva University.
• Abdullah M. C., Elias H., Mahyuddin R., Uli J. (2004). EI and academic achievement among malaysian secondary students. Pakistan J. Psychol. Res. 19, 105–121.
• Abel N. R. (2014). Trait Emotional Intelligence, Perceived Discrimination, and Academic Achievement among African American and Latina/O High School Students: A Study of Academic Resilience. Mankato, MN: Minnesota State University.
• Ang S., van Dyne L. (2015). Conceptualization of cultural intelligence: definition, distinctiveness, and nomological network, in Handbook of Cultural Intelligence (New York, NY: Routledge; ) 21–33.
• Aremu O. A., Tella A., Tella A. (2006). Relationship among emotional intelligence, parental involvement and academic achievement of secondory school students in Ibadan, Nigeria. Essays Educ. 18, 1–14.

Publication types

• Search in MeSH

Related information

Linkout - more resources, full text sources.

• Europe PubMed Central
• Frontiers Media SA
• PubMed Central

Miscellaneous

• NCI CPTAC Assay Portal

• Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

REVIEW article

The measurement of emotional intelligence: a critical review of the literature and recommendations for researchers and practitioners.

• 1 School of Management, QUT Business School, Queensland University of Technology, Brisbane, QLD, Australia
• 2 Clinical Skills Development Service, Metro North Hospital and Health Service, Queensland Health, Brisbane, QLD, Australia
• 3 School of Psychology, Faculty of Health and Behavioural Sciences, The University of Queensland, St. Lucia, QLD, Australia
• 4 School of Advertising, Marketing and Public Relations, QUT Business School, Queensland University of Technology, Brisbane, QLD, Australia

Emotional Intelligence (EI) emerged in the 1990s as an ability based construct analogous to general Intelligence. However, over the past 3 decades two further, conceptually distinct forms of EI have emerged (often termed “trait EI” and “mixed model EI”) along with a large number of psychometric tools designed to measure these forms. Currently more than 30 different widely-used measures of EI have been developed. Although there is some clarity within the EI field regarding the types of EI and their respective measures, those external to the field are faced with a seemingly complex EI literature, overlapping terminology, and multiple published measures. In this paper we seek to provide guidance to researchers and practitioners seeking to utilize EI in their work. We first provide an overview of the different conceptualizations of EI. We then provide a set of recommendations for practitioners and researchers regarding the most appropriate measures of EI for a range of different purposes. We provide guidance both on how to select and use different measures of EI. We conclude with a comprehensive review of the major measures of EI in terms of factor structure, reliability, and validity.

Overview and Purpose

The purpose of this article is to review major, widely-used measures of Emotional Intelligence (EI) and make recommendations regarding their appropriate use. This article is written primarily for academics and practitioners who are not currently experts on EI but who are considering utilizing EI in their research and/or practice. For ease of reading therefore, we begin this article with an introduction to the different types of EI, followed by a brief summary of different measures of EI and their respective facets. We then provide a detailed set of recommendations for researchers and practitioners. Recommendations focus primarily on choosing between EI constructs (ability EI, trait EI, mixed models) as well as choosing between specific tests. We take into account such factors as test length, number of facets measured and whether tests are freely available. Consequently we also provide recommendations both for users willing to purchase tests and those preferring to utilize freely available measures.

In our detailed literature review, we focus on a set of widely used measures and summarize evidence for their validity, reliability, and conceptual basis. Our review includes studies that focus purely on psychometric properties of EI measures as well as studies conducted within applied settings, particularly health care settings. We include comprehensive tables summarizing key empirical studies on each measure, in terms of their research design and main findings. Our review includes measures that are academic and/or commercial as well as those that are freely available or require payment. To assist users with accessing measures, we include web links to complete EI questionaries for freely available measures and to websites and/or example items for copyrighted measures. For readers interested in reviews relating primarily to EI constructs, theory and outcomes rather than specifically measures of EI, we recommend a number of recent high quality publications (e.g., Kun and Demetrovics, 2010 ; Gutiérrez-Cobo et al., 2016 ). Additionally, for readers interested in a review of measures without the extensive recommendations we provide here, we recommend the chapter by Siegling et al. (2015) .

Early Research on Emotional Intelligence

EI emerged as a major psychological construct in the early 1990s, where it was conceptualized as a set of abilities largely analogous to general intelligence. Early influential work on EI was conducted by Salovey and Mayer (1990) , who defined EI as the “the ability to monitor one's own and others' feelings and emotions, to discriminate among them and to use this information to guide one's thinking and actions” (p. 189). They argued that individuals high in EI had certain emotional abilities and skills related to appraising and regulating emotions in the self and others. Accordingly, it was argued that individuals high in EI could accurately perceive certain emotions in themselves and others (e.g., anger, sadness) and also regulate emotions in themselves and others in order to achieve a range of adaptive outcomes or emotional states (e.g., motivation, creative thinking).

However, despite having a clear definition and conceptual basis, early research on EI was characterized by the development of multiple measures (e.g., Bar-On, 1997a , b ; Schutte et al., 1998 ; Mayer et al., 1999 ) with varying degrees of similarity (see Van Rooy et al., 2005 ). One cause of this proliferation was the commercial opportunities such tests offered to developers and the difficulties faced by researchers seeking to obtain copyrighted measures (see section Mixed EI for a summary of commercial measures). A further cause of this proliferation was the difficulty researchers faced in developing measures with good psychometric properties. A comprehensive discussion of this issue is beyond the scope of this article (see Petrides, 2011 for more details) however one clear challenge faced by early EI test developers was constructing emotion-focused questions that could be scored with objective criteria. In comparison to measures of cognitive ability that have objectively right/wrong answers (e.g., mathematical problems), items designed to measure emotional abilities often rely on expert judgment to define correct answers which is problematic for multiple reasons ( Roberts et al., 2001 ; Maul, 2012 ).

A further characteristic of many early measures was their failure to discriminate between measures of typical and maximal performance. In particular, some test developers moved away from pure ability based questions and utilized self-report questions (i.e., questions asking participants to rate behavioral tendencies and/or abilities rather than objectively assessing their abilities; e.g., Schutte et al., 1998 ). Other measures utilized broader definitions of EI that included social effectiveness in addition to typical EI facets (see Ashkanasy and Daus, 2005 ) (e.g., Boyatzis et al., 2000 ; Boyatzis and Goleman, 2007 ). Over time it became clear that these different measures were tapping into related, yet distinct underlying constructs. Currently, there are two popular methods of classifying EI measures. First is the distinction between trait and ability EI proposed initially by Petrides and Furnham (2000) and further clarified by Pérez et al. (2005) . Second is in terms of the three EI “streams” as proposed by Ashkanasy and Daus (2005) . Fortunately there is overlap between these two methods of classification as we discuss below.

Methods of Classifying EI

The distinction between ability EI and trait EI first proposed by Petrides and Furnham (2000) was based purely on whether the measure was a test of maximal performance (ability EI) or a self-report questionnaire (trait EI) ( Petrides and Furnham, 2000 ; Pérez et al., 2005 ). According to this method of classification, Ability EI tests measure constructs related to an individual's theoretical understanding of emotions and emotional functioning, whereas trait EI questionnaires measure typical behaviors in emotion-relevant situations (e.g., when an individual is confronted with stress or an upset friend) as well as self-rated abilities. Importantly, the key aspect of this method of classification is that EI type is best defined by method of measurement: all EI measures that are based on self-report items are termed “trait EI” whereas all measures that are based on maximal performance items are termed “ability EI”.

The second popular method of classifying EI measures refers the three EI “streams” ( Ashkanasy and Daus, 2005 ). According to this method of classification, stream 1 includes ability measures based on Mayer and Salovey's model; stream 2 includes self-report measures based on Mayer and Salovey's model and stream 3 includes “expanded models of emotional intelligence that encompass components not included in Salovey and Mayer's definition” (p. 443). Ashkanasy and Daus (2005) noted that stream 3 had also been referred to as “mixed” models in that they comprise a mixture of personality and behavioral items. The term “mixed EI” is now frequently used in the literature to refer to EI measures that measure a combination of traits, social skills and competencies and overlaps with other personality measures ( O'Boyle et al., 2011 ).

Prior to moving on, we note that Petrides and Furnham's (2000 ) trait vs. ability distinction is sufficient to categorize the vast majority of EI tests. Utilizing this system, both stream 2 (self-report) and stream 3 (self-report mixed) are simply classified as “trait” measures. Indeed as argued by Pérez et al. (2005) , this method of classification is probably sufficient given that self-report measures of EI tend to correlate strongly regardless of whether they are stream 2 or stream 3 measures. However, given that the terms “stream 3” and “mixed” are so extensively used in the EI literature, we will also use them here. We are not proposing that these terms are ideal or even useful when classifying EI, but rather we wish to adopt language that is most representative of the existing literature on EI. In the following section therefore, we refer to ability EI (stream 1), trait EI (steam 2), and mixed EI (stream 3). As outlined later, decisions regarding which measure of EI to use should be based on what form of EI is relevant to a particular research project or professional application.

For the purposes of this review, we refer to “ability” based measures as tests that utilize questions/items comparable to those found in IQ tests (see Austin, 2010 ). These include all tests containing ability-type items and not only those based directly on Mayer and Salovey's model. In contrast to trait based measures, ability measures do not require that participants self-report on various statements, but rather require that participants solve emotion-related problems that have answers that are deemed to be correct or incorrect (e.g., what emotion might someone feel prior to a job interview? (a) sadness, (b) excitement, (c) nervousness, (d) all of the above). Ability based measures give a good indication of individuals' ability to understand emotions and how they work. However since they are tests of maximal ability, they do not tend to predict typical behavior as well as trait based measures (see O'Connor et al., 2017 ). Nevertheless, ability-based measures are valid, albeit weak, predictors of a range of outcomes including work related attitudes such as job satisfaction ( Miao et al., 2017 ), and job performance ( O'Boyle et al., 2011 ).

In this review, we define trait based measures as those that utilize self-report items to measure overall EI and its sub dimensions. We utilize this term for measures that are self-report, and have not explicitly been termed as “mixed” or “stream 3” by others. Individuals high in various measures of trait EI have been found to have high levels of self-efficacy regarding emotion-related behaviors and tend to be competent at managing and regulating emotions in themselves and others. Also, since trait EI measures tend to measure typical behavior rather than maximal performance, they tend to provide a good prediction of actual behaviors in a range of situations ( Petrides and Furnham, 2000 ). Recent meta-analyses have linked trait EI to a range of work attitudes such as job satisfaction and organization commitment ( Miao et al., 2017 ), Job Performance ( O'Boyle et al., 2011 ).

As noted earlier, although the majority of EI measures can be categorized using the terms “ability EI” and “trait EI”, we adopt the term “mixed EI” in this review when this term has been explicitly used in our source articles. The term mixed EI is predominately used to refer to questionnaires that measure a combination of traits, social skills and competencies that overlap with other personality measures. Generally these measures are self-report, however a number also utilize 360 degree forms of assessment (self-report combined with multiple peer reports from supervisors, colleagues and subordinates) (e.g., Bar-On, 1997a , b ) This is particularly true for commercial measures designed to predict and improve performance in the workplace. A common aspect in many of these measures is the focus on emotional “competencies” which can theoretically be developed in individuals to enhance their professional success (See Goleman, 1995 ). Research on mixed measures have found them to be valid predictors of multiple emotion-related outcomes including job satisfaction, organizational commitment ( Miao et al., 2017 ), and job performance ( O'Boyle et al., 2011 ). Effect sizes of these relationships tend to be moderate and on par with trait-based measures.

We note that although different forms of EI have emerged (trait, ability, mixed) there are nevertheless a number of conceptual similarities in the majority of measures. In particular, the majority of EI measures are regarded as hierarchical meaning that they produce a total “EI score” for test takers along with scores on multiple facets/subscales. Additionally, the facets in ability, trait and mixed measures of EI have numerous conceptual overlaps. This is largely due to the early influential work of Mayer and Salovey. In particular, the majority of measures include facets relating to (1) perceiving emotions (in self and others), (2) regulating emotions in self, (3) regulating emotions in others, and (4) strategically utilizing emotions. Where relevant therefore, this article will compare how well different measures of EI assess the various facets common to multiple EI measures.

Emotional Intelligence Scales

The following emotional intelligence scales were selected to be reviewed in this article because they are all widely researched general measures of EI that also measure several of the major facets common to EI measures (perceiving emotions, regulating emotions, utilizing emotions).

1. Mayer-Salovey-Caruso Emotional Intelligence Tests (MSCEIT) ( Mayer et al., 2002a , b ).

2. Self-report Emotional Intelligence Test (SREIT) ( Schutte et al., 1998 )

3. Trait Emotional Intelligence Questionnaire (TEIQue) ( Petrides and Furnham, 2001 )

4. Bar-On Emotional Quotient Inventory (EQ-i) ( Bar-On, 1997a , b )

5. i) The Situational Test of Emotional Management (STEM) ( MacCann and Roberts, 2008 )

ii) The Situational Test of Emotional Understanding (STEU) ( MacCann and Roberts, 2008 )

6. Emotional and Social competence Inventory (ESCI) ( Boyatzis and Goleman, 2007 )

The complete literature review of these measures is included in the Literature Review section of this article. The following section provides a set of recommendations regarding which of these measures is appropriate to use across various research and applied scenarios.

Recommendations Regarding the Appropriate Use of Measures

Deciding between measuring trait ei, ability ei and mixed ei.

A key decision researchers/practitioners need to make prior to incorporating EI measures into their work is whether they should utilize a trait, ability or mixed measure of EI. In general, we suggest that when researchers/practitioners are interested in emotional abilities and competencies then they should utilize measures of ability EI. In particular ability EI is important in situations where a good theoretical understanding of emotions is required. For example a manager high in ability EI is more likely to make good decisions regarding team composition. Indeed numerous studies on ability EI and decision making in professionals indicates that those high in EI tend to be competent decision makers, problem solvers and negotiators due primarily to their enhanced abilities at perceiving and understanding emotions (see Mayer et al., 2008 ). More generally, ability EI research also has demonstrated associations between ability EI and social competence in children ( Schultz et al., 2004 ) and adults ( Brackett et al., 2006 ).

We suggest that researchers/practitioners should select trait measures of EI when they are interested in measuring behavioral tendencies and/or emotional self-efficacy. This should be when ongoing, typical behavior is likely to lead to positive outcomes, rather than intermittent, maximal performance. For example, research on task-induced stress (i.e., temporary states of negative affect evoked by short term, challenging tasks) has shown trait EI to have incremental validity over other predictors ( O'Connor et al., 2017 ). More generally, research tends to show that trait EI is a good predictor of effective coping styles in response to life stressors (e.g., Austin et al., 2010 ). Overall, trait EI is associated with a broad set of emotion and social related outcomes adults and children ( Mavroveli and Sánchez-Ruiz, 2011 ; Petrides et al., 2016 ) Therefore in situations characterized by ongoing stressors such as educational contexts and employment, we suggest that trait measures be used.

When both abilities and traits are important, researchers/practitioners might choose to use both ability and trait measures. Indeed some research demonstrates that both forms of EI are important stress buffers and that they exert their protective effects at different stages of the coping process: ability EI aids in the selection of coping strategies whereas trait EI predicts the implementation of such strategies once selected ( Davis and Humphrey, 2014 ).

Finally, when researchers/practitioners are interested in a broader set of emotion-related and social-related dispositions and competencies we recommend a mixed measure. Mixed measures are particularly appropriate in the context of the workplace. This seems to be the case for two reasons: first, the tendency to frame EI as a set of competencies that can be trained (e.g., Goleman, 1995 ; Boyatzis and Goleman, 2007 ) is likely to equip workers with a positive growth mindset regarding their EI. Second, the emphasis on 360 degree forms of assessment in mixed measures provides individuals with information not only on their self-perceptions, but on how others perceive them which is also particularly useful in training situations.

Advantages and Disadvantages of Trait and Ability EI

There are numerous advantages and disadvantages of the different forms of EI that test users should factor into their decision. One disadvantage of self-report measures is that people are not always good judges of their emotion-related abilities and tendencies ( Brackett et al., 2006 ; Sheldon et al., 2014 ; Boyatzis, 2018 ). A further disadvantage of self-report, trait based measures is their susceptibility to faking. Participants can easily come across as high in EI by answering questions in a strategic, socially desirable way. However, this is usually only an issue when test-takers believe that someone of importance (e.g., a supervisor or potential employer) will have access to their results. When it is for self-development or research, individuals are less likely to fake their answers to trait EI measures (see Tett et al., 2012 ). We also note that the theoretical bases of trait and mixed measures have also been questioned. Some have argued for example that self-report measures of EI measure nothing fundamentally different from the Big Five (e.g., Davies et al., 1998 ). We will not address this issue here as it has been extensively discussed elsewhere (e.g., Bucich and MacCann, 2019 ) however we emphasize that regardless of the statistical distinctiveness of self-report measures of EI, there is little question regarding their utility and predictive validity ( O'Boyle et al., 2011 ; Miao et al., 2017 ).

One advantage of ability based measures is that they cannot be faked. Test-takers are told to give the answer they believe is correct, and consequently should try to obtain a score as high as possible. A further advantage is that they are often more engaging tests. Rather than simply rating agreement with statements as in trait based measures, test-takers attempt to solve emotion-related problems, solve puzzles, and rate emotions in pictures.

Overall however, there are a number of fundamental problems with ability based measures. First, many personality and intelligence theorists question the very existence of ability EI, and suggest it is nothing more than intelligence. This claim is supported by high correlations between ability EI and IQ, although some have provided evidence to the contrary (e.g., MacCann et al., 2014 ). Additionally, the common measures of ability EI tend to have relatively poor psychometric properties in terms of reliability and validity. Ability EI measures do not tend to strongly predict outcomes that they theoretically should predict (e.g., O'Boyle et al., 2011 ; Miao et al., 2017 ). Maul (2012) also outlines a comprehensive set of problems with the most widely used ability measure, the MSCEIT, related to consensus-based scoring, reliability, and underrepresentation of the EI construct. Also see Petrides (2011) for a comprehensive critique of ability measures.

General Recommendation for Non-experts Choosing Between Ability and Trait EI

While the distinction between trait, ability and mixed EI is important, we acknowledge that many readers will simply be looking for an overall measure of emotional functioning that can predict personal and professional effectiveness. Therefore, when potential users have no overt preference for trait or ability measures but need to decide, we strongly recommend researchers/ practitioners begin with a trait-based measure of EI . Compared to ability based measures, trait based measures tend to have very good psychometric properties, do not have questionable theoretical bases and correlate moderately and meaningfully with a broad set of outcome variables. In general, we believe that trait based measures are more appropriate for most purposes than ability based measures. That being said, several adequate measures of ability EI exist and these have been reviewed in the Literature Review section. If there is a strong preference to use ability measures of EI then several good options exist as outlined later.

Choosing a Specific Measure of Trait EI

Based on our literature review we suggest that a very good, comprehensive measure of trait EI is the Trait Emotional Intelligence Questionnaire, or TEIQue ( Petrides and Furnham, 2001 ). If users are not restricted by time or costs (commercial users need to pay, researchers do not) then the TEIQue is a very good option. The TEIQue is a widely used questionnaire that measures 4 factors and 15 facets of trait EI. It has been cited in more than 2,000 academic studies. It is regarded as a “trait” measure of EI because it is based entirely on self-report responses, and facet scores represent typical behavior rather than maximal performance. There is extensive evidence in support of its reliability and validity ( Andrei et al., 2016 ). The four factors of the TEIQue map on to the broad EI facets present in multiple measures of EI as follows: emotionality = perceiving emotions, self-control = regulating emotions in self, sociability = regulating emotions in others, well-being = strategically utilizing emotions.

One disadvantage of the TEIQue however is that it is not freely available for commercial use. The website states that commercial or quasi-commercial use without permission is prohibited. The test can nevertheless be commercially used for a relatively small fee. The relevant webpage can be found here ( http://psychometriclab.com/ ). A second disadvantage is that the test can be fairly easily faked due to its use of a self-report response scale. However, this is generally only an issue when individuals have a reason for faking (e.g., their score will be seen by someone else and might impact their prospects of being selected for a job) (see Tett et al., 2012 ). Consequently, we do not recommend the TEIQue to be used for personnel selection, but it is relevant for other professional purposes such as in EI training and executive coaching.

There are very few free measures of trait EI that have been adequately investigated. One exception is the widely used, freely available measure termed the Self-Report Emotional Intelligence Test (SREIT, Schutte et al., 1998 ). The SREIT has been cited more than 3,000 times. The full paper which includes all test items can be accessed here ( https://www.researchgate.net/publication/247166550_Development_and_Validation_of_a_Measure_of_Emotional_Intelligence ). Although it was designed to measure overall EI, subsequent research indicates that it performs better as a multidimensional scale measuring 4 distinct factors including: optimism/mood regulation, appraisal of emotions, social skills and utilization of emotions. These four scales again map closely to the broad facets present in many EI instruments as follows: optimism/mood regulation = regulating emotions in self, appraisal of emotions = perceiving emotions in self, social skills = regulating emotions in others, and utilization of emotions = strategically utilizing emotions. Please note that although one study has comprehensively critiqued the SREIT ( Petrides and Furnham, 2000 ), it actually works well as a multidimensional measure. This was acknowledged by the authors of the critique and has been subsequently confirmed (e.g., by O'Connor and Athota, 2013 ).

Long vs. Short Measures of Trait EI

The TEIQue is available in long form (153 items, 15 facets, 4 factors) and short form (30 items, 4 factors/subscales). A complete description of all factors and facets can be found here ( http://www.psychometriclab.com/adminsdata/files/TEIQue%20interpretations.pdf ). We recommend using the short form when users are interested in measuring only the 4 broad EI factors measured by this questionnaire (self-control, well-being, sociability, emotionality). Additionally, there is much more research on the short form of the questionnaire (e.g., Cooper and Petrides, 2010 ) (see Table 5 ), and the scoring instructions for the short form are freely available for researchers. If the short form is used, it is recommended that all factors/subscales are utilized because they predict outcomes in different ways (e.g., O'Connor and Brown, 2016 ). The SREIT is available only as a short, 33 item measure. All subscales are regarded as equally important and should be included if possible. Again it is noted that this test is freely available and the article publishing the items specifically states “Note: the authors permit free use of the scale for research and clinical purposes.”

When users require a comprehensive measure of trait EI, the long form of the TEIQue is also a good option (see Table 5 ). Although not as widely researched as the short version, the long version nevertheless has strong empirical support for reliability and validity. The long form is likely to be particularly useful for coaching and training purposes, because the use of 15 narrow facets allows for more focused training and intervention than measures with fewer broad facets/factors.

Choosing Between Measures of Ability EI

The most researched and supported measure of ability EI is the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT) (see Tables 2 , 3 ). It has been cited in more than 1,500 academic studies. It uses a 4 branch approach to ability EI and measures ability dimensions of perceiving emotions, facilitating thought, understanding emotions and managing emotions. These scales broadly map onto the broad constructs present in many measures of EI as follows: facilitating thought = strategically utilizing emotions, perceiving emotions = perceiving emotions in self and others, understanding emotions = understanding emotions, and managing emotions = regulating emotions in self and others. However, this is a highly commercialized test and relatively expensive to use. The test is also relatively long (141 items) and time consuming to complete (30–45 min).

A second, potentially more practical option includes two related tests of ability EI designed by MacCann and Roberts (2008) (see Tables 2 , 7 ). These tests are called the Situational Test of Emotion Management (STEM) and the Situational Test of Emotional Understanding (the STEU). These tests are becoming increasingly used in academic articles; the original paper has now been cited more than 250 times. The two aspects of ability EI measured in these tests map neatly onto two of the broad EI constructs present in multiple measures of EI. Specifically, the STEM can be regarded as a measure of emotional regulation in oneself and the STEU can be regarded as a measure of emotional understanding. As indicated in Table 7 , there is strong psychometric support for these tests (although the alpha for STEU is sometimes borderline/low). A further advantage of STEU is that it contains several items regarding workplace behavior, making it highly applicable for use in professional contexts.

If researchers/practitioners decide to use the STEM and STEU, additional measures might be required to measure the remaining broad EI constructs present in other tests. Although these measures could all come from relevant scales of tests reviewed in this article (see Table 1 ), there is a further option. Users should consider the Diagnostic Analysis of Non-verbal Accuracy scale (DANVA) which is a widely used, validated measure of perceiving emotion in others (see Nowicki and Duke, 1994 for an introduction to the DANVA). Alternatively, for those open to using a combination of ability and trait measures, users might wish to use Schutte et al.'s (1998) SREIT to assess remaining facets of EI (see Table 4 ). This is because it is free and captures aspects of EI not measured by STEM/STEU. These include appraisal of emotions (for perceiving emotions) and utilization of emotions (for strategically utilizing emotions), respectively.

Table 1 . Summary of recommended emotional intelligence assessment measures for each broad EI construct.

Therefore, if there is a strong preference to utilize ability based measures, the STEM, STEU, and DANVA represent some very good options worth considering. The advantage of using these over the MSCEIT is the lower cost of these measures and the reduced test time. Although the STEM, STEU, and DANVA do not seem to be freely available for commercial use, they are nevertheless appropriate for commercial use and likely to be cheaper than alternative options at this point in time.

Deciding Between Using a Single Measure or Multiple Measures

When seeking to measure EI, researchers/practitioners could choose to use (1) a single EI tool that measures overall EI along with common EI facets (i.e., perceiving emotions in self and others, regulating emotions in self and others and strategically utilizing emotions) or (2) some combination of existing scales from EI tool/s to cumulatively measure the four constructs.

The first option represents the most pragmatic and generally optimal solution because all information about the relevant facets and related measures would usually be located in a single document (e.g., test manual, journal article) or website. Additionally, if a paid test is used it would only require a single payment to a single author/institution. Furthermore, single EI tools are generally based on theoretical models of EI that have implications for training and development. For example EI facets in Goleman's (1995 ) model (as measured using the ESCI, Boyatzis and Goleman, 2007 ) are regarded as characteristics that can be trained. Therefore, if a single EI tool is selected, the theory underlying the tool could be used to model the interventions.

However, a disadvantage of the first option is that some EI measures will not contain the specific set of EI constructs researchers/practitioners are interested in assessing. This will often be the case when practitioners are seeking a comprehensive measure of EI but prefer a freely available measure. The second option specified above would solve this problem. However, the trade-off would be increased complexity and the absence of a single underlying theory that relates to the selected measures. Tables 2 – 8 describe facets within each measure as well as reliability and validity evidence for each facet and can be used to assist the selection of multiple measures if users choose to do this.

Table 2 . Summary of major emotional Intelligence assessment measures.

Table 3 . Review of selected studies detailing psychometric properties of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT).

Table 4 . Review of selected studies detailing psychometric properties of the Self-report Emotional Intelligence Test (SREIT).

Table 5 . Review of selected studies on psychometric properties of the Trait Emotional Intelligence Questionnaire (TEIQue).

Table 6 . Review of selected studies on psychometric properties of the Emotional Quotient Inventory (EQ-i) ( Bar-On, 1997a , b ).

Table 7 . Review of selected studies on psychometric properties of the STEU and STEM.

Table 8 . Review of selected studies on psychometric properties of the Emotional and Social competence Inventory (ESCI).

The Best Measure of Each Broad EI Construct (Evaluated Across all Reviewed Tests)

In some cases, researchers/practitioners will not need to measure overall EI, but instead seek to measure a single dimension of EI (e.g., emotion perception, emotion management etc.). In general, we caution the selective use of individual EI scales and recommend that users habitually measure and control for EI facets they are not directly interested in. Nevertheless, we acknowledge that in some cases users will have to select a single measure and consequently, this section specifies a selection of what we consider the “best” measures for each construct. We do this for both free measures and those requiring payment. In order to determine which measure constitutes the “best” measure for each construct, the following criteria were applied:

1. The measure should have been used in multiple research studies published in high quality journals.

2. There should be good evidence for the reliability of the measure in multiple academic studies incorporating the measure.

3. The measure should have obtained adequate validity evidence in multiple academic studies. Most importantly, evidence of construct validity should have been established, including findings demonstrating that the measure correlates meaningfully with measures of related constructs.

4. The measure should be based on a strong and well-supported theory of EI.

5. The measure should be practical (i.e., easy to administer, quickly completed and scored).

Where multiple measures met the above criteria, they were compared on their performance on each criterion (i.e., a measure with a lot of research scored higher on the first criteria than a measure with a medium level of research). Table 1 summarizes these results.

Please note that the Emotional and Social Intelligence Inventory (ESCI) by Boyatzis and Goleman (2007) has subscales that are also closely related to the ones listed in Table 1 (see full technical manual here ( http://www.eiconsortium.org/pdf/ESCI_user_guide.pdf ). The measure was developed primarily to predict and enhance performance at work and items are generally written to reflect workplace scenarios. Subscales from this test were not consistently chosen as the “best” measures because it has not had as extensive published research as the other tests. Most research using this measure has also used peer-ratings rather than self-ratings which makes it difficult to compare with the majority of measures (this is not a weakness though). Nevertheless, it should be considered if cost is not an issue and there is a strong desire to utilize a test specifically developed for the workplace.

Qualifications and Training

Although our purpose in this paper is not to outline the necessary training or qualifications required to administer the set of tests/questionnaires reviewed, we feel it is important to make some comments on this. First, we recommend that all researchers and practitioners considering using one more of these tests have a good understanding of the principles of psychological assessment. Users should understand the concepts of reliability, validity and the role of norms in psychological testing. There are many good introductory texts in this area (e.g., Kaplan and Saccuzzo, 2017 ). Furthermore, we recommend users have a good understanding of the limitations of psychological testing and assessment. When using EI measures to evaluate suitability of job applicants, these measures should form only part of the assessment process and should not be regarded as comprehensive information about applicants. Finally, some of the tests outlined in this review require specific certification and/or qualifications. Certification and/or qualification is required for administrators of the ESCI, MSCEIT, and EQi 2.0).

Literature Review

The final section of this article is a literature review of the 6 popular measures we have covered. We have included our review at the end of this article because we regard it as optional reading. We suggest that this section will be useful primarily for those seeking a more in depth understanding of the key studies underlying the various measures we have presented in earlier sections.

This literature review had two related aims; first to identify prominent EI measures used in the literature, as well as specifically in applied (e.g., health care) contexts. The emotional intelligence measures we included were those that measured both overall EI as well as more specific EI constructs common to multiple measures (e.g., those related to perceiving emotions in self and others, regulating emotions in self and others and strategically utilizing emotions). The second aim was to identify individual studies that have explored the validity and reliability of the specific emotional intelligence measures identified.

Inclusion Criteria

Four main inclusion criteria were applied to select literature: (a) focus on adult samples, (b) use of reputable, peer-reviewed journal articles, (c) use of an EI scale, and (d) where possible, use of a professional sample (e.g., health care professionals) rather than primarily student samples. The literature search therefore focused on empirical, quantitative investigations published in peer-reviewed journals. The articles reviewed therefore were generally methodologically sound and enabled a thorough analysis of some aspect of reliability or validity. We only reviewed articles published after 1990. Additionally, only papers in English were reviewed.

Papers were identified by conducting searches in the following electronic databases: PsycINFO, Medline, PubMED, CINAHL (Cumulative Index for Nursing and Allied Health Literature), EBSCO host and Google Scholar. Individual journals were also scanned such as The Journal of Nursing Measurement and Psychological Assessment.

Search Terms

When searching for emotional intelligence scales and related literature, search terms included: trait emotional intelligence, ability emotional intelligence, emotional intelligence scales, mixed emotional intelligence and emotional intelligence measures. Some common EI facet titles (e.g., self-awareness, self-regulation/self-management, social awareness, and relationship management) were also entered as search terms however this revealed far less relevant literature than searches based on EI terms. To access studies using professionals we also used terms such as workplace, healthcare, and nursing, along with emotional intelligence.

When searching for literature on the identified scales, the name of the respective scale was included in the search term (such as TEIQue scale) and the authors' names, along with terms such as workplace, organization, health care, nurses, health care professionals, to identify specific studies with a professional employee sample that utilized the specific scale. The terms validity and reliability were also used. Additionally, a similar search was conducted on articles that had cited the original papers. This search was done conducted utilizing Google Scholar. Table 2 summarizes the result of the first part of the literature review. It provides an overview of major Emotional Intelligence assessment measures, in terms of when they were developed, who developed them, what form of EI they measure, theoretical basis, test length and details regarding cost.

Tables 3 – 8 summarize research on the validity and reliability of the 6 tests included in Table 2 . In these tables we summarize the methodology used in major studies assessing reliability and validity as well as the results from these studies.

Collectively, these tables indicate that all 6 of the measures we reviewed have received some support for their reliability and validity. Measures with extensive research include the MSCEIT, SREIT, and TEIQue, and EQ-I and those with less total research are the STEU/STEM and ESCI. Existing research does not indicate that these latter measures are any less valid or reliable that the others; on the contrary they are promising measures but require further tests of reliability and validity. As noted previously, this table confirms that the tests with the strongest current evidence for construct and predictive validity are the self-report/trait EI measures (TEIQue, EQ-I, and SREIT). We note that although there is evidence for construct validity of the SREIT based on associations with theoretically related constructs (e.g., alexithymia, optimism; see Table 4 ), some have suggested the measure is problematic due to its use of self-report questions that primarily measure ability based constructs (see Petrides and Furnham, 2000 ).

In this article we have reviewed six widely used measures of EI and made recommendations regarding their appropriate use. This article was written primarily for researchers and practitioners who are not currently experts on EI and therefore we also clarified the difference between ability EI, trait EI and mixed EI. Overall, we recommend that users should use single, complete tests where possible and choose measures of EI most suitable for their purpose (i.e., choose ability EI when maximal performance is important and trait EI when typical performance is important). We also point out that, across the majority of emotion-related outcomes, trait EI tends to be a stronger predictor and consequently we suggest that new users of EI consider using a trait-based measure before assessing alternatives. The exception is in employment contexts where tests utilizing 360 degree assessment (primarily mixed measures) can also be very useful.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

The QUT library funded the article processing charges for this paper.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Andrei, F., Siegling, A. B., Aloe, A. M., Baldaro, B., and Petrides, K. V. (2016). The incremental validity of the trait emotional intelligence questionnaire (TEIQue): a systematic review and meta-analysis. J. Personal. Assess. 98, 261–276. doi: 10.1080/00223891.2015.1084630

PubMed Abstract | CrossRef Full Text | Google Scholar

Ashkanasy, N. M., and Daus, C. S. (2005). Rumors of the death of emotional intelligence in organizational behavior are vastly exaggerated. J. Organiz. Behav. 26, 441–452. doi: 10.1002/job.320

CrossRef Full Text | Google Scholar

Austin, E. J. (2010). Measurement of ability emotional intelligence: Results for two new tests. Br. J. Psychol. 101, 563–578. doi: 10.1348/000712609X474370

Austin, E. J., Saklofske, D. H., and Mastoras, S. M. (2010). Emotional intelligence, coping and exam-related stress in Canadian undergraduate students. Austral. J. Psychol. 62, 42–50. doi: 10.1080/00049530903312899

Bar-On, R. (1996). The Emotional Quotient Inventory (EQ-i): A Test of Emotional Intelligence . Toronto, ON: Multi-Health Systems.

Google Scholar

Bar-On, R. (1997a). Bar-On Emotional Quotient Inventory: User's Manual. Toronto, ON: Multihealth Systems.

Bar-On, R. (1997b). The Emotional Quotient Inventory (EQ-i): Technical manual . Toronto, ON: Multi-Health Systems, Inc.

Bar-On, R. (2006). The Bar-On model of emotional-social intelligence (ESI). Psicothema 18, 13–25.

PubMed Abstract | Google Scholar

Bar-On, R., Brown, J. M., Kirkcaldy, B. D., and Thomé, E. P. (2000). Emotional expression and implications for occupational stress; an application of the emotional quotient inventory (EQ-i). Personal. Indiv. Differe. 28, 1107–1118. doi: 10.1016/S0191-8869(99)00160-9

Boyatzis, R., Rochford, K., and Cavanagh, K. V. (2017). Emotional intelligence competencies in engineer's effectiveness and engagement. Career Dev. Int. 22, 70–86. doi: 10.1108/CDI-08-2016-0136

Boyatzis, R. E. (2018). The behavioral level of emotional intelligence and its measurement. Front. Psychol. 9:01438. doi: 10.3389/fpsyg.2018.01438

Boyatzis, R. E., and Gaskin, J. (2010). A Technical Note on the ESCI and ESCI-U: Factor Structure, Reliability, Convergent and Discriminant Validity Using EFA and CFA . Boston, MA: The Hay Group.

Boyatzis, R. E., and Goleman, D. (2007). Emotional and Social Competency Inventory. Boston, MA: The Hay Group.

Boyatzis, R. E., Goleman, D., and Rhee, K. (2000). “Clustering competence in emotional intelligence: insights from the emotional competence inventory (ECI),”in Handbook of Emotional Intelligence, eds R. Bar-On and J. D. A. Parker (San Francisco, CA: Jossey-Bass), 343–362

Brackett, M. A., and Mayer, J. D. (2003). Convergent, discriminant, and incremental validity of competing measures of emotional intelligence. Personal. Social Psychol. Bull. 29, 1147–1158. doi: 10.1177/0146167203254596

Brackett, M. A., Rivers, S. E., Shiffman, S., Lerner, N., and Salovey, P. (2006). Relating emotional abilities to social functioning: a comparison of self-report and performance measures of emotional intelligence. J. Personal. Social Psychol. 91:780. doi: 10.1037/0022-3514.91.4.780

Bucich, M., and MacCann, C. (2019). Emotional intelligence research in Australia: Past contributions and future directions. Austral. J. Psychol. 71, 59–67. doi: 10.1111/ajpy.12231

Conte, J. M. (2005). A review and critique of emotional intelligence measures. J. Organiz. Behav. 26, 433–440. doi: 10.1002/job.319

Cooper, A., and Petrides, K. (2010). A psychometric analysis of the trait emotional intelligence questionnaire–short form (TEIQue–SF) using item response theory. J. Personal. Assess. 92, 449–457. doi: 10.1080/00223891.2010.497426

Davies, M., Stankov, L., and Roberts, R. D. (1998). Emotional intelligence: in search of an elusive construct. J. Personal. Social Psychol. 75:989. doi: 10.1037/0022-3514.75.4.989

Davis, S. K., and Humphrey, N. (2014). Ability versus trait emotional intelligence. J. Indiv. Differ. 35, 54–52. doi: 10.1027/1614-0001/a000127

Dawda, D., and Hart, S. D. (2000). Assessing emotional intelligence: reliability and validity of the bar-on emotional quotient inventory (EQ-i) in university students. Personal. Indiv. Diff. 28, 797–812. doi: 10.1016/S0191-8869(99)00139-7

Dulewicz, V., Higgs, M., and Slaski, M. (2003). Measuring emotional intelligence: content, construct and criterion-related validity. J. Manag. Psychol. 18, 405–420. doi: 10.1108/02683940310484017

Goleman, D. (1995). Emotional Intelligence . New York, NY: Bantam Books.

Grant, A. M. (2013). Rocking the boat but keeping it steady: The role of emotion regulation in employee voice. Acad. Manag. J. 56, 1703–1723. doi: 10.5465/amj.2011.0035

Gutiérrez-Cobo, M. J., Cabello, R., and Fernández-Berrocal, P. (2016). The relationship between emotional intelligence and cool and hot cognitive processes: a systematic review. Front. Behav. Neurosci. 10:101. doi: 10.3389/fnbeh.2016.00101

Heffernan, M., Quinn Griffin, M. T., Sister Rita McNulty, S. R., and Fitzpatrick, J. J. (2010). Self-compassion and emotional intelligence in nurses. Int. J. Nurs. Pract. 16, 366–373. doi: 10.1111/j.1440-172X.2010.01853.x

Kaplan, R. M., and Saccuzzo, D. P. (2017). Psychological Testing: Principles, Applications, and Issues . Mason, OH: Nelson Education.

Kinman, G., and Grant, L. (2011). Exploring stress resilience in trainee social workers: the role of emotional and social competencies. Br. J. Social Work 41, 261–275. doi: 10.1093/bjsw/bcq088

Kun, B., and Demetrovics, Z. (2010). Emotional intelligence and addictions: a systematic review. Subst. Misuse 45, 1131–1160. doi: 10.3109/10826080903567855

MacCann, C. (2006). Appendix 2.1 Instructions and Items in STEU (Situational Test of Emotional Understanding). Retrieved from: https://ses.library.usyd.edu.au/bitstream/2123/934/3/03Appendices.pdf

MacCann, C., Joseph, D. L., Newman, D. A., and Roberts, R. D. (2014). Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models. Emotion 14, 358–374. doi: 10.1037/a0034755

MacCann, C., and Roberts, R. D. (2008). New paradigms for assessing emotional intelligence: theory and data. Emotion 8, 540–551. doi: 10.1037/a0012746

Maul, A. (2012). The validity of the mayer–salovey–caruso emotional intelligence test (MSCEIT) as a measure of emotional intelligence. Emot. Rev. 4, 394–402. doi: 10.1177/1754073912445811

Mavroveli, S., and Sánchez-Ruiz, M. J. (2011). Trait emotional intelligence influences on academic achievement and school behaviour. Br. J. Edu. Psychol. 81, 112–134. doi: 10.1348/2044-8279.002009

Mayer, J. D., Caruso, D. R., and Salovey, P. (1999). Emotional intelligence meets traditional standards for an intelligence. Intelligence 27, 267–298. doi: 10.1016/S0160-2896(99)00016-1

Mayer, J. D., Roberts, R. D., and Barsade, S. G. (2008). Human abilities: Emotional intelligence. Annu. Rev. Psychol . 59, 507–536. doi: 10.1146/annurev.psych.59.103006.093646

Mayer, J. D., Salovey, P., Caruso, D., and Sternberg, R. J. (2000). Models of Emotional Intelligence , ed R. J. Sternberg (New York, NY: Cambridge University Press), 396–420.

Mayer, J. D., Salovey, P., and Caruso, D. R. (2002a). Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) Item Booklet . Toronto, ON: MHS Publishers.

Mayer, J. D., Salovey, P., and Caruso, D. R. (2002b). Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) User's Manual . Toronto, ON: MHS Publishers.

Mayer, J. D., Salovey, P., Caruso, D. R., and Sitarenios, G. (2001). Emotional intelligence as a standard intelligence. Emotion 1, 232–242. doi: 10.1037/1528-3542.1.3.232

Mayer, J. D., Salovey, P., Caruso, D. R., and Sitarenios, G. (2003). Measuring emotional intelligence with the MSCEIT V2. 0. Emotion 3 , 97–105. doi: 10.1037/1528-3542.3.1.97

Miao, C., Humphrey, R. H., and Qian, S. (2017). A meta-analysis of emotional intelligence and work attitudes. J. Occupat. Organiz. Psychol. 90, 177–202. doi: 10.1111/joop.12167

Mikolajczak, M., Menil, C., and Luminet, O. (2007). Explaining the protective effect of trait emotional intelligence regarding occupational stress: exploration of emotional labour processes. J. Res. Person. 41, 1107–1117. doi: 10.1016/j.jrp.2007.01.003

Morrison, J. (2008). The relationship between emotional intelligence competencies and preferred conflict-handling styles. J. Nurs. Manage. 16, 974–983. doi: 10.1111/j.1365-2834.2008.00876.x

Nowicki, S., and Duke, M. P. (1994). Individual differences in the nonverbal communication of affect: the diagnostic analysis of nonverbal accuracy scale. J. Nonverb. Behav. 18, 9–35. doi: 10.1007/BF02169077

O'Boyle, E. H. Jr., Humphrey, R. H., Pollack, J. M., Hawver, T. H., and Story, P. A. (2011). The relation between emotional intelligence and job performance: a meta-analysis. J. Organiz. Beha. 32, 788–818. doi: 10.1002/job.714

O'Connor, P., Nguyen, J., and Anglim, J. (2017). Effectively coping with task stress: a study of the validity of the trait emotional intelligence questionnaire–short form (TEIQue–SF). J. Personal. Assess. 99, 304–314. doi: 10.1080/00223891.2016.1226175

O'Connor, P. J., and Athota, V. S. (2013). The intervening role of Agreeableness in the relationship between trait emotional intelligence and machiavellianism: reassessing the potential dark side of EI. Personal. Indiv. Differe. 55, 750–754. doi: 10.1016/j.paid.2013.06.006

O'Connor, P. J., and Brown, C. M. (2016). Sex-linked personality traits and stress: emotional skills protect feminine women from stress but not feminine men. Personal. Indiv. Differe. 99, 28–32. doi: 10.1016/j.paid.2016.04.075

Palmer, B. R., Stough, C., Harmer, R., and Gignac, G. (2009). “The genos emotional intelligence inventory: a measure designed specifically for workplace applications.” in Assessing Emotional Intelligence (Boston, MA: Springer), 103–117.

Pérez, J. C., Petrides, K. V., and Furnham, A. (2005). Measuring Trait Emotional Intelligence. Emotional intelligence: An International Handbook , ed R. Schulze and R. D. Roberts (Cambridge, MA: Hogrefe & Huber), 181–201.

Petrides, K. V. (2009). “Psychometric properties of the Trait Emotional Intelligence Questionnaire,” in Advances in the Assessment of Emotional Intelligence , eds C. Stough, D. H. Saklofske and J. D. Parker (New York, NY: Springer), 85–101.

Petrides, K. V. (2011). “Ability and trait emotional intelligence,” in The Blackwell-Wiley Handbook of Individual Differences , eds T. Chamorro-Premuzic, A. Furnham, and S. von Stumm (New York, NY: Wiley).

Petrides, K. V., and Furnham, A. (2000). On the dimensional structure of emotional intelligence. Personal. Indivi. Differ. 29, 313–320. doi: 10.1016/S0191-8869(99)00195-6

Petrides, K. V., and Furnham, A. (2001). Trait emotional intelligence: psychometric investigation with reference to established trait taxonomies. Eur. J. Person. 15, 425–448. doi: 10.1002/per.416

Petrides, K. V., Mikolajczak, M., Mavroveli, S., Sanchez-Ruiz, M. J., Furnham, A., and Pérez-González, J. C. (2016). Developments in trait emotional intelligence research. Emot. Rev. 8, 335–341. doi: 10.1177/1754073916650493

Por, J., Barriball, L., Fitzpatrick, J., and Roberts, J. (2011). Emotional intelligence: Its relationship to stress, coping, well-being and professional performance in nursing students. Nurse Edu. Today 31, 855–860. doi: 10.1016/j.nedt.2010.12.023

Reed, S., Kassis, K., Nagel, R., Verbeck, N., Mahan, J. D., and Shell, R. (2015). Does emotional intelligence predict breaking bad news skills in pediatric interns? A pilot study. Med. Edu. Online 20:e24245. doi: 10.3402/meo.v20.24245

Roberts, R. D., Zeidner, M., and Matthews, G. (2001). Does emotional intelligence meet traditional standards for an intelligence? Some new data and conclusions. Emotion 1:196. doi: 10.1037/1528-3542.1.3.196

Roseman, I. J. (2001). A Model of Appraisal in the Emotion System. Appraisal Processes in Emotion: Theory, Methods, Research , ed K. R. Scherer, A. Schorr and T. Johnstone (Oxford: Oxford University Press), 68–91.

Rosete, D., and Ciarrochi, J. (2005). Emotional intelligence and its relationship to workplace performance outcomes of leadership effectiveness. Leadership Organiz. Dev. J. 26, 388–399. doi: 10.1108/01437730510607871

Ruiz-Aranda, D., Extremera, N., and Pineda-Galán, C. (2014). Emotional intelligence, life satisfaction and subjective happiness in female student health professionals: the mediating effect of perceived stress. J. Psychia. Mental Health Nurs. 21, 106–113. doi: 10.1111/jpm.12052

Salovey, P., and Mayer, J. D. (1990). Emotional intelligence. Imag. Cogn. Persona. 9, 185–211. doi: 10.2190/DUGG-P24E-52WK-6CDG

Schlegel, K., and Mortillaro, M. (2019). The Geneva Emotional Competence Test (GECo): an ability measure of workplace emotional intelligence. J. Appl. Psychol. 104, 559–580. doi: 10.1037/apl0000365

Schultz, D., Izard, C. E., and Bear, G. (2004). Children's emotion processing: Relations to emotionality and aggression. Dev. Psychopathol. 16, 371–387. doi: 10.1017/S0954579404044566

Schutte, N. S., Malouff, J. M., Hall, L. E., Haggerty, D. J., Cooper, J. T., Golden, C. J., et al. (1998). Development and validation of a measure of emotional intelligence. Personal. Indivi. Diff. 25, 167–177. doi: 10.1016/S0191-8869(98)00001-4

Sheldon, O. J., Dunning, D., and Ames, D. R. (2014). Emotionally unskilled, unaware, and uninterested in learning more: reactions to feedback about deficits in emotional intelligence. J. Appl. Psychol. 99, 125–137. doi: 10.1037/a0034138

Siegling, A. B., Saklofske, D. H., and Petrides, K. V. (2015). Measures of ability and trait emotional intelligence. Measures of Personality and Social Psychological Constructs , eds G. J. Boyle, G. Matthews, and D. H. Saklofske (San Diego, CA: Academic Press), 381–414.

Tett, R. P., Freund, K. A., Christiansen, N. D., Fox, K. E., and Coaster, J. (2012). Faking on self-report emotional intelligence and personality tests: Effects of faking opportunity, cognitive ability, and job type. Personal. Indivi. Diffe. 52, 195–201. doi: 10.1016/j.paid.2011.10.017

Van Rooy, D. L., Viswesvaran, C., and Pluta, P. (2005). An evaluation of construct validity: What is this thing called emotional intelligence? Hum. Perform. 18, 445–462. doi: 10.1207/s15327043hup1804_9

Wong, C. S., Law, K. S., and Wong, P. M. (2004). Development and validation of a forced choice emotional intelligence for Chinese respondents in Hong Kong. Asia Pacific J. Manage. 21, 535–559. doi: 10.1023/B:APJM.0000048717.31261.d0

Wong, C. S., Wong, P. M., and Law, K. S. (2007). Evidence of the practical utility of Wong's emotional intelligence scale in Hong Kong and mainland China. Asia Pac. J. Manage. 24, 43–60. doi: 10.1007/s10490-006-9024-1

Keywords: emotional intelligence, measures, questionnaires, trait, ability, mixed, recommendations

Citation: O'Connor PJ, Hill A, Kaya M and Martin B (2019) The Measurement of Emotional Intelligence: A Critical Review of the Literature and Recommendations for Researchers and Practitioners. Front. Psychol. 10:1116. doi: 10.3389/fpsyg.2019.01116

Received: 05 October 2018; Accepted: 29 April 2019; Published: 28 May 2019.

Reviewed by:

Copyright © 2019 O'Connor, Hill, Kaya and Martin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Peter J. O'Connor, peter.oconnor@qut.edu.au

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Search Menu

Sign in through your institution

• Advance articles
• AHFS First Release
• AJHP Voices
• AJHP Residents Edition
• Supplements
• Top Twenty-Five Articles
• ASHP National Surveys of Pharmacy Practice in Hospital Settings
• Medication Safety
• Pharmacy Technicians
• Specialty Pharmacy
• Emergency Preparedness and Clinician Well-being
• Author Guidelines
• Submission Site
• Open Access
• Information for Reviewers
• Self-Archiving Policy
• Author Instructions for Residents Edition
• Advertising and Corporate Services
• Advertising
• Reprints and ePrints
• Sponsored Supplements
• Editorial Board
• Permissions
• Journals on Oxford Academic
• Books on Oxford Academic
• < Previous

A quantitative study of the emotional intelligence of participants in the ASHP Foundation’s Pharmacy Leadership Academy

• Article contents
• Figures & tables
• Supplementary Data

Cherin M. Hall, Sharon Murphy Enright, Sara J. White, Stephen J. Allen, A quantitative study of the emotional intelligence of participants in the ASHP Foundation’s Pharmacy Leadership Academy, American Journal of Health-System Pharmacy , Volume 72, Issue 21, 1 November 2015, Pages 1890–1895, https://doi.org/10.2146/ajhp140812

• Permissions Icon Permissions

Results of a quantitative assessment of emotional intelligence in a sample of pharmacists affiliated with the ASHP Research and Education Foundation’s Pharmacy Leadership Academy (PLA) are presented.

A demographic questionnaire and a validated instrument for assessing emotional intelligence, the Emotional Quotient Inventory, version 2.0 (EQ-i 2.0), were administered to a group of practicing pharmacists who graduated from the PLA during the period 2008–12 ( n = 82) and a control group of pharmacists who were accepted into the PLA in 2013 but had not begun leadership training ( n = 40). The dependent variables were the mean total EQ-I 2.0 score and mean scores on five EQ-i 2.0 composite scales. The independent variables were PLA affiliation status (graduate versus matriculant) and demographic variables. Descriptive and inferential statistics were used to calculate between-group differences in EQ-i 2.0 scores. The relationship of demographic variables to EQ-i 2.0 scores was analyzed via multiple linear regression.

Among the 122 pharmacists who completed both assessments, the overall mean total EQ-i 2.0 score was 101.11, which indicated an average level of emotional intelligence. There were significant differences between the PLA graduate group and the control group in total EQ-i 2.0 scores and in EQ-i 2.0 scores for self-expression, decision-making, interpersonal skills, and other aspects of emotional intelligence. The evaluated demographic factors were not found to be significant predictors of EQ-i 2.0 scores.

The study results indicated an average level of emotional intelligence among all PLA affiliates but revealed significant differences in mean total EQ-i 2.0 scores and EQ-i 2.0 composite scale scores favoring PLA graduates.

American Society of Health-System Pharmacists members

Personal account.

• Sign in with email/username & password
• Get email alerts
• Save searches
• Purchase content
• Activate your purchase/trial code
• Add your ORCID iD

Institutional access

Sign in with a library card.

• Sign in with username/password
• Recommend to your librarian
• Institutional account management
• Get help with access

Access to content on Oxford Academic is often provided through institutional subscriptions and purchases. If you are a member of an institution with an active account, you may be able to access content in one of the following ways:

IP based access

Typically, access is provided across an institutional network to a range of IP addresses. This authentication occurs automatically, and it is not possible to sign out of an IP authenticated account.

Choose this option to get remote access when outside your institution. Shibboleth/Open Athens technology is used to provide single sign-on between your institution’s website and Oxford Academic.

• Click Sign in through your institution.
• Select your institution from the list provided, which will take you to your institution's website to sign in.
• When on the institution site, please use the credentials provided by your institution. Do not use an Oxford Academic personal account.
• Following successful sign in, you will be returned to Oxford Academic.

If your institution is not listed or you cannot sign in to your institution’s website, please contact your librarian or administrator.

Enter your library card number to sign in. If you cannot sign in, please contact your librarian.

Society Members

Society member access to a journal is achieved in one of the following ways:

Sign in through society site

Many societies offer single sign-on between the society website and Oxford Academic. If you see ‘Sign in through society site’ in the sign in pane within a journal:

• Click Sign in through society site.
• When on the society site, please use the credentials provided by that society. Do not use an Oxford Academic personal account.

If you do not have a society account or have forgotten your username or password, please contact your society.

Sign in using a personal account

Some societies use Oxford Academic personal accounts to provide access to their members. See below.

A personal account can be used to get email alerts, save searches, purchase content, and activate subscriptions.

Some societies use Oxford Academic personal accounts to provide access to their members.

Viewing your signed in accounts

Click the account icon in the top right to:

• View your signed in personal account and access account management features.
• View the institutional accounts that are providing access.

Signed in but can't access content

Oxford Academic is home to a wide variety of products. The institutional subscription may not cover the content that you are trying to access. If you believe you should have access to that content, please contact your librarian.

For librarians and administrators, your personal account also provides access to institutional account management. Here you will find options to view and activate subscriptions, manage institutional settings and access options, access usage statistics, and more.

Short-term Access

To purchase short-term access, please sign in to your personal account above.

Don't already have a personal account? Register

Email alerts

Citing articles via.

• Recommend to Your Librarian

Affiliations

• Online ISSN 1535-2900
• Print ISSN 1079-2082
• Copyright © 2024 American Society of Health-System Pharmacists
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Rights and permissions
• Accessibility
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

How to Be Emotionally Intelligent in Romantic Relationships

Emotional intelligence toolkit.

• Stress Management: Techniques & Strategies to Deal with Stress

Raising Emotionally Intelligent Children

Tips to improve family relationships, improving relationships at work with eq, how to improve your leadership skills with eq.

• Why Emotions Matter
• Online Therapy: Is it Right for You?
• Mental Health
• Health & Wellness
• Children & Family
• Relationships

Are you or someone you know in crisis?

• Bipolar Disorder
• Eating Disorders
• Grief & Loss
• Personality Disorders
• PTSD & Trauma
• Schizophrenia
• Therapy & Medication
• Exercise & Fitness
• Healthy Eating
• Well-being & Happiness
• Weight Loss
• Work & Career
• Illness & Disability
• Heart Health
• Learning Disabilities
• Family Caregiving
• Teen Issues
• Communication
• Emotional Intelligence
• Love & Friendship
• Domestic Abuse
• Healthy Aging
• Alzheimer’s Disease & Dementia
• End of Life
• Meet Our Team

What is emotional intelligence (EQ)?

The importance of emotional intelligence (eq), building emotional intelligence: four key skills to increasing eq, skill 1: self-management to build eq, skill 2: self-awareness for eq, skill 3: social awareness for eq, skill 4: relationship management for eq, improving emotional intelligence (eq) manage emotions to build better relationships and achieve success.

Using these 4 key skills, you can improve your emotional intelligence, build stronger relationships, and reach your goals at work, school, and in your personal life.

Emotional intelligence (also known as emotional quotient or EQ) is the ability to understand, use, and manage your own emotions in positive ways to relieve stress, communicate effectively, empathize with others, overcome challenges and defuse conflict.

Emotional intelligence helps you build stronger relationships, succeed at school and work, and achieve your career and personal goals. It can also help you to connect with your feelings, turn intention into action, and make informed decisions about what matters most to you.

The 4 Key Skills to Emotional intelligence:

• Self-management . You’re able to control impulsive feelings and behaviors, manage your emotions in healthy ways, take initiative, follow through on commitments, and adapt to changing circumstances.
• Self-awareness . You recognize your own emotions and how they affect your thoughts and behavior. You know your strengths and weaknesses, and have self-confidence.
• Social awareness . You have empathy. You can understand the emotions, needs, and concerns of other people, pick up on emotional cues, feel comfortable socially, and recognize the power dynamics in a group or organization.
• Relationship management . You know how to develop and maintain good relationships, communicate clearly, inspire and influence others, work well in a team, and manage conflict.

As we know, it’s not the smartest people who are the most successful or the most fulfilled in life. You probably know people who are academically brilliant and yet are socially inept and unsuccessful at work or in their personal relationships. Intellectual ability or your intelligence quotient (IQ) isn’t enough on its own to achieve success in life. Yes, your IQ can help you get into college, but it’s your EQ that will help you manage the stress and emotions when facing your final exams. IQ and EQ exist in tandem and are most effective when they build off one another.

Emotional intelligence affects:

Your performance at school or work.  High emotional intelligence can help you navigate the social complexities of the workplace, lead and motivate others, and excel in your career. In fact, when it comes to gauging important job candidates, many companies now rate emotional intelligence as important as technical ability and employ EQ testing before hiring.

Your physical health. If you’re unable to manage your emotions, you are probably not managing your stress either. This can lead to serious health problems. Uncontrolled stress raises blood pressure, suppresses the immune system, increases the risk of heart attacks and strokes, contributes to infertility, and speeds up the aging process. The first step to improving emotional intelligence is to learn how to manage stress.

Your mental health. Uncontrolled emotions and stress can also impact your mental health, making you vulnerable to anxiety and depression. If you are unable to understand, get comfortable with, or manage your emotions, you’ll also struggle to form strong relationships. This in turn can leave you feeling lonely and isolated and further exacerbate any mental health problems.

[Read: Building Better Mental Health]

Your relationships. By understanding your emotions and how to control them, you’re better able to express how you feel and understand how others are feeling. This allows you to communicate more effectively and forge stronger relationships, both at work and in your personal life.

Your social intelligence. Being in tune with your emotions serves a social purpose, connecting you to other people and the world around you. Social intelligence enables you to recognize friend from foe, measure another person’s interest in you, reduce stress, balance your nervous system through social communication, and feel loved and happy.

The skills that make up emotional intelligence can be learned at any time. However, it’s important to remember that there is a difference between simply learning about EQ and applying that knowledge to your life. Just because you know you should do something doesn’t mean you will—especially when you become overwhelmed by stress, which can override your best intentions.

In order to permanently change behavior in ways that stand up under pressure, you need to learn how to overcome stress in the moment, and in your relationships, in order to remain emotionally aware.

The following 4 key skills can help you build your EQ and improve your ability to manage emotions and connect with others.

In order for you to engage your EQ, you must be able to use your emotions to make constructive decisions about your behavior. When you become overly stressed, you can lose control of your emotions and the ability to act thoughtfully and appropriately.

Think about a time when stress has overwhelmed you. Was it easy to think clearly or make a rational decision? Probably not. When you become overly stressed, your ability to both think clearly and accurately assess emotions—your own and other people’s—becomes compromised.

[Read: Stress Management]

Emotions are important pieces of information that tell you about yourself and others, but in the face of stress that takes us out of our comfort zone, we can become overwhelmed and lose control of ourselves. With the ability to manage stress and stay emotionally present, you can learn to receive upsetting information without letting it override your thoughts and self-control. You’ll be able to make choices that allow you to control impulsive feelings and behaviors, manage your emotions in healthy ways, take initiative, follow through on commitments, and adapt to changing circumstances.

Managing stress is just the first step to building emotional intelligence.

The theory of attachment indicates that your current emotional experience is likely a reflection of your early life experience. Your ability to manage core feelings such as anger, sadness, fear, and joy often depends on the quality and consistency of your early life emotional experiences. If your primary caretaker as an infant understood and valued your emotions, it’s likely your emotions have become valuable assets in adult life. But, if your emotional experiences as an infant were confusing, threatening or painful, it’s likely you’ve tried to distance yourself from your emotions.

But being able to connect to your emotions—having a moment-to-moment connection with your changing emotional experience—is the key to understanding how emotion influences your thoughts and actions.

Do you experience feelings that flow, encountering one emotion after another as your experiences change from moment to moment?

Are your emotions accompanied by physical sensations that you experience in places like your stomach, throat, or chest?

Do you experience individual feelings and emotions, such as anger, sadness, fear, and joy, each of which is evident in subtle facial expressions?

Can you experience intense feelings that are strong enough to capture both your attention and that of others?

Do you pay attention to your emotions? Do they factor into your decision making?

If any of these experiences are unfamiliar, you may have “turned down” or “turned off” your emotions. In order to build EQ—and become emotionally healthy—you must reconnect to your core emotions, accept them, and become comfortable with them. You can achieve this through the practice of mindfulness.

[Listen: Mindful Breathing Meditation]

Mindfulness is the practice of purposely focusing your attention on the present moment—and without judgment. The cultivation of mindfulness has roots in Buddhism, but most religions include some type of similar prayer or meditation technique. Mindfulness helps shift your preoccupation with thought toward an appreciation of the moment, your physical and emotional sensations, and brings a larger perspective on life. Mindfulness calms and focuses you, making you more self-aware in the process.

Developing emotional awareness

It’s important that you learn how to manage stress first, so you’ll feel more comfortable reconnecting to strong or unpleasant emotions and changing how you experience and respond to your feelings. You can develop your emotional awareness by using HelpGuide’s free Emotional Intelligence Toolkit .

Social awareness enables you to recognize and interpret the mainly nonverbal cues others are constantly using to communicate with you. These cues let you know how others are really feeling, how their emotional state is changing from moment to moment, and what’s truly important to them.

[Read: Effective Communication]

When groups of people send out similar nonverbal cues, you’re able to read and understand the power dynamics and shared emotional experiences of the group. In short, you’re empathetic and socially comfortable.

Using mindfulness to build social awareness

To build social awareness, you need to recognize the importance of mindfulness in the social process. After all, you can’t pick up on subtle nonverbal cues when you’re in your own head, thinking about other things, or simply zoning out on your phone. Social awareness requires your presence in the moment. While many of us pride ourselves on an ability to multitask, this means that you’ll miss the subtle emotional shifts taking place in other people that help you fully understand them.

• You are actually more likely to further your social goals by setting other thoughts aside and focusing on the interaction itself.
• Following the flow of another person’s emotional responses is a give-and-take process that requires you to also pay attention to the changes in your own emotional experience.
• Paying attention to others doesn’t diminish your own self-awareness. By investing the time and effort to really pay attention to others, you’ll actually gain insight into your own emotional state as well as your values and beliefs. For example, if you feel discomfort hearing others express certain views, you’ll have learned something important about yourself.

Speak to a Licensed Therapist

BetterHelp is an online therapy service that matches you to licensed, accredited therapists who can help with depression, anxiety, relationships, and more. Take the assessment and get matched with a therapist in as little as 48 hours.

Working well with others is a process that begins with emotional awareness and your ability to recognize and understand what other people are experiencing. Once emotional awareness is in play, you can effectively develop additional social/emotional skills that will make your relationships more effective, fruitful, and fulfilling.

Become aware of how effectively you use nonverbal communication. It’s impossible to avoid sending nonverbal messages to others about what you think and feel. The many muscles in the face, especially those around the eyes, nose, mouth and forehead, help you to wordlessly convey your own emotions as well as read other peoples’ emotional intent. The emotional part of your brain is always on—and even if you ignore its messages—others won’t. Recognizing the nonverbal messages that you send to others can play a huge part in improving your relationships.

Use humor and play to relieve stress. Humor, laughter and play are natural antidotes to stress. They lessen your burdens and help you keep things in perspective. Laughter brings your nervous system into balance, reducing stress, calming you down, sharpening your mind and making you more empathic.

[Read: How to Be Emotionally Intelligent in Romantic Relationships]

Learn to see conflict as an opportunity to grow closer to others. Conflict and disagreements are inevitable in human relationships. Two people can’t possibly have the same needs, opinions, and expectations at all times. However, that needn’t be a bad thing. Resolving conflict in healthy, constructive ways can strengthen trust between people. When conflict isn’t perceived as threatening or punishing, it fosters freedom, creativity, and safety in relationships.

More Information

• Gilar-Corbi, R., Pozo-Rico, T., Sánchez, B., & Castejón, J.-L. (2019). Can emotional intelligence be improved? A randomized experimental study of a business-oriented EI training program for senior managers. PLOS ONE , 14(10), e0224254. Link
• How to Improve Your Emotional Intelligence—Professional Development | Harvard DCE . (n.d.). Retrieved June 18, 2022, from Link
• Jiménez-Picón, N., Romero-Martín, M., Ponce-Blandón, J. A., Ramirez-Baena, L., Palomo-Lara, J. C., & Gómez-Salgado, J. (2021). The Relationship between Mindfulness and Emotional Intelligence as a Protective Factor for Healthcare Professionals: Systematic Review. International Journal of Environmental Research and Public Health , 18(10), 5491. Link
• Segal, Jeanne. The Language of Emotional Intelligence: The Five Essential Tools for Building Powerful and Effective Relationships. 1st edition. McGraw Hill, 2008. Link
• Segal, Jeanne S. Raising Your Emotional Intelligence: A Practical Guide–A Hands-on Program for Harnessing the Power of Your Instincts and Emotions. 1st edition. Holt Paperbacks, 2015. Link

More in Emotional Intelligence

Learn why emotional intelligence matters in romantic relationships

Tools for managing emotions and bringing your life into balance

Stress Management

How to reduce, prevent, and relieve stress

Parenting strategies to help you build empathy and emotional awareness

Learn how emotional intelligence can help strengthen bonds

How EQ can make you a better employee, co-worker, or boss

To be an effective leader, emotional intelligence is an essential skill

VIDEO: Why Emotions Matter

Discover the powerful role of emotions

Professional therapy, done online

BetterHelp makes starting therapy easy. Take the assessment and get matched with a professional, licensed therapist.

Help us help others

Millions of readers rely on HelpGuide.org for free, evidence-based resources to understand and navigate mental health challenges. Please donate today to help us save, support, and change lives.

More From Forbes

The importance of emotional intelligence at work.

• Share to Facebook
• Share to Twitter
• Share to Linkedin

CEO at BrightHR and COO at the Peninsula Group, responsible for the global rollout of HR tech supporting over 95,000 organizations.

Do you think you are emotionally intelligent? By definition, it's your ability to understand and manage emotions. We might say someone is emotionally intelligent when they can regulate how they feel, diffuse arguments easily or stay calm in stressful situations.

Research by emotional intelligence expert Travis Bradberry suggests that only 36% of people have this ability. It's a surprisingly low number when you consider that we now know emotional intelligence helps employees progress and perform better. Additionally, a TalentSmart study found that, on average, people who show high emotional intelligence make $29,000 more each year than low-EQ professionals.

So why is emotional intelligence so important at work?

It improves communication.

For starters, emotionally intelligent employees tend to be better communicators, and good communication is key to any strong workforce. Let's say an employee is nervous as they begin leading a presentation in front of colleagues. They could let their nerves take over, so they'd appear flustered or trip over their words. This would undermine their ability to convey the ideas and concepts of their presentation. An emotionally intelligent employee, on the other hand, would recognize nerves as an emotional response and stay in control. This would allow them to communicate clearly and confidently.

People who are emotionally intelligent also tend to have a better grip on handling conflict and negative emotions. For example, if an employee believes that management hasn’t recognized their role in the success of a project, they might feel frustrated and hurt. As a result, they could lash out by making passive-aggressive comments or sending an angry email. But this is more likely to trigger a negative response and can damage working relationships.

An emotionally intelligent response would be if the employee identified and assessed their feelings before acting on them. Then, they could address the issue from a more stable, clear-headed place and collaborate on the best way to resolve it. This is more likely to produce a positive result and maintain a harmonious relationship with management.

It builds stronger relationships with colleagues.

Because strong communication is key to a good working relationship, emotional intelligence can help employees build better connections with colleagues.

If an employee has a low EQ, they might struggle to work as part of a team. They might have poor listening skills, get into arguments or refuse to take accountability for any mistakes. They might also not be very aware of other people’s feelings. This kind of behavior can be incredibly disruptive for a team, breaking down trust and communication as well as impacting workplace morale.

When an employee shows high emotional intelligence, they respect other people’s ideas and feelings, even if they don’t agree. This means they’re open to collaboration and are able to voice how they feel in meetings without being dismissive or confrontational.

Emotionally intelligent employees are also good at being supportive. They can identify when a colleague is upset about a work or personal issue and talk to them in a way that helps reduce stress and allows the other person to cope. This can create stronger relationships where everyone feels heard and supported, which can lead to them working harder and staying with a company for the long haul.

It helps improve performance.

On top of being better team players, emotionally intelligent people tend to perform better. Bradberry discussed how 90% of top performers score highly for emotional intelligence. A study conducted at a Motorola manufacturing site found that employees were 93% more productive after undergoing stress management and EQ training. So why do emotionally intelligent employees perform better? There are several reasons.

They make positive decisions, have better relationships with colleagues and know how to manage stress. Additionally, when employees have emotionally intelligent managers, they're more engaged at work . This is because managers with high EQ often give positive and constructive feedback that focuses on what employees can do next, not what went wrong. Therefore, employees are likely to understand how they can improve their performance, which creates a more motivated team. This also leads to less turnover; according to research by Korn Ferry , managers who lead with emotional intelligence retain 70% of their employees for five years or more.

It helps employees progress in their careers.

Emotionally intelligent employees have a strong ability to empathize, self-regulate and outperform. So they can make effective leaders. In a Lee Hecht Harrison Penna survey , 75% of respondents used EQ to determine promotions and pay rises. But 68% of organizations didn’t actually have any tools in place to identify or develop EQ. Even so, most employers say soft skills and emotional intelligence are essential for growth and success.

So incorporating EQ training and values into an employee's development plan is vital. Here are some examples of strategies to ensure this skill development.

• Enrolling staff in emotional intelligence training, mindfulness and stress management courses.

• Setting up team-building exercises for employees to get to know each other outside of work.

• Encouraging a culture of open communication with regular opportunities for employees to voice how they feel and offer feedback.

Emotional intelligence can have a profoundly positive impact on the workplace. When people across an organization, particularly leaders, display emotional intelligence, it encourages everyone to do the same.

Forbes Human Resources Council is an invitation-only organization for HR executives across all industries. Do I qualify?

• Editorial Standards
• Reprints & Permissions

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Quantitative research on emotional intelligence and leadership effectiveness.

2013, Review of the Institute of Strategic and International Studies

This manuscript examines the quantitative research methods employed in the study of emotional intelligence (EI) and its relationship to leadership effectiveness. It begins with an overview of the EI construct, discusses leadership effectiveness, and briefly surveys quantitative research methods. The manuscript continues with an analysis of EI research based on the three streams approach suggested by Ashkanasy and Daus (2005). It offers a description of typical research designs, sampling methods, measurement instruments, validity, reliability, and potential bias. It concludes with a summary of the present state of research into EI and leadership effectiveness, and offers recommendations for additional research. The manuscript begins with an overview of the EI construct. Keywords: Emotional Intelligence, Leadership, Effectiveness, Quantitative Methods

Related Papers

Joseph Ciarrochi

Abstract Does Emotional Intelligence (EI) make someone a better leader? We utilized a cross-sectional survey to examine the relationships between leadership effectiveness and tests of ability EI and cognitive reasoning, and self-report measures of EI and personality. The sample consisted of 117 senior executives (Males= 56; Females= 60; 1 unreported; mean age= 40.54). Regression analyses indicated medium to large relationships between ability EI scales and achieving business outcomes.

Leadership & Organization Development Journal

Pawan Chand

Advances in Developing Human Resources

Lisa Weinberger

Effective leadership is critical for today’s rapidly changing organizations. Emotional intelligence has been identified by some as that crucial element needed for this effective leadership. Although the research is growing, there still remains a gap on the relationships that exist between emotional intelligence and leadership. The study outlined in this article explored the relationships between emotional intelligence, leadership style, and leadership effectiveness. One hundred fifty-one managers completed the MSCEIT, an ability-measuring instrument of emotional intelligence. Those managers’ direct reports were asked to complete the MLQ5x, on their perceptions of their managers’ leadership style and leadership effectiveness. The results showed that there are no relationships between a manager’s emotional intelligence and leadership style or the leader’s perceived effectiveness. Implications for human resource development theory and practice are discussed.

International Journal of Organizational Analysis

Jim A McCleskey

Purpose – In 1990, Salovey and Mayer presented a framework for emotional intelligence (EI). This marked the beginning of 20 years of academic research, development, and debate on the subject of EI. A significant amount of previous research has attempted to draw out the relationship between EI and leadership performance. EI has been a uniquely controversial area of the social sciences. EI is based on three simple yet fundamental premises. This manuscript reviews the definitions and models in the field of EI with special emphasis on the Mayer ability model and the connection between EI and leadership. The paper aims to discuss these issues. Design/methodology/approach – This paper takes the form of a literature review. Findings – EI appears to have a foothold in both our popular vernacular and our academic lexicon. However, it is not entirely clear what future form it will take. Originality/value – This manuscript explores the current relationship between EI and leadership, discusses the various instruments and scales used to measure the construct, and examines the controversy and criticism surrounding EI. Finally, it illuminates some areas for additional research. Keywords Leadership, Emotional intelligence, Organizational behavior Paper type: Literature review

Vera Ami Ayitey

Shanthakumary Milroy Christy Mahenthiran Aloysius

International Journal on Leadership

Publishing India Group

Leaders have got a significant role to play in all spheres of life. An organization can attain remarkable achievements under a strong leadership; whereas, the presence of unsuccessful leaders can prove to be quite detrimental. The notion that a vital part is played by emotional intelligence (EI) in the effectiveness of leaders has been introduced recently. An emotionally stable professional is able to cope up with imperfection and uncertainty, since he is not very critical and believes in win-win situation. He has the ability to handle every sort of situation whether it is a demanding job, an atrocious boss, or undisciplined subordinates. At present, the definition of leadership has become more people-focused. A person with good understanding of Emotional Intelligence Quotient (EIQ) is expected to be an excellent team person and thus an effective leader. This paper is aimed at unifying the literature that evaluates the possible connection between leadership effectiveness and EI. A survey in the college of Haryana is conducted based on Trait Emotional Intelligence Questionnaire (TEIQue), which is psychometrically certified and provides self-awareness regarding EI. For the same, 50 teachers (leaders and non-leaders) were asked to fill the questionnaire. A SPSS analysis is carried out for evaluating the claims regarding significant relationship of EI with leadership, and to analyse the worth of EI in the success of professional and personal life of a leader. The impact of EI has been analysed on the perception, expression, and management of emotions, adaptability, relationships, stress management, self-motivation, happiness, empathy, and optimism. It is revealed through the results that a positive relationship exists between effective leadership and EI, which is beneficial for all the parties involved in the loop. Moreover, a noticeable difference has been observed in the EIQ rating of leaders and non-leaders in the way they utilize their EI in dealing with their personal matters or interacting with others.

virat chirania

Leadership is one of the most researched topics in world history and there is no dearth of theories on what impacts effective leadership. The interest of this article lies in exploring the relationship between emotional intelligence and leadership abilities. Emotional Intelligence surfaced way back in Nineteen Twenty and today is considered significant in areas of management and leadership success. The authors have reviewed the existing literature in this context and compiled the most relevant and interesting pieces of information on this subject. The authors find that based on existing research, it is evident that emotional intelligence has a strong positive correlation with entrepreneurial abilities. Keywords: EI,EQ,IQ,Leadership, INTRODUCTION TO EMOTIONAL INTELLIGENCE: From time immemorial, human beings have strived to understand and analyze the concept of ‘intelligence’, since human species is the most generously gifted by this aspect of life. Till the early twentieth century, i...

Advances in Human Resources Management and Organizational Development

Rina Pandey

Leadership theories hold a pertinent place in the effective management of people. In the Contemporary scenario, business leaders and managers have a huge onus on themselves of driving a workforce thriving with diverse Human Resource Management challenges. Interest in the role Emotional Intelligence in the workplace has increased in recent years, with greater emphasis on the benefits of understanding and utilizing emotions for managing people at work. In the contemporary scenario, the role of emotional intelligence competencies as predictors of leadership is being researched in order to leverage this information for increased leader effectiveness and performance. The present study identifies the congruence between various aspects of emotional intelligence and essential leadership competencies. It also identifies the role of Emotional intelligence in the effectiveness of Transformational Leaders.

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

Barbara Alston

Journal of Managerial Psychology

Malcolm Higgs

Casa do Macedo

Dr Amit B Dutta

The Impact of Emotional Intelligence on Leadership

Maxwell Gyamfi

manjari srivastava

Vanda L. Zammuner , Sergio Agnoli , Domenico Dionisio

Dirk Lindebaum

The Leadership Quarterly

Neal Ashkanasy

International Journal of Trend in Scientific Research and Development

Organizational Analysis

John Antonakis

Asad Khan Blouch

SA Journal of Industrial Psychology

Pieter Schaap

OANA-MATILDA SABIE

Conceptions of Leadership

IAEME Publication

Journal of Leadership, Accountability and Ethics

Leon C. Prieto , Simone T. A. Phipps

András Göndör

The International Journal of Organizational Analysis

Tony Ammeter

Universal Review

JOURNAL OF MANAGEMENT

Academy of Management Perspectives

Ronald Humphrey

Joan Marques

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Empirical research on ai technology-supported precision teaching in high school science subjects, 1. introduction, 1.1. development and application of precision teaching, 1.2. the present study, 2. precision teaching model supported by ai technology.

Click here to enlarge figure

2.1. Teachers and Parents: Precision Teaching and Precision Intervention Supported by Formative Assessment

2.1.1. learning preview, 2.1.2. classroom interaction, 2.1.3. learning report, 2.1.4. stage report, 2.2. students: personalized learning and individual development supported by intelligent technology systems, 2.2.1. pre-class study, 2.2.2. homework, 2.2.3. practice, 2.2.4. exams, 2.2.5. error logbook, 2.3. examples of pedagogical models in use, 3.1. procedure and sample, 3.2. measures, 3.2.1. midterm examination papers, 3.2.2. self-directed learning report, 3.2.3. teacher emotional attitude survey questionnaire ( questionnaire s1 ), 3.3. data analysis, 4.1. results of t-test, 4.2. results of regression analysis, 4.3. results of correlation analysis, 4.4. results of descriptive analysis, 5. discussion, 5.1. measures 1 and 2, 5.2. measure 3, 5.3. limitations for research, 6. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

• Schmitz, M.-L.; Antonietti, C.; Cattaneo, A.; Gonon, P.; Petko, D. When barriers are not an issue: Tracing the relationship between hindering factors and technology use in secondary schools across Europe. Comput. Educ. 2022 , 179 , 104411. [ Google Scholar ] [ CrossRef ]
• European Commission. European Commission 2nd Survey of Schools–ICT in Education–Objective 1–Benchmark Progress in ICT in Schools, Final Report ; Publications Office: Luxembourg, 2019. [ Google Scholar ]
• European Commission. EU European Commission Survey of Schools–ICT in Education–Benchmarking Access, Use and Attitudes to Technology in Europe’s Schools ; Publications Office of the European Union: Luxembourg, 2013. [ Google Scholar ]
• Zhan, Z.; Tong, Y.; Lan, X.; Zhong, B. A systematic literature review of game-based learning in Artificial Intelligence education. Interact. Learn. Environ. 2024 , 32 , 1137–1158. [ Google Scholar ] [ CrossRef ]
• Park, W.; Kwon, H. Implementing artificial intelligence education for middle school technology education in Republic of Korea. Int. J. Technol. Des. Educ. 2024 , 34 , 109–135. [ Google Scholar ] [ CrossRef ]
• Cook, C.R.; Kilgus, S.P.; Burns, M.K. Advancing the science and practice of precision education to enhance student outcomes. J. Sch. Psychol. 2018 , 66 , 4–10. [ Google Scholar ] [ CrossRef ]
• Hwang, G.-J.; Xie, H.; Wah, B.W.; Gašević, D. Vision, challenges, roles and research issues of Artificial Intelligence in Education. Comput. Educ. Artif. Intell. 2020 , 1 , 100001. [ Google Scholar ] [ CrossRef ]
• Guan, C.; Mou, J.; Jiang, Z. Artificial intelligence innovation in education: A twenty-year data-driven historical analysis. Int. J. Innov. Stud. 2020 , 4 , 134–147. [ Google Scholar ] [ CrossRef ]
• Tsai, S.-C.; Chen, C.-H.; Shiao, Y.-T.; Ciou, J.-S.; Wu, T.-N. Precision education with statistical learning and deep learning: A case study in Taiwan. Int. J. Educ. Technol. High. Educ. 2020 , 17 , 12. [ Google Scholar ] [ CrossRef ]
• Lu, O.H.; Huang, A.Y.; Huang, J.C.; Lin, A.J.; Ogata, H.; Yang, S.J. Applying Learning Analytics for the Early Prediction of Students’ Academic Performance in Blended Learning. J. Educ. Technol. Soc. 2018 , 21 , 220–232. [ Google Scholar ]
• Forero-Corba, W.; Bennasar, F.N. Techniques and Applications of Machine Learning and Artificial Intelligence in Education: A Systematic Review. RIED-Rev. Iberoam. Educ. Distancia 2024 , 27 , 1–19. [ Google Scholar ]
• Deepika, A.; Kandakatla, R.; Saida, A.; Reddy, V.B. Implementation of ICAP Principles through Technology Tools: Exploring the Alignment between Pedagogy and Technology. J. Eng. Educ. Transform. 2021 , 34 , 542. [ Google Scholar ] [ CrossRef ]
• Hew, K.F.; Lan, M.; Tang, Y.; Jia, C.; Lo, C.K. Where is the “theory” within the field of educational technology research? Br. J. Educ. Technol. 2019 , 50 , 956–971. [ Google Scholar ] [ CrossRef ]
• Chen, X.; Xie, H.; Zou, D.; Hwang, G.-J. Application and theory gaps during the rise of Artificial Intelligence in Education. Comput. Educ. Artif. Intell. 2020 , 1 , 100002. [ Google Scholar ] [ CrossRef ]
• Schunk, D.H. Learning Theories an Educational Perspective , 8th ed.; Pearson Education, Inc.: London, UK, 2020. [ Google Scholar ]
• Sønderlund, A.L.; Hughes, E.; Smith, J. The efficacy of learning analytics interventions in higher education: A systematic review. Br. J. Educ. Technol. 2019 , 50 , 2594–2618. [ Google Scholar ] [ CrossRef ]
• Viberg, O.; Hatakka, M.; Bälter, O.; Mavroudi, A. The Current Landscape of Learning Analytics in Higher Education. Comput. Hum. Behav. 2018 , 89 , 98–110. [ Google Scholar ] [ CrossRef ]
• Luan, H.; Tsai, C.-C. A Review of Using Machine Learning Approaches for Precision Education. Educ. Technol. Soc. 2021 , 24 , 250–266. [ Google Scholar ]
• Shan, S.; Liu, Y. Blended Teaching Design of College Students’ Mental Health Education Course Based on Artificial Intelligence Flipped Class. Math. Probl. Eng. 2021 , 2021 , 1–10. [ Google Scholar ] [ CrossRef ]
• Dong, X. Application of Precision Teaching Under the Guidance of Big Data in The Course of Internal Medicine Nursing. Front. Bus. Econ. Manag. 2022 , 5 , 37–39. [ Google Scholar ] [ CrossRef ]
• Wei, X.; Jiang, J.; Zhang, L.; Feng, H. Research on Precision Teaching Management Methods in Universities in the Era of Big Data Based on Entropy Weight Method. In Frontiers in Artificial Intelligence and Applications ; Grigoras, G., Lorenz, P., Eds.; IOS Press: Amsterdam, The Netherlands, 2023; ISBN 978-1-64368-444-4. [ Google Scholar ]
• Yanfei, M. Online and Offline Mixed Intelligent Teaching Assistant Mode of English Based on Mobile Information System. Mob. Inf. Syst. 2021 , 2021 , 7074629. [ Google Scholar ] [ CrossRef ]
• Wang, Y.; Xiao, L.; Mo, S.; Shen, Y.; Tong, G. Research on the Effectiveness of Precision Teaching Model Empowered by e-Schoolbag—A Case Study of Mathematics Review Lessons in Junior High School. China Educ. Technol. 2019 , 5 , 106–113+119. Available online: https://qikan.cqvip.com/Qikan/Article/Detail?id=7002036138 (accessed on 20 August 2024).
• Lindsley, O.R. Precision teaching: Discoveries and effects. J. Appl. Behav. Anal. 1992 , 25 , 51–57. [ Google Scholar ] [ CrossRef ]
• Kubina, R.M.; Yurich, K.K. Precision Teaching Book ; Greatness Achieved Publishing Company Lemont: Pittsburgh, PA, USA, 2012; ISBN 0-615-55420-2. [ Google Scholar ]
• Yin, B.; Yuan, C.-H. Precision Teaching and Learning Performance in a Blended Learning Environment. Front. Psychol. 2021 , 12 , 631125. [ Google Scholar ] [ CrossRef ]
• Binder, C.; Watkins, C.L. Precision Teaching and Direct Instruction: Measurably Superior Instructional Technology in Schools. Perform. Improv. Q. 1990 , 3 , 74–96. [ Google Scholar ] [ CrossRef ]
• Hughes, J.C.; Beverley, M.; Whitehead, J. Using precision teaching to increase the fluency of word reading with problem readers. Eur. J. Behav. Anal. 2007 , 8 , 221–238. [ Google Scholar ] [ CrossRef ]
• Liu, C.; Zhang, L. Research Focuses and Future Directions of Precision Teaching in China: A Visualized Analysis Based on CiteSpace. J. Suzhou Vocat. Univ. 2023 , 34 , 72–78. [ Google Scholar ]
• Guo, L.; Yang, X.; Zhang, Y. Analysis on New Development and Value Orientation of Precision Teaching in the Era of Big Data. E-Educ. Res. 2019 , 40 , 76–81+88. [ Google Scholar ]
• Yang, X.; Luo, J.; Liu, Y.; Chen, S. Data-Driven Instruction: A New Trend of Teaching Paradigm in Big Data Era. E-Educ. Res. 2017 , 38 , 13–20+26. [ Google Scholar ]
• Zhang, X.; Mou, Z. The Research on the Design of Precise Instruction Model Facing Personalized Learning under the Data Learning Environment. Mod. Distance Educ. 2018 , 5 , 65–72. Available online: https://qikan.cqvip.com/Qikan/Article/Detail?id=676261576 (accessed on 20 August 2024).
• Yang, Z.; Wang, J.; Wu, D.; Wang, M. Developing Intelligent Education to Promote Sustainable Development of Education. E-Educ. Res. 2022 , 43 , 5–10+17. [ Google Scholar ]
• Shemshack, A.; Spector, J.M. A systematic literature review of personalized learning terms. Smart Learn. Environ. 2020 , 7 , 1–20. [ Google Scholar ] [ CrossRef ]
• Gallagher, E. Improving a mathematical key skill using precision teaching. Ir. Educ. Stud. 2006 , 25 , 303–319. [ Google Scholar ] [ CrossRef ]
• Strømgren, B.; Berg-Mortensen, C.; Tangen, L. The Use of Precision Teaching to Teach Basic Math Facts. Eur. J. Behav. Anal. 2014 , 15 , 225–240. [ Google Scholar ] [ CrossRef ]
• Gist, C.; Bulla, A.J. A Systematic Review of Frequency Building and Precision Teaching with School-Aged Children. J. Behav. Educ. 2022 , 31 , 43–68. [ Google Scholar ] [ CrossRef ]
• Yang, S.J.H. Precision Education: New Challenges for AI in Education [Conference Keynote]. In Proceedings of the 27th International Conference on Computers in Education (ICCE), Kenting, Taiwan, 2–6 December 2019; Asia-Pacific Society for Computers in Education (APSCE): Taoyuan City, Taiwan, 2019; pp. XXVII–XXVIII. [ Google Scholar ]
• Peng, X.; Wu, B. How Is Data-Driven Precision Teaching Possible?From the Perspective of Cultivating Teacher’s Data Wisdom. J. East China Norm. Univ. Sci. 2021 , 39 , 45–56. [ Google Scholar ]
• Taber, K.S. Mediated Learning Leading Development—The Social Development Theory of Lev Vygotsky. In Science Education in Theory and Practice: An Introductory Guide to Learning Theory ; Springer: Cham, Switzerland, 2020; pp. 277–291. [ Google Scholar ]
• Ness, I.J. Zone of Proximal Development. In The Palgrave Encyclopedia of the Possible ; Springer: Berlin/Heidelberg, Germany, 2023; pp. 1781–1786. [ Google Scholar ]
• Liu, N.; Yu, S. Research on Precision Teaching Based on Zone of Proximal Development. E-Educ. Res. 2020 , 41 , 77–85. [ Google Scholar ]
• Liu, H.; Sun, J.; Chen, J.; Zhang, Y. Persona Model and Its Application in Library. Libr. Theory Pract. 2018 , 92 , 97. Available online: https://qikan.cqvip.com/Qikan/Article/Detail?id=7000905917 (accessed on 20 August 2024).
• Liu, H.; Sun, J.; Su, Y.; Zhang, Y. A Multi Contextual Interest Recommender Method for Library Big Data Knowledge Service. J. Mod. Inf. 2018 , 38 , 62–67,156. [ Google Scholar ]
• Liu, H.; Sun, J.; Su, Y.; Zhang, Y. Research on the Tourism Situational Recommendation Service Based on Persona. Inf. Stud. Theory Appl. 2018 , 41 , 87–92. [ Google Scholar ]
• Liu, H. Contextual Recommendation for the Big Data Knowledge Service Oriented the Cloud Computing. Libr. Dev. 2014 , 31–35. Available online: https://qikan.cqvip.com/Qikan/Article/Detail?id=661733950 (accessed on 20 August 2024).
• Liu, H.; Liu, X.; Yao, S.; Xie, S. Statistical Analysis of Information Behavior Characteristics of Online Social Users Based on Public Opinion Portrait. J. Mod. Inf. 2019 , 39 , 64–73. [ Google Scholar ]
• Liu, H.; Sun, J.; Zhang, Y.; Zhao, P. Research on User Portrayal and Information Dissemination Behavior in Online Social Activities. Inf. Sci. 2018 , 36 , 17–21. [ Google Scholar ]
• Liu, H.; Huang, W.; Xie, S. Research on the Situational Recommendation-Oriented Library User Profiles. Res. Libr. Sci. 2018 , 62–68. Available online: https://qikan.cqvip.com/Qikan/Article/Detail?id=676852789 (accessed on 20 August 2024).
• Erümit, A.K.; Çetin, I. Design framework of adaptive intelligent tutoring systems. Educ. Inf. Technol. 2020 , 25 , 4477–4500. [ Google Scholar ] [ CrossRef ]
• U.S. Department of Education, Office of Educational Technology. Transforming American Education: Learning Powered by Technology ; U.S. Department of Education, Office of Educational Technology: Washington, DC, USA, 2010. [ Google Scholar ]
• Fei, L.; Ma, Y. Developing Personalized Learning to Promote Educational Equity: An Exploration of the Basic Theory and Practical Experience of Personalized Learning in the UK. Glob. Educ. 2010 , 39 , 42–46. Available online: https://qikan.cqvip.com/Qikan/Article/Detail?id=34931923 (accessed on 20 August 2024).
• Yu, S. Internet Plus Education: Future Schools ; Publishing House of Electronics Industry: Beijing, China, 2019; ISBN 978-7-121-36043-5. [ Google Scholar ]
• Luan, H.; Geczy, P.; Lai, H.; Gobert, J.; Yang, S.J.; Ogata, H.; Baltes, J.; Guerra, R.; Li, P.; Tsai, C.-C. Challenges and Future Directions of Big Data and Artificial Intelligence in Education. Front. Psychol. 2020 , 11 , 580820. [ Google Scholar ] [ CrossRef ]
• Bray, B.; McClaskey, K. Personalization vs. Differentiation vs Individualization. Dostopno Na Httpeducation Ky Govschool-innovDocumentsBB-KM-Pers.-2012 Pdf Pridobljeno 12 10 2013 2012. Available online: https://www.marshfieldschools.org/cms/lib/WI01919828/Centricity/Domain/82/PL_Diff_Indiv.pdf (accessed on 20 August 2024).
• Li, y.; Zhang, S. Self-study and Adaptive Adjusting of Exam-question Difficulty Coefficient. Comput. Eng. 2005 , 31 , 181–182. [ Google Scholar ]
• Lourdusamy, R.; Magendiran, P. A systematic analysis of difficulty level of the question paper using student’s marks: A case study. Int. J. Inf. Technol. 2021 , 13 , 1127–1143. [ Google Scholar ] [ CrossRef ]
• Peng, J.; Sun, M.; Yuan, B.; Lim, C.P.; van Merriënboer, J.J.G.; Wang, M. Visible thinking to support online project-based learning: Narrowing the achievement gap between high- and low-achieving students. Educ. Inf. Technol. 2024 , 29 , 2329–2363. [ Google Scholar ] [ CrossRef ]
• Chiesa, M.; Robertson, A. Precision Teaching and Fluency Training: Making maths easier for pupils and teachers. Educ. Psychol. Pract. 2000 , 16 , 297–310. [ Google Scholar ] [ CrossRef ]
• Yang, Z. Empowering Teaching and Learning with Artificial Intelligence. Front. Digit. Educ. 2024 , 1 , 1–3. [ Google Scholar ]

Share and Cite

Hao, M.; Wang, Y.; Peng, J. Empirical Research on AI Technology-Supported Precision Teaching in High School Science Subjects. Appl. Sci. 2024 , 14 , 7544. https://doi.org/10.3390/app14177544

Hao M, Wang Y, Peng J. Empirical Research on AI Technology-Supported Precision Teaching in High School Science Subjects. Applied Sciences . 2024; 14(17):7544. https://doi.org/10.3390/app14177544

Hao, Miaomiao, Yi Wang, and Jun Peng. 2024. "Empirical Research on AI Technology-Supported Precision Teaching in High School Science Subjects" Applied Sciences 14, no. 17: 7544. https://doi.org/10.3390/app14177544

Article Metrics

Article access statistics, supplementary material.

ZIP-Document (ZIP, 71 KiB)

Further Information

Mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals