experimental thesis

Biology 194A,B: Experimental Thesis

The laboratory/field experimental research thesis.

The experimental thesis option requires that you complete an original research project, either in the laboratory or in the field, and submit a scientific paper describing that research. You will spend most of your efforts in this option testing and modifying your experimental design, conducting your experiments, and analyzing your results. The written product of this work will be similar in format to formal lab reports you have written in biology classes, although all aspects of your thesis will be much more extensive than a lab paper for a class.

Outline of Research

(included in the senior exercise contract):  For an experimental thesis, you must arrange for a place to carry out your research.  Typically, this would be in the lab of (one of) your reader(s).  You must discuss with your reader(s) what your needs will be for such things as facilities, equipment, supplies, and field sites.  In fact, you should give these matters considerable thought prior to approaching a potential experimental thesis reader. You will submit a list of your research needs along with the senior exercise contract so that the department can determine how we can best meet these needs.  The department will provide modest funding for expenses incurred in research ($500)/student), but it is unlikely that we will purchase specialized equipment just for senior projects.  You may NOT use department vehicles for regular transportation to a field site. For several reasons it is essential that you discuss your research needs with your thesis advisor(s) first and use his/her suggestions in drafting your list of research requirements.  You may be able to use equipment and/or supplies available through your reader(s), and all reimbursements must be approved prior to purchase by your thesis advisor(s).   In addition to a list of your research needs, you must also write an abstract that describes the problem you plan to address, the experimental approach you plan to take and a proposed calendar (time-line) for your research.

Progress Report

This is a non-graded (P/NC), written report that describes the early progress you have made in obtaining experimental results and is due part way through the fall semester (see Deadlines, p. 14).  The purpose of this report is to demonstrate to your reader(s) that you have made reasonable progress in tackling your proposed thesis problem, have clearly identified any unforeseen obstacles, and have a plan to resolve them over the course of the remaining weeks of the semester.  We want to know in detail how successful your experimental design has been to date and any problems you have encountered.  You must receive a passing grade on this progress report in order to proceed with your thesis for the rest of the semester.

1 st Semester Draft

This is a graded, written report that is a permanent grade on your transcript for Bio 194A and is due on the last day of classes, Fall Semester.  This paper must include a complete, critical literature review of your topic, your materials and methods section, results to date along with any conclusions that can be drawn from the data you report, and the literature cited section.  Your readers will expect the Introduction, Materials and Methods and Literature Cited sections to essentially complete and polished.  You will report results of experiments in progress, so the Results and Discussion sections will be considerably less complete than those in the final, second semester version. You will receive one credit for this course and a letter grade. It will appear on your transcript as “Experimental Thesis (1 st half).” A passing grade in Bio 194A is a requirement for enrollment in Bio 194B.

Complete Draft/Final Revised Version

These are both graded final reports of your research, written in the format of a scientific paper, which includes an abstract, introduction with literature review and analysis, materials and methods, results, discussion with conclusions, and a complete literature cited section.  You will receive one credit for this course and a letter grade. It will appear on your transcript as “Experimental Thesis (2nd half).”

Public Presentation

All experimental thesis students are required to deliver a public presentation to students and faculty in a forum at the end of the Spring Semester, usually held on the last Friday of classes.

You must write your thesis in the format of a scientific journal paper, the sections of which are described below.

A good title is brief and informative. Try to encapsulate the research topic and objectives – i.e. what your thesis is about.  Humor is not appropriate in a thesis title.

This short paragraph summarizes the entire thesis: the question you asked, the hypothesis you proposed, the approach you took, the results you predicted, the most important, specific (quantitative) results that you obtained, and the conclusions you drew.  Refer to your experimental organism(s) by scientific name(s).  The reader should be able to understand the purpose and conclusions of your study by reading this brief statement: it must be able to stand alone.  Often a reader reads only your abstract.  It is always best to write the abstract last, but it should not be merely a duplicate of your conclusions.  Do not just cut and paste from other sections; write the abstract in its own, very concise style.

Introduction

In a typical research paper, this section briefly covers the general nature of the problem and the significance of the study; that is, why you undertook the study and what you hoped to learn. For a thesis, however, it is necessary to include an historical overview of your problem, its background, and its significance. This section will consist of a critical review of the work that has already been carried out in the field and define the question and hypothesis you propose to test. Critically discuss the background information relevant to the problem you have chosen to study; show why this problem is scientifically interesting and worth investigating experimentally. You should not merely state the conclusions of the work you are reviewing; instead, briefly describe the experiments, the actual results (in quantitative terms whenever possible), and THEN what the results mean.  Do you agree with the interpretation of the results?  Did the investigators use the most appropriate approach(es) to address their question?  Taken together, the background information you present should lead the reader to the inevitable conclusion that it is important to know the answer to the question you have posed and that your hypothesis must be tested.  The relevance of this background information to your research question and hypotheses should be made clear throughout the entire section.

Materials and Methods

What did you do?  Using the past tense, describe your methods concisely but in sufficient detail that your reader could duplicate your techniques.  For field projects, you should describe your study area, how you selected the specific areas sampled or studied, and how you identified your organisms, etc.  Be sure to include scientific names of species studied, your sample sizes, and the types of statistical tests used (if any). Scientific names should be given in full at the first mention, and thereafter the genus (but not the species) can be abbreviated to the initial, e.g., C. annuum.

What did you find out?  Concisely present the results of your experiments and observations in words.  Also include tables, graphs, diagrams, maps, etc., where appropriate. Be sure that all figures and tables are numbered, and referred to in the text by their numbers.  Your text should describe the content of figures and tables, and the significance levels resulting from statistical analyses, but it should not attempt to explain these results; leave this for your Discussion.  Biology is a quantitative science, so be as quantitative as possible: it is much more informative to state that "species X has density of 34 + 5 m -2  at site A and 5 + 2 m -2  at site B" than "species X is more abundant at site A than at site B".  Tables should include pertinent summarizing data such as mean values (± Standard error), and not merely exhaustive lists of primary data.  All numerical data must abide by the significant digits allowed by the measurements themselves and subsequent calculations using measured values.   Insert your Tables and Figures at the appropriate places in the text.

What does it all mean?  In this section you evaluate and explain your data and other results, and discuss them in relation to other similar studies reported in the literature.  As always, when you make a statement of fact beyond common knowledge, you must give a reference to that statement in the form of a text citation, using proper format (see TEXT CITATIONS on pp. 9-10 for details).  In the text of your paper, the literature should be referred to as follows:  "Lopez (2004) stated that . . ..", or, "The animals were observed to blah blah blah (Kuwahara and Schmidt, 1999)".  Examine your data carefully, and then make the most informative and informed statements about them that you can.  Distinguish between clear conclusions that derive from your study, and what is merely indicated or suggested.  Discuss specific items of interest, such as (in the above example) why you think Species X is more abundant at site A than at site B.  Discuss the significance of your study, both in relation to the specifics of your experimental system, and to more general principles of biology.  You may find it appropriate to include brief comments on the accuracy, adequacy, and limitations of your own study, difficulties encountered, possible ways to circumvent these in the future, and ideas for future work, etc.

Conclusions

The Conclusions section is not the same as the Abstract.  Rather, it should contain a brief summary of your results, stated as conclusions, and nothing more.  Listing them as bulleted points is one convenient way to present them.  Be certain that these conclusions are fully justified by your data.

Acknowledgements

In this section you acknowledge help you received during any aspect of your project, including data and suggestions you received from others, as well as funding you or your advisor may have received from outside the department.  It is always acceptable to discuss laboratory and field activities with others and to analyze data as a group, and you are free to discuss your ideas with others; scientists do this all the time.  It is very important, however, that the final thesis document represent your own original thoughts, organization, and expression.  It is always appropriate to recognize and thank those who have significantly assisted you with laboratory or fieldwork, calculations, or the formulations of ideas, e.g., "I thank my roommate Al Gnowing for many stimulating discussions and my advisor Dr. Nobel for teaching me how to use high explosives safely."

Literature Cited

This section is always the last of your thesis, and must include every paper you have cited in the text, and only those papers.  See pp. 9-10 for a description of how to present your literature citations.

Fall Experimental Thesis 194A

Spring Experimental Thesis 194B

*** Turn a hard copy of the final version to each reader. You must also turn in the complete drafts, with the reader's comments, when you turn in the final draft.   Also submit the final version on a CD in either pdf or Word format to Dr. Karnovsky.  Links to the abstracts may be put on the Department web page, and the full electronic version of your thesis will be available to future students for several years. Please remember to put page numbers on ALL written material given to readers for feedback.  When handing in your draft and final version to your readers, you should determine when you can pick up the graded and critiqued copy.  Be sure to get your graded progress report back from faculty readers before the course drop deadline.

Please remember to put page numbers on ALL written material given to readers for feedback. When handing in your draft and final version to your readers, you should determine when you can pick up the graded and critiqued copy. Be sure to get your graded progress report back from faculty readers before the course drop deadline.

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Writing Center: Experimental Research Papers

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FAQs About Experimental Research Papers (APA)

What is a research paper? 

A researcher uses a research paper to explain how they conducted a research study to answer a question or test a hypothesis. They explain why they conducted the study, the research question or hypothesis they tested, how they conducted the study, the results of their study, and the implications of these results. 

What is the purpose of an experimental research paper? 

A research paper is intended to inform others about advancement in a particular field of study. The researcher who wrote the paper identified a gap in the research in a field of study and used their research to help fill this gap. The researcher uses their paper to inform others about the knowledge that the results of their study contribute. 

What sections are included in an experimental research paper?

A typical research paper contains a Title Page, Abstract, Introduction, Methods, Results, Discussion, and References section. Some also contain a Table and Figures section and Appendix section. 

What citation style is used for experimental research papers? 

APA (American Psychological Association) style is most commonly used for research papers. 

Structure Of Experimental Research Papers (APA)

• Answers the question of “What is this paper about and who wrote it?”
• Located on the first page of the paper 
• The author’s note acknowledges any support that the authors received from others
• A student paper also includes the course number and name, instructor’s name, and assignment due date
• Contains a title that summarizes the purpose and content of the research study and engages the audience 
• No longer than 250 words
• Summarizes important background information, the research questions and/or hypothesis, methods, key findings, and implications of the findings
• Explains what the topic of the research is and why the topic is worth studying
• Summarizes and discusses prior research conducted on the topic 
• Identifies unresolved issues and gaps in past research that the current research will address
• Ends with an overview of the current research study, including how the independent and dependent variables, the research questions or hypotheses, and the objective of the research 
• Explains how the research study was conducted 
• Typically includes 3 sections: Participants, Materials, and Procedure
• Includes characteristics of the subjects, how the subjects were selected and recruited, how their anonymity was protected, and what feedback was provided to the participants
• Describes any equipment, surveys, tests, questionnaires, informed consent forms, and observational techniques 
• Describes the independent and dependent variables, the type of research design, and how the data was collected
• Explains what results were found in the research study 
• Describes the data that was collected and the results of statistical tests 
• Explains the significance of the results 
• Accepts or denies the hypotheses 
• Details the implications of these findings 
• Addresses the limitations of the study and areas for future research 
• Includes all sources that were mentioned in the research study 
• Adheres to APA citation styles
• Includes all tables and/or figures that were used in the research study 
• Each table and figure is placed on a separate page 
• Tables are included before figures
• Begins with a bolded, centered header such as “ Table 1 ”
• Appends all forms, surveys, tests, etc. that were used in the study 
• Only includes documents that were referenced in the Methods section 
• Each entry is placed on a separate page 
• Begins with a bolded, centered header such as “ Appendix A ”

Tips For Experimental Research Papers (APA)

• Initial interest will motivate you to complete your study 
• Your entire study will be centered around this question or statement 
• Use only verifiable sources that provide accurate information about your topic 
• You need to thoroughly understand the field of study your topic is on to help you recognize the gap your research will fill and the significance of your results
• This will help you identify what you should study and what the significance of your study will be 
• Create an outline before you begin writing to help organize your thoughts and direct you in your writing 
• This will prevent you from losing the source or forgetting to cite the source 
• Work on one section at a time, rather than trying to complete multiple sections at once
• This information can be easily referred to as your write your various sections 
• When conducting your research, working general to specific will help you narrow your topic and fully understand the field your topic is in 
• When writing your literature review, writing from general to specific will help the audience understand your overall topic and the narrow focus of your research 
• This will prevent you from losing sources you may need later 
• Incorporate correct APA formatting as you write, rather than changing the formatting at the end of the writing process 

Checklist For Experimental Research Papers (APA)

• If the paper is a student paper, it contains the title of the project, the author’s name(s), the instructor's name, course number and name, and assignment due date
• If the paper is a professional paper, it includes the title of the paper, the author’s name(s), the institutional affiliation, and the author note
• Begins on the first page of the paper
• The title is typed in upper and lowercase letters, four spaces below the top of the paper, and written in boldface 
• Other information is separated by a space from the title

Title (found on title page)

• Informs the audience about the purpose of the paper 
• Captures the attention of the audience 
• Accurately reflects the purpose and content of the research paper 

Abstract 

• Labeled as “ Abstract ”
• Begins on the second page 
• Provides a short, concise summary of the content of the research paper 
• Includes background information necessary to understand the topic 
• Background information demonstrates the purpose of the paper
• Contains the hypothesis and/or research questions addressed in the paper
• Has a brief description of the methods used 
• Details the key findings and significance of the results
• Illustrates the implications of the research study 
• Contains less than 250 words

Introduction 

• Starts on the third page 
• Includes the title of the paper in bold at the top of the page
• Contains a clear statement of the problem that the paper sets out to address 
• Places the research paper within the context of previous research on the topic 
• Explains the purpose of the research study and what you hope to find
• Describes the significance of the study 
• Details what new insights the research will contribute
• Concludes with a brief description of what information will be mentioned in the literature review

Literature Review

• Labeled as “ Literature Review”
• Presents a general description of the problem area 
• Defines any necessary terms 
• Discusses and summarizes prior research on the selected topic 
• Identifies any unresolved issues or gaps in research that the current research plans to address
• Concludes with a summary of the current research study, including the independent and dependent variables, the research questions or hypotheses, and the objective of the research  
• Labeled as “ Methods ”
• Efficiently explains how the research study was conducted 
• Appropriately divided into sections
• Describes the characteristics of the participants 
• Explains how the participants were selected 
• Details how the anonymity of the participants was protected 
• Notes what feedback the participants will be provided 
• Describes all materials and instruments that were used 
• Mentions how the procedure was conducted and data collected
• Notes the independent and dependent variables 
• Includes enough information that another researcher could duplicate the research 

Results 

• Labeled as “ Results ”
• Describes the data was collected
• Explains the results of statistical tests that were performed
• Omits any analysis or discussion of the implications of the study 

Discussion 

• Labeled as “ Discussion ”
• Describes the significance of the results 
• Relates the results to the research questions and/or hypotheses
• States whether the hypotheses should be rejected or accepted 
• Addresses limitations of the study, including potential bias, confounds, imprecision of measures, and limits to generalizability
• Explains how the study adds to the knowledge base and expands upon past research
• Labeled as “ References ”
• Correctly cites sources according to APA formatting 
• Orders sources alphabetically
• All sources included in the study are cited in the reference section 

Table and Figures (optional)

•  Each table and each figure is placed on a separate page 
• Tables and figures are included after the reference page
• Tables and figures are correctly labeled
• Each table and figure begins with a bolded, centered header such as “ Table 1 ,” “ Table 2 ,”

Appendix (optional) 

• Any forms, surveys, tests, etc. are placed in the Appendix
• All appendix entries are mentioned in the Methods section 
• Each appendix begins on a new page
• Each appendix begins with a bolded, centered header such as “ Appendix A, ” “ Appendix B ”

Additional Resources For Experimental Research Papers (APA)

• https://www.mcwritingcenterblog.org/single-post/how-to-conduct-research-using-the-library-s-resources
• https://www.mcwritingcenterblog.org/single-post/how-to-read-academic-articles
• https://researchguides.ben.edu/source-evaluation   
• https://researchguides.library.brocku.ca/external-analysis/evaluating-sources
• https://writing.wisc.edu/handbook/assignments/planresearchpaper/
• https://nmu.edu/writingcenter/tips-writing-research-paper
• https://writingcenter.gmu.edu/guides/how-to-write-a-research-question
• https://www.unr.edu/writing-speaking-center/student-resources/writing-speaking-resources/guide-to-writing-research-papers
• https://drive.google.com/drive/folders/1F4DFWf85zEH4aZvm10i8Ahm_3xnAekal?usp=sharing
• https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html
• https://libguides.elmira.edu/research
• https://www.nhcc.edu/academics/library/doing-library-research/basic-steps-research-process
• https://libguides.wustl.edu/research
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• A Quick Guide to Experimental Design | 5 Steps & Examples

A Quick Guide to Experimental Design | 5 Steps & Examples

Published on 11 April 2022 by Rebecca Bevans . Revised on 5 December 2022.

Experiments are used to study causal relationships . You manipulate one or more independent variables and measure their effect on one or more dependent variables.

Experimental design means creating a set of procedures to systematically test a hypothesis . A good experimental design requires a strong understanding of the system you are studying. 

There are five key steps in designing an experiment:

• Consider your variables and how they are related
• Write a specific, testable hypothesis
• Design experimental treatments to manipulate your independent variable
• Assign subjects to groups, either between-subjects or within-subjects
• Plan how you will measure your dependent variable

For valid conclusions, you also need to select a representative sample and control any  extraneous variables that might influence your results. If if random assignment of participants to control and treatment groups is impossible, unethical, or highly difficult, consider an observational study instead.

Table of contents

Step 1: define your variables, step 2: write your hypothesis, step 3: design your experimental treatments, step 4: assign your subjects to treatment groups, step 5: measure your dependent variable, frequently asked questions about experimental design.

You should begin with a specific research question . We will work with two research question examples, one from health sciences and one from ecology:

To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.

Start by simply listing the independent and dependent variables .

Then you need to think about possible extraneous and confounding variables and consider how you might control  them in your experiment.

Finally, you can put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.

Here we predict that increasing temperature will increase soil respiration and decrease soil moisture, while decreasing soil moisture will lead to decreased soil respiration.

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Now that you have a strong conceptual understanding of the system you are studying, you should be able to write a specific, testable hypothesis that addresses your research question.

The next steps will describe how to design a controlled experiment . In a controlled experiment, you must be able to:

• Systematically and precisely manipulate the independent variable(s).
• Precisely measure the dependent variable(s).
• Control any potential confounding variables.

If your study system doesn’t match these criteria, there are other types of research you can use to answer your research question.

How you manipulate the independent variable can affect the experiment’s external validity – that is, the extent to which the results can be generalised and applied to the broader world.

First, you may need to decide how widely to vary your independent variable.

• just slightly above the natural range for your study region.
• over a wider range of temperatures to mimic future warming.
• over an extreme range that is beyond any possible natural variation.

Second, you may need to choose how finely to vary your independent variable. Sometimes this choice is made for you by your experimental system, but often you will need to decide, and this will affect how much you can infer from your results.

• a categorical variable : either as binary (yes/no) or as levels of a factor (no phone use, low phone use, high phone use).
• a continuous variable (minutes of phone use measured every night).

How you apply your experimental treatments to your test subjects is crucial for obtaining valid and reliable results.

First, you need to consider the study size : how many individuals will be included in the experiment? In general, the more subjects you include, the greater your experiment’s statistical power , which determines how much confidence you can have in your results.

Then you need to randomly assign your subjects to treatment groups . Each group receives a different level of the treatment (e.g. no phone use, low phone use, high phone use).

You should also include a control group , which receives no treatment. The control group tells us what would have happened to your test subjects without any experimental intervention.

When assigning your subjects to groups, there are two main choices you need to make:

• A completely randomised design vs a randomised block design .
• A between-subjects design vs a within-subjects design .

Randomisation

An experiment can be completely randomised or randomised within blocks (aka strata):

• In a completely randomised design , every subject is assigned to a treatment group at random.
• In a randomised block design (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

Sometimes randomisation isn’t practical or ethical , so researchers create partially-random or even non-random designs. An experimental design where treatments aren’t randomly assigned is called a quasi-experimental design .

Between-subjects vs within-subjects

In a between-subjects design (also known as an independent measures design or classic ANOVA design), individuals receive only one of the possible levels of an experimental treatment.

In medical or social research, you might also use matched pairs within your between-subjects design to make sure that each treatment group contains the same variety of test subjects in the same proportions.

In a within-subjects design (also known as a repeated measures design), every individual receives each of the experimental treatments consecutively, and their responses to each treatment are measured.

Within-subjects or repeated measures can also refer to an experimental design where an effect emerges over time, and individual responses are measured over time in order to measure this effect as it emerges.

Counterbalancing (randomising or reversing the order of treatments among subjects) is often used in within-subjects designs to ensure that the order of treatment application doesn’t influence the results of the experiment.

Finally, you need to decide how you’ll collect data on your dependent variable outcomes. You should aim for reliable and valid measurements that minimise bias or error.

Some variables, like temperature, can be objectively measured with scientific instruments. Others may need to be operationalised to turn them into measurable observations.

• Ask participants to record what time they go to sleep and get up each day.
• Ask participants to wear a sleep tracker.

How precisely you measure your dependent variable also affects the kinds of statistical analysis you can use on your data.

Experiments are always context-dependent, and a good experimental design will take into account all of the unique considerations of your study system to produce information that is both valid and relevant to your research question.

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

• A testable hypothesis
• One or more independent variables that you will manipulate
• One or more dependent variables that you will measure

When designing the experiment, first decide:

• How your variable(s) will be manipulated
• How you will control for any potential confounding or lurking variables
• How many subjects you will include
• How you will assign treatments to your subjects

The key difference between observational studies and experiments is that, done correctly, an observational study will never influence the responses or behaviours of participants. Experimental designs will have a treatment condition applied to at least a portion of participants.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word ‘between’ means that you’re comparing different conditions between groups, while the word ‘within’ means you’re comparing different conditions within the same group.

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Experimental Research Design — 6 mistakes you should never make!

Since school days’ students perform scientific experiments that provide results that define and prove the laws and theorems in science. These experiments are laid on a strong foundation of experimental research designs.

An experimental research design helps researchers execute their research objectives with more clarity and transparency.

In this article, we will not only discuss the key aspects of experimental research designs but also the issues to avoid and problems to resolve while designing your research study.

Table of Contents

What Is Experimental Research Design?

Experimental research design is a framework of protocols and procedures created to conduct experimental research with a scientific approach using two sets of variables. Herein, the first set of variables acts as a constant, used to measure the differences of the second set. The best example of experimental research methods is quantitative research .

Experimental research helps a researcher gather the necessary data for making better research decisions and determining the facts of a research study.

When Can a Researcher Conduct Experimental Research?

A researcher can conduct experimental research in the following situations —

• When time is an important factor in establishing a relationship between the cause and effect.
• When there is an invariable or never-changing behavior between the cause and effect.
• Finally, when the researcher wishes to understand the importance of the cause and effect.

Importance of Experimental Research Design

To publish significant results, choosing a quality research design forms the foundation to build the research study. Moreover, effective research design helps establish quality decision-making procedures, structures the research to lead to easier data analysis, and addresses the main research question. Therefore, it is essential to cater undivided attention and time to create an experimental research design before beginning the practical experiment.

By creating a research design, a researcher is also giving oneself time to organize the research, set up relevant boundaries for the study, and increase the reliability of the results. Through all these efforts, one could also avoid inconclusive results. If any part of the research design is flawed, it will reflect on the quality of the results derived.

Types of Experimental Research Designs

Based on the methods used to collect data in experimental studies, the experimental research designs are of three primary types:

1. Pre-experimental Research Design

A research study could conduct pre-experimental research design when a group or many groups are under observation after implementing factors of cause and effect of the research. The pre-experimental design will help researchers understand whether further investigation is necessary for the groups under observation.

Pre-experimental research is of three types —

• One-shot Case Study Research Design
• One-group Pretest-posttest Research Design
• Static-group Comparison

2. True Experimental Research Design

A true experimental research design relies on statistical analysis to prove or disprove a researcher’s hypothesis. It is one of the most accurate forms of research because it provides specific scientific evidence. Furthermore, out of all the types of experimental designs, only a true experimental design can establish a cause-effect relationship within a group. However, in a true experiment, a researcher must satisfy these three factors —

• There is a control group that is not subjected to changes and an experimental group that will experience the changed variables
• A variable that can be manipulated by the researcher
• Random distribution of the variables

This type of experimental research is commonly observed in the physical sciences.

3. Quasi-experimental Research Design

The word “Quasi” means similarity. A quasi-experimental design is similar to a true experimental design. However, the difference between the two is the assignment of the control group. In this research design, an independent variable is manipulated, but the participants of a group are not randomly assigned. This type of research design is used in field settings where random assignment is either irrelevant or not required.

The classification of the research subjects, conditions, or groups determines the type of research design to be used.

Advantages of Experimental Research

Experimental research allows you to test your idea in a controlled environment before taking the research to clinical trials. Moreover, it provides the best method to test your theory because of the following advantages:

• Researchers have firm control over variables to obtain results.
• The subject does not impact the effectiveness of experimental research. Anyone can implement it for research purposes.
• The results are specific.
• Post results analysis, research findings from the same dataset can be repurposed for similar research ideas.
• Researchers can identify the cause and effect of the hypothesis and further analyze this relationship to determine in-depth ideas.
• Experimental research makes an ideal starting point. The collected data could be used as a foundation to build new research ideas for further studies.

6 Mistakes to Avoid While Designing Your Research

There is no order to this list, and any one of these issues can seriously compromise the quality of your research. You could refer to the list as a checklist of what to avoid while designing your research.

1. Invalid Theoretical Framework

Usually, researchers miss out on checking if their hypothesis is logical to be tested. If your research design does not have basic assumptions or postulates, then it is fundamentally flawed and you need to rework on your research framework.

2. Inadequate Literature Study

Without a comprehensive research literature review , it is difficult to identify and fill the knowledge and information gaps. Furthermore, you need to clearly state how your research will contribute to the research field, either by adding value to the pertinent literature or challenging previous findings and assumptions.

3. Insufficient or Incorrect Statistical Analysis

Statistical results are one of the most trusted scientific evidence. The ultimate goal of a research experiment is to gain valid and sustainable evidence. Therefore, incorrect statistical analysis could affect the quality of any quantitative research.

4. Undefined Research Problem

This is one of the most basic aspects of research design. The research problem statement must be clear and to do that, you must set the framework for the development of research questions that address the core problems.

5. Research Limitations

Every study has some type of limitations . You should anticipate and incorporate those limitations into your conclusion, as well as the basic research design. Include a statement in your manuscript about any perceived limitations, and how you considered them while designing your experiment and drawing the conclusion.

6. Ethical Implications

The most important yet less talked about topic is the ethical issue. Your research design must include ways to minimize any risk for your participants and also address the research problem or question at hand. If you cannot manage the ethical norms along with your research study, your research objectives and validity could be questioned.

Experimental Research Design Example

In an experimental design, a researcher gathers plant samples and then randomly assigns half the samples to photosynthesize in sunlight and the other half to be kept in a dark box without sunlight, while controlling all the other variables (nutrients, water, soil, etc.)

By comparing their outcomes in biochemical tests, the researcher can confirm that the changes in the plants were due to the sunlight and not the other variables.

Experimental research is often the final form of a study conducted in the research process which is considered to provide conclusive and specific results. But it is not meant for every research. It involves a lot of resources, time, and money and is not easy to conduct, unless a foundation of research is built. Yet it is widely used in research institutes and commercial industries, for its most conclusive results in the scientific approach.

Have you worked on research designs? How was your experience creating an experimental design? What difficulties did you face? Do write to us or comment below and share your insights on experimental research designs!

Frequently Asked Questions

Randomization is important in an experimental research because it ensures unbiased results of the experiment. It also measures the cause-effect relationship on a particular group of interest.

Experimental research design lay the foundation of a research and structures the research to establish quality decision making process.

There are 3 types of experimental research designs. These are pre-experimental research design, true experimental research design, and quasi experimental research design.

The difference between an experimental and a quasi-experimental design are: 1. The assignment of the control group in quasi experimental research is non-random, unlike true experimental design, which is randomly assigned. 2. Experimental research group always has a control group; on the other hand, it may not be always present in quasi experimental research.

Experimental research establishes a cause-effect relationship by testing a theory or hypothesis using experimental groups or control variables. In contrast, descriptive research describes a study or a topic by defining the variables under it and answering the questions related to the same.

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Experimental Research: What it is + Types of designs

Any research conducted under scientifically acceptable conditions uses experimental methods. The success of experimental studies hinges on researchers confirming the change of a variable is based solely on the manipulation of the constant variable. The research should establish a notable cause and effect.

What is Experimental Research?

Experimental research is a study conducted with a scientific approach using two sets of variables. The first set acts as a constant, which you use to measure the differences of the second set. Quantitative research methods , for example, are experimental.

If you don’t have enough data to support your decisions, you must first determine the facts. This research gathers the data necessary to help you make better decisions.

You can conduct experimental research in the following situations:

• Time is a vital factor in establishing a relationship between cause and effect.
• Invariable behavior between cause and effect.
• You wish to understand the importance of cause and effect.

Experimental Research Design Types

The classic experimental design definition is: “The methods used to collect data in experimental studies.”

There are three primary types of experimental design:

• Pre-experimental research design
• True experimental research design
• Quasi-experimental research design

The way you classify research subjects based on conditions or groups determines the type of research design  you should use.

0 1. Pre-Experimental Design

A group, or various groups, are kept under observation after implementing cause and effect factors. You’ll conduct this research to understand whether further investigation is necessary for these particular groups.

You can break down pre-experimental research further into three types:

• One-shot Case Study Research Design
• One-group Pretest-posttest Research Design
• Static-group Comparison

0 2. True Experimental Design

It relies on statistical analysis to prove or disprove a hypothesis, making it the most accurate form of research. Of the types of experimental design, only true design can establish a cause-effect relationship within a group. In a true experiment, three factors need to be satisfied:

• There is a Control Group, which won’t be subject to changes, and an Experimental Group, which will experience the changed variables.
• A variable that can be manipulated by the researcher
• Random distribution

This experimental research method commonly occurs in the physical sciences.

0 3. Quasi-Experimental Design

The word “Quasi” indicates similarity. A quasi-experimental design is similar to an experimental one, but it is not the same. The difference between the two is the assignment of a control group. In this research, an independent variable is manipulated, but the participants of a group are not randomly assigned. Quasi-research is used in field settings where random assignment is either irrelevant or not required.

Importance of Experimental Design

Experimental research is a powerful tool for understanding cause-and-effect relationships. It allows us to manipulate variables and observe the effects, which is crucial for understanding how different factors influence the outcome of a study.

But the importance of experimental research goes beyond that. It’s a critical method for many scientific and academic studies. It allows us to test theories, develop new products, and make groundbreaking discoveries.

For example, this research is essential for developing new drugs and medical treatments. Researchers can understand how a new drug works by manipulating dosage and administration variables and identifying potential side effects.

Similarly, experimental research is used in the field of psychology to test theories and understand human behavior. By manipulating variables such as stimuli, researchers can gain insights into how the brain works and identify new treatment options for mental health disorders.

It is also widely used in the field of education. It allows educators to test new teaching methods and identify what works best. By manipulating variables such as class size, teaching style, and curriculum, researchers can understand how students learn and identify new ways to improve educational outcomes.

In addition, experimental research is a powerful tool for businesses and organizations. By manipulating variables such as marketing strategies, product design, and customer service, companies can understand what works best and identify new opportunities for growth.

Advantages of Experimental Research

When talking about this research, we can think of human life. Babies do their own rudimentary experiments (such as putting objects in their mouths) to learn about the world around them, while older children and teens do experiments at school to learn more about science.

Ancient scientists used this research to prove that their hypotheses were correct. For example, Galileo Galilei and Antoine Lavoisier conducted various experiments to discover key concepts in physics and chemistry. The same is true of modern experts, who use this scientific method to see if new drugs are effective, discover treatments for diseases, and create new electronic devices (among others).

It’s vital to test new ideas or theories. Why put time, effort, and funding into something that may not work?

This research allows you to test your idea in a controlled environment before marketing. It also provides the best method to test your theory thanks to the following advantages:

• Researchers have a stronger hold over variables to obtain desired results.
• The subject or industry does not impact the effectiveness of experimental research. Any industry can implement it for research purposes.
• The results are specific.
• After analyzing the results, you can apply your findings to similar ideas or situations.
• You can identify the cause and effect of a hypothesis. Researchers can further analyze this relationship to determine more in-depth ideas.
• Experimental research makes an ideal starting point. The data you collect is a foundation for building more ideas and conducting more action research .

Whether you want to know how the public will react to a new product or if a certain food increases the chance of disease, experimental research is the best place to start. Begin your research by finding subjects using  QuestionPro Audience  and other tools today.

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• Experimental Research Designs: Types, Examples & Methods

Experimental research is the most familiar type of research design for individuals in the physical sciences and a host of other fields. This is mainly because experimental research is a classical scientific experiment, similar to those performed in high school science classes.

Imagine taking 2 samples of the same plant and exposing one of them to sunlight, while the other is kept away from sunlight. Let the plant exposed to sunlight be called sample A, while the latter is called sample B.

If after the duration of the research, we find out that sample A grows and sample B dies, even though they are both regularly wetted and given the same treatment. Therefore, we can conclude that sunlight will aid growth in all similar plants.

What is Experimental Research?

Experimental research is a scientific approach to research, where one or more independent variables are manipulated and applied to one or more dependent variables to measure their effect on the latter. The effect of the independent variables on the dependent variables is usually observed and recorded over some time, to aid researchers in drawing a reasonable conclusion regarding the relationship between these 2 variable types.

The experimental research method is widely used in physical and social sciences, psychology, and education. It is based on the comparison between two or more groups with a straightforward logic, which may, however, be difficult to execute.

Mostly related to a laboratory test procedure, experimental research designs involve collecting quantitative data and performing statistical analysis on them during research. Therefore, making it an example of quantitative research method .

What are The Types of Experimental Research Design?

The types of experimental research design are determined by the way the researcher assigns subjects to different conditions and groups. They are of 3 types, namely; pre-experimental, quasi-experimental, and true experimental research.

Pre-experimental Research Design

In pre-experimental research design, either a group or various dependent groups are observed for the effect of the application of an independent variable which is presumed to cause change. It is the simplest form of experimental research design and is treated with no control group.

Although very practical, experimental research is lacking in several areas of the true-experimental criteria. The pre-experimental research design is further divided into three types

• One-shot Case Study Research Design

In this type of experimental study, only one dependent group or variable is considered. The study is carried out after some treatment which was presumed to cause change, making it a posttest study.

• One-group Pretest-posttest Research Design: 

This research design combines both posttest and pretest study by carrying out a test on a single group before the treatment is administered and after the treatment is administered. With the former being administered at the beginning of treatment and later at the end.

• Static-group Comparison: 

In a static-group comparison study, 2 or more groups are placed under observation, where only one of the groups is subjected to some treatment while the other groups are held static. All the groups are post-tested, and the observed differences between the groups are assumed to be a result of the treatment.

Quasi-experimental Research Design

  The word “quasi” means partial, half, or pseudo. Therefore, the quasi-experimental research bearing a resemblance to the true experimental research, but not the same.  In quasi-experiments, the participants are not randomly assigned, and as such, they are used in settings where randomization is difficult or impossible.

 This is very common in educational research, where administrators are unwilling to allow the random selection of students for experimental samples.

Some examples of quasi-experimental research design include; the time series, no equivalent control group design, and the counterbalanced design.

True Experimental Research Design

The true experimental research design relies on statistical analysis to approve or disprove a hypothesis. It is the most accurate type of experimental design and may be carried out with or without a pretest on at least 2 randomly assigned dependent subjects.

The true experimental research design must contain a control group, a variable that can be manipulated by the researcher, and the distribution must be random. The classification of true experimental design include:

• The posttest-only Control Group Design: In this design, subjects are randomly selected and assigned to the 2 groups (control and experimental), and only the experimental group is treated. After close observation, both groups are post-tested, and a conclusion is drawn from the difference between these groups.
• The pretest-posttest Control Group Design: For this control group design, subjects are randomly assigned to the 2 groups, both are presented, but only the experimental group is treated. After close observation, both groups are post-tested to measure the degree of change in each group.
• Solomon four-group Design: This is the combination of the pretest-only and the pretest-posttest control groups. In this case, the randomly selected subjects are placed into 4 groups.

The first two of these groups are tested using the posttest-only method, while the other two are tested using the pretest-posttest method.

Examples of Experimental Research

Experimental research examples are different, depending on the type of experimental research design that is being considered. The most basic example of experimental research is laboratory experiments, which may differ in nature depending on the subject of research.

Administering Exams After The End of Semester

During the semester, students in a class are lectured on particular courses and an exam is administered at the end of the semester. In this case, the students are the subjects or dependent variables while the lectures are the independent variables treated on the subjects.

Only one group of carefully selected subjects are considered in this research, making it a pre-experimental research design example. We will also notice that tests are only carried out at the end of the semester, and not at the beginning.

Further making it easy for us to conclude that it is a one-shot case study research. 

Employee Skill Evaluation

Before employing a job seeker, organizations conduct tests that are used to screen out less qualified candidates from the pool of qualified applicants. This way, organizations can determine an employee’s skill set at the point of employment.

In the course of employment, organizations also carry out employee training to improve employee productivity and generally grow the organization. Further evaluation is carried out at the end of each training to test the impact of the training on employee skills, and test for improvement.

Here, the subject is the employee, while the treatment is the training conducted. This is a pretest-posttest control group experimental research example.

Evaluation of Teaching Method

Let us consider an academic institution that wants to evaluate the teaching method of 2 teachers to determine which is best. Imagine a case whereby the students assigned to each teacher is carefully selected probably due to personal request by parents or due to stubbornness and smartness.

This is a no equivalent group design example because the samples are not equal. By evaluating the effectiveness of each teacher’s teaching method this way, we may conclude after a post-test has been carried out.

However, this may be influenced by factors like the natural sweetness of a student. For example, a very smart student will grab more easily than his or her peers irrespective of the method of teaching.

What are the Characteristics of Experimental Research?  

Experimental research contains dependent, independent and extraneous variables. The dependent variables are the variables being treated or manipulated and are sometimes called the subject of the research.

The independent variables are the experimental treatment being exerted on the dependent variables. Extraneous variables, on the other hand, are other factors affecting the experiment that may also contribute to the change.

The setting is where the experiment is carried out. Many experiments are carried out in the laboratory, where control can be exerted on the extraneous variables, thereby eliminating them. 

Other experiments are carried out in a less controllable setting. The choice of setting used in research depends on the nature of the experiment being carried out.

• Multivariable

Experimental research may include multiple independent variables, e.g. time, skills, test scores, etc.

Why Use Experimental Research Design?  

Experimental research design can be majorly used in physical sciences, social sciences, education, and psychology. It is used to make predictions and draw conclusions on a subject matter. 

Some uses of experimental research design are highlighted below.

• Medicine: Experimental research is used to provide the proper treatment for diseases. In most cases, rather than directly using patients as the research subject, researchers take a sample of the bacteria from the patient’s body and are treated with the developed antibacterial

The changes observed during this period are recorded and evaluated to determine its effectiveness. This process can be carried out using different experimental research methods.

• Education: Asides from science subjects like Chemistry and Physics which involves teaching students how to perform experimental research, it can also be used in improving the standard of an academic institution. This includes testing students’ knowledge on different topics, coming up with better teaching methods, and the implementation of other programs that will aid student learning.
• Human Behavior: Social scientists are the ones who mostly use experimental research to test human behaviour. For example, consider 2 people randomly chosen to be the subject of the social interaction research where one person is placed in a room without human interaction for 1 year.

The other person is placed in a room with a few other people, enjoying human interaction. There will be a difference in their behaviour at the end of the experiment.

• UI/UX: During the product development phase, one of the major aims of the product team is to create a great user experience with the product. Therefore, before launching the final product design, potential are brought in to interact with the product.

For example, when finding it difficult to choose how to position a button or feature on the app interface, a random sample of product testers are allowed to test the 2 samples and how the button positioning influences the user interaction is recorded.

What are the Disadvantages of Experimental Research?  

• It is highly prone to human error due to its dependency on variable control which may not be properly implemented. These errors could eliminate the validity of the experiment and the research being conducted.
• Exerting control of extraneous variables may create unrealistic situations. Eliminating real-life variables will result in inaccurate conclusions. This may also result in researchers controlling the variables to suit his or her personal preferences.
• It is a time-consuming process. So much time is spent on testing dependent variables and waiting for the effect of the manipulation of dependent variables to manifest.
• It is expensive. 
• It is very risky and may have ethical complications that cannot be ignored. This is common in medical research, where failed trials may lead to a patient’s death or a deteriorating health condition.
• Experimental research results are not descriptive.
• Response bias can also be supplied by the subject of the conversation.
• Human responses in experimental research can be difficult to measure. 

What are the Data Collection Methods in Experimental Research?  

Data collection methods in experimental research are the different ways in which data can be collected for experimental research. They are used in different cases, depending on the type of research being carried out.

1. Observational Study

This type of study is carried out over a long period. It measures and observes the variables of interest without changing existing conditions.

When researching the effect of social interaction on human behavior, the subjects who are placed in 2 different environments are observed throughout the research. No matter the kind of absurd behavior that is exhibited by the subject during this period, its condition will not be changed.

This may be a very risky thing to do in medical cases because it may lead to death or worse medical conditions.

2. Simulations

This procedure uses mathematical, physical, or computer models to replicate a real-life process or situation. It is frequently used when the actual situation is too expensive, dangerous, or impractical to replicate in real life.

This method is commonly used in engineering and operational research for learning purposes and sometimes as a tool to estimate possible outcomes of real research. Some common situation software are Simulink, MATLAB, and Simul8.

Not all kinds of experimental research can be carried out using simulation as a data collection tool . It is very impractical for a lot of laboratory-based research that involves chemical processes.

A survey is a tool used to gather relevant data about the characteristics of a population and is one of the most common data collection tools. A survey consists of a group of questions prepared by the researcher, to be answered by the research subject.

Surveys can be shared with the respondents both physically and electronically. When collecting data through surveys, the kind of data collected depends on the respondent, and researchers have limited control over it.

Formplus is the best tool for collecting experimental data using survey s. It has relevant features that will aid the data collection process and can also be used in other aspects of experimental research.

Differences between Experimental and Non-Experimental Research 

1. In experimental research, the researcher can control and manipulate the environment of the research, including the predictor variable which can be changed. On the other hand, non-experimental research cannot be controlled or manipulated by the researcher at will.

This is because it takes place in a real-life setting, where extraneous variables cannot be eliminated. Therefore, it is more difficult to conclude non-experimental studies, even though they are much more flexible and allow for a greater range of study fields.

2. The relationship between cause and effect cannot be established in non-experimental research, while it can be established in experimental research. This may be because many extraneous variables also influence the changes in the research subject, making it difficult to point at a particular variable as the cause of a particular change

3. Independent variables are not introduced, withdrawn, or manipulated in non-experimental designs, but the same may not be said about experimental research.

Conclusion  

Experimental research designs are often considered to be the standard in research designs. This is partly due to the common misconception that research is equivalent to scientific experiments—a component of experimental research design.

In this research design, one or more subjects or dependent variables are randomly assigned to different treatments (i.e. independent variables manipulated by the researcher) and the results are observed to conclude. One of the uniqueness of experimental research is in its ability to control the effect of extraneous variables.

Experimental research is suitable for research whose goal is to examine cause-effect relationships, e.g. explanatory research. It can be conducted in the laboratory or field settings, depending on the aim of the research that is being carried out. 

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Theoretical Framework Example for a Thesis or Dissertation

Published on October 14, 2015 by Sarah Vinz . Revised on July 18, 2023 by Tegan George.

Your theoretical framework defines the key concepts in your research, suggests relationships between them, and discusses relevant theories based on your literature review .

A strong theoretical framework gives your research direction. It allows you to convincingly interpret, explain, and generalize from your findings and show the relevance of your thesis or dissertation topic in your field.

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Table of contents

Sample problem statement and research questions, sample theoretical framework, your theoretical framework, other interesting articles.

Your theoretical framework is based on:

• Your problem statement
• Your research questions
• Your literature review

A new boutique downtown is struggling with the fact that many of their online customers do not return to make subsequent purchases. This is a big issue for the otherwise fast-growing store.Management wants to increase customer loyalty. They believe that improved customer satisfaction will play a major role in achieving their goal of increased return customers.

To investigate this problem, you have zeroed in on the following problem statement, objective, and research questions:

• Problem : Many online customers do not return to make subsequent purchases.
• Objective : To increase the quantity of return customers.
• Research question : How can the satisfaction of the boutique’s online customers be improved in order to increase the quantity of return customers?

The concepts of “customer loyalty” and “customer satisfaction” are clearly central to this study, along with their relationship to the likelihood that a customer will return. Your theoretical framework should define these concepts and discuss theories about the relationship between these variables.

Some sub-questions could include:

• What is the relationship between customer loyalty and customer satisfaction?
• How satisfied and loyal are the boutique’s online customers currently?
• What factors affect the satisfaction and loyalty of the boutique’s online customers?

As the concepts of “loyalty” and “customer satisfaction” play a major role in the investigation and will later be measured, they are essential concepts to define within your theoretical framework .

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Below is a simplified example showing how you can describe and compare theories in your thesis or dissertation . In this example, we focus on the concept of customer satisfaction introduced above.

Customer satisfaction

Thomassen (2003, p. 69) defines customer satisfaction as “the perception of the customer as a result of consciously or unconsciously comparing their experiences with their expectations.” Kotler & Keller (2008, p. 80) build on this definition, stating that customer satisfaction is determined by “the degree to which someone is happy or disappointed with the observed performance of a product in relation to his or her expectations.”

Performance that is below expectations leads to a dissatisfied customer, while performance that satisfies expectations produces satisfied customers (Kotler & Keller, 2003, p. 80).

The definition of Zeithaml and Bitner (2003, p. 86) is slightly different from that of Thomassen. They posit that “satisfaction is the consumer fulfillment response. It is a judgement that a product or service feature, or the product of service itself, provides a pleasurable level of consumption-related fulfillment.” Zeithaml and Bitner’s emphasis is thus on obtaining a certain satisfaction in relation to purchasing.

Thomassen’s definition is the most relevant to the aims of this study, given the emphasis it places on unconscious perception. Although Zeithaml and Bitner, like Thomassen, say that customer satisfaction is a reaction to the experience gained, there is no distinction between conscious and unconscious comparisons in their definition.

The boutique claims in its mission statement that it wants to sell not only a product, but also a feeling. As a result, unconscious comparison will play an important role in the satisfaction of its customers. Thomassen’s definition is therefore more relevant.

Thomassen’s Customer Satisfaction Model

According to Thomassen, both the so-called “value proposition” and other influences have an impact on final customer satisfaction. In his satisfaction model (Fig. 1), Thomassen shows that word-of-mouth, personal needs, past experiences, and marketing and public relations determine customers’ needs and expectations.

These factors are compared to their experiences, with the interplay between expectations and experiences determining a customer’s satisfaction level. Thomassen’s model is important for this study as it allows us to determine both the extent to which the boutique’s customers are satisfied, as well as where improvements can be made.

Figure 1 Customer satisfaction creation 

Of course, you could analyze the concepts more thoroughly and compare additional definitions to each other. You could also discuss the theories and ideas of key authors in greater detail and provide several models to illustrate different concepts.

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How to write an experimental thesis?

Write an experimental thesis: do you want to understand what a research thesis is and how do you write it? Here are all the tips to follow!

Table of Contents

What is it and how to write it?

You thought that this moment would never have come, but finally you did it: did you give all the exams and now to get out of the university you miss the choice, writing and compiling the thesis? Since you’ve done 30 (maybe even the average, eh?) We do 31 and end up in your study path trying to bring home the best possible vote. 

The choice of the thesis topic is certainly not trivial as it depends on a number of factors, such as the choice of subject, the rapporteurs availability, your interests, and also the labor market speediness. Before deciding what you are going to write, you have to make another important choice: Better to focus on an experimental thesis or compilation?

The second is certainly faster, while the research thesis requires a much longer, but also satisfying and relevant work for the purpose of voting and future job opportunities. You still do not understand what an experimental argument is and how do you write it down?

What is and differences with the compilation thesis?

What does experimental thesis mean? It is essentially a research thesis, i.e. the graduate must demonstrate and articulate an innovative idea or bring new results on a particular subject, thus carrying out a real work as a researcher.

The experimental thesis differs from the compilation thesis: the second one is “only” in deciphering a certain topic, collecting as much information as the student can find, comparing and evaluating the sources and submitting a summary, in a clear and orderly synthesis to submit to the committee.

The experimental thesis includes a compilation part, as research is based on the study and analysis of existing material and studies, but the objective is to carry out work autonomously (qualitative and quantitative surveys, surveys, experiments, sampling, laboratory analysis, projects, etc.) and then present the results of their analyzes, confirming or refuting the initially supported thesis.

You may also like to read: Your PHD Thesis Could Have Been Better if You Avoided These Blunders

How to write, materials and methods?

The first thing to know when you want to start writing an experimental thesis is not to have too much trouble in concluding. A research work takes time, dedication and organization, so if your goal is to graduate as soon as possible, maybe you should opt for a compilation thesis, which is not said to be simpler, but depending on the topic you choose, it can be faster implementation.

To realize an experimental thesis, try to follow these tips …

• Try to find a topic and a point of view you would like to pursue because it is driven by a strong personal interest.
• Do not start writing the thesis without getting your rapporteurs approval on the subject: you would risk wasting time and resources if your prof. would not be convinced of your choice and decide not to follow you.
• Once you’ve set the guidelines, start collecting the study material you need and perform the compilation work to ensure that no one has come to your conclusion or has done your same job.
• Organize the job well, keeping track of what the thesis you want to demonstrate and what steps you need to reach your conclusions. This aspect is important not to risk unnecessarily wasting.
• Start looking at surveys, surveys well in advance, especially if you have to interview a sample of people or experts or you need to book and have at your disposal materials, classrooms, professors and labs.
• Once you have collected all the data, start writing your thesis by dividing it into chapters with paragraphs and sub-paragraphs. You can devote the first part to the compilation thesis, exposing what studies and conclusions so far have been made on the subject matter, and then go to a second part in which you analyze your research details. Obviously, you can not miss graphics, tables, support videos, graphics presentations, and more to help you explain clearly all the steps and conclusions you’ve come to.
• It uses formal, objective and scientific language.
• Always mention the sources you are drawing on!
• Write the introduction after writing all the rest of the thesis. The introduction must contain a brief explanation of the topic chosen, the reasons for choosing the theme, the goals you have set, the research method used and then a brief summary of the chapters of your workbook.

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Study/Experimental/Research Design: Much More Than Statistics

Kenneth l. knight.

Brigham Young University, Provo, UT

The purpose of study, experimental, or research design in scientific manuscripts has changed significantly over the years. It has evolved from an explanation of the design of the experiment (ie, data gathering or acquisition) to an explanation of the statistical analysis. This practice makes “Methods” sections hard to read and understand.

To clarify the difference between study design and statistical analysis, to show the advantages of a properly written study design on article comprehension, and to encourage authors to correctly describe study designs.

Description:

The role of study design is explored from the introduction of the concept by Fisher through modern-day scientists and the AMA Manual of Style . At one time, when experiments were simpler, the study design and statistical design were identical or very similar. With the complex research that is common today, which often includes manipulating variables to create new variables and the multiple (and different) analyses of a single data set, data collection is very different than statistical design. Thus, both a study design and a statistical design are necessary.

Advantages:

Scientific manuscripts will be much easier to read and comprehend. A proper experimental design serves as a road map to the study methods, helping readers to understand more clearly how the data were obtained and, therefore, assisting them in properly analyzing the results.

Study, experimental, or research design is the backbone of good research. It directs the experiment by orchestrating data collection, defines the statistical analysis of the resultant data, and guides the interpretation of the results. When properly described in the written report of the experiment, it serves as a road map to readers, 1 helping them negotiate the “Methods” section, and, thus, it improves the clarity of communication between authors and readers.

A growing trend is to equate study design with only the statistical analysis of the data. The design statement typically is placed at the end of the “Methods” section as a subsection called “Experimental Design” or as part of a subsection called “Data Analysis.” This placement, however, equates experimental design and statistical analysis, minimizing the effect of experimental design on the planning and reporting of an experiment. This linkage is inappropriate, because some of the elements of the study design that should be described at the beginning of the “Methods” section are instead placed in the “Statistical Analysis” section or, worse, are absent from the manuscript entirely.

Have you ever interrupted your reading of the “Methods” to sketch out the variables in the margins of the paper as you attempt to understand how they all fit together? Or have you jumped back and forth from the early paragraphs of the “Methods” section to the “Statistics” section to try to understand which variables were collected and when? These efforts would be unnecessary if a road map at the beginning of the “Methods” section outlined how the independent variables were related, which dependent variables were measured, and when they were measured. When they were measured is especially important if the variables used in the statistical analysis were a subset of the measured variables or were computed from measured variables (such as change scores).

The purpose of this Communications article is to clarify the purpose and placement of study design elements in an experimental manuscript. Adopting these ideas may improve your science and surely will enhance the communication of that science. These ideas will make experimental manuscripts easier to read and understand and, therefore, will allow them to become part of readers' clinical decision making.

WHAT IS A STUDY (OR EXPERIMENTAL OR RESEARCH) DESIGN?

The terms study design, experimental design, and research design are often thought to be synonymous and are sometimes used interchangeably in a single paper. Avoid doing so. Use the term that is preferred by the style manual of the journal for which you are writing. Study design is the preferred term in the AMA Manual of Style , 2 so I will use it here.

A study design is the architecture of an experimental study 3 and a description of how the study was conducted, 4 including all elements of how the data were obtained. 5 The study design should be the first subsection of the “Methods” section in an experimental manuscript (see the Table ). “Statistical Design” or, preferably, “Statistical Analysis” or “Data Analysis” should be the last subsection of the “Methods” section.

Table. Elements of a “Methods” Section

The “Study Design” subsection describes how the variables and participants interacted. It begins with a general statement of how the study was conducted (eg, crossover trials, parallel, or observational study). 2 The second element, which usually begins with the second sentence, details the number of independent variables or factors, the levels of each variable, and their names. A shorthand way of doing so is with a statement such as “A 2 × 4 × 8 factorial guided data collection.” This tells us that there were 3 independent variables (factors), with 2 levels of the first factor, 4 levels of the second factor, and 8 levels of the third factor. Following is a sentence that names the levels of each factor: for example, “The independent variables were sex (male or female), training program (eg, walking, running, weight lifting, or plyometrics), and time (2, 4, 6, 8, 10, 15, 20, or 30 weeks).” Such an approach clearly outlines for readers how the various procedures fit into the overall structure and, therefore, enhances their understanding of how the data were collected. Thus, the design statement is a road map of the methods.

The dependent (or measurement or outcome) variables are then named. Details of how they were measured are not given at this point in the manuscript but are explained later in the “Instruments” and “Procedures” subsections.

Next is a paragraph detailing who the participants were and how they were selected, placed into groups, and assigned to a particular treatment order, if the experiment was a repeated-measures design. And although not a part of the design per se, a statement about obtaining written informed consent from participants and institutional review board approval is usually included in this subsection.

The nuts and bolts of the “Methods” section follow, including such things as equipment, materials, protocols, etc. These are beyond the scope of this commentary, however, and so will not be discussed.

The last part of the “Methods” section and last part of the “Study Design” section is the “Data Analysis” subsection. It begins with an explanation of any data manipulation, such as how data were combined or how new variables (eg, ratios or differences between collected variables) were calculated. Next, readers are told of the statistical measures used to analyze the data, such as a mixed 2 × 4 × 8 analysis of variance (ANOVA) with 2 between-groups factors (sex and training program) and 1 within-groups factor (time of measurement). Researchers should state and reference the statistical package and procedure(s) within the package used to compute the statistics. (Various statistical packages perform analyses slightly differently, so it is important to know the package and specific procedure used.) This detail allows readers to judge the appropriateness of the statistical measures and the conclusions drawn from the data.

STATISTICAL DESIGN VERSUS STATISTICAL ANALYSIS

Avoid using the term statistical design . Statistical methods are only part of the overall design. The term gives too much emphasis to the statistics, which are important, but only one of many tools used in interpreting data and only part of the study design:

The most important issues in biostatistics are not expressed with statistical procedures. The issues are inherently scientific, rather than purely statistical, and relate to the architectural design of the research, not the numbers with which the data are cited and interpreted. 6

Stated another way, “The justification for the analysis lies not in the data collected but in the manner in which the data were collected.” 3 “Without the solid foundation of a good design, the edifice of statistical analysis is unsafe.” 7 (pp4–5)

The intertwining of study design and statistical analysis may have been caused (unintentionally) by R.A. Fisher, “… a genius who almost single-handedly created the foundations for modern statistical science.” 8 Most research did not involve statistics until Fisher invented the concepts and procedures of ANOVA (in 1921) 9 , 10 and experimental design (in 1935). 11 His books became standard references for scientists in many disciplines. As a result, many ANOVA books were titled Experimental Design (see, for example, Edwards 12 ), and ANOVA courses taught in psychology and education departments included the words experimental design in their course titles.

Before the widespread use of computers to analyze data, designs were much simpler, and often there was little difference between study design and statistical analysis. So combining the 2 elements did not cause serious problems. This is no longer true, however, for 3 reasons: (1) Research studies are becoming more complex, with multiple independent and dependent variables. The procedures sections of these complex studies can be difficult to understand if your only reference point is the statistical analysis and design. (2) Dependent variables are frequently measured at different times. (3) How the data were collected is often not directly correlated with the statistical design.

For example, assume the goal is to determine the strength gain in novice and experienced athletes as a result of 3 strength training programs. Rate of change in strength is not a measurable variable; rather, it is calculated from strength measurements taken at various time intervals during the training. So the study design would be a 2 × 2 × 3 factorial with independent variables of time (pretest or posttest), experience (novice or advanced), and training (isokinetic, isotonic, or isometric) and a dependent variable of strength. The statistical design , however, would be a 2 × 3 factorial with independent variables of experience (novice or advanced) and training (isokinetic, isotonic, or isometric) and a dependent variable of strength gain. Note that data were collected according to a 3-factor design but were analyzed according to a 2-factor design and that the dependent variables were different. So a single design statement, usually a statistical design statement, would not communicate which data were collected or how. Readers would be left to figure out on their own how the data were collected.

MULTIVARIATE RESEARCH AND THE NEED FOR STUDY DESIGNS

With the advent of electronic data gathering and computerized data handling and analysis, research projects have increased in complexity. Many projects involve multiple dependent variables measured at different times, and, therefore, multiple design statements may be needed for both data collection and statistical analysis. Consider, for example, a study of the effects of heat and cold on neural inhibition. The variables of H max and M max are measured 3 times each: before, immediately after, and 30 minutes after a 20-minute treatment with heat or cold. Muscle temperature might be measured each minute before, during, and after the treatment. Although the minute-by-minute data are important for graphing temperature fluctuations during the procedure, only 3 temperatures (time 0, time 20, and time 50) are used for statistical analysis. A single dependent variable H max :M max ratio is computed to illustrate neural inhibition. Again, a single statistical design statement would tell little about how the data were obtained. And in this example, separate design statements would be needed for temperature measurement and H max :M max measurements.

As stated earlier, drawing conclusions from the data depends more on how the data were measured than on how they were analyzed. 3 , 6 , 7 , 13 So a single study design statement (or multiple such statements) at the beginning of the “Methods” section acts as a road map to the study and, thus, increases scientists' and readers' comprehension of how the experiment was conducted (ie, how the data were collected). Appropriate study design statements also increase the accuracy of conclusions drawn from the study.

CONCLUSIONS

The goal of scientific writing, or any writing, for that matter, is to communicate information. Including 2 design statements or subsections in scientific papers—one to explain how the data were collected and another to explain how they were statistically analyzed—will improve the clarity of communication and bring praise from readers. To summarize:

• Purge from your thoughts and vocabulary the idea that experimental design and statistical design are synonymous.
• Study or experimental design plays a much broader role than simply defining and directing the statistical analysis of an experiment.
• A properly written study design serves as a road map to the “Methods” section of an experiment and, therefore, improves communication with the reader.
• Study design should include a description of the type of design used, each factor (and each level) involved in the experiment, and the time at which each measurement was made.
• Clarify when the variables involved in data collection and data analysis are different, such as when data analysis involves only a subset of a collected variable or a resultant variable from the mathematical manipulation of 2 or more collected variables.

Acknowledgments

Thanks to Thomas A. Cappaert, PhD, ATC, CSCS, CSE, for suggesting the link between R.A. Fisher and the melding of the concepts of research design and statistics.

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A Complete Guide to Experimental Research

Published by Carmen Troy at August 14th, 2021 , Revised On August 25, 2023

A Quick Guide to Experimental Research

Experimental research refers to the experiments conducted in the laboratory or observation under controlled conditions. Researchers try to find out the cause-and-effect relationship between two or more variables. 

The subjects/participants in the experiment are selected and observed. They receive treatments such as changes in room temperature, diet, atmosphere, or given a new drug to observe the changes. Experiments can vary from personal and informal natural comparisons. It includes three  types of variables ;

• Independent variable
• Dependent variable
• Controlled variable

Before conducting experimental research, you need to have a clear understanding of the experimental design. A true experimental design includes  identifying a problem , formulating a  hypothesis , determining the number of variables, selecting and assigning the participants,  types of research designs , meeting ethical values, etc.

There are many  types of research  methods that can be classified based on:

• The nature of the problem to be studied
• Number of participants (individual or groups)
• Number of groups involved (Single group or multiple groups)
• Types of data collection methods (Qualitative/Quantitative/Mixed methods)
• Number of variables (single independent variable/ factorial two independent variables)
• The experimental design

Types of Experimental Research

Laboratory Experiment  

It is also called experimental research. This type of research is conducted in the laboratory. A researcher can manipulate and control the variables of the experiment.

Example: Milgram’s experiment on obedience.

Field Experiment

Field experiments are conducted in the participants’ open field and the environment by incorporating a few artificial changes. Researchers do not have control over variables under measurement. Participants know that they are taking part in the experiment.

Natural Experiments

The experiment is conducted in the natural environment of the participants. The participants are generally not informed about the experiment being conducted on them.

Examples: Estimating the health condition of the population. Did the increase in tobacco prices decrease the sale of tobacco? Did the usage of helmets decrease the number of head injuries of the bikers?

Quasi-Experiments

A quasi-experiment is an experiment that takes advantage of natural occurrences. Researchers cannot assign random participants to groups.

Example: Comparing the academic performance of the two schools.

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If not, we can help. Our panel of experts makes sure to keep the 3 pillars of Research Methodology strong.

How to Conduct Experimental Research?

Step 1. identify and define the problem.

You need to identify a problem as per your field of study and describe your  research question .

Example: You want to know about the effects of social media on the behavior of youngsters. It would help if you found out how much time students spend on the internet daily.

Example: You want to find out the adverse effects of junk food on human health. It would help if you found out how junk food frequent consumption can affect an individual’s health.

Step 2. Determine the Number of Levels of Variables

You need to determine the number of  variables . The independent variable is the predictor and manipulated by the researcher. At the same time, the dependent variable is the result of the independent variable.

In the first example, we predicted that increased social media usage negatively correlates with youngsters’ negative behaviour.

In the second example, we predicted the positive correlation between a balanced diet and a good healthy and negative relationship between junk food consumption and multiple health issues.

Step 3. Formulate the Hypothesis

One of the essential aspects of experimental research is formulating a hypothesis . A researcher studies the cause and effect between the independent and dependent variables and eliminates the confounding variables. A  null hypothesis is when there is no significant relationship between the dependent variable and the participants’ independent variables. A researcher aims to disprove the theory. H0 denotes it.  The  Alternative hypothesis  is the theory that a researcher seeks to prove.  H1or HA denotes it. 

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Step 4. Selection and Assignment of the Subjects

It’s an essential feature that differentiates the experimental design from other research designs . You need to select the number of participants based on the requirements of your experiment. Then the participants are assigned to the treatment group. There should be a control group without any treatment to study the outcomes without applying any changes compared to the experimental group.

Randomisation:  The participants are selected randomly and assigned to the experimental group. It is known as probability sampling. If the selection is not random, it’s considered non-probability sampling.

Stratified sampling : It’s a type of random selection of the participants by dividing them into strata and randomly selecting them from each level. 

Matching:   Even though participants are selected randomly, they can be assigned to the various comparison groups. Another procedure for selecting the participants is ‘matching.’ The participants are selected from the controlled group to match the experimental groups’ participants in all aspects based on the dependent variables.  

What is Replicability?

When a researcher uses the same methodology  and subject groups to carry out the experiments, it’s called ‘replicability.’ The  results will be similar each time. Researchers usually replicate their own work to strengthen external validity.

Step 5. Select a Research Design

You need to select a  research design  according to the requirements of your experiment. There are many types of experimental designs as follows.

Step 6. Meet Ethical and Legal Requirements

• Participants of the research should not be harmed.
• The dignity and confidentiality of the research should be maintained.
• The consent of the participants should be taken before experimenting.
• The privacy of the participants should be ensured.
• Research data should remain confidential.
• The anonymity of the participants should be ensured.
• The rules and objectives of the experiments should be followed strictly.
• Any wrong information or data should be avoided.

Tips for Meeting the Ethical Considerations

To meet the ethical considerations, you need to ensure that.

• Participants have the right to withdraw from the experiment.
• They should be aware of the required information about the experiment.
• It would help if you avoided offensive or unacceptable language while framing the questions of interviews, questionnaires, or Focus groups.
• You should ensure the privacy and anonymity of the participants.
• You should acknowledge the sources and authors in your dissertation using any referencing styles such as APA/MLA/Harvard referencing style.

Step 7. Collect and Analyse Data.

Collect the data  by using suitable data collection according to your experiment’s requirement, such as observations,  case studies ,  surveys ,  interviews , questionnaires, etc. Analyse the obtained information.

Step 8. Present and Conclude the Findings of the Study.

Write the report of your research. Present, conclude, and explain the outcomes of your study .  

Frequently Asked Questions

What is the first step in conducting an experimental research.

The first step in conducting experimental research is to define your research question or hypothesis. Clearly outline the purpose and expectations of your experiment to guide the entire research process.

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MSc. Eng. thesis - Failed experiment - How to put it in the thesis?

I'm currently writing a thesis. I'm simulating a problem using CFD model. The model has been validated by using it to investigate similar problem with known results. The model vs. experimental results are showing good consistency.

As for my problem, I've modeled it and I've got the results. I've spent few weeks designing, building and testing the experimental equipment but I've concluded the experimental equipment must be rebuilt using different components and I don't have time.

So, where in the paper do I report the failed experiment and how do I put it in words that it failed?

Here is the main structure of my paper.

1: Introduction

2: Literature Review

3:1 Model observation

3:2 Experimental observation

4: Results and discussion

4:1 Model validation

4:2 Problem Results (Here I was going to compare model vs. experiment)

4:3 Discussion

5: Conclusion and future work.

• negative-results

• Did you get results that differ from the model, or can you not get any results at all? –  Patricia Shanahan Commented Apr 29, 2017 at 15:43
• I couldn't get any sensible results. The equipment is vibrating allot which have direct effect on the sensors and data acquisition. The equipment is partially controlled by motors which doesn't seem to have enough torque and the motor is changing position when load is applied. As for the force sensor I was allocated, it's just unfavorable for this kind of measurements (Weak tolerance for momentum which is unavoidable in this case). –  Bjartmar Commented Apr 29, 2017 at 16:56
• If you have not already done so, still have access to the experimental setup, and have time, try to quantify as much as possible. How much torque does the motor supply? How much is needed? Vibration amplitude and frequency? –  Patricia Shanahan Commented May 1, 2017 at 12:50

You need a slight mental twist. Your experiment was not a failure. The purpose of an experiment is to ask the real world a question, and unexpected answers from the real world are at least as interesting as ones you expected.

The question you asked the real world was "Does this experimental set-up work for Problem X?". The short answer to the question, based on your experiments, is "No". Of course, you will go into a lot more detail in your thesis.

The early sections of your thesis will be much the same as they would have been if you had got the results you expected.

In 4:2, you describe your tests of your experimental set-up. To the extent that you got results at all, you do compare them to the model.

In 4:3 you discuss what you learned from building and testing your experimental equipment. If you are getting different results from model and experiment, you need to discuss why the model is more reliable than the experiment. One learns more from unexpected results than from expected ones, so this section will be richer and more interesting than it would have been if you had got the results you expected.

Your question contains the outline for "Conclusion and future work", easily identified through the keyword "concluded":

I've concluded the experimental equipment must be rebuilt using different components

The conclusion is that the equipment you built is not suitable for your problem. The future work is to rebuild it using different components. Again, you need to go into a lot more detail. What aspects of your set-up were unsuitable? Why do you think particular changes might improve it?

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Design, Modeling, and Synthesis of Active Nanosystems and Therapeutics

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A THESIS ANALYSIS (AN EXPERIMENTAL RESEARCH THESIS

contoh pengerjaan tugas analisis thesis pada mata kuliah metodologi penelitian

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Quantum Probes for Far-field thermal Sensing and Imaging

Quantum-enhanced approaches enable high-resolution imaging and sensing with signal-to-noise ratios beyond classical limits. However, operating in the quantum regime is highly susceptible to environmental influences and experimental conditions. Implementing these techniques necessitates highly controlled environments or intricate preparation methods, which can restrict their practical applications. This thesis explores the practical applications of quantum sensing, focusing on thermal sensing with bright quantum sources in biological and electronic contexts. Additionally, I discuss the development of a multimode source for quantum imaging applications and an on-chip atomic interface for scalable light-atom interactions. I built all the experimental setups from the beginning; a microscope setup for nanodiamond-based thermal sensing inside living cells, a four-wave mixing setup using a Rb cell for thermal imaging of microelectronics and multimode source, and a vacuum chamber for on-chip atomic interface.

Quantum sensing can be realized using atomic spins or optical photons possessing quantum information. Among these, color centers inside diamonds stand out as robust quantum spin defects (effective atomic spins), maintaining their quantum properties even in ambient conditions. In this thesis, I studied the role of an ensemble of color centers inside nanodiamonds as a probe of temperature in a living cell. Our approach involves incubating nanodiamonds in endothelial culture cells to achieve sub-kelvin sensitivity in temperature measurement. The results reveal a temperature error of 0.38 K and a sensitivity of 3.46 K/sqrt(Hz) after 83 seconds of measurement. Furthermore, I discuss the constraints of nanodiamond temperature sensing in living cells, propose strategies to surmount these limitations, and explore potential applications arising from such measurements.

Another ubiquitous quantum probe is light with quantum properties. Photons, the particles of light, can carry quantum correlations and have minimal interactions with each other and, to some extent, the environment. This capability theoretically allows for quantum-enhanced imaging or sensing of sample’s properties. In this thesis, I report on the demonstration of quantum-enhanced temperature sensing in microelectronics using bright quantum optical signals. I discuss the first demonstration of quantum thermal imaging used to identify hot spots and analyze heat transport in electronic systems.

To achieve this, we employed lock-in detection of thermoreflectivity, enabling us to measure temperature changes in a micro-wire induced by an electric current with an accuracy better than 0.04 degrees, averaged over 0.1 seconds. Our results demonstrate a nearly 50 % improvement in accuracy compared to using classical light at the same power, marking the first demonstration of below-shot-noise thermoreflectivity sensing. We applied this imaging technique to both aluminum and niobium-based circuits, achieving a thermal resolution of 42 mK during imaging. We scanned a 48 × 48 μm area with 3-4 dB squeezing compared to classical measurements. Based on these results, we infer possibility of generating a 256×256 pixel image with a temperature sensitivity of 42 mK within 10 minutes. This quantum thermoreflective imaging technique offers a more accurate method for detecting electronic hot spots and assessing heat distribution, and it may provide insights into the fundamental properties of electronic materials and superconductors.

In transitioning from single-mode to multimode quantum imaging, I conducted further research on techniques aimed at generating multimode quantum light. This involved an in-depth analysis of the correlation characteristics essential for utilizing quantum light sources in imaging applications. To achieve the desired multimode correlation regime, I developed a system centered on warm Rubidium vapor with nonlinear gain and feedback processes. The dynamics of optical nonlinearity in the presence of gain and feedback can lead to complexity, even chaos, in certain scenarios. Instabilities in temporal, spectral, spatial, or polarization aspects of optical fields may arise from chaotic responses within an optical x (2) or x (3) nonlinear medium positioned between two cavity mirrors or preceding a single feedback mirror. However, the complex mode dynamics, high-order correlations, and transitions to instability in such systems remain insufficiently understood.

In this study, we focused on a x (3) medium featuring an amplified four-wave mixing process, investigating noise and correlations among multiple optical modes. While individual modes displayed intensity fluctuations, we observed a reduction in relative intensity noise approaching the standard quantum limit, constrained by the camera speed. Remarkably, we recorded a relative noise reduction exceeding 20 dB and detected fourth-order intensity correlations among four spatial modes. Moreover, this process demonstrated the capability to generate over 100 distinct correlated quadruple modes.

In addition to conducting multimode analysis to develop a scalable imaging system, I have explored methodologies aimed at miniaturizing light-atom interactions on a chip for the scalable generation of quantum correlations. While warm atomic vapors have been utilized for generating or storing quantum correlations, they are plagued by challenges such as inhomogeneous broadening and low coherence time. Enhancing control over the velocity, location, and density of atomic gases could significantly improve light-atom interaction. Although laser cooling is a common technique for cooling and trapping atoms in a vacuum, its implementation in large-scale systems poses substantial challenges. As an alternative, I focused on developing an on-chip system integrated with atomic vapor controlled by surface acoustic waves (SAWs).

Surface acoustic waves are induced by an RF signal along the surface of a piezoelectric material and have already been proven to be effective for manipulating particles within microfluidic channels. Expanding upon this concept, I investigated the feasibility of employing a similar approach to manipulate atoms near the surface of a photonic circuit. The interaction between SAWs and warm atomic vapor is expected as a mechanism for controlling atomic gases in proximity to photonic chips for quantum applications. Through theoretical analysis spanning molecular dynamics and fluid dynamics regimes, I identified the experimental conditions necessary to observe acoustic wave behavior in atomic vapor. To validate this theory, I constructed an experiment comprising a vacuum chamber housing Rb atoms and a lithium niobate chip featuring interdigital transducers for launching SAWs. However, preliminary experimental results yielded no significant signals from SAW-atom interactions. Subsequent analysis revealed that observing such interactions requires sensitivity and signal-to-noise ratio (SNR) beyond the capabilities of the current setup. Multiple modifications, including increasing buffer gas pressure and mitigating RF cross-talk, are essential for conclusively observing and controlling these interactions.

STTR Program (Contract No. FA864920P0542) awarded by the United States Air Force Research Lab

Kirk grant awarded by purdue’s birck nanotechnology center, career: active nonlinear photonics with applications in quantum networks.

Directorate for Engineering

DoD-NDEP Award number HQ0034-21-1-0014

Degree type.

• Doctor of Philosophy
• Electrical and Computer Engineering

Campus location

• West Lafayette

Advisor/Supervisor/Committee Chair

Additional committee member 2, additional committee member 3, additional committee member 4, usage metrics.

• Atomic and molecular physics
• Lasers and quantum electronics
• Degenerate quantum gases and atom optics
• Quantum optics and quantum optomechanics
• Quantum technologies