research conceptual or empirical

Home » Education » Difference Between Conceptual and Empirical Research

Difference Between Conceptual and Empirical Research

The main difference between conceptual and empirical research is that conceptual research involves abstract ideas and concepts, whereas empirical research involves research based on observation, experiments and verifiable evidence.

Conceptual research and empirical research are two ways of doing scientific research. These are two opposing types of research frameworks since conceptual research doesn’t involve any experiments and empirical research does.

Key Areas Covered

1. What is Empirical Research     – Definition, Characteristics, Uses 2. What is Empirical Research     – Definition, Characteristics, Uses 3. What is the Difference Between Conceptual and Empirical Research     – Comparison of Key Differences

Conceptual Research, Empirical Research, Research

What is Conceptual Research?

Conceptual research is a type of research that is generally related to abstract ideas or concepts. It doesn’t particularly involve any practical experimentation. However, this type of research typically involves observing and analyzing information already present on a given topic. Philosophical research is a generally good example for conceptual research.

Conceptual research can be used to solve real-world problems. Conceptual frameworks, which are analytical tools researchers use in their studies, are based on conceptual research. Furthermore, these frameworks help to make conceptual distinctions and organize ideas researchers need for research purposes.

Figure 2: Conceptual Framework

In simple words, a conceptual framework is the researcher’s synthesis of the literature (previous research studies) on how to explain a particular phenomenon. It explains the actions required in the course of the study based on the researcher’s observations on the subject of research as well as the knowledge gathered from previous studies.

What is Empirical Research?

Empirical research is basically a research that uses empirical evidence. Empirical evidence refers to evidence verifiable by observation or experience rather than theory or pure logic. Thus, empirical research is research studies with conclusions based on empirical evidence. Moreover, empirical research studies are observable and measurable.

Empirical evidence can be gathered through qualitative research studies or quantitative research studies . Qualitative research methods gather non-numerical or non-statistical data. Thus, this type of studies helps to understand the underlying reasons, opinions, and motivations behind something as well as to uncover trends in thought and opinions. Quantitative research studies, on the other hand, gather statistical data. These have the ability to quantify behaviours, opinions, or other defined variables. Moreover, a researcher can even use a combination of quantitative and qualitative methods to find answers to his research questions .

Figure 2: Empirical Research Cycle

A.D. de Groot, a famous psychologist, came up with a cycle (figure 2) to explain the process of the empirical research process. Moreover, this cycle has five steps, each as important as the other. These steps include observation, induction, deduction, testing and evaluation.

Conceptual research is a type of research that is generally related to abstract ideas or concepts whereas empirical research is any research study where conclusions of the study are drawn from evidence verifiable by observation or experience rather than theory or pure logic.

Conceptual research involves abstract idea and concepts; however, it doesn’t involve any practical experiments. Empirical research, on the other hand, involves phenomena that are observable and measurable.

Type of Studies

Philosophical research studies are examples of conceptual research studies, whereas empirical research includes both quantitative and qualitative studies.

The main difference between conceptual and empirical research is that conceptual research involves abstract ideas and concepts whereas empirical research involves research based on observation, experiments and verifiable evidence.

1.“Empirical Research: Definition, Methods, Types and Examples.” QuestionPro, 14 Dec. 2018, Available here . 2. “Empirical Research.” Wikipedia, Wikimedia Foundation, 15 Sept. 2019, Available here . 3.“Conceptual Research: Definition, Framework, Example and Advantages.” QuestionPro, 18 Sept. 2018, Available here. 4. Patrick. “Conceptual Framework: A Step-by-Step Guide on How to Make One.” SimplyEducate.Me, 4 Dec. 2018, Available here .

Image Courtesy:

1. “APM Conceptual Framework” By LarryDragich – Created for a Technical Management Counsel meeting Previously published: First published in APM Digest in March (CC BY-SA 3.0) via Commons Wikimedia 2. “Empirical Cycle” By Empirical_Cycle.png: TesseUndDaanderivative work: Beao (talk) – Empirical_Cycle.png (CC BY 3.0) via Commons Wikimedia

About the Author: Hasa

Hasanthi is a seasoned content writer and editor with over 8 years of experience. Armed with a BA degree in English and a knack for digital marketing, she explores her passions for literature, history, culture, and food through her engaging and informative writing.

​You May Also Like These

Leave a reply cancel reply.

Conceptual Research vs. Empirical Research: What's the Difference?

Key Differences

Comparison chart, nature of research, data collection, methodology, conceptual research and empirical research definitions, conceptual research, empirical research, what methods are used in empirical research, is conceptual research important, what are examples of conceptual research, how is empirical research different from conceptual research, how does empirical research validate theories, what's a key characteristic of empirical research, can conceptual research include data collection, is empirical research always quantitative, how does conceptual research contribute to academia, what is conceptual research, can conceptual research lead to practical applications, are surveys considered empirical research, what fields commonly use empirical research, do empirical studies always confirm theories, can a study combine conceptual and empirical research, how does one validate results in conceptual research, can conceptual research be subjective, what role do case studies play in empirical research, what is a hypothesis in empirical research, is literature review a part of conceptual research.

Trending Comparisons

Popular Comparisons

New Comparisons

• Conduct , Resources

Conceptual Research Vs Empirical Research?

Conceptual research.

Conceptual research is a technique wherein investigation is conducted by watching and analyzing already present data on a given point. Conceptual research does not include any viable tests. It is related to unique concepts or thoughts. Philosophers have long utilized conceptual research to create modern speculations or decipher existing hypotheses in a diverse light.

It doesn’t include viable experimentation, but the instep depends on analyzing accessible data on a given theme. Conceptual research has been broadly utilized within logic to create modern hypotheses, counter existing speculations, or distinctively decipher existing hypotheses. 

Today, conceptual research is utilized to answer business questions and fathom real-world problems. Researchers utilize explanatory apparatuses called conceptual systems to form conceptual refinements and organize thoughts required for investigation purposes.

Conceptual Research Framework

A conceptual research framework is built utilizing existing writing and studies from which inferences can be drawn. A conceptual research system constitutes a researcher’s combination of past research and related work and clarifies the phenomenon. The study is conducted to diminish the existing information gap on a specific theme and make important and dependable data available. 

The following steps can be taken to make a conceptual research framework:

Explain a topic for research

The primary step is to characterize the subject of your research. Most analysts will choose a topic relating to their field of expertise.

Collect and Organize relevant research

As conceptual research depends on pre-existing studies and writing, analysts must collect all important data relating to their point. It’s imperative to utilize dependable sources and information from scientific journals or investigate well-presumed papers. As conceptual research does not utilize experimentation and tests, the significance of analyzing dependable, fact-based information is reinforced.

Distinguish factors for the research

The other step is to choose important factors for their research. These factors will be the measuring sticks by which inductions will be drawn. They provide modern scope to inquire about and offer to help identify how distinctive factors may influence the subject of research.

Make the Framework 

The last step is to make the research framework by utilizing significant writing, factors, and other significant material. 

Advantages of Conceptual Research

It requires few resources compared to other types of market research where practical experimentation is required. This spares time and assets.

It is helpful as this form of investigation only requires the assessment of existing writing. 

Disadvantages of Conceptual Research

Speculations based on existing writing instead of experimentation and perception draw conclusions that are less fact-based and may not essentially be considered dependable.

Often, we see philosophical hypotheses being countered or changed since their conclusions or inferences are drawn from existing writings instead of practical experimentation. 

Empirical Research:

Empirical research is based on observed and established phenomena and determines information from real involvement instead of hypothesis or conviction. It derives knowledge from actual experiences. How do you know a study is empirical? Pay attention to the subheadings inside the article, book, or report and examine them to seek a depiction of the investigating “strategy.” Inquire yourself: Could I recreate this study and test these results?

Key characteristics to see for: 

• Specific research questions to be answered 
• Definition of the population, behavior, or wonders being studied 
• Description of the methods used to consider the population of the area of phenomena, including various aspects like choice criteria, controls, and testing instruments.

Empirical Research Framework:

Since empirical research is based on perception and capturing experiences, it is critical to arrange the steps to experiment and how to examine it. This will empower the analyst to resolve issues or obstacles amid the test.

• Define your purpose for this research:

This is often the step where the analyst must answer questions like what precisely I need to discover? What is the issue articulation? Are there any issues regarding the accessibility of knowledge, data, time, or assets? Will this research be more useful than what it’ll cost? Before going ahead, an analyst should characterize his reason for the investigation and plan to carry out assist tasks.

• Supporting theories and relevant literature:

The analyst should discover if some hypotheses can be connected to his research issue. He must figure out if any hypothesis can offer assistance in supporting his discoveries. All kinds of significant writing will offer assistance to the analyst to discover if others have researched this before. The analyst will also need to set up presumptions and also discover if there’s any history concerning his investigation issue

• Creation of Hypothesis and measurement:

Before starting the proper research related to his subject, he must give himself a working theory or figure out the probable result. The researcher has to set up factors, choose the environment for the research and find out how he can relate between the variables. The researcher will also need to characterize the units of estimations, tolerable degree for mistakes, and discover in the event that the estimation chosen will be approved by others.

• Methodology and data collection:

In this step, the analyst has to characterize a strategy for conducting his investigation. He must set up tests to gather the information that can empower him to propose the theory. The analyst will choose whether to require a test or non-test strategy for conducting the research. The research design will shift depending on the field in which the research is being conducted. Finally, the analyst will discover parameters that will influence the legitimacy of the research plan. The information collected will need to be done by choosing appropriate tests depending on the inquire-about address. To carry out the inquiry, he can utilize one of the numerous testing strategies. Once information collection is complete, the analyst will have experimental information which must be examined.

• Data Analysis and result:

Data analysis can be tried in two ways, qualitatively and quantitatively. The analyst will need to discover what subjective strategy or quantitative strategy will be required or will require a combination of both. Depending on the examination of his information, he will know if his speculation is backed or rejected. Analyzing this information is the foremost vital portion to bolster his speculation.

A report will need to be made with the discoveries of the research. The analyst can deliver the hypotheses and writing that support his investigation. He can make recommendations or suggestions to assist research on his subject

Advantages of empirical research

• Empirical research points to discover the meaning behind a specific phenomenon. In other words, it looks for answers to how and why something works the way it is. 
• By recognizing why something happens, it is conceivable to imitate or avoid comparative events. 
• The adaptability of the research permits the analysts to alter certain perspectives of the research and alter them to new objectives. 
• It is more dependable since it speaks to a real-life involvement and not fair theories. 
• Data collected through experimental research may be less biased since the analyst is there amid the collection handle. In contrast, it is incomprehensible to confirm the precision of the information in non-empirical research.

Disadvantages of empirical research

• It can be time-consuming depending on the research subject that you have chosen. 
• It isn’t a cost-effective way of information collection in most cases because of the viable costly strategies of information gathering. Additionally, it may require traveling between numerous locations. 
• Lack of proof and research subjects may not surrender the required result. A little test estimate avoids generalization since it may not be enough to speak to the target audience.
• It isn’t easy to induce data on touchy points. Additionally, analysts may require participants’ consent to utilize the data

Difference Between Conceptual and Empirical Research

Conceptual research and empirical research are two ways of doing logical research. These are two restricting investigation systems since conceptual research doesn’t include any tests, and empirical investigation does.

Conceptual research includes unique thoughts and ideas; as it may, it doesn’t include any experiments and tests. Empirical research, on the other hand, includes phenomena that are observable and can be measured.

• Type of Studies:

Philosophical research studies are cases of conceptual research, while empirical research incorporates both quantitative and subjective studies.

The major difference between conceptual and empirical investigation is that conceptual research involves unique thoughts and ideas, though experimental investigation includes investigation based on perception, tests, and unquestionable evidence.

References:

• Empirical Research: Advantages, Drawbacks, and Differences with Non-Empirical Research. In Voicedocs . Retrieved from https://voicedocs.com/en/blog/empirical-research-advantages-drawbacks-and-differences-non-empirical-research
• Empirical Research: Definition, Methods, Types and Examples. In QuestionPro . Retrieved from https://www.questionpro.com/blog/empirical-research/
• Conceptual vs. empirical research: which is better? In Enago Academy . Retrieved from https://www.enago.com/academy/conceptual-vs-empirical-research-which-is-better/

We’ve collected the items for you to purchase for your convenience.

Get the entire package for up to 50% discount with our Replication program.

Our Location

Conduct science.

• Become a Partner
• Social Media
• Career /Academia
• Privacy Policy
• Shipping & Returns
• Request a quote

Customer service

• Account details
• Lost password

DISCLAIMER: ConductScience and affiliate products are NOT designed for human consumption, testing, or clinical utilization. They are designed for pre-clinical utilization only. Customers purchasing apparatus for the purposes of scientific research or veterinary care affirm adherence to applicable regulatory bodies for the country in which their research or care is conducted.

• University of Memphis Libraries
• Research Guides

Empirical Research: Defining, Identifying, & Finding

Defining empirical research, what is empirical research, quantitative or qualitative.

• Introduction
• Database Tools
• Search Terms
• Image Descriptions

Calfee & Chambliss (2005)  (UofM login required) describe empirical research as a "systematic approach for answering certain types of questions."  Those questions are answered "[t]hrough the collection of evidence under carefully defined and replicable conditions" (p. 43). 

The evidence collected during empirical research is often referred to as "data." 

Characteristics of Empirical Research

Emerald Publishing's guide to conducting empirical research identifies a number of common elements to empirical research: 

• A  research question , which will determine research objectives.
• A particular and planned  design  for the research, which will depend on the question and which will find ways of answering it with appropriate use of resources.
• The gathering of  primary data , which is then analysed.
• A particular  methodology  for collecting and analysing the data, such as an experiment or survey.
• The limitation of the data to a particular group, area or time scale, known as a sample [emphasis added]: for example, a specific number of employees of a particular company type, or all users of a library over a given time scale. The sample should be somehow representative of a wider population.
• The ability to  recreate  the study and test the results. This is known as  reliability .
• The ability to  generalize  from the findings to a larger sample and to other situations.

If you see these elements in a research article, you can feel confident that you have found empirical research. Emerald's guide goes into more detail on each element. 

Empirical research methodologies can be described as quantitative, qualitative, or a mix of both (usually called mixed-methods).

Ruane (2016)  (UofM login required) gets at the basic differences in approach between quantitative and qualitative research:

• Quantitative research  -- an approach to documenting reality that relies heavily on numbers both for the measurement of variables and for data analysis (p. 33).
• Qualitative research  -- an approach to documenting reality that relies on words and images as the primary data source (p. 33).

Both quantitative and qualitative methods are empirical . If you can recognize that a research study is quantitative or qualitative study, then you have also recognized that it is empirical study. 

Below are information on the characteristics of quantitative and qualitative research. This video from Scribbr also offers a good overall introduction to the two approaches to research methodology: 

Characteristics of Quantitative Research 

Researchers test hypotheses, or theories, based in assumptions about causality, i.e. we expect variable X to cause variable Y. Variables have to be controlled as much as possible to ensure validity. The results explain the relationship between the variables. Measures are based in pre-defined instruments.

Examples: experimental or quasi-experimental design, pretest & post-test, survey or questionnaire with closed-ended questions. Studies that identify factors that influence an outcomes, the utility of an intervention, or understanding predictors of outcomes. 

Characteristics of Qualitative Research

Researchers explore “meaning individuals or groups ascribe to social or human problems (Creswell & Creswell, 2018, p3).” Questions and procedures emerge rather than being prescribed. Complexity, nuance, and individual meaning are valued. Research is both inductive and deductive. Data sources are multiple and varied, i.e. interviews, observations, documents, photographs, etc. The researcher is a key instrument and must be reflective of their background, culture, and experiences as influential of the research.

Examples: open question interviews and surveys, focus groups, case studies, grounded theory, ethnography, discourse analysis, narrative, phenomenology, participatory action research.

Calfee, R. C. & Chambliss, M. (2005). The design of empirical research. In J. Flood, D. Lapp, J. R. Squire, & J. Jensen (Eds.),  Methods of research on teaching the English language arts: The methodology chapters from the handbook of research on teaching the English language arts (pp. 43-78). Routledge.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=125955&site=eds-live&scope=site .

Creswell, J. W., & Creswell, J. D. (2018).  Research design: Qualitative, quantitative, and mixed methods approaches  (5th ed.). Thousand Oaks: Sage.

How to... conduct empirical research . (n.d.). Emerald Publishing.  https://www.emeraldgrouppublishing.com/how-to/research-methods/conduct-empirical-research .

Scribbr. (2019). Quantitative vs. qualitative: The differences explained  [video]. YouTube.  https://www.youtube.com/watch?v=a-XtVF7Bofg .

Ruane, J. M. (2016).  Introducing social research methods : Essentials for getting the edge . Wiley-Blackwell.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1107215&site=eds-live&scope=site .  

• << Previous: Home
• Next: Identifying Empirical Research >>
• Last Updated: Apr 2, 2024 11:25 AM
• URL: https://libguides.memphis.edu/empirical-research

An official website of the United States government

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

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

• Publications
• Account settings

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

• Advanced Search
• Journal List
• CBE Life Sci Educ
• v.21(3); Fall 2022

Literature Reviews, Theoretical Frameworks, and Conceptual Frameworks: An Introduction for New Biology Education Researchers

Julie a. luft.

† Department of Mathematics, Social Studies, and Science Education, Mary Frances Early College of Education, University of Georgia, Athens, GA 30602-7124

Sophia Jeong

‡ Department of Teaching & Learning, College of Education & Human Ecology, Ohio State University, Columbus, OH 43210

Robert Idsardi

§ Department of Biology, Eastern Washington University, Cheney, WA 99004

Grant Gardner

∥ Department of Biology, Middle Tennessee State University, Murfreesboro, TN 37132

Associated Data

To frame their work, biology education researchers need to consider the role of literature reviews, theoretical frameworks, and conceptual frameworks as critical elements of the research and writing process. However, these elements can be confusing for scholars new to education research. This Research Methods article is designed to provide an overview of each of these elements and delineate the purpose of each in the educational research process. We describe what biology education researchers should consider as they conduct literature reviews, identify theoretical frameworks, and construct conceptual frameworks. Clarifying these different components of educational research studies can be helpful to new biology education researchers and the biology education research community at large in situating their work in the broader scholarly literature.

INTRODUCTION

Discipline-based education research (DBER) involves the purposeful and situated study of teaching and learning in specific disciplinary areas ( Singer et al. , 2012 ). Studies in DBER are guided by research questions that reflect disciplines’ priorities and worldviews. Researchers can use quantitative data, qualitative data, or both to answer these research questions through a variety of methodological traditions. Across all methodologies, there are different methods associated with planning and conducting educational research studies that include the use of surveys, interviews, observations, artifacts, or instruments. Ensuring the coherence of these elements to the discipline’s perspective also involves situating the work in the broader scholarly literature. The tools for doing this include literature reviews, theoretical frameworks, and conceptual frameworks. However, the purpose and function of each of these elements is often confusing to new education researchers. The goal of this article is to introduce new biology education researchers to these three important elements important in DBER scholarship and the broader educational literature.

The first element we discuss is a review of research (literature reviews), which highlights the need for a specific research question, study problem, or topic of investigation. Literature reviews situate the relevance of the study within a topic and a field. The process may seem familiar to science researchers entering DBER fields, but new researchers may still struggle in conducting the review. Booth et al. (2016b) highlight some of the challenges novice education researchers face when conducting a review of literature. They point out that novice researchers struggle in deciding how to focus the review, determining the scope of articles needed in the review, and knowing how to be critical of the articles in the review. Overcoming these challenges (and others) can help novice researchers construct a sound literature review that can inform the design of the study and help ensure the work makes a contribution to the field.

The second and third highlighted elements are theoretical and conceptual frameworks. These guide biology education research (BER) studies, and may be less familiar to science researchers. These elements are important in shaping the construction of new knowledge. Theoretical frameworks offer a way to explain and interpret the studied phenomenon, while conceptual frameworks clarify assumptions about the studied phenomenon. Despite the importance of these constructs in educational research, biology educational researchers have noted the limited use of theoretical or conceptual frameworks in published work ( DeHaan, 2011 ; Dirks, 2011 ; Lo et al. , 2019 ). In reviewing articles published in CBE—Life Sciences Education ( LSE ) between 2015 and 2019, we found that fewer than 25% of the research articles had a theoretical or conceptual framework (see the Supplemental Information), and at times there was an inconsistent use of theoretical and conceptual frameworks. Clearly, these frameworks are challenging for published biology education researchers, which suggests the importance of providing some initial guidance to new biology education researchers.

Fortunately, educational researchers have increased their explicit use of these frameworks over time, and this is influencing educational research in science, technology, engineering, and mathematics (STEM) fields. For instance, a quick search for theoretical or conceptual frameworks in the abstracts of articles in Educational Research Complete (a common database for educational research) in STEM fields demonstrates a dramatic change over the last 20 years: from only 778 articles published between 2000 and 2010 to 5703 articles published between 2010 and 2020, a more than sevenfold increase. Greater recognition of the importance of these frameworks is contributing to DBER authors being more explicit about such frameworks in their studies.

Collectively, literature reviews, theoretical frameworks, and conceptual frameworks work to guide methodological decisions and the elucidation of important findings. Each offers a different perspective on the problem of study and is an essential element in all forms of educational research. As new researchers seek to learn about these elements, they will find different resources, a variety of perspectives, and many suggestions about the construction and use of these elements. The wide range of available information can overwhelm the new researcher who just wants to learn the distinction between these elements or how to craft them adequately.

Our goal in writing this paper is not to offer specific advice about how to write these sections in scholarly work. Instead, we wanted to introduce these elements to those who are new to BER and who are interested in better distinguishing one from the other. In this paper, we share the purpose of each element in BER scholarship, along with important points on its construction. We also provide references for additional resources that may be beneficial to better understanding each element. Table 1 summarizes the key distinctions among these elements.

Comparison of literature reviews, theoretical frameworks, and conceptual reviews

This article is written for the new biology education researcher who is just learning about these different elements or for scientists looking to become more involved in BER. It is a result of our own work as science education and biology education researchers, whether as graduate students and postdoctoral scholars or newly hired and established faculty members. This is the article we wish had been available as we started to learn about these elements or discussed them with new educational researchers in biology.

LITERATURE REVIEWS

Purpose of a literature review.

A literature review is foundational to any research study in education or science. In education, a well-conceptualized and well-executed review provides a summary of the research that has already been done on a specific topic and identifies questions that remain to be answered, thus illustrating the current research project’s potential contribution to the field and the reasoning behind the methodological approach selected for the study ( Maxwell, 2012 ). BER is an evolving disciplinary area that is redefining areas of conceptual emphasis as well as orientations toward teaching and learning (e.g., Labov et al. , 2010 ; American Association for the Advancement of Science, 2011 ; Nehm, 2019 ). As a result, building comprehensive, critical, purposeful, and concise literature reviews can be a challenge for new biology education researchers.

Building Literature Reviews

There are different ways to approach and construct a literature review. Booth et al. (2016a) provide an overview that includes, for example, scoping reviews, which are focused only on notable studies and use a basic method of analysis, and integrative reviews, which are the result of exhaustive literature searches across different genres. Underlying each of these different review processes are attention to the s earch process, a ppraisa l of articles, s ynthesis of the literature, and a nalysis: SALSA ( Booth et al. , 2016a ). This useful acronym can help the researcher focus on the process while building a specific type of review.

However, new educational researchers often have questions about literature reviews that are foundational to SALSA or other approaches. Common questions concern determining which literature pertains to the topic of study or the role of the literature review in the design of the study. This section addresses such questions broadly while providing general guidance for writing a narrative literature review that evaluates the most pertinent studies.

The literature review process should begin before the research is conducted. As Boote and Beile (2005 , p. 3) suggested, researchers should be “scholars before researchers.” They point out that having a good working knowledge of the proposed topic helps illuminate avenues of study. Some subject areas have a deep body of work to read and reflect upon, providing a strong foundation for developing the research question(s). For instance, the teaching and learning of evolution is an area of long-standing interest in the BER community, generating many studies (e.g., Perry et al. , 2008 ; Barnes and Brownell, 2016 ) and reviews of research (e.g., Sickel and Friedrichsen, 2013 ; Ziadie and Andrews, 2018 ). Emerging areas of BER include the affective domain, issues of transfer, and metacognition ( Singer et al. , 2012 ). Many studies in these areas are transdisciplinary and not always specific to biology education (e.g., Rodrigo-Peiris et al. , 2018 ; Kolpikova et al. , 2019 ). These newer areas may require reading outside BER; fortunately, summaries of some of these topics can be found in the Current Insights section of the LSE website.

In focusing on a specific problem within a broader research strand, a new researcher will likely need to examine research outside BER. Depending upon the area of study, the expanded reading list might involve a mix of BER, DBER, and educational research studies. Determining the scope of the reading is not always straightforward. A simple way to focus one’s reading is to create a “summary phrase” or “research nugget,” which is a very brief descriptive statement about the study. It should focus on the essence of the study, for example, “first-year nonmajor students’ understanding of evolution,” “metacognitive prompts to enhance learning during biochemistry,” or “instructors’ inquiry-based instructional practices after professional development programming.” This type of phrase should help a new researcher identify two or more areas to review that pertain to the study. Focusing on recent research in the last 5 years is a good first step. Additional studies can be identified by reading relevant works referenced in those articles. It is also important to read seminal studies that are more than 5 years old. Reading a range of studies should give the researcher the necessary command of the subject in order to suggest a research question.

Given that the research question(s) arise from the literature review, the review should also substantiate the selected methodological approach. The review and research question(s) guide the researcher in determining how to collect and analyze data. Often the methodological approach used in a study is selected to contribute knowledge that expands upon what has been published previously about the topic (see Institute of Education Sciences and National Science Foundation, 2013 ). An emerging topic of study may need an exploratory approach that allows for a description of the phenomenon and development of a potential theory. This could, but not necessarily, require a methodological approach that uses interviews, observations, surveys, or other instruments. An extensively studied topic may call for the additional understanding of specific factors or variables; this type of study would be well suited to a verification or a causal research design. These could entail a methodological approach that uses valid and reliable instruments, observations, or interviews to determine an effect in the studied event. In either of these examples, the researcher(s) may use a qualitative, quantitative, or mixed methods methodological approach.

Even with a good research question, there is still more reading to be done. The complexity and focus of the research question dictates the depth and breadth of the literature to be examined. Questions that connect multiple topics can require broad literature reviews. For instance, a study that explores the impact of a biology faculty learning community on the inquiry instruction of faculty could have the following review areas: learning communities among biology faculty, inquiry instruction among biology faculty, and inquiry instruction among biology faculty as a result of professional learning. Biology education researchers need to consider whether their literature review requires studies from different disciplines within or outside DBER. For the example given, it would be fruitful to look at research focused on learning communities with faculty in STEM fields or in general education fields that result in instructional change. It is important not to be too narrow or too broad when reading. When the conclusions of articles start to sound similar or no new insights are gained, the researcher likely has a good foundation for a literature review. This level of reading should allow the researcher to demonstrate a mastery in understanding the researched topic, explain the suitability of the proposed research approach, and point to the need for the refined research question(s).

The literature review should include the researcher’s evaluation and critique of the selected studies. A researcher may have a large collection of studies, but not all of the studies will follow standards important in the reporting of empirical work in the social sciences. The American Educational Research Association ( Duran et al. , 2006 ), for example, offers a general discussion about standards for such work: an adequate review of research informing the study, the existence of sound and appropriate data collection and analysis methods, and appropriate conclusions that do not overstep or underexplore the analyzed data. The Institute of Education Sciences and National Science Foundation (2013) also offer Common Guidelines for Education Research and Development that can be used to evaluate collected studies.

Because not all journals adhere to such standards, it is important that a researcher review each study to determine the quality of published research, per the guidelines suggested earlier. In some instances, the research may be fatally flawed. Examples of such flaws include data that do not pertain to the question, a lack of discussion about the data collection, poorly constructed instruments, or an inadequate analysis. These types of errors result in studies that are incomplete, error-laden, or inaccurate and should be excluded from the review. Most studies have limitations, and the author(s) often make them explicit. For instance, there may be an instructor effect, recognized bias in the analysis, or issues with the sample population. Limitations are usually addressed by the research team in some way to ensure a sound and acceptable research process. Occasionally, the limitations associated with the study can be significant and not addressed adequately, which leaves a consequential decision in the hands of the researcher. Providing critiques of studies in the literature review process gives the reader confidence that the researcher has carefully examined relevant work in preparation for the study and, ultimately, the manuscript.

A solid literature review clearly anchors the proposed study in the field and connects the research question(s), the methodological approach, and the discussion. Reviewing extant research leads to research questions that will contribute to what is known in the field. By summarizing what is known, the literature review points to what needs to be known, which in turn guides decisions about methodology. Finally, notable findings of the new study are discussed in reference to those described in the literature review.

Within published BER studies, literature reviews can be placed in different locations in an article. When included in the introductory section of the study, the first few paragraphs of the manuscript set the stage, with the literature review following the opening paragraphs. Cooper et al. (2019) illustrate this approach in their study of course-based undergraduate research experiences (CUREs). An introduction discussing the potential of CURES is followed by an analysis of the existing literature relevant to the design of CUREs that allows for novel student discoveries. Within this review, the authors point out contradictory findings among research on novel student discoveries. This clarifies the need for their study, which is described and highlighted through specific research aims.

A literature reviews can also make up a separate section in a paper. For example, the introduction to Todd et al. (2019) illustrates the need for their research topic by highlighting the potential of learning progressions (LPs) and suggesting that LPs may help mitigate learning loss in genetics. At the end of the introduction, the authors state their specific research questions. The review of literature following this opening section comprises two subsections. One focuses on learning loss in general and examines a variety of studies and meta-analyses from the disciplines of medical education, mathematics, and reading. The second section focuses specifically on LPs in genetics and highlights student learning in the midst of LPs. These separate reviews provide insights into the stated research question.

Suggestions and Advice

A well-conceptualized, comprehensive, and critical literature review reveals the understanding of the topic that the researcher brings to the study. Literature reviews should not be so big that there is no clear area of focus; nor should they be so narrow that no real research question arises. The task for a researcher is to craft an efficient literature review that offers a critical analysis of published work, articulates the need for the study, guides the methodological approach to the topic of study, and provides an adequate foundation for the discussion of the findings.

In our own writing of literature reviews, there are often many drafts. An early draft may seem well suited to the study because the need for and approach to the study are well described. However, as the results of the study are analyzed and findings begin to emerge, the existing literature review may be inadequate and need revision. The need for an expanded discussion about the research area can result in the inclusion of new studies that support the explanation of a potential finding. The literature review may also prove to be too broad. Refocusing on a specific area allows for more contemplation of a finding.

It should be noted that there are different types of literature reviews, and many books and articles have been written about the different ways to embark on these types of reviews. Among these different resources, the following may be helpful in considering how to refine the review process for scholarly journals:

• Booth, A., Sutton, A., & Papaioannou, D. (2016a). Systemic approaches to a successful literature review (2nd ed.). Los Angeles, CA: Sage. This book addresses different types of literature reviews and offers important suggestions pertaining to defining the scope of the literature review and assessing extant studies.
• Booth, W. C., Colomb, G. G., Williams, J. M., Bizup, J., & Fitzgerald, W. T. (2016b). The craft of research (4th ed.). Chicago: University of Chicago Press. This book can help the novice consider how to make the case for an area of study. While this book is not specifically about literature reviews, it offers suggestions about making the case for your study.
• Galvan, J. L., & Galvan, M. C. (2017). Writing literature reviews: A guide for students of the social and behavioral sciences (7th ed.). Routledge. This book offers guidance on writing different types of literature reviews. For the novice researcher, there are useful suggestions for creating coherent literature reviews.

THEORETICAL FRAMEWORKS

Purpose of theoretical frameworks.

As new education researchers may be less familiar with theoretical frameworks than with literature reviews, this discussion begins with an analogy. Envision a biologist, chemist, and physicist examining together the dramatic effect of a fog tsunami over the ocean. A biologist gazing at this phenomenon may be concerned with the effect of fog on various species. A chemist may be interested in the chemical composition of the fog as water vapor condenses around bits of salt. A physicist may be focused on the refraction of light to make fog appear to be “sitting” above the ocean. While observing the same “objective event,” the scientists are operating under different theoretical frameworks that provide a particular perspective or “lens” for the interpretation of the phenomenon. Each of these scientists brings specialized knowledge, experiences, and values to this phenomenon, and these influence the interpretation of the phenomenon. The scientists’ theoretical frameworks influence how they design and carry out their studies and interpret their data.

Within an educational study, a theoretical framework helps to explain a phenomenon through a particular lens and challenges and extends existing knowledge within the limitations of that lens. Theoretical frameworks are explicitly stated by an educational researcher in the paper’s framework, theory, or relevant literature section. The framework shapes the types of questions asked, guides the method by which data are collected and analyzed, and informs the discussion of the results of the study. It also reveals the researcher’s subjectivities, for example, values, social experience, and viewpoint ( Allen, 2017 ). It is essential that a novice researcher learn to explicitly state a theoretical framework, because all research questions are being asked from the researcher’s implicit or explicit assumptions of a phenomenon of interest ( Schwandt, 2000 ).

Selecting Theoretical Frameworks

Theoretical frameworks are one of the most contemplated elements in our work in educational research. In this section, we share three important considerations for new scholars selecting a theoretical framework.

The first step in identifying a theoretical framework involves reflecting on the phenomenon within the study and the assumptions aligned with the phenomenon. The phenomenon involves the studied event. There are many possibilities, for example, student learning, instructional approach, or group organization. A researcher holds assumptions about how the phenomenon will be effected, influenced, changed, or portrayed. It is ultimately the researcher’s assumption(s) about the phenomenon that aligns with a theoretical framework. An example can help illustrate how a researcher’s reflection on the phenomenon and acknowledgment of assumptions can result in the identification of a theoretical framework.

In our example, a biology education researcher may be interested in exploring how students’ learning of difficult biological concepts can be supported by the interactions of group members. The phenomenon of interest is the interactions among the peers, and the researcher assumes that more knowledgeable students are important in supporting the learning of the group. As a result, the researcher may draw on Vygotsky’s (1978) sociocultural theory of learning and development that is focused on the phenomenon of student learning in a social setting. This theory posits the critical nature of interactions among students and between students and teachers in the process of building knowledge. A researcher drawing upon this framework holds the assumption that learning is a dynamic social process involving questions and explanations among students in the classroom and that more knowledgeable peers play an important part in the process of building conceptual knowledge.

It is important to state at this point that there are many different theoretical frameworks. Some frameworks focus on learning and knowing, while other theoretical frameworks focus on equity, empowerment, or discourse. Some frameworks are well articulated, and others are still being refined. For a new researcher, it can be challenging to find a theoretical framework. Two of the best ways to look for theoretical frameworks is through published works that highlight different frameworks.

When a theoretical framework is selected, it should clearly connect to all parts of the study. The framework should augment the study by adding a perspective that provides greater insights into the phenomenon. It should clearly align with the studies described in the literature review. For instance, a framework focused on learning would correspond to research that reported different learning outcomes for similar studies. The methods for data collection and analysis should also correspond to the framework. For instance, a study about instructional interventions could use a theoretical framework concerned with learning and could collect data about the effect of the intervention on what is learned. When the data are analyzed, the theoretical framework should provide added meaning to the findings, and the findings should align with the theoretical framework.

A study by Jensen and Lawson (2011) provides an example of how a theoretical framework connects different parts of the study. They compared undergraduate biology students in heterogeneous and homogeneous groups over the course of a semester. Jensen and Lawson (2011) assumed that learning involved collaboration and more knowledgeable peers, which made Vygotsky’s (1978) theory a good fit for their study. They predicted that students in heterogeneous groups would experience greater improvement in their reasoning abilities and science achievements with much of the learning guided by the more knowledgeable peers.

In the enactment of the study, they collected data about the instruction in traditional and inquiry-oriented classes, while the students worked in homogeneous or heterogeneous groups. To determine the effect of working in groups, the authors also measured students’ reasoning abilities and achievement. Each data-collection and analysis decision connected to understanding the influence of collaborative work.

Their findings highlighted aspects of Vygotsky’s (1978) theory of learning. One finding, for instance, posited that inquiry instruction, as a whole, resulted in reasoning and achievement gains. This links to Vygotsky (1978) , because inquiry instruction involves interactions among group members. A more nuanced finding was that group composition had a conditional effect. Heterogeneous groups performed better with more traditional and didactic instruction, regardless of the reasoning ability of the group members. Homogeneous groups worked better during interaction-rich activities for students with low reasoning ability. The authors attributed the variation to the different types of helping behaviors of students. High-performing students provided the answers, while students with low reasoning ability had to work collectively through the material. In terms of Vygotsky (1978) , this finding provided new insights into the learning context in which productive interactions can occur for students.

Another consideration in the selection and use of a theoretical framework pertains to its orientation to the study. This can result in the theoretical framework prioritizing individuals, institutions, and/or policies ( Anfara and Mertz, 2014 ). Frameworks that connect to individuals, for instance, could contribute to understanding their actions, learning, or knowledge. Institutional frameworks, on the other hand, offer insights into how institutions, organizations, or groups can influence individuals or materials. Policy theories provide ways to understand how national or local policies can dictate an emphasis on outcomes or instructional design. These different types of frameworks highlight different aspects in an educational setting, which influences the design of the study and the collection of data. In addition, these different frameworks offer a way to make sense of the data. Aligning the data collection and analysis with the framework ensures that a study is coherent and can contribute to the field.

New understandings emerge when different theoretical frameworks are used. For instance, Ebert-May et al. (2015) prioritized the individual level within conceptual change theory (see Posner et al. , 1982 ). In this theory, an individual’s knowledge changes when it no longer fits the phenomenon. Ebert-May et al. (2015) designed a professional development program challenging biology postdoctoral scholars’ existing conceptions of teaching. The authors reported that the biology postdoctoral scholars’ teaching practices became more student-centered as they were challenged to explain their instructional decision making. According to the theory, the biology postdoctoral scholars’ dissatisfaction in their descriptions of teaching and learning initiated change in their knowledge and instruction. These results reveal how conceptual change theory can explain the learning of participants and guide the design of professional development programming.

The communities of practice (CoP) theoretical framework ( Lave, 1988 ; Wenger, 1998 ) prioritizes the institutional level , suggesting that learning occurs when individuals learn from and contribute to the communities in which they reside. Grounded in the assumption of community learning, the literature on CoP suggests that, as individuals interact regularly with the other members of their group, they learn about the rules, roles, and goals of the community ( Allee, 2000 ). A study conducted by Gehrke and Kezar (2017) used the CoP framework to understand organizational change by examining the involvement of individual faculty engaged in a cross-institutional CoP focused on changing the instructional practice of faculty at each institution. In the CoP, faculty members were involved in enhancing instructional materials within their department, which aligned with an overarching goal of instituting instruction that embraced active learning. Not surprisingly, Gehrke and Kezar (2017) revealed that faculty who perceived the community culture as important in their work cultivated institutional change. Furthermore, they found that institutional change was sustained when key leaders served as mentors and provided support for faculty, and as faculty themselves developed into leaders. This study reveals the complexity of individual roles in a COP in order to support institutional instructional change.

It is important to explicitly state the theoretical framework used in a study, but elucidating a theoretical framework can be challenging for a new educational researcher. The literature review can help to identify an applicable theoretical framework. Focal areas of the review or central terms often connect to assumptions and assertions associated with the framework that pertain to the phenomenon of interest. Another way to identify a theoretical framework is self-reflection by the researcher on personal beliefs and understandings about the nature of knowledge the researcher brings to the study ( Lysaght, 2011 ). In stating one’s beliefs and understandings related to the study (e.g., students construct their knowledge, instructional materials support learning), an orientation becomes evident that will suggest a particular theoretical framework. Theoretical frameworks are not arbitrary , but purposefully selected.

With experience, a researcher may find expanded roles for theoretical frameworks. Researchers may revise an existing framework that has limited explanatory power, or they may decide there is a need to develop a new theoretical framework. These frameworks can emerge from a current study or the need to explain a phenomenon in a new way. Researchers may also find that multiple theoretical frameworks are necessary to frame and explore a problem, as different frameworks can provide different insights into a problem.

Finally, it is important to recognize that choosing “x” theoretical framework does not necessarily mean a researcher chooses “y” methodology and so on, nor is there a clear-cut, linear process in selecting a theoretical framework for one’s study. In part, the nonlinear process of identifying a theoretical framework is what makes understanding and using theoretical frameworks challenging. For the novice scholar, contemplating and understanding theoretical frameworks is essential. Fortunately, there are articles and books that can help:

• Creswell, J. W. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Los Angeles, CA: Sage. This book provides an overview of theoretical frameworks in general educational research.
• Ding, L. (2019). Theoretical perspectives of quantitative physics education research. Physical Review Physics Education Research , 15 (2), 020101-1–020101-13. This paper illustrates how a DBER field can use theoretical frameworks.
• Nehm, R. (2019). Biology education research: Building integrative frameworks for teaching and learning about living systems. Disciplinary and Interdisciplinary Science Education Research , 1 , ar15. https://doi.org/10.1186/s43031-019-0017-6 . This paper articulates the need for studies in BER to explicitly state theoretical frameworks and provides examples of potential studies.
• Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice . Sage. This book also provides an overview of theoretical frameworks, but for both research and evaluation.

CONCEPTUAL FRAMEWORKS

Purpose of a conceptual framework.

A conceptual framework is a description of the way a researcher understands the factors and/or variables that are involved in the study and their relationships to one another. The purpose of a conceptual framework is to articulate the concepts under study using relevant literature ( Rocco and Plakhotnik, 2009 ) and to clarify the presumed relationships among those concepts ( Rocco and Plakhotnik, 2009 ; Anfara and Mertz, 2014 ). Conceptual frameworks are different from theoretical frameworks in both their breadth and grounding in established findings. Whereas a theoretical framework articulates the lens through which a researcher views the work, the conceptual framework is often more mechanistic and malleable.

Conceptual frameworks are broader, encompassing both established theories (i.e., theoretical frameworks) and the researchers’ own emergent ideas. Emergent ideas, for example, may be rooted in informal and/or unpublished observations from experience. These emergent ideas would not be considered a “theory” if they are not yet tested, supported by systematically collected evidence, and peer reviewed. However, they do still play an important role in the way researchers approach their studies. The conceptual framework allows authors to clearly describe their emergent ideas so that connections among ideas in the study and the significance of the study are apparent to readers.

Constructing Conceptual Frameworks

Including a conceptual framework in a research study is important, but researchers often opt to include either a conceptual or a theoretical framework. Either may be adequate, but both provide greater insight into the research approach. For instance, a research team plans to test a novel component of an existing theory. In their study, they describe the existing theoretical framework that informs their work and then present their own conceptual framework. Within this conceptual framework, specific topics portray emergent ideas that are related to the theory. Describing both frameworks allows readers to better understand the researchers’ assumptions, orientations, and understanding of concepts being investigated. For example, Connolly et al. (2018) included a conceptual framework that described how they applied a theoretical framework of social cognitive career theory (SCCT) to their study on teaching programs for doctoral students. In their conceptual framework, the authors described SCCT, explained how it applied to the investigation, and drew upon results from previous studies to justify the proposed connections between the theory and their emergent ideas.

In some cases, authors may be able to sufficiently describe their conceptualization of the phenomenon under study in an introduction alone, without a separate conceptual framework section. However, incomplete descriptions of how the researchers conceptualize the components of the study may limit the significance of the study by making the research less intelligible to readers. This is especially problematic when studying topics in which researchers use the same terms for different constructs or different terms for similar and overlapping constructs (e.g., inquiry, teacher beliefs, pedagogical content knowledge, or active learning). Authors must describe their conceptualization of a construct if the research is to be understandable and useful.

There are some key areas to consider regarding the inclusion of a conceptual framework in a study. To begin with, it is important to recognize that conceptual frameworks are constructed by the researchers conducting the study ( Rocco and Plakhotnik, 2009 ; Maxwell, 2012 ). This is different from theoretical frameworks that are often taken from established literature. Researchers should bring together ideas from the literature, but they may be influenced by their own experiences as a student and/or instructor, the shared experiences of others, or thought experiments as they construct a description, model, or representation of their understanding of the phenomenon under study. This is an exercise in intellectual organization and clarity that often considers what is learned, known, and experienced. The conceptual framework makes these constructs explicitly visible to readers, who may have different understandings of the phenomenon based on their prior knowledge and experience. There is no single method to go about this intellectual work.

Reeves et al. (2016) is an example of an article that proposed a conceptual framework about graduate teaching assistant professional development evaluation and research. The authors used existing literature to create a novel framework that filled a gap in current research and practice related to the training of graduate teaching assistants. This conceptual framework can guide the systematic collection of data by other researchers because the framework describes the relationships among various factors that influence teaching and learning. The Reeves et al. (2016) conceptual framework may be modified as additional data are collected and analyzed by other researchers. This is not uncommon, as conceptual frameworks can serve as catalysts for concerted research efforts that systematically explore a phenomenon (e.g., Reynolds et al. , 2012 ; Brownell and Kloser, 2015 ).

Sabel et al. (2017) used a conceptual framework in their exploration of how scaffolds, an external factor, interact with internal factors to support student learning. Their conceptual framework integrated principles from two theoretical frameworks, self-regulated learning and metacognition, to illustrate how the research team conceptualized students’ use of scaffolds in their learning ( Figure 1 ). Sabel et al. (2017) created this model using their interpretations of these two frameworks in the context of their teaching.

Conceptual framework from Sabel et al. (2017) .

A conceptual framework should describe the relationship among components of the investigation ( Anfara and Mertz, 2014 ). These relationships should guide the researcher’s methods of approaching the study ( Miles et al. , 2014 ) and inform both the data to be collected and how those data should be analyzed. Explicitly describing the connections among the ideas allows the researcher to justify the importance of the study and the rigor of the research design. Just as importantly, these frameworks help readers understand why certain components of a system were not explored in the study. This is a challenge in education research, which is rooted in complex environments with many variables that are difficult to control.

For example, Sabel et al. (2017) stated: “Scaffolds, such as enhanced answer keys and reflection questions, can help students and instructors bridge the external and internal factors and support learning” (p. 3). They connected the scaffolds in the study to the three dimensions of metacognition and the eventual transformation of existing ideas into new or revised ideas. Their framework provides a rationale for focusing on how students use two different scaffolds, and not on other factors that may influence a student’s success (self-efficacy, use of active learning, exam format, etc.).

In constructing conceptual frameworks, researchers should address needed areas of study and/or contradictions discovered in literature reviews. By attending to these areas, researchers can strengthen their arguments for the importance of a study. For instance, conceptual frameworks can address how the current study will fill gaps in the research, resolve contradictions in existing literature, or suggest a new area of study. While a literature review describes what is known and not known about the phenomenon, the conceptual framework leverages these gaps in describing the current study ( Maxwell, 2012 ). In the example of Sabel et al. (2017) , the authors indicated there was a gap in the literature regarding how scaffolds engage students in metacognition to promote learning in large classes. Their study helps fill that gap by describing how scaffolds can support students in the three dimensions of metacognition: intelligibility, plausibility, and wide applicability. In another example, Lane (2016) integrated research from science identity, the ethic of care, the sense of belonging, and an expertise model of student success to form a conceptual framework that addressed the critiques of other frameworks. In a more recent example, Sbeglia et al. (2021) illustrated how a conceptual framework influences the methodological choices and inferences in studies by educational researchers.

Sometimes researchers draw upon the conceptual frameworks of other researchers. When a researcher’s conceptual framework closely aligns with an existing framework, the discussion may be brief. For example, Ghee et al. (2016) referred to portions of SCCT as their conceptual framework to explain the significance of their work on students’ self-efficacy and career interests. Because the authors’ conceptualization of this phenomenon aligned with a previously described framework, they briefly mentioned the conceptual framework and provided additional citations that provided more detail for the readers.

Within both the BER and the broader DBER communities, conceptual frameworks have been used to describe different constructs. For example, some researchers have used the term “conceptual framework” to describe students’ conceptual understandings of a biological phenomenon. This is distinct from a researcher’s conceptual framework of the educational phenomenon under investigation, which may also need to be explicitly described in the article. Other studies have presented a research logic model or flowchart of the research design as a conceptual framework. These constructions can be quite valuable in helping readers understand the data-collection and analysis process. However, a model depicting the study design does not serve the same role as a conceptual framework. Researchers need to avoid conflating these constructs by differentiating the researchers’ conceptual framework that guides the study from the research design, when applicable.

Explicitly describing conceptual frameworks is essential in depicting the focus of the study. We have found that being explicit in a conceptual framework means using accepted terminology, referencing prior work, and clearly noting connections between terms. This description can also highlight gaps in the literature or suggest potential contributions to the field of study. A well-elucidated conceptual framework can suggest additional studies that may be warranted. This can also spur other researchers to consider how they would approach the examination of a phenomenon and could result in a revised conceptual framework.

It can be challenging to create conceptual frameworks, but they are important. Below are two resources that could be helpful in constructing and presenting conceptual frameworks in educational research:

• Maxwell, J. A. (2012). Qualitative research design: An interactive approach (3rd ed.). Los Angeles, CA: Sage. Chapter 3 in this book describes how to construct conceptual frameworks.
• Ravitch, S. M., & Riggan, M. (2016). Reason & rigor: How conceptual frameworks guide research . Los Angeles, CA: Sage. This book explains how conceptual frameworks guide the research questions, data collection, data analyses, and interpretation of results.

CONCLUDING THOUGHTS

Literature reviews, theoretical frameworks, and conceptual frameworks are all important in DBER and BER. Robust literature reviews reinforce the importance of a study. Theoretical frameworks connect the study to the base of knowledge in educational theory and specify the researcher’s assumptions. Conceptual frameworks allow researchers to explicitly describe their conceptualization of the relationships among the components of the phenomenon under study. Table 1 provides a general overview of these components in order to assist biology education researchers in thinking about these elements.

It is important to emphasize that these different elements are intertwined. When these elements are aligned and complement one another, the study is coherent, and the study findings contribute to knowledge in the field. When literature reviews, theoretical frameworks, and conceptual frameworks are disconnected from one another, the study suffers. The point of the study is lost, suggested findings are unsupported, or important conclusions are invisible to the researcher. In addition, this misalignment may be costly in terms of time and money.

Conducting a literature review, selecting a theoretical framework, and building a conceptual framework are some of the most difficult elements of a research study. It takes time to understand the relevant research, identify a theoretical framework that provides important insights into the study, and formulate a conceptual framework that organizes the finding. In the research process, there is often a constant back and forth among these elements as the study evolves. With an ongoing refinement of the review of literature, clarification of the theoretical framework, and articulation of a conceptual framework, a sound study can emerge that makes a contribution to the field. This is the goal of BER and education research.

Supplementary Material

• Allee, V. (2000). Knowledge networks and communities of learning . OD Practitioner , 32 ( 4 ), 4–13. [ Google Scholar ]
• Allen, M. (2017). The Sage encyclopedia of communication research methods (Vols. 1–4 ). Los Angeles, CA: Sage. 10.4135/9781483381411 [ CrossRef ] [ Google Scholar ]
• American Association for the Advancement of Science. (2011). Vision and change in undergraduate biology education: A call to action . Washington, DC. [ Google Scholar ]
• Anfara, V. A., Mertz, N. T. (2014). Setting the stage . In Anfara, V. A., Mertz, N. T. (eds.), Theoretical frameworks in qualitative research (pp. 1–22). Sage. [ Google Scholar ]
• Barnes, M. E., Brownell, S. E. (2016). Practices and perspectives of college instructors on addressing religious beliefs when teaching evolution . CBE—Life Sciences Education , 15 ( 2 ), ar18. https://doi.org/10.1187/cbe.15-11-0243 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Boote, D. N., Beile, P. (2005). Scholars before researchers: On the centrality of the dissertation literature review in research preparation . Educational Researcher , 34 ( 6 ), 3–15. 10.3102/0013189x034006003 [ CrossRef ] [ Google Scholar ]
• Booth, A., Sutton, A., Papaioannou, D. (2016a). Systemic approaches to a successful literature review (2nd ed.). Los Angeles, CA: Sage. [ Google Scholar ]
• Booth, W. C., Colomb, G. G., Williams, J. M., Bizup, J., Fitzgerald, W. T. (2016b). The craft of research (4th ed.). Chicago, IL: University of Chicago Press. [ Google Scholar ]
• Brownell, S. E., Kloser, M. J. (2015). Toward a conceptual framework for measuring the effectiveness of course-based undergraduate research experiences in undergraduate biology . Studies in Higher Education , 40 ( 3 ), 525–544. https://doi.org/10.1080/03075079.2015.1004234 [ Google Scholar ]
• Connolly, M. R., Lee, Y. G., Savoy, J. N. (2018). The effects of doctoral teaching development on early-career STEM scholars’ college teaching self-efficacy . CBE—Life Sciences Education , 17 ( 1 ), ar14. https://doi.org/10.1187/cbe.17-02-0039 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Cooper, K. M., Blattman, J. N., Hendrix, T., Brownell, S. E. (2019). The impact of broadly relevant novel discoveries on student project ownership in a traditional lab course turned CURE . CBE—Life Sciences Education , 18 ( 4 ), ar57. https://doi.org/10.1187/cbe.19-06-0113 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Creswell, J. W. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Los Angeles, CA: Sage. [ Google Scholar ]
• DeHaan, R. L. (2011). Education research in the biological sciences: A nine decade review (Paper commissioned by the NAS/NRC Committee on the Status, Contributions, and Future Directions of Discipline Based Education Research) . Washington, DC: National Academies Press. Retrieved May 20, 2022, from www7.nationalacademies.org/bose/DBER_Mee ting2_commissioned_papers_page.html [ Google Scholar ]
• Ding, L. (2019). Theoretical perspectives of quantitative physics education research . Physical Review Physics Education Research , 15 ( 2 ), 020101. [ Google Scholar ]
• Dirks, C. (2011). The current status and future direction of biology education research . Paper presented at: Second Committee Meeting on the Status, Contributions, and Future Directions of Discipline-Based Education Research, 18–19 October (Washington, DC). Retrieved May 20, 2022, from http://sites.nationalacademies.org/DBASSE/BOSE/DBASSE_071087 [ Google Scholar ]
• Duran, R. P., Eisenhart, M. A., Erickson, F. D., Grant, C. A., Green, J. L., Hedges, L. V., Schneider, B. L. (2006). Standards for reporting on empirical social science research in AERA publications: American Educational Research Association . Educational Researcher , 35 ( 6 ), 33–40. [ Google Scholar ]
• Ebert-May, D., Derting, T. L., Henkel, T. P., Middlemis Maher, J., Momsen, J. L., Arnold, B., Passmore, H. A. (2015). Breaking the cycle: Future faculty begin teaching with learner-centered strategies after professional development . CBE—Life Sciences Education , 14 ( 2 ), ar22. https://doi.org/10.1187/cbe.14-12-0222 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Galvan, J. L., Galvan, M. C. (2017). Writing literature reviews: A guide for students of the social and behavioral sciences (7th ed.). New York, NY: Routledge. https://doi.org/10.4324/9781315229386 [ Google Scholar ]
• Gehrke, S., Kezar, A. (2017). The roles of STEM faculty communities of practice in institutional and departmental reform in higher education . American Educational Research Journal , 54 ( 5 ), 803–833. https://doi.org/10.3102/0002831217706736 [ Google Scholar ]
• Ghee, M., Keels, M., Collins, D., Neal-Spence, C., Baker, E. (2016). Fine-tuning summer research programs to promote underrepresented students’ persistence in the STEM pathway . CBE—Life Sciences Education , 15 ( 3 ), ar28. https://doi.org/10.1187/cbe.16-01-0046 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Institute of Education Sciences & National Science Foundation. (2013). Common guidelines for education research and development . Retrieved May 20, 2022, from www.nsf.gov/pubs/2013/nsf13126/nsf13126.pdf
• Jensen, J. L., Lawson, A. (2011). Effects of collaborative group composition and inquiry instruction on reasoning gains and achievement in undergraduate biology . CBE—Life Sciences Education , 10 ( 1 ), 64–73. https://doi.org/10.1187/cbe.19-05-0098 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kolpikova, E. P., Chen, D. C., Doherty, J. H. (2019). Does the format of preclass reading quizzes matter? An evaluation of traditional and gamified, adaptive preclass reading quizzes . CBE—Life Sciences Education , 18 ( 4 ), ar52. https://doi.org/10.1187/cbe.19-05-0098 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Labov, J. B., Reid, A. H., Yamamoto, K. R. (2010). Integrated biology and undergraduate science education: A new biology education for the twenty-first century? CBE—Life Sciences Education , 9 ( 1 ), 10–16. https://doi.org/10.1187/cbe.09-12-0092 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lane, T. B. (2016). Beyond academic and social integration: Understanding the impact of a STEM enrichment program on the retention and degree attainment of underrepresented students . CBE—Life Sciences Education , 15 ( 3 ), ar39. https://doi.org/10.1187/cbe.16-01-0070 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life . New York, NY: Cambridge University Press. [ Google Scholar ]
• Lo, S. M., Gardner, G. E., Reid, J., Napoleon-Fanis, V., Carroll, P., Smith, E., Sato, B. K. (2019). Prevailing questions and methodologies in biology education research: A longitudinal analysis of research in CBE — Life Sciences Education and at the Society for the Advancement of Biology Education Research . CBE—Life Sciences Education , 18 ( 1 ), ar9. https://doi.org/10.1187/cbe.18-08-0164 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lysaght, Z. (2011). Epistemological and paradigmatic ecumenism in “Pasteur’s quadrant:” Tales from doctoral research . In Official Conference Proceedings of the Third Asian Conference on Education in Osaka, Japan . Retrieved May 20, 2022, from http://iafor.org/ace2011_offprint/ACE2011_offprint_0254.pdf
• Maxwell, J. A. (2012). Qualitative research design: An interactive approach (3rd ed.). Los Angeles, CA: Sage. [ Google Scholar ]
• Miles, M. B., Huberman, A. M., Saldaña, J. (2014). Qualitative data analysis (3rd ed.). Los Angeles, CA: Sage. [ Google Scholar ]
• Nehm, R. (2019). Biology education research: Building integrative frameworks for teaching and learning about living systems . Disciplinary and Interdisciplinary Science Education Research , 1 , ar15. https://doi.org/10.1186/s43031-019-0017-6 [ Google Scholar ]
• Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice . Los Angeles, CA: Sage. [ Google Scholar ]
• Perry, J., Meir, E., Herron, J. C., Maruca, S., Stal, D. (2008). Evaluating two approaches to helping college students understand evolutionary trees through diagramming tasks . CBE—Life Sciences Education , 7 ( 2 ), 193–201. https://doi.org/10.1187/cbe.07-01-0007 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Posner, G. J., Strike, K. A., Hewson, P. W., Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change . Science Education , 66 ( 2 ), 211–227. [ Google Scholar ]
• Ravitch, S. M., Riggan, M. (2016). Reason & rigor: How conceptual frameworks guide research . Los Angeles, CA: Sage. [ Google Scholar ]
• Reeves, T. D., Marbach-Ad, G., Miller, K. R., Ridgway, J., Gardner, G. E., Schussler, E. E., Wischusen, E. W. (2016). A conceptual framework for graduate teaching assistant professional development evaluation and research . CBE—Life Sciences Education , 15 ( 2 ), es2. https://doi.org/10.1187/cbe.15-10-0225 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Reynolds, J. A., Thaiss, C., Katkin, W., Thompson, R. J. Jr. (2012). Writing-to-learn in undergraduate science education: A community-based, conceptually driven approach . CBE—Life Sciences Education , 11 ( 1 ), 17–25. https://doi.org/10.1187/cbe.11-08-0064 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Rocco, T. S., Plakhotnik, M. S. (2009). Literature reviews, conceptual frameworks, and theoretical frameworks: Terms, functions, and distinctions . Human Resource Development Review , 8 ( 1 ), 120–130. https://doi.org/10.1177/1534484309332617 [ Google Scholar ]
• Rodrigo-Peiris, T., Xiang, L., Cassone, V. M. (2018). A low-intensity, hybrid design between a “traditional” and a “course-based” research experience yields positive outcomes for science undergraduate freshmen and shows potential for large-scale application . CBE—Life Sciences Education , 17 ( 4 ), ar53. https://doi.org/10.1187/cbe.17-11-0248 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sabel, J. L., Dauer, J. T., Forbes, C. T. (2017). Introductory biology students’ use of enhanced answer keys and reflection questions to engage in metacognition and enhance understanding . CBE—Life Sciences Education , 16 ( 3 ), ar40. https://doi.org/10.1187/cbe.16-10-0298 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sbeglia, G. C., Goodridge, J. A., Gordon, L. H., Nehm, R. H. (2021). Are faculty changing? How reform frameworks, sampling intensities, and instrument measures impact inferences about student-centered teaching practices . CBE—Life Sciences Education , 20 ( 3 ), ar39. https://doi.org/10.1187/cbe.20-11-0259 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Schwandt, T. A. (2000). Three epistemological stances for qualitative inquiry: Interpretivism, hermeneutics, and social constructionism . In Denzin, N. K., Lincoln, Y. S. (Eds.), Handbook of qualitative research (2nd ed., pp. 189–213). Los Angeles, CA: Sage. [ Google Scholar ]
• Sickel, A. J., Friedrichsen, P. (2013). Examining the evolution education literature with a focus on teachers: Major findings, goals for teacher preparation, and directions for future research . Evolution: Education and Outreach , 6 ( 1 ), 23. https://doi.org/10.1186/1936-6434-6-23 [ Google Scholar ]
• Singer, S. R., Nielsen, N. R., Schweingruber, H. A. (2012). Discipline-based education research: Understanding and improving learning in undergraduate science and engineering . Washington, DC: National Academies Press. [ Google Scholar ]
• Todd, A., Romine, W. L., Correa-Menendez, J. (2019). Modeling the transition from a phenotypic to genotypic conceptualization of genetics in a university-level introductory biology context . Research in Science Education , 49 ( 2 ), 569–589. https://doi.org/10.1007/s11165-017-9626-2 [ Google Scholar ]
• Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes . Cambridge, MA: Harvard University Press. [ Google Scholar ]
• Wenger, E. (1998). Communities of practice: Learning as a social system . Systems Thinker , 9 ( 5 ), 2–3. [ Google Scholar ]
• Ziadie, M. A., Andrews, T. C. (2018). Moving evolution education forward: A systematic analysis of literature to identify gaps in collective knowledge for teaching . CBE—Life Sciences Education , 17 ( 1 ), ar11. https://doi.org/10.1187/cbe.17-08-0190 [ PMC free article ] [ PubMed ] [ Google Scholar ]

• Skip to main content
• Skip to primary sidebar
• Skip to footer
• QuestionPro

• Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
• Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Market Research

Empirical Research: Definition, Methods, Types and Examples

Content Index

Empirical research: Definition

Empirical research: origin, quantitative research methods, qualitative research methods, steps for conducting empirical research, empirical research methodology cycle, advantages of empirical research, disadvantages of empirical research, why is there a need for empirical research.

Empirical research is defined as any research where conclusions of the study is strictly drawn from concretely empirical evidence, and therefore “verifiable” evidence.

This empirical evidence can be gathered using quantitative market research and  qualitative market research  methods.

For example: A research is being conducted to find out if listening to happy music in the workplace while working may promote creativity? An experiment is conducted by using a music website survey on a set of audience who are exposed to happy music and another set who are not listening to music at all, and the subjects are then observed. The results derived from such a research will give empirical evidence if it does promote creativity or not.

LEARN ABOUT: Behavioral Research

You must have heard the quote” I will not believe it unless I see it”. This came from the ancient empiricists, a fundamental understanding that powered the emergence of medieval science during the renaissance period and laid the foundation of modern science, as we know it today. The word itself has its roots in greek. It is derived from the greek word empeirikos which means “experienced”.

In today’s world, the word empirical refers to collection of data using evidence that is collected through observation or experience or by using calibrated scientific instruments. All of the above origins have one thing in common which is dependence of observation and experiments to collect data and test them to come up with conclusions.

LEARN ABOUT: Causal Research

Types and methodologies of empirical research

Empirical research can be conducted and analysed using qualitative or quantitative methods.

• Quantitative research : Quantitative research methods are used to gather information through numerical data. It is used to quantify opinions, behaviors or other defined variables . These are predetermined and are in a more structured format. Some of the commonly used methods are survey, longitudinal studies, polls, etc
• Qualitative research:   Qualitative research methods are used to gather non numerical data.  It is used to find meanings, opinions, or the underlying reasons from its subjects. These methods are unstructured or semi structured. The sample size for such a research is usually small and it is a conversational type of method to provide more insight or in-depth information about the problem Some of the most popular forms of methods are focus groups, experiments, interviews, etc.

Data collected from these will need to be analysed. Empirical evidence can also be analysed either quantitatively and qualitatively. Using this, the researcher can answer empirical questions which have to be clearly defined and answerable with the findings he has got. The type of research design used will vary depending on the field in which it is going to be used. Many of them might choose to do a collective research involving quantitative and qualitative method to better answer questions which cannot be studied in a laboratory setting.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

Quantitative research methods aid in analyzing the empirical evidence gathered. By using these a researcher can find out if his hypothesis is supported or not.

• Survey research: Survey research generally involves a large audience to collect a large amount of data. This is a quantitative method having a predetermined set of closed questions which are pretty easy to answer. Because of the simplicity of such a method, high responses are achieved. It is one of the most commonly used methods for all kinds of research in today’s world.

Previously, surveys were taken face to face only with maybe a recorder. However, with advancement in technology and for ease, new mediums such as emails , or social media have emerged.

For example: Depletion of energy resources is a growing concern and hence there is a need for awareness about renewable energy. According to recent studies, fossil fuels still account for around 80% of energy consumption in the United States. Even though there is a rise in the use of green energy every year, there are certain parameters because of which the general population is still not opting for green energy. In order to understand why, a survey can be conducted to gather opinions of the general population about green energy and the factors that influence their choice of switching to renewable energy. Such a survey can help institutions or governing bodies to promote appropriate awareness and incentive schemes to push the use of greener energy.

Learn more: Renewable Energy Survey Template Descriptive Research vs Correlational Research

• Experimental research: In experimental research , an experiment is set up and a hypothesis is tested by creating a situation in which one of the variable is manipulated. This is also used to check cause and effect. It is tested to see what happens to the independent variable if the other one is removed or altered. The process for such a method is usually proposing a hypothesis, experimenting on it, analyzing the findings and reporting the findings to understand if it supports the theory or not.

For example: A particular product company is trying to find what is the reason for them to not be able to capture the market. So the organisation makes changes in each one of the processes like manufacturing, marketing, sales and operations. Through the experiment they understand that sales training directly impacts the market coverage for their product. If the person is trained well, then the product will have better coverage.

• Correlational research: Correlational research is used to find relation between two set of variables . Regression analysis is generally used to predict outcomes of such a method. It can be positive, negative or neutral correlation.

LEARN ABOUT: Level of Analysis

For example: Higher educated individuals will get higher paying jobs. This means higher education enables the individual to high paying job and less education will lead to lower paying jobs.

• Longitudinal study: Longitudinal study is used to understand the traits or behavior of a subject under observation after repeatedly testing the subject over a period of time. Data collected from such a method can be qualitative or quantitative in nature.

For example: A research to find out benefits of exercise. The target is asked to exercise everyday for a particular period of time and the results show higher endurance, stamina, and muscle growth. This supports the fact that exercise benefits an individual body.

• Cross sectional: Cross sectional study is an observational type of method, in which a set of audience is observed at a given point in time. In this type, the set of people are chosen in a fashion which depicts similarity in all the variables except the one which is being researched. This type does not enable the researcher to establish a cause and effect relationship as it is not observed for a continuous time period. It is majorly used by healthcare sector or the retail industry.

For example: A medical study to find the prevalence of under-nutrition disorders in kids of a given population. This will involve looking at a wide range of parameters like age, ethnicity, location, incomes  and social backgrounds. If a significant number of kids coming from poor families show under-nutrition disorders, the researcher can further investigate into it. Usually a cross sectional study is followed by a longitudinal study to find out the exact reason.

• Causal-Comparative research : This method is based on comparison. It is mainly used to find out cause-effect relationship between two variables or even multiple variables.

For example: A researcher measured the productivity of employees in a company which gave breaks to the employees during work and compared that to the employees of the company which did not give breaks at all.

LEARN ABOUT: Action Research

Some research questions need to be analysed qualitatively, as quantitative methods are not applicable there. In many cases, in-depth information is needed or a researcher may need to observe a target audience behavior, hence the results needed are in a descriptive analysis form. Qualitative research results will be descriptive rather than predictive. It enables the researcher to build or support theories for future potential quantitative research. In such a situation qualitative research methods are used to derive a conclusion to support the theory or hypothesis being studied.

LEARN ABOUT: Qualitative Interview

• Case study: Case study method is used to find more information through carefully analyzing existing cases. It is very often used for business research or to gather empirical evidence for investigation purpose. It is a method to investigate a problem within its real life context through existing cases. The researcher has to carefully analyse making sure the parameter and variables in the existing case are the same as to the case that is being investigated. Using the findings from the case study, conclusions can be drawn regarding the topic that is being studied.

For example: A report mentioning the solution provided by a company to its client. The challenges they faced during initiation and deployment, the findings of the case and solutions they offered for the problems. Such case studies are used by most companies as it forms an empirical evidence for the company to promote in order to get more business.

• Observational method:   Observational method is a process to observe and gather data from its target. Since it is a qualitative method it is time consuming and very personal. It can be said that observational research method is a part of ethnographic research which is also used to gather empirical evidence. This is usually a qualitative form of research, however in some cases it can be quantitative as well depending on what is being studied.

For example: setting up a research to observe a particular animal in the rain-forests of amazon. Such a research usually take a lot of time as observation has to be done for a set amount of time to study patterns or behavior of the subject. Another example used widely nowadays is to observe people shopping in a mall to figure out buying behavior of consumers.

• One-on-one interview: Such a method is purely qualitative and one of the most widely used. The reason being it enables a researcher get precise meaningful data if the right questions are asked. It is a conversational method where in-depth data can be gathered depending on where the conversation leads.

For example: A one-on-one interview with the finance minister to gather data on financial policies of the country and its implications on the public.

• Focus groups: Focus groups are used when a researcher wants to find answers to why, what and how questions. A small group is generally chosen for such a method and it is not necessary to interact with the group in person. A moderator is generally needed in case the group is being addressed in person. This is widely used by product companies to collect data about their brands and the product.

For example: A mobile phone manufacturer wanting to have a feedback on the dimensions of one of their models which is yet to be launched. Such studies help the company meet the demand of the customer and position their model appropriately in the market.

• Text analysis: Text analysis method is a little new compared to the other types. Such a method is used to analyse social life by going through images or words used by the individual. In today’s world, with social media playing a major part of everyone’s life, such a method enables the research to follow the pattern that relates to his study.

For example: A lot of companies ask for feedback from the customer in detail mentioning how satisfied are they with their customer support team. Such data enables the researcher to take appropriate decisions to make their support team better.

Sometimes a combination of the methods is also needed for some questions that cannot be answered using only one type of method especially when a researcher needs to gain a complete understanding of complex subject matter.

We recently published a blog that talks about examples of qualitative data in education ; why don’t you check it out for more ideas?

Since empirical research is based on observation and capturing experiences, it is important to plan the steps to conduct the experiment and how to analyse it. This will enable the researcher to resolve problems or obstacles which can occur during the experiment.

Step #1: Define the purpose of the research

This is the step where the researcher has to answer questions like what exactly do I want to find out? What is the problem statement? Are there any issues in terms of the availability of knowledge, data, time or resources. Will this research be more beneficial than what it will cost.

Before going ahead, a researcher has to clearly define his purpose for the research and set up a plan to carry out further tasks.

Step #2 : Supporting theories and relevant literature

The researcher needs to find out if there are theories which can be linked to his research problem . He has to figure out if any theory can help him support his findings. All kind of relevant literature will help the researcher to find if there are others who have researched this before, or what are the problems faced during this research. The researcher will also have to set up assumptions and also find out if there is any history regarding his research problem

Step #3: Creation of Hypothesis and measurement

Before beginning the actual research he needs to provide himself a working hypothesis or guess what will be the probable result. Researcher has to set up variables, decide the environment for the research and find out how can he relate between the variables.

Researcher will also need to define the units of measurements, tolerable degree for errors, and find out if the measurement chosen will be acceptable by others.

Step #4: Methodology, research design and data collection

In this step, the researcher has to define a strategy for conducting his research. He has to set up experiments to collect data which will enable him to propose the hypothesis. The researcher will decide whether he will need experimental or non experimental method for conducting the research. The type of research design will vary depending on the field in which the research is being conducted. Last but not the least, the researcher will have to find out parameters that will affect the validity of the research design. Data collection will need to be done by choosing appropriate samples depending on the research question. To carry out the research, he can use one of the many sampling techniques. Once data collection is complete, researcher will have empirical data which needs to be analysed.

LEARN ABOUT: Best Data Collection Tools

Step #5: Data Analysis and result

Data analysis can be done in two ways, qualitatively and quantitatively. Researcher will need to find out what qualitative method or quantitative method will be needed or will he need a combination of both. Depending on the unit of analysis of his data, he will know if his hypothesis is supported or rejected. Analyzing this data is the most important part to support his hypothesis.

Step #6: Conclusion

A report will need to be made with the findings of the research. The researcher can give the theories and literature that support his research. He can make suggestions or recommendations for further research on his topic.

A.D. de Groot, a famous dutch psychologist and a chess expert conducted some of the most notable experiments using chess in the 1940’s. During his study, he came up with a cycle which is consistent and now widely used to conduct empirical research. It consists of 5 phases with each phase being as important as the next one. The empirical cycle captures the process of coming up with hypothesis about how certain subjects work or behave and then testing these hypothesis against empirical data in a systematic and rigorous approach. It can be said that it characterizes the deductive approach to science. Following is the empirical cycle.

• Observation: At this phase an idea is sparked for proposing a hypothesis. During this phase empirical data is gathered using observation. For example: a particular species of flower bloom in a different color only during a specific season.
• Induction: Inductive reasoning is then carried out to form a general conclusion from the data gathered through observation. For example: As stated above it is observed that the species of flower blooms in a different color during a specific season. A researcher may ask a question “does the temperature in the season cause the color change in the flower?” He can assume that is the case, however it is a mere conjecture and hence an experiment needs to be set up to support this hypothesis. So he tags a few set of flowers kept at a different temperature and observes if they still change the color?
• Deduction: This phase helps the researcher to deduce a conclusion out of his experiment. This has to be based on logic and rationality to come up with specific unbiased results.For example: In the experiment, if the tagged flowers in a different temperature environment do not change the color then it can be concluded that temperature plays a role in changing the color of the bloom.
• Testing: This phase involves the researcher to return to empirical methods to put his hypothesis to the test. The researcher now needs to make sense of his data and hence needs to use statistical analysis plans to determine the temperature and bloom color relationship. If the researcher finds out that most flowers bloom a different color when exposed to the certain temperature and the others do not when the temperature is different, he has found support to his hypothesis. Please note this not proof but just a support to his hypothesis.
• Evaluation: This phase is generally forgotten by most but is an important one to keep gaining knowledge. During this phase the researcher puts forth the data he has collected, the support argument and his conclusion. The researcher also states the limitations for the experiment and his hypothesis and suggests tips for others to pick it up and continue a more in-depth research for others in the future. LEARN MORE: Population vs Sample

LEARN MORE: Population vs Sample

There is a reason why empirical research is one of the most widely used method. There are a few advantages associated with it. Following are a few of them.

• It is used to authenticate traditional research through various experiments and observations.
• This research methodology makes the research being conducted more competent and authentic.
• It enables a researcher understand the dynamic changes that can happen and change his strategy accordingly.
• The level of control in such a research is high so the researcher can control multiple variables.
• It plays a vital role in increasing internal validity .

Even though empirical research makes the research more competent and authentic, it does have a few disadvantages. Following are a few of them.

• Such a research needs patience as it can be very time consuming. The researcher has to collect data from multiple sources and the parameters involved are quite a few, which will lead to a time consuming research.
• Most of the time, a researcher will need to conduct research at different locations or in different environments, this can lead to an expensive affair.
• There are a few rules in which experiments can be performed and hence permissions are needed. Many a times, it is very difficult to get certain permissions to carry out different methods of this research.
• Collection of data can be a problem sometimes, as it has to be collected from a variety of sources through different methods.

LEARN ABOUT:  Social Communication Questionnaire

Empirical research is important in today’s world because most people believe in something only that they can see, hear or experience. It is used to validate multiple hypothesis and increase human knowledge and continue doing it to keep advancing in various fields.

For example: Pharmaceutical companies use empirical research to try out a specific drug on controlled groups or random groups to study the effect and cause. This way, they prove certain theories they had proposed for the specific drug. Such research is very important as sometimes it can lead to finding a cure for a disease that has existed for many years. It is useful in science and many other fields like history, social sciences, business, etc.

LEARN ABOUT: 12 Best Tools for Researchers

With the advancement in today’s world, empirical research has become critical and a norm in many fields to support their hypothesis and gain more knowledge. The methods mentioned above are very useful for carrying out such research. However, a number of new methods will keep coming up as the nature of new investigative questions keeps getting unique or changing.

Create a single source of real data with a built-for-insights platform. Store past data, add nuggets of insights, and import research data from various sources into a CRM for insights. Build on ever-growing research with a real-time dashboard in a unified research management platform to turn insights into knowledge.

LEARN MORE         FREE TRIAL

MORE LIKE THIS

Raked Weighting: A Key Tool for Accurate Survey Results

May 31, 2024

Top 8 Data Trends to Understand the Future of Data

May 30, 2024

Top 12 Interactive Presentation Software to Engage Your User

May 29, 2024

Trend Report: Guide for Market Dynamics & Strategic Analysis

Other categories.

• Academic Research
• Artificial Intelligence
• Assessments
• Brand Awareness
• Case Studies
• Communities
• Consumer Insights
• Customer effort score
• Customer Engagement
• Customer Experience
• Customer Loyalty
• Customer Research
• Customer Satisfaction
• Employee Benefits
• Employee Engagement
• Employee Retention
• Friday Five
• General Data Protection Regulation
• Insights Hub
• Life@QuestionPro
• Market Research
• Mobile diaries
• Mobile Surveys
• New Features
• Online Communities
• Question Types
• Questionnaire
• QuestionPro Products
• Release Notes
• Research Tools and Apps
• Revenue at Risk
• Survey Templates
• Training Tips
• Uncategorized
• Video Learning Series
• What’s Coming Up
• Workforce Intelligence

Yearly paid plans are up to 65% off for the spring sale. Limited time only! 🌸

• Form Builder
• Survey Maker
• AI Form Generator
• AI Survey Tool
• AI Quiz Maker
• Store Builder
• WordPress Plugin

HubSpot CRM

Google Sheets

Google Analytics

Microsoft Excel

• Popular Forms
• Job Application Form Template
• Rental Application Form Template
• Hotel Accommodation Form Template
• Online Registration Form Template
• Employment Application Form Template
• Application Forms
• Booking Forms
• Consent Forms
• Contact Forms
• Donation Forms
• Customer Satisfaction Surveys
• Employee Satisfaction Surveys
• Evaluation Surveys
• Feedback Surveys
• Market Research Surveys
• Personality Quiz Template
• Geography Quiz Template
• Math Quiz Template
• Science Quiz Template
• Vocabulary Quiz Template

Try without registration Quick Start

Read engaging stories, how-to guides, learn about forms.app features.

Inspirational ready-to-use templates for getting started fast and powerful.

Spot-on guides on how to use forms.app and make the most out of it.

See the technical measures we take and learn how we keep your data safe and secure.

• Integrations
• Help Center
• Sign In Sign Up Free
• What is conceptual research: Definition & examples

Defne Çobanoğlu

How did Newton figure out the gravity after seeing an apple fall from a tree? What kind of research did Nicolaus Copernicus conduct to figure out that the planets revolve around the sun and not vice versa? It is certain that they did not conduct practical experiments to figure this stuff out.

The type of research these two scientists do is called conceptual research. They basically observed their surroundings to conceptualize and develop theories about gravitation, motion, and astronomy. That is what some scientists and philosophers do to wrap their heads around existing concepts and new ideas. Now, let us see what exactly conceptual research is and other details.

• What is conceptual research?

Conceptual research is a type of research that does not involve conducting any practical experiments . It is based on observing and analyzing already existing concepts and theories. The researcher can observe their surroundings and develop brand-new theories, or they can build on existing ones.

Conceptual research is widely used in the study of philosophy to develop new ideas. And this type of research is also used to answer business questions and organize ideas, or interpret existing theories differently.

Conceptual research definition

• Conceptual research frameworks

Even if the researcher is not conducting any experiments of their own, they should still work in a systematic manner, to be precise. And a conceptual research framework is built around existing literature and appropriate research studies that can explain the phenomenon. Here is a step-by-step guide to creating a conceptual research framework:

The steps for a conceptual research framework

1 - Define a topic for research:

The first step in creating your research framework is to choose the topic you will be working on. Most researchers define a topic in their area of expertise and go along with it.

2 - Collect relevant literature:

After deciding on the subject, the next and most important step is collecting relevant literature. As this type of research heavily relies on existing literature, it is important to find reliable sources. Successfully collecting relevant information is key to successfully completing this step. The reliable sources one can use are:

• scientific journals
• research papers (published by well-known scientists)
• Public libraries
• Online databases
• Relevant books

3 - Identify specific variables:

In this step, identify specific variables that may affect your research. These variables may give your study a new scope and a new area to cover during your research. For example, let us say you want to conduct research about the occurrence of depression in teenage boys aged 14 to 19. Here, the two variables are teenage boys and depression.

During your research, you figure that substance abuse among teenage boys has a big effect on their mental wellbeings. Therefore, you add substance abuse as a relevant variable and be mindful of that when you are continuing your research. 

4 - Create the framework:

The final step is creating the framework after going through all the relevant data available. The research question in hand becomes the research framework

• Conceptual research examples

When a researcher decides on the subject they want to explore, the next thing they should decide is what kind of methods they want to do. They can choose the experiments and surveys, but sometimes these methods are not possible for different reasons. And when they can not do practical experimenting, they can use existing literature and observation. Here are two examples where conceptual research can be used: 

• Example 1 of conceptual research:

A researcher wants to explore the key factors that influence consumer behavior in the online shopping environment. That is their research question. Once the researcher decides on the subject, they can begin by reviewing the existing literature on consumer behavior and examining different theories and models of consumer behavior. 

Then, they can identify common themes or factors that have emerged. By understanding this phenomenon, the researcher can develop a conceptual framework.

• Example 2 of conceptual research:

A group of researchers wants to see if there is any correlation between chemically dyeing your hair and the risk of cancer in women. They can start collecting data on women that had cancer and usage of hair dye. They can collect research papers on this particular subject. And they can create a conceptual framework with the information they collected and analyzed.

• Advantages and disadvantages of conceptual research

There are multiple research types for researchers to get to the goal they want, and they all offer different advantages. It is up to the researchers to decide on the most suitable one for their study and go along with that. The conceptual study also has its positive and negative aspects one should have in mind. Now, let us go through the list of conceptual research advantages and disadvantages.

Advantages vs. disadvantages of conceptual research

Advantages of conceptual research:

• Requires fewer sources: This type of research does not involve any type of experiment. Therefore it saves money, energy, and manpower. It only involves theorizing and searching through existing literature. 
• Generates new ideas:  Conceptual research can help generate new ideas and hypotheses. Researchers can use data collection to add on top of abstract ideas or concepts
• Helps to identify patterns: Conceptual research can help identify patterns in complex concepts and help develop a conceptual analysis. This can lead to a better understanding of how different factors are related to each other.

Disadvantages of conceptual research:

• Questionable reliability and validity: Conclusions drawn from literature reviews on conceptual research topics are less fact-based and may not essentially be considered dependable. Because they are not backed up by practical experimentation, they may have less credibility.
• May be prone to subjectivity: Because it relies on abstract concepts, conceptual research may be influenced by personal biases and perspectives. Researchers should be mindful of this effect and act on it accordingly.
• Can be time-consuming:  As conceptual research involves extensive research and analyses of relevant literature, it may take a longer time to finalize the study on hand. This can be challenging for researchers who are working within time constraints.
• Conceptual research vs. empirical research

Conceptual research is about creating an idea after looking at existing data or adding on a theory after going through available literature. And the empirical research includes something different than the prior one. Empirical research involves research based on observation, experiments, and verifiable evidence .

The main difference between the two is the fact that empirical research involves doing experiments to develop a conceptual framework. Empirical research studies are observable and measurable as they are verifiable by observations or experience. In order to see if a study is empirical, you can ask yourself this question: Can I create this study and test these results myself?

The difference between conceptual research and empirical research

• Wrapping it up

Once you encounter a problem you want to solve but you are unable to do experiments, you can go with conceptual research. Instead of conducting experiments, you should find appropriate existing literature and analyze them thoroughly. Just then, you can create a conceptual framework.

And you can always use the help of a good online tool for your needs when doing research. The best tool for all your needs, from forms to surveys to questionnaires, is forms.app. forms.app is an online survey maker that offers more than 1000 ready-to-use templates and can be the help you need!

Defne is a content writer at forms.app. She is also a translator specializing in literary translation. Defne loves reading, writing, and translating professionally and as a hobby. Her expertise lies in survey research, research methodologies, content writing, and translation.

• Form Features
• Data Collection

Table of Contents

Related posts.

35+ Dark mode statistics you need to know (2024)

Fatih Özkan

Formstack vs. Typeform: Which one should you choose?

Can I do my own prenuptial agreement? (free samples)

Concepts and Reasoning: a Conceptual Review and Analysis of Logical Issues in Empirical Social Science Research

• Published: 08 July 2023
• Volume 58 , pages 502–530, ( 2024 )

Cite this article

• Qingjiang Yao   ORCID: orcid.org/0000-0002-0550-4211 1  

410 Accesses

Explore all metrics

A substantial number of social science studies have shown a lack of conceptual clarity, inadequate understanding of the nature of the empirical research approaches, and undue preference for deduction, which have caused much confusion, created paradigmatic incommensurability, and impeded scientific advancement. This study, through conceptual review and analysis of canonical discussions of concepts and the reasoning approaches of deduction and induction and their applications in social science theorization by philosophers and social scientists, is purported to unveil the logical nature of empirical research and examine the legitimacy of the preference of deduction among social scientists. The findings note that conceptual clarity as the foundation of social science research, exchange, and replication can be achieved through interdisciplinary stress of conceptual analyses to establish universal measurements and that the primacy of deduction in social sciences needs to concede to or be balanced with induction for new knowledge, more discoveries, and scientific advancement. The study recommends that institutions and researchers of social sciences invest more in conceptual analysis and inductive research through collaboration and separate efforts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Social sciences, social reality and the false division between theory and method: some implications for social research

Theory in Social Research

Reflections on Methodological Issues

Data availability.

This conceptual review paper involves no empirical data.

American Educational Research Association, American Psychological Association, National Council on Measurement in Education. (2014). Standards for educational and psychological testing . American Educational Research Association. https://www.apa.org/science/programs/testing/standards

Allen, M. S., Iliescu, D., & Greiff, S. (2022). Single item measures in psychological science: A call to action. European Journal of Psychological Assessment, 38 (1), 1–5. https://doi.org/10.1027/1015-5759/a000699

Article   Google Scholar  

Aristotle. (1984). The organon. In J. Barnes (Ed.), The complete works of Aristotle: The revised Oxford translation (v. 1) . Princeton University Press.

Aven, T. (2018). Reflections on the use of conceptual research in risk analysis. Risk Analysis, 38 (11), 2415–2423. https://doi.org/10.1111/risa.13139

Article   PubMed   Google Scholar  

Babbie, E. (2021). The practice of social research (15th ed.). Cengage.

Bacon, F. (2000). In L. Jardine, & M. Silverthorne (Eds.), The new organon . Cambridge University Press.

Bal, M. (2009). Working with concepts. European Journal of English Studies, 13 (1), 13–23. https://doi.org/10.1080/13825570802708121

Baldwin, D. (1980). Interdependence and power: A conceptual analysis. International Organization, 34 (4), 471–506. https://doi.org/10.1017/S0020818300018828

Baskaran, S., Ng, C. H., Mahadi, N., & Ayob, S. A. (2017). Youth and social media comportment: A conceptual perspective. International Journal of Academic Research in Business and Social Sciences, 7 (11), 1260–1277. https://doi.org/10.6007/IJARBSS/v7-i11/3563

Bergkvist, L. (2015). Appropriate use of single-item measures is here to stay. Marketing Letters, 26 , 245–255. https://doi.org/10.1007/s11002-014-9325-y

Bird, F. (2020). A defense of objectivity in the social sciences, rightly understood. Sustainability: Science Practice and Policy, 16 (1), 83–98. https://doi.org/10.1080/15487733.2020.1785679

Birks, M., & Mills, J. (2015). Grounded theory: A practical guide (2nd ed.). Sage Publications.

Blumer, H. (1956). Sociological analysis and the “variable. American Sociological Review, 21 (6), 683–690. https://doi.org/10.2307/2088418

Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quinonez, H., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6 , 149. https://doi.org/10.3389/fpubh.2018.00149

Article   PubMed   PubMed Central   Google Scholar  

Boole, G. (1952/2012). Studies in logic and probability . Dover Publications.

Boyd, N. M., & Bogen, J. (2021). Theory and observation in science. In N. Zalta & U. Nodelman (Eds.), Stanford Encyclopedia of Philosophy (Winter 2021 Edition) .   https://plato.stanford.edu/archives/win2021/entries/science-theory-observation/ . Accessed 1 Apr 2023.

Brandt, P., & Timmermans, S. (2021). Abductive logic of inquiry for quantitative research in the digital age. Sociological Science, 8 , 191–210. https://doi.org/10.15195/v8.a10

Brewer, W. F., & Chinn, C. A. (1994). The theory-ladenness of data: An experimental demonstration. In A. Ram & K. Eiselt (Eds.), Proceedings of the sixteenth annual conference of the cognitive science society (p.5). Routledge. https://doi.org/10.4324/9781315789354

Bringmann, L. F., Elmer, T., & Eronen, M. I. (2022). Back to basics: The importance of conceptual clarification in psychological science. Current Direction in Psychological Science, 31 (4), 340–346. https://doi.org/10.1177/09637214221096485

Carnap, R. (1956). The methodological character of theoretical concepts. In H. Feigl, & M. Scriven (Eds.), Foundations of science and the concepts of psychology and psychoanalysis (pp. 38–76). University of Minnesota Press.

Carnap, R. (1963). Replies and systematic expositions. In P. A. Shilpp (Ed.), The philosophy of Rudolf Carnap (pp. 859–1013). Open Court.

Chaffee, S. (1991). Explication . Sage Publications.

Charmaz, K., & Thornberg, R. (2021). The pursuit of quality in grounded theory. Qualitative Research in Psychology, 18 (3), 305–327. https://doi.org/10.1080/14780887.2020.1780357

Clark, L. A., & Watson, D. (2019). Constructing validity: New developments in creating objective measuring instruments. Psychological Assessment, 31 (12), 1412–1427. https://doi.org/10.1037/pas0000626

Clark, T., Foster, L., Sloan, L., & Bryman, A. (2021). Bryman’s social research methods (6th ed.). Oxford University Press.

Cohen, I. B. (1994). A note on “social science” and on “natural science.” In I. B. Cohen (Ed.), The natural sciences and the social sciences (pp. xxv-xxxvi). Kluwer Academic Publishers.

Copi, I., Cohen, C., & McMahon, K. (2010). Introduction to logic (14th ed.). Prentice-Hall.

Darwin, C. (1897). In F. Darwin (Eds.), The life and letters of Charles Darwin . D. Appleton and Company.

Dewey, J. (1910/1997). How we think . Dover Publications.

Dreher, A. (2000). Foundations for conceptual research in psychoanalysis . Karnac (Books) Ltd.

Dreher, A. (2003). What does conceptual research have to offer? In M. Leuzinger-Bohleber, A. Dreher, & J. Ganestri (Eds.), Pluralism and unity? Methods of research in psychoanalysis (pp. 109–124). IPA.

Dubin, R. (1978). Theory building (2nd ed.). Free Press.

Dummett, M. (1991). The logical basis of metaphysics . Harvard University Press.

Dunwoody, S. (2005). Explicate, please. MAPOR News , fall issue, 4. http://www.mapor.org/newsletters/Fall2005.pdf

Eagly, A., & Chaiken, S. (1993). The psychology of attitudes . Harcourt Brace Jovanovich College Publishers.

Fetzer, J. (2022). Carl Hempel. In N. Zalta & U. Nodelman (Eds.), Stanford encyclopedia of philosophy . Retrieved April 1, 2023, from https://plato.stanford.edu/entries/hempel/

Fisher, R. (1955). Statistical methods and scientific induction. Journal of the Royal Statistical Society: Series B(Methodological), 17 (1), 69–78. https://doi.org/10.1111/j.2517-6161.1955.tb00180.x

Fodor, J. (1998). Concepts: Where cognitive science went wrong . Oxford University Press.

Fodor, J. (2004). Having concepts: A brief refutation of the 20th century. Mind and Language, 19 , 29–47. https://doi.org/10.1111/j.1468-0017.2004.00245.x

Foxall, G. R. (1986). The role of radical behaviorism in the explanation of consumer choice. In R. J. Lutz (Ed.), Advances in consumer research (13 vol., pp. 187–191). Association for Consumer Research.

Francis, G. (2012). Publication bias and the failure of replication in experimental psychology. Psychonomic Bulletin and Review, 19 , 975–991. https://doi.org/10.3758/s13423-012-0322-y

Gardner, D. G., Cummings, L. L., Dunham, R. B., & Pierce, J. L. (1998). Single-item versus multiple-item measurement scales: An empirical comparison. Educational and Psychological Measurement, 58 (6), 898–915. https://doi.org/10.1177/0013164498058006003

Gatzka, T. (2021). Aspects of openness as predictors of academic achievement. Personality and Individual Differences, 170 ,. https://doi.org/10.1016/j.paid.2020.110422

Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research . Aldine de Gruyter.

Gunnell, J. (1975). Philosophy, science, and political inquiry . General Learning Press.

Haslam, N. (2016). Concept creep: Psychology’s expanding concepts of harm and pathology. Psychological Inquiry, 27 (1), 1–17. https://doi.org/10.1080/1047840X.2016.1082418

Haslam, N., Dakin, B. C., Fabiano, F., McGrath, M. J., Rhee, J., Vylomova, E., Weaving, M., & Wheeler, M. A. (2020). Harm inflation: Making sense of concept creep. European Review of Social Psychology, 31 (1), 254–286. https://doi.org/10.1080/10463283.2020.1796080

Haslam, N., Tse, J. S. Y., & Deyne, S. D. (2021). Concept creep and psychiatrization. Frontiers in Sociology, 6 , 806147. https://doi.org/10.3389/fsoc.2021.806147

Hayes, A. F., & Coutts, J. J. (2020). Use Omega rather than Cronbach’s alpha for estimating reliability but…. Communication Methods and Measures, 14 (1), 1–24. https://doi.org/10.1080/19312458.2020.1718629

Hempel, C. (1965). Aspects of scientific explanation and other essays in the philosophy of science . Free Press.

Homans, G. (1951). The human group . Routledge.

Hume, D. (1748/1999). An enquiry concerning human understanding . Oxford University Press.

Hurley, P., & Watson, L. (2018). A concise introduction to logic (13th ed.). Cengage Learning.

Husserl, E. (1900/1973). Logical investigations (trans. Findlay J.N.). Routledge & Kegan Paul.

Jackson, F. (1998). From metaphysics to ethics: A defense of conceptual analysis . Oxford University Press.

Kant, I. (1781/1998). The critique of pure reason (Trans. P Guyer, & A. W. Wood). Cambridge University Press.

Kerlinger, F. N, & Lee, H. B. (1999). Foundations of behavioral research (4th ed.). Wadsworth Publishing.

King, G., Keohane, R. O., & Verba, S. (2021). Designing social inquiry: Scientific inference in qualitative research (new ed.). Princeton University Press.

Kistruck, G. M., & Shantz, A. S. (2022). Research on grand challenges: Adopting an abductive experimentation methodology. Organization Studies, 43 (9), 1479–1505. https://doi.org/10.1177/01708406211044886

Kuhn, T. (1996). The structure of scientific revolutions . The University of Chicago Press.

Leibniz, G. W. (1989). Dissertation on the art of combinations. In L. E. Loemker (Ed.) Philosophical papers and letters. The new synthese historical library (Texts and studies in the history of philosophy) (vol 2). Springer. https://doi.org/10.1007/978-94-010-1426-7_2

Lakatos, I. (1978). The methodology of scientific research programmes. In J. Worrall, & G. Currie (Eds.), Philosophical papers, V 1 . Cambridge University Press.

Locke, E. A. (2007). The case for inductive theory building. Journal of Management, 33 (6), 867–890. https://doi.org/10.1177/0149206307307636

Locke, J. (1689/1997). An essay concerning human understanding, book III . Penguin Press.

Locke, E. A., & Latham, G. P. (2020). Building a theory by induction: The example of goal setting theory. Organizational Psychology Review, 10 (3–4), 223–239. https://doi.org/10.1177/2041386620921931

Margolis, E., & Laurence, S. (2022). Concepts. In E. N. Zalta & U. Nodelman (Eds.),  The Stanford encyclopedia of philosophy (Fall 2022 Edition). https://plato.stanford.edu/archives/fall2022/entries/concepts/ . Accessed 1 Apr 2023.

Martinez, R. A. M., Andrabi, N., Goodwin, A. N., Wilbur, R. E., Smith, N. R., & Zivich, P. N. (2023). Conceptualization, operationalization, and utilization of race and ethnicity in major epidemiology journals, 1995–2018: A systematic review. American Journal of Epidemiology, 192 (3), 483–496. https://doi.org/10.1093/aje/kwac146

McCombs, M., & Donald, S. (1972). The agenda-setting function of mass media. The Public Opinion Quarterly, 36 (2), 176–187. https://doi.org/10.1086/267990

McLeod, J., & Chaffee, S. (2017). The construction of social reality. In J. T. Tedeschi (Ed.), The social influence processes (pp50-99) . Routledge.

Mill, J. S. (1843/2011). A system of logic, ratiocinative and inductive: Being a connected view of the principles of evidence, and the methods of scientific investigation (1V vol). Cambridge University Press. https://doi.org/10.1017/CBO9781139149839.017

Mokgohloa, K., Kanakana-Katumba, G., Maladzhi, R., & Xaba, S. (2021). A grounded theory approach to digital transformation in the postal sector in southern Africa. Advances in Science Technology and Engineering Systems Journal, 6 (2), 313–323. https://doi.org/10.25046/aj060236

Mollaret, P. (2009). Using common psychological terms to describe other people: From lexical hypothesis to polysemous conception. Theory and Psychology, 19 (3), 315–334. https://doi.org/10.1177/0959354309104157

Mukumbang, F. C., Kabongo, E. M., & Eastwood, J. G. (2021). Examining the application of retroductive theorizing in realist-informed studies. International Journal of Qualitative Methods, 20 , 1–14. https://doi.org/10.1177/16094069211053516

Nuhoglu, H. (2020). The effect of deduction and induction methods used in modeling current environmental issues with system dynamics approach in science education. Participatory Education Research (PER), 7 (1), 111–126. https://doi.org/10.17275/per.20.7.7.1

Nunnally, J. (1987). Introduction to psychological measurement . McGraw-Hill Book Company.

O’Shaughnessy, J. (1992). Explaining buyer behavior: Central concepts and philosophy of science issues . Oxford University Press.

Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349 , 1–8. https://doi.org/10.1126/science.aac4716

Pan, Z., & Kosicki, G. (1993). Framing analysis: An approach to news discourse. Political Communication, 10 (1), 55–75. https://doi.org/10.1080/10584609.1993.9962963

Peacocke, P. (2009). Frege’s hierarchy: A puzzle. In J. Almog, & P. Leonardi (Eds.), The philosophy of David Kaplan (pp. 159–186). Oxford University Press.

Peirce, C. S. (1898/1992). Reason and the logic of things: The Cambridge conferences lectures of 1898 (ed. Ketner, K.L). Harvard University Press.

Petronio, S., & Child, J. T. (2020). Conceptualization and operationalization: Utility of communication privacy management theory. Current Opinion in Psychology, 31 , 76–82. https://doi.org/10.1016/j.copsyc.2019.08.009

Philipsen, K. (2017). Theory building: Using abductive search strategies. In P. Freytag, & L. Young (Eds.), Collaborative research design (pp. 45–71). Springer. https://doi.org/10.1007/978-981-10-5008-4_3

Popper, K. (1959). The logic of scientific discovery . Hutchinson.

Popper, K. (1963). Conjectures and refutations: The growth of scientific knowledge . Routledge & Kegan Paul.

Popper, K. (1982). Unended quest: An intellectual autobiography . Open Court.

Potter, J. (2012). Media effects . Sage Publications.

Putnam, H. (1962). The analytic and the synthetic. In H. Feigl, & G. Maxwell (Eds.), Minnesota studies in the philosophy of science , V III (pp. 358–97). University of Minnesota Press.

Quine, W. (1974). Roots of reference . Open Court.

Rose, J., & Johnson, C. W. (2020). Contextualizing reliability and validity in qualitative research: Toward more rigorous and trustworthy qualitative social science in leisure research. Journal of Leisure Research, 51 (4), 432–451. https://doi.org/10.1080/00222216.2020.1722042

Rosenberg-Jansen, S. (2022). The emerging world of humanitarian energy: A conceptual research review. Energy Research and Social Science, 92 ,. https://doi.org/10.1016/j.erss.2022.102779

Russell, B. (1946). A history of western philosophy . George Allen and Unwin Ltd.

Sætre, A. S., & Van de Ven, A. (2021). Generating theory by abduction. Academy of Management Review, 46 (4), 684–701. https://doi.org/10.5465/amr.2019.0233

Salmon, W. (1971). Statistical explanation and statistical relevance . University of Pittsburgh Press.

Schimmack, U. (2020). A meta-psychological perspective on the decade of replication failures in social psychology. Canadian Psychology/Psychologie Canadienne, 61 (4), 364–376. https://doi.org/10.1037/cap0000246

Schlagwein, D. (2021). Natural sciences, philosophy of science and the orientation of the social sciences. Journal of Information Technology, 36 (1), 85–80. https://doi.org/10.1177/0268396220951203

Schrepp, M. (2020). On the usage of Cronbach’s alpha to measure reliability of UX scales. Journal of Usability Studies, 15 (4), 247–258.

Google Scholar  

Shrestha, Y. R., He, V. F., Puranam, P., & von Krogh, G. (2020). Algorithm supported induction for building theory: How can we use prediction models to theorize? Organization Science, 32 (3), 856–880. https://doi.org/10.1287/orsc.2020.1382

Stadler, M., Sailer, M., & Fischer, F. (2021). Knowledge as a formative construct: A good alpha is not always better. New Ideas in Psychology, 60 ,. https://doi.org/10.1016/j.newideapsych.2020.100832

Stich, S., & Weinberg, J. (2001). Jackson’s empirical assumptions. Philosophy and Phenomenological Research, 62 (3), 637–643. https://doi.org/10.1111/j.1933-1592.2001.tb00081.x

Surma-aho, A., & Otto, K. H. (2021). Conceptualization and operationalization of empathy in design research. Design Studies, 78 , 101075. https://doi.org/10.1016/j.destud.2021.101075

Svejvid, P. (2021). A meta-theoretical framework for theory building in project management. International Journal of Project Management, 39 , 849–9722. https://doi.org/10.1016/j.ijproman.2021.09.006

Szatek, P. K. (2020). The Duhem-Quine thesis reconsidered. Studies in Logic, Grammar, and Rhetoric, 62 (75), 73–93. https://doi.org/10.2478/slgr-2020-0014

Tarski, A. (1946/1996). Introduction to logic: And to the methodology of deductive sciences . Dover Publications.

Toulmin, S. (1953). The philosophy of science: An introduction . Hutchinson.

Thomas, C. G. (2021). Research methodology and scientific writing (2nd ed.). Springer Nature. https://doi.org/10.1007/978-3-030-64865-7

Tie, Y. T., Birks, M., & Francis, K. (2019). Grounded theory research: A design framework for novice researchers. Sage Open Medicine, 7 , 1–8. https://doi.org/10.1177/2050312118822927

Veen, M. (2021). Creative leaps in theory: The might of abduction. Advances in Health Sciences Education, 26 , 1173–1183. https://doi.org/10.1007/s10459-021-10057-8

Verster, J. C., Sandalova, E., Garssen, J., & Bruce, G. (2021). The use of single-item ratings versus traditional multiple-item questionnaires to assess mood and health. European Journal of Investigation in Health Psychology and Education, 11 , 183–198. https://doi.org/10.3390/ejihpe11010015

Whitehead, A. N., & Russell, B. (1956). Principia Mathematica to *56 . Cambridge University Press.

Wittgenstein, L. (1922/2007). Tractatus Logico-Philosohicus . Cosimo, Inc.

Woiceshyn, J., & Daellenbach, U. (2018). Evaluating inductive versus deductive research in management studies: Implications for authors, editors, and reviewers. Qualitative Research in Organizations and Management: An International Journal, 13 (2), 183–195. https://doi.org/10.1108/QROM-06-2017-1538

Wu, X., Levis, B., Sun, Y., Krishnan, A., He, C., et al. (2020). Probability of major depression diagnostic classification based on the SCID, CIDI and MINI diagnostic interviews controlling for hospital anxiety and depression scale-depression subscale score: An individual participant data meta-analysis of 73 primary studies. Journal of Psychosomatic Research, 129 , 109892. https://doi.org/10.1016/j.jpsychores.2019.109892

Xin, S., Tribe, J., & Chambers, D. (2013). Conceptual research in tourism. Annals of Tourism Research, 41 , 66–88. https://doi.org/10.1016/j.annals.2012.12.003

Yao, Q. J. (2023a). Conceptual analysis. In J. Mattingly (Ed.), The Sage encyclopedia of theory in science, technology, engineering, and mathematics . Sage Reference. https://doi.org/10.4135/9781071872383

Yao, Q. J. (2023b). Deduction. In J. Mattingly (Ed.), The Sage encyclopedia of theory in science, technology, engineering, and mathematics . Sage Reference. https://doi.org/10.4135/9781071872383

Yao, Q. J. (2023c). Induction. In J. Mattingly (Ed.), The Sage encyclopedia of theory in science, technology, engineering, and mathematics . Sage Reference. https://doi.org/10.4135/9781071872383

Yao, Q. J., Liu, Z., & Stephens, L. S. (2020). Exploring the dynamics in the environmental discourse: The longitudinal interaction among public opinion, presidential opinion, media coverage, policymaking in 3 decades and an integrated model of media effects. Environment Systems and Decision, 40 (1), 14–28. https://doi.org/10.1007/s10669-019-09746-y

Young, C. (2008). The advertising research handbook (2nd ed.). Ad Essentials, LLC.

Download references

Acknowledgements

The author appreciates Dr. Steven H. Chaffee for the inspiration of his work on explication in conducting this study.

Author information

Authors and affiliations.

Department of Communication & Media, Lamar University, P.O. Box 10050, Beaumont, TX, 77710, USA

Qingjiang Yao

You can also search for this author in PubMed   Google Scholar

Contributions

This paper is solely authored by Qingjiang (Q. J.) Yao, who bears all responsibility related to the paper.

Corresponding author

Correspondence to Qingjiang Yao .

Ethics declarations

The author has no financial or non-financial interests that are directly or indirectly related to this work submitted.

Ethical Approval

This conceptual research study is conducted in accordance with relevant guidelines/regulations applicable and involves no human participants. *

Informed Consent

Competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Yao, Q. Concepts and Reasoning: a Conceptual Review and Analysis of Logical Issues in Empirical Social Science Research. Integr. psych. behav. 58 , 502–530 (2024). https://doi.org/10.1007/s12124-023-09792-x

Download citation

Accepted : 14 June 2023

Published : 08 July 2023

Issue Date : June 2024

DOI : https://doi.org/10.1007/s12124-023-09792-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Conceptual analysis
• Hypotheticodeductive model
• Falsification
• Social sciences
• Find a journal
• Publish with us
• Track your research