what is conceptual review in research

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What is a Conceptual Framework and How to Make It (with Examples)

A strong conceptual framework underpins good research. A conceptual framework in research is used to understand a research problem and guide the development and analysis of the research. It serves as a roadmap to conceptualize and structure the work by providing an outline that connects different ideas, concepts, and theories within the field of study. A conceptual framework pictorially or verbally depicts presumed relationships among the study variables.

The purpose of a conceptual framework is to serve as a scheme for organizing and categorizing knowledge and thereby help researchers in developing theories and hypotheses and conducting empirical studies.

In this post, we explain what is a conceptual framework, and provide expert advice on how to make a conceptual framework, along with conceptual framework examples.

Table of Contents

What is a Conceptual Framework in Research

Definition of a conceptual framework.

A conceptual framework includes key concepts, variables, relationships, and assumptions that guide the academic inquiry. It establishes the theoretical underpinnings and provides a lens through which researchers can analyze and interpret data. A conceptual framework draws upon existing theories, models, or established bodies of knowledge to provide a structure for understanding the research problem. It defines the scope of research, identifying relevant variables, establishing research questions, and guiding the selection of appropriate methodologies and data analysis techniques.

Conceptual frameworks can be written or visual. Other types of conceptual framework representations might be taxonomic (verbal description categorizing phenomena into classes without showing relationships between classes) or mathematical descriptions (expression of phenomena in the form of mathematical equations).

Figure 1: Definition of a conceptual framework explained diagrammatically

Conceptual Framework Origin

The term conceptual framework appears to have originated in philosophy and systems theory, being used for the first time in the 1930s by the philosopher Alfred North Whitehead. He bridged the theological, social, and physical sciences by providing a common conceptual framework. The use of the conceptual framework began early in accountancy and can be traced back to publications by William A. Paton and John B. Canning in the first quarter of the 20 th century. Thus, in the original framework, financial issues were addressed, such as useful features, basic elements, and variables needed to prepare financial statements. Nevertheless, a conceptual framework approach should be considered when starting your research journey in any field, from finance to social sciences to applied sciences.

Purpose and Importance of a Conceptual Framework in Research

The importance of a conceptual framework in research cannot be understated, irrespective of the field of study. It is important for the following reasons:

• It clarifies the context of the study.
• It justifies the study to the reader.
• It helps you check your own understanding of the problem and the need for the study.
• It illustrates the expected relationship between the variables and defines the objectives for the research.
• It helps further refine the study objectives and choose the methods appropriate to meet them.

What to Include in a Conceptual Framework

Essential elements that a conceptual framework should include are as follows:

• Overarching research question(s)
• Study parameters
• Study variables
• Potential relationships between those variables.

The sources for these elements of a conceptual framework are literature, theory, and experience or prior knowledge.

How to Make a Conceptual Framework

Now that you know the essential elements, your next question will be how to make a conceptual framework.

For this, start by identifying the most suitable set of questions that your research aims to answer. Next, categorize the various variables. Finally, perform a rigorous analysis of the collected data and compile the final results to establish connections between the variables.

In short, the steps are as follows:

• Choose appropriate research questions.
• Define the different types of variables involved.
• Determine the cause-and-effect relationships.

Be sure to make use of arrows and lines to depict the presence or absence of correlational linkages among the variables.

Developing a Conceptual Framework

Researchers should be adept at developing a conceptual framework. Here are the steps for developing a conceptual framework:

1. Identify a research question

Your research question guides your entire study, making it imperative to invest time and effort in formulating a question that aligns with your research goals and contributes to the existing body of knowledge. This step involves the following:

• Choose a broad topic of interest
• Conduct background research
• Narrow down the focus
• Define your goals
• Make it specific and answerable
• Consider significance and novelty
• Seek feedback.

 2. Choose independent and dependent variables

The dependent variable is the main outcome you want to measure, explain, or predict in your study. It should be a variable that can be observed, measured, or assessed quantitatively or qualitatively. Independent variables are the factors or variables that may influence, explain, or predict changes in the dependent variable.

Choose independent and dependent variables for your study according to the research objectives, the nature of the phenomenon being studied, and the specific research design. The identification of variables is rooted in existing literature, theories, or your own observations.

3. Consider cause-and-effect relationships

To better understand and communicate the relationships between variables in your study, cause-and-effect relationships need to be visualized. This can be done by using path diagrams, cause-and-effect matrices, time series plots, scatter plots, bar charts, or heatmaps.

4. Identify other influencing variables

Besides the independent and dependent variables, researchers must understand and consider the following types of variables:

• Moderating variable: A variable that influences the strength or direction of the relationship between an independent variable and a dependent variable.
• Mediating variable: A variable that explains the relationship between an independent variable and a dependent variable and clarifies how the independent variable affects the dependent variable.
• Control variable: A variable that is kept constant or controlled to avoid the influence of other factors that may affect the relationship between the independent and dependent variables.
• Confounding variable: A type of unmeasured variable that is related to both the independent and dependent variables.

Example of a Conceptual Framework

Let us examine the following conceptual framework example. Let’s say your research topic is “ The Impact of Social Media Usage on Academic Performance among College Students .” Here, you want to investigate how social media usage affects academic performance in college students. Social media usage (encompassing frequency of social media use, time spent on social media platforms, and types of social media platforms used) is the independent variable, and academic performance (covering grades, exam scores, and class attendance) is the dependent variable.

This conceptual framework example also includes a mediating variable, study habits, which may explain how social media usage affects academic performance. Study habits (time spent studying, study environment, and use of study aids or resources) can act as a mechanism through which social media usage influences academic outcomes. Additionally, a moderating variable, self-discipline (level of self-control and self-regulation, ability to manage distractions, and prioritization skills), is included to examine how individual differences in self-control and discipline may influence the relationship between social media usage and academic performance.

Confounding variables are also identified (socioeconomic status, prior academic achievement), which are potential factors that may influence both social media usage and academic performance. These variables need to be considered and controlled in the study to ensure that any observed effects are specifically attributed to social media usage. A visual representation of this conceptual framework example is seen in Figure 2.

Figure 2: Visual representation of a conceptual framework for the topic “The Impact of Social Media Usage on Academic Performance among College Students”

Key Takeaways

Here is a snapshot of the basics of a conceptual framework in research:

• A conceptual framework is an idea or model representing the subject or phenomena you intend to study.
• It is primarily a researcher’s perception of the research problem. It can be used to develop hypotheses or testable research questions.
• It provides a preliminary understanding of the factors at play, their interrelationships, and the underlying reasons.
• It guides your research by aiding in the formulation of meaningful research questions, selection of appropriate methods, and identification of potential challenges to the validity of your findings.
• It provides a structure for organizing and understanding data.
• It allows you to chalk out the relationships between concepts and variables to understand them.
• Variables besides dependent and independent variables (moderating, mediating, control, and confounding variables) must be considered when developing a conceptual framework.

Frequently Asked Questions

What is the difference between a moderating variable and a mediating variable.

Moderating and mediating variables are easily confused. A moderating variable affects the direction and strength of this relationship, whereas a mediating explains how two variables relate.

What is the difference between independent variables, dependent variables, and confounding variables?

Independent variables are the variables manipulated to affect the outcome of an experiment (e.g., the dose of a fat-loss drug administered to rats). Dependent variables are variables being measured or observed in an experiment (e.g., changes in rat body weight as a result of the drug). A confounding variable distorts or masks the effects of the variables being studied because it is associated both with dependent variable and with the independent variable. For instance, in this example, pre-existing metabolic dysfunction in some rats could interact differently with the drug being studied and also affect rat body weight.

Should I have more than one dependent or independent variable in a study?

The need for more than one dependent or independent variable in a study depends on the research question, study design, and relationships being investigated. Note the following when making this decision for your research:

• If your research question involves exploring the relationships between multiple variables or factors, it may be appropriate to have more than one dependent or independent variable.
• If you have specific hypotheses about the relationships between several variables, it may be necessary to include multiple dependent or independent variables.
• Adequate resources, sample size, and data collection methods should be considered when determining the number of dependent and independent variables to include.

What is a confounding variable?

A confounding variable is not the main focus of the study but can unintentionally influence the relationship between the independent and dependent variables. Confounding variables can introduce bias and give rise to misleading conclusions. These variables must be controlled to ensure that any observed relationship is genuinely due to the independent variable.

What is a control variable?

A control variable is something not of interest to the study’s objectives but is kept constant because it could influence the outcomes. Control variables can help prevent research biases and allow for a more accurate assessment of the relationship between the independent and dependent variables. Examples are (i) testing all participants at the same time (e.g., in the morning) to minimize the potential effects of circadian rhythms, (ii) ensuring that instruments are calibrated consistently before each measurement to minimize the influence of measurement errors, and (iii) randomization of participants across study groups.

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Conceptual Research: Definition, Framework, Example and Advantages

Conceptual Research: Definition

Conceptual research is defined as a methodology wherein research is conducted by observing and analyzing already present information on a given topic. Conceptual research doesn’t involve conducting any practical experiments. It is related to abstract concepts or ideas. Philosophers have long used conceptual research to develop new theories or interpret existing theories in a different light.

For example, Copernicus used conceptual research to come up with the concepts of stellar constellations based on his observations of the universe. Down the line, Galileo simplified Copernicus’s research by making his own conceptual observations which gave rise to more experimental research and confirmed the predictions made at that time.

The most famous example of conceptual research is Sir Issac Newton. He observed his surroundings to conceptualize and develop theories about gravitation and motion.

Einstein is widely known and appreciated for his work on conceptual research. Although his theories were based on conceptual observations, Einstein also proposed experiments to come up with theories to test the conceptual research.

Nowadays, conceptual research is used to answer business questions and solve real-world problems. Researchers use analytical research tools called conceptual frameworks to make conceptual distinctions and organize ideas required for research purposes.

Conceptual Research Framework

Conceptual research framework constitutes of a researcher’s combination of previous research and associated work and explains the occurring phenomenon. It systematically explains the actions needed in the course of the research study based on the knowledge obtained from other ongoing research and other researchers’ points of view on the subject matter.

Here is a stepwise guide on how to create the conceptual research framework:

01. Choose the topic for research

Before you start working on collecting any research material, you should have decided on your topic for research. It is important that the topic is selected beforehand and should be within your field of specialization.

02. Collect relevant literature

Once you have narrowed down a topic, it is time to collect relevant information about it. This is an important step, and much of your research is dependent on this particular step, as conceptual research is mostly based on information obtained from previous research. Here collecting relevant literature and information is the key to successfully completing research.

The material that you should preferably use is scientific journals , research papers published by well-known scientists , and similar material. There is a lot of information available on the internet and in public libraries as well. All the information that you find on the internet may not be relevant or true. So before you use the information, make sure you verify it.  

03. Identify specific variables

Identify the specific variables that are related to the research study you want to conduct. These variables can give your research a new scope and can also help you identify how these can be related to your research design . For example, consider hypothetically you want to conduct research about the occurrence of cancer in married women. Here the two variables that you will be concentrating on are married women and cancer.

While collecting relevant literature, you understand that the spread of cancer is more aggressive in married women who are beyond 40 years of age. Here there is a third variable which is age, and this is a relevant variable that can affect the end result of your research.  

04. Generate the framework

In this step, you start building the required framework using the mix of variables from the scientific articles and other relevant materials. The research problem statement in your research becomes the research framework. Your attempt to start answering the question becomes the basis of your research study. The study is carried out to reduce the knowledge gap and make available more relevant and correct information.

Example of Conceptual Research Framework

Thesis statement/ Purpose of research: Chronic exposure to sunlight can lead to precancerous (actinic keratosis), cancerous (basal cell carcinoma, squamous cell carcinoma, and melanoma), and even skin lesions (caused by loss of skin’s immune function) in women over 40 years of age.

The study claims that constant exposure to sunlight can cause the precancerous condition and can eventually lead to cancer and other skin abnormalities. Those affected by these experience symptoms like fatigue, fine or coarse wrinkles, discoloration of the skin, freckles, and a burning sensation in the more exposed areas.

Note that in this study, there are two variables associated- cancer and women over 40 years in the African subcontinent. But one is a dependent variable (women over 40 years, in the African subcontinent), and the other is an independent variable (cancer). Cumulative exposure to the sun till the age of 18 years can lead to symptoms similar to skin cancer. If this is not taken care of, there are chances that cancer can spread entirely.

Assuming that the other factors are constant during the research period, it will be possible to correlate the two variables and thus confirm that, indeed, chronic exposure to sunlight causes cancer in women over the age of 40 in the African subcontinent. Further, correlational research can verify this association further.

Advantages of Conceptual Research

1. Conceptual research mainly focuses on the concept of the research or the theory that explains a phenomenon. What causes the phenomenon, what are its building blocks, and so on? It’s research based on pen and paper.

2. This type of research heavily relies on previously conducted studies; no form of experiment is conducted, which saves time, effort, and resources. More relevant information can be generated by conducting conceptual research.

3. Conceptual research is considered the most convenient form of research. In this type of research, if the conceptual framework is ready, only relevant information and literature need to be sorted.

QuestionPro for Conceptual Research

QuestionPro offers readily available conceptual frameworks. These frameworks can be used to research consumer trust, customer satisfaction (CSAT) , product evaluations, etc. You can select from a wide range of templates question types, and examples curated by expert researchers.

We also help you decide which conceptual framework might be best suited for your specific situation.

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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.

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Home » Conceptual Framework – Types, Methodology and Examples

Conceptual Framework – Types, Methodology and Examples

Table of Contents

Conceptual Framework

Definition:

A conceptual framework is a structured approach to organizing and understanding complex ideas, theories, or concepts. It provides a systematic and coherent way of thinking about a problem or topic, and helps to guide research or analysis in a particular field.

A conceptual framework typically includes a set of assumptions, concepts, and propositions that form a theoretical framework for understanding a particular phenomenon. It can be used to develop hypotheses, guide empirical research, or provide a framework for evaluating and interpreting data.

Conceptual Framework in Research

In research, a conceptual framework is a theoretical structure that provides a framework for understanding a particular phenomenon or problem. It is a key component of any research project and helps to guide the research process from start to finish.

A conceptual framework provides a clear understanding of the variables, relationships, and assumptions that underpin a research study. It outlines the key concepts that the study is investigating and how they are related to each other. It also defines the scope of the study and sets out the research questions or hypotheses.

Types of Conceptual Framework

Types of Conceptual Framework are as follows:

Theoretical Framework

A theoretical framework is an overarching set of concepts, ideas, and assumptions that help to explain and interpret a phenomenon. It provides a theoretical perspective on the phenomenon being studied and helps researchers to identify the relationships between different concepts. For example, a theoretical framework for a study on the impact of social media on mental health might draw on theories of communication, social influence, and psychological well-being.

Conceptual Model

A conceptual model is a visual or written representation of a complex system or phenomenon. It helps to identify the main components of the system and the relationships between them. For example, a conceptual model for a study on the factors that influence employee turnover might include factors such as job satisfaction, salary, work-life balance, and job security, and the relationships between them.

Empirical Framework

An empirical framework is based on empirical data and helps to explain a particular phenomenon. It involves collecting data, analyzing it, and developing a framework to explain the results. For example, an empirical framework for a study on the impact of a new health intervention might involve collecting data on the intervention’s effectiveness, cost, and acceptability to patients.

Descriptive Framework

A descriptive framework is used to describe a particular phenomenon. It helps to identify the main characteristics of the phenomenon and to develop a vocabulary to describe it. For example, a descriptive framework for a study on different types of musical genres might include descriptions of the instruments used, the rhythms and beats, the vocal styles, and the cultural contexts of each genre.

Analytical Framework

An analytical framework is used to analyze a particular phenomenon. It involves breaking down the phenomenon into its constituent parts and analyzing them separately. This type of framework is often used in social science research. For example, an analytical framework for a study on the impact of race on police brutality might involve analyzing the historical and cultural factors that contribute to racial bias, the organizational factors that influence police behavior, and the psychological factors that influence individual officers’ behavior.

Conceptual Framework for Policy Analysis

A conceptual framework for policy analysis is used to guide the development of policies or programs. It helps policymakers to identify the key issues and to develop strategies to address them. For example, a conceptual framework for a policy analysis on climate change might involve identifying the key stakeholders, assessing their interests and concerns, and developing policy options to mitigate the impacts of climate change.

Logical Frameworks

Logical frameworks are used to plan and evaluate projects and programs. They provide a structured approach to identifying project goals, objectives, and outcomes, and help to ensure that all stakeholders are aligned and working towards the same objectives.

Conceptual Frameworks for Program Evaluation

These frameworks are used to evaluate the effectiveness of programs or interventions. They provide a structure for identifying program goals, objectives, and outcomes, and help to measure the impact of the program on its intended beneficiaries.

Conceptual Frameworks for Organizational Analysis

These frameworks are used to analyze and evaluate organizational structures, processes, and performance. They provide a structured approach to understanding the relationships between different departments, functions, and stakeholders within an organization.

Conceptual Frameworks for Strategic Planning

These frameworks are used to develop and implement strategic plans for organizations or businesses. They help to identify the key factors and stakeholders that will impact the success of the plan, and provide a structure for setting goals, developing strategies, and monitoring progress.

Components of Conceptual Framework

The components of a conceptual framework typically include:

• Research question or problem statement : This component defines the problem or question that the conceptual framework seeks to address. It sets the stage for the development of the framework and guides the selection of the relevant concepts and constructs.
• Concepts : These are the general ideas, principles, or categories that are used to describe and explain the phenomenon or problem under investigation. Concepts provide the building blocks of the framework and help to establish a common language for discussing the issue.
• Constructs : Constructs are the specific variables or concepts that are used to operationalize the general concepts. They are measurable or observable and serve as indicators of the underlying concept.
• Propositions or hypotheses : These are statements that describe the relationships between the concepts or constructs in the framework. They provide a basis for testing the validity of the framework and for generating new insights or theories.
• Assumptions : These are the underlying beliefs or values that shape the framework. They may be explicit or implicit and may influence the selection and interpretation of the concepts and constructs.
• Boundaries : These are the limits or scope of the framework. They define the focus of the investigation and help to clarify what is included and excluded from the analysis.
• Context : This component refers to the broader social, cultural, and historical factors that shape the phenomenon or problem under investigation. It helps to situate the framework within a larger theoretical or empirical context and to identify the relevant variables and factors that may affect the phenomenon.
• Relationships and connections: These are the connections and interrelationships between the different components of the conceptual framework. They describe how the concepts and constructs are linked and how they contribute to the overall understanding of the phenomenon or problem.
• Variables : These are the factors that are being measured or observed in the study. They are often operationalized as constructs and are used to test the propositions or hypotheses.
• Methodology : This component describes the research methods and techniques that will be used to collect and analyze data. It includes the sampling strategy, data collection methods, data analysis techniques, and ethical considerations.
• Literature review : This component provides an overview of the existing research and theories related to the phenomenon or problem under investigation. It helps to identify the gaps in the literature and to situate the framework within the broader theoretical and empirical context.
• Outcomes and implications: These are the expected outcomes or implications of the study. They describe the potential contributions of the study to the theoretical and empirical knowledge in the field and the practical implications for policy and practice.

Conceptual Framework Methodology

Conceptual Framework Methodology is a research method that is commonly used in academic and scientific research to develop a theoretical framework for a study. It is a systematic approach that helps researchers to organize their thoughts and ideas, identify the variables that are relevant to their study, and establish the relationships between these variables.

Here are the steps involved in the conceptual framework methodology:

Identify the Research Problem

The first step is to identify the research problem or question that the study aims to answer. This involves identifying the gaps in the existing literature and determining what specific issue the study aims to address.

Conduct a Literature Review

The second step involves conducting a thorough literature review to identify the existing theories, models, and frameworks that are relevant to the research question. This will help the researcher to identify the key concepts and variables that need to be considered in the study.

Define key Concepts and Variables

The next step is to define the key concepts and variables that are relevant to the study. This involves clearly defining the terms used in the study, and identifying the factors that will be measured or observed in the study.

Develop a Theoretical Framework

Once the key concepts and variables have been identified, the researcher can develop a theoretical framework. This involves establishing the relationships between the key concepts and variables, and creating a visual representation of these relationships.

Test the Framework

The final step is to test the theoretical framework using empirical data. This involves collecting and analyzing data to determine whether the relationships between the key concepts and variables that were identified in the framework are accurate and valid.

Examples of Conceptual Framework

Some realtime Examples of Conceptual Framework are as follows:

• In economics , the concept of supply and demand is a well-known conceptual framework. It provides a structure for understanding how prices are set in a market, based on the interplay of the quantity of goods supplied by producers and the quantity of goods demanded by consumers.
• In psychology , the cognitive-behavioral framework is a widely used conceptual framework for understanding mental health and illness. It emphasizes the role of thoughts and behaviors in shaping emotions and the importance of cognitive restructuring and behavior change in treatment.
• In sociology , the social determinants of health framework provides a way of understanding how social and economic factors such as income, education, and race influence health outcomes. This framework is widely used in public health research and policy.
• In environmental science , the ecosystem services framework is a way of understanding the benefits that humans derive from natural ecosystems, such as clean air and water, pollination, and carbon storage. This framework is used to guide conservation and land-use decisions.
• In education, the constructivist framework is a way of understanding how learners construct knowledge through active engagement with their environment. This framework is used to guide instructional design and teaching strategies.

Applications of Conceptual Framework

Some of the applications of Conceptual Frameworks are as follows:

• Research : Conceptual frameworks are used in research to guide the design, implementation, and interpretation of studies. Researchers use conceptual frameworks to develop hypotheses, identify research questions, and select appropriate methods for collecting and analyzing data.
• Policy: Conceptual frameworks are used in policy-making to guide the development of policies and programs. Policymakers use conceptual frameworks to identify key factors that influence a particular problem or issue, and to develop strategies for addressing them.
• Education : Conceptual frameworks are used in education to guide the design and implementation of instructional strategies and curriculum. Educators use conceptual frameworks to identify learning objectives, select appropriate teaching methods, and assess student learning.
• Management : Conceptual frameworks are used in management to guide decision-making and strategy development. Managers use conceptual frameworks to understand the internal and external factors that influence their organizations, and to develop strategies for achieving their goals.
• Evaluation : Conceptual frameworks are used in evaluation to guide the development of evaluation plans and to interpret evaluation results. Evaluators use conceptual frameworks to identify key outcomes, indicators, and measures, and to develop a logic model for their evaluation.

Purpose of Conceptual Framework

The purpose of a conceptual framework is to provide a theoretical foundation for understanding and analyzing complex phenomena. Conceptual frameworks help to:

• Guide research : Conceptual frameworks provide a framework for researchers to develop hypotheses, identify research questions, and select appropriate methods for collecting and analyzing data. By providing a theoretical foundation for research, conceptual frameworks help to ensure that research is rigorous, systematic, and valid.
• Provide clarity: Conceptual frameworks help to provide clarity and structure to complex phenomena by identifying key concepts, relationships, and processes. By providing a clear and systematic understanding of a phenomenon, conceptual frameworks help to ensure that researchers, policymakers, and practitioners are all on the same page when it comes to understanding the issue at hand.
• Inform decision-making : Conceptual frameworks can be used to inform decision-making and strategy development by identifying key factors that influence a particular problem or issue. By understanding the complex interplay of factors that contribute to a particular issue, decision-makers can develop more effective strategies for addressing the problem.
• Facilitate communication : Conceptual frameworks provide a common language and conceptual framework for researchers, policymakers, and practitioners to communicate and collaborate on complex issues. By providing a shared understanding of a phenomenon, conceptual frameworks help to ensure that everyone is working towards the same goal.

When to use Conceptual Framework

There are several situations when it is appropriate to use a conceptual framework:

• To guide the research : A conceptual framework can be used to guide the research process by providing a clear roadmap for the research project. It can help researchers identify key variables and relationships, and develop hypotheses or research questions.
• To clarify concepts : A conceptual framework can be used to clarify and define key concepts and terms used in a research project. It can help ensure that all researchers are using the same language and have a shared understanding of the concepts being studied.
• To provide a theoretical basis: A conceptual framework can provide a theoretical basis for a research project by linking it to existing theories or conceptual models. This can help researchers build on previous research and contribute to the development of a field.
• To identify gaps in knowledge : A conceptual framework can help identify gaps in existing knowledge by highlighting areas that require further research or investigation.
• To communicate findings : A conceptual framework can be used to communicate research findings by providing a clear and concise summary of the key variables, relationships, and assumptions that underpin the research project.

Characteristics of Conceptual Framework

key characteristics of a conceptual framework are:

• Clear definition of key concepts : A conceptual framework should clearly define the key concepts and terms being used in a research project. This ensures that all researchers have a shared understanding of the concepts being studied.
• Identification of key variables: A conceptual framework should identify the key variables that are being studied and how they are related to each other. This helps to organize the research project and provides a clear focus for the study.
• Logical structure: A conceptual framework should have a logical structure that connects the key concepts and variables being studied. This helps to ensure that the research project is coherent and consistent.
• Based on existing theory : A conceptual framework should be based on existing theory or conceptual models. This helps to ensure that the research project is grounded in existing knowledge and builds on previous research.
• Testable hypotheses or research questions: A conceptual framework should include testable hypotheses or research questions that can be answered through empirical research. This helps to ensure that the research project is rigorous and scientifically valid.
• Flexibility : A conceptual framework should be flexible enough to allow for modifications as new information is gathered during the research process. This helps to ensure that the research project is responsive to new findings and is able to adapt to changing circumstances.

Advantages of Conceptual Framework

Advantages of the Conceptual Framework are as follows:

• Clarity : A conceptual framework provides clarity to researchers by outlining the key concepts and variables that are relevant to the research project. This clarity helps researchers to focus on the most important aspects of the research problem and develop a clear plan for investigating it.
• Direction : A conceptual framework provides direction to researchers by helping them to develop hypotheses or research questions that are grounded in existing theory or conceptual models. This direction ensures that the research project is relevant and contributes to the development of the field.
• Efficiency : A conceptual framework can increase efficiency in the research process by providing a structure for organizing ideas and data. This structure can help researchers to avoid redundancies and inconsistencies in their work, saving time and effort.
• Rigor : A conceptual framework can help to ensure the rigor of a research project by providing a theoretical basis for the investigation. This rigor is essential for ensuring that the research project is scientifically valid and produces meaningful results.
• Communication : A conceptual framework can facilitate communication between researchers by providing a shared language and understanding of the key concepts and variables being studied. This communication is essential for collaboration and the advancement of knowledge in the field.
• Generalization : A conceptual framework can help to generalize research findings beyond the specific study by providing a theoretical basis for the investigation. This generalization is essential for the development of knowledge in the field and for informing future research.

Limitations of Conceptual Framework

Limitations of Conceptual Framework are as follows:

• Limited applicability: Conceptual frameworks are often based on existing theory or conceptual models, which may not be applicable to all research problems or contexts. This can limit the usefulness of a conceptual framework in certain situations.
• Lack of empirical support : While a conceptual framework can provide a theoretical basis for a research project, it may not be supported by empirical evidence. This can limit the usefulness of a conceptual framework in guiding empirical research.
• Narrow focus: A conceptual framework can provide a clear focus for a research project, but it may also limit the scope of the investigation. This can make it difficult to address broader research questions or to consider alternative perspectives.
• Over-simplification: A conceptual framework can help to organize and structure research ideas, but it may also over-simplify complex phenomena. This can limit the depth of the investigation and the richness of the data collected.
• Inflexibility : A conceptual framework can provide a structure for organizing research ideas, but it may also be inflexible in the face of new data or unexpected findings. This can limit the ability of researchers to adapt their research project to new information or changing circumstances.
• Difficulty in development : Developing a conceptual framework can be a challenging and time-consuming process. It requires a thorough understanding of existing theory or conceptual models, and may require collaboration with other researchers.

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What is a good example of a conceptual framework?

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• The importance of a conceptual framework

The main purpose of a conceptual framework is to improve the quality of a research study. A conceptual framework achieves this by identifying important information about the topic and providing a clear roadmap for researchers to study it.

Through the process of developing this information, researchers will be able to improve the quality of their studies in a few key ways.

Clarify research goals and objectives

A conceptual framework helps researchers create a clear research goal. Research projects often become vague and lose their focus, which makes them less useful. However, a well-designed conceptual framework helps researchers maintain focus. It reinforces the project’s scope, ensuring it stays on track and produces meaningful results.

Provide a theoretical basis for the study

Forming a hypothesis requires knowledge of the key variables and their relationship to each other. Researchers need to identify these variables early on to create a conceptual framework. This ensures researchers have developed a strong understanding of the topic before finalizing the study design. It also helps them select the most appropriate research and analysis methods.

Guide the research design

As they develop their conceptual framework, researchers often uncover information that can help them further refine their work.

Here are some examples:

Confounding variables they hadn’t previously considered

Sources of bias they will have to take into account when designing the project

Whether or not the information they were going to study has already been covered—this allows them to pivot to a more meaningful goal that brings new and relevant information to their field

• Steps to develop a conceptual framework

There are four major steps researchers will follow to develop a conceptual framework. Each step will be described in detail in the sections that follow. You’ll also find examples of how each might be applied in a range of fields.

Step 1: Choose the research question

The first step in creating a conceptual framework is choosing a research question . The goal of this step is to create a question that’s specific and focused.

By developing a clear question, researchers can more easily identify the variables they will need to account for and keep their research focused. Without it, the next steps will be more difficult and less effective.

Here are some examples of good research questions in a few common fields:

Natural sciences: How does exposure to ultraviolet radiation affect the growth rate of a particular type of algae?

Health sciences: What is the effectiveness of cognitive-behavioral therapy for treating depression in adolescents?

Business: What factors contribute to the success of small businesses in a particular industry?

Education: How does implementing technology in the classroom impact student learning outcomes?

Step 2: Select the independent and dependent variables

Once the research question has been chosen, it’s time to identify the dependent and independent variables .

The independent variable is the variable researchers think will affect the dependent variable . Without this information, researchers cannot develop a meaningful hypothesis or design a way to test it.

The dependent and independent variables for our example questions above are:

Natural sciences

Independent variable: exposure to ultraviolet radiation

Dependent variable: the growth rate of a particular type of algae

Health sciences

Independent variable: cognitive-behavioral therapy

Dependent variable: depression in adolescents

Independent variables: factors contributing to the business’s success

Dependent variable: sales, return on investment (ROI), or another concrete metric

Independent variable: implementation of technology in the classroom

Dependent variable: student learning outcomes, such as test scores, GPAs, or exam results

Step 3: Visualize the cause-and-effect relationship

This step is where researchers actually develop their hypothesis. They will predict how the independent variable will impact the dependent variable based on their knowledge of the field and their intuition.

With a hypothesis formed, researchers can more accurately determine what data to collect and how to analyze it. They will then visualize their hypothesis by creating a diagram. This visualization will serve as a framework to help guide their research.

The diagrams for our examples might be used as follows:

Natural sciences : how exposure to radiation affects the biological processes in the algae that contribute to its growth rate

Health sciences : how different aspects of cognitive behavioral therapy can affect how patients experience symptoms of depression

Business : how factors such as market demand, managerial expertise, and financial resources influence a business’s success

Education : how different types of technology interact with different aspects of the learning process and alter student learning outcomes

Step 4: Identify other influencing variables

The independent and dependent variables are only part of the equation. Moderating, mediating, and control variables are also important parts of a well-designed study. These variables can impact the relationship between the two main variables and must be accounted for.

A moderating variable is one that can change how the independent variable affects the dependent variable. A mediating variable explains the relationship between the two. Control variables are kept the same to eliminate their impact on the results. Examples of each are given below:

Moderating variable: water temperature (might impact how algae respond to radiation exposure)

Mediating variable: chlorophyll production (might explain how radiation exposure affects algae growth rate)

Control variable: nutrient levels in the water

Moderating variable: the severity of depression symptoms at baseline might impact how effective the therapy is for different adolescents

Mediating variable: social support might explain how cognitive-behavioral therapy leads to improvements in depression

Control variable: other forms of treatment received before or during the study

Moderating variable: the size of the business (might impact how different factors contribute to market share, sales, ROI, and other key success metrics)

Mediating variable: customer satisfaction (might explain how different factors impact business success)

Control variable: industry competition

Moderating variable: student age (might impact how effective technology is for different students)

Mediating variable: teacher training (might explain how technology leads to improvements in learning outcomes)

Control variable: student learning style

• Conceptual versus theoretical frameworks

Although they sound similar, conceptual and theoretical frameworks have different goals and are used in different contexts. Understanding which to use will help researchers craft better studies.

Conceptual frameworks describe a broad overview of the subject and outline key concepts, variables, and the relationships between them. They provide structure to studies that are more exploratory in nature, where the relationships between the variables are still being established. They are particularly helpful in studies that are complex or interdisciplinary because they help researchers better organize the factors involved in the study.

Theoretical frameworks, on the other hand, are used when the research question is more clearly defined and there’s an existing body of work to draw upon. They define the relationships between the variables and help researchers predict outcomes. They are particularly helpful when researchers want to refine the existing body of knowledge rather than establish it.

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews
• Research question
• Introduction

Understanding conceptual frameworks

Selecting and developing your framework, variables in a conceptual framework.

• Conceptual vs. theoretical framework
• Data collection
• Qualitative research methods
• Focus groups
• Observational research
• Case studies
• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Conceptual framework: Definition and theory

Theoretical and conceptual frameworks ultimately go hand in hand, but while there is significant overlap with theoretical perspectives and theoretical frameworks, understanding the essential differences is important when designing your research project.

Let's explore the idea of a conceptual framework, provide a few common examples, and discuss how to choose a framework for your study. Keep in mind that a conceptual framework will differ from a theoretical framework and that we will explore these differences in the next section.

In this section, we'll delve into the intricacies of conceptual frameworks and their role in qualitative research . They are essentially the scaffolding on which you hang your research questions and analysis . They define the concepts that you'll study and articulate the relationships among them.

Developing conceptual frameworks in research

At the most basic level, a conceptual framework is a visual or written product that explains, either graphically or in narrative form, the main things to be studied, the key factors, variables, or constructs, and any presumed relationships among them. It acts as a road map guiding the course of your research, directing what will be studied, and helping to organize and analyze the data.

The purpose of a conceptual framework

A conceptual framework serves multiple functions in a research project. It helps in clarifying the research problem and purpose, assists in refining the research questions, and guides the data collection and analysis process. It's the tool that ties all aspects of the study together, offering a coherent perspective for the researcher and readers to understand the research more holistically.

Relation between theoretical perspectives and conceptual frameworks

Theoretical perspectives offer overarching philosophies and assumptions that guide the research process, while conceptual frameworks are the specific devices that are derived from these perspectives to operationalize the study. If a theoretical perspective is the broad philosophical underpinning, a conceptual framework is a pragmatic approach that puts that philosophy into practice in the context of the study.

For instance, if you're working from a feminist theoretical perspective, your conceptual framework might involve specific constructs like gender roles, power dynamics , and societal norms, as well as the relationships between these constructs. The conceptual framework would be the lens through which you examine and interpret your data, guided by your theoretical perspective.

Critical theory

Critical theory is a theoretical perspective that seeks to confront social, historical, and ideological forces and structures that produce and constrain social problems. The corresponding conceptual framework might focus on constructs like power relations, historical context, and societal structures. For instance, a study on income inequality might have a conceptual framework involving constructs of socioeconomic status, institutional policies, and the distribution of resources.

Feminist theory

Feminist theory emphasizes the societal roles of gender and power relationships. A conceptual framework derived from this theory might involve constructs like gender roles, power dynamics, and societal norms. In a study about gender representation in media, a feminist conceptual framework could involve constructs such as stereotyping, representation, and societal expectations of gender.

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Choosing and developing your conceptual framework is a pivotal process in your research design. This framework will help guide your study, inform your methodology , and shape your analysis .

Factors to consider when choosing a framework

Your conceptual framework should be derived from and align with your chosen theoretical perspective , but there are other considerations as well. It should resonate with your research question , problem, or purpose and be applicable to the specific context or population you are studying. You should also consider the feasibility of operationalizing the constructs in your framework.

When selecting a conceptual framework, consider the following questions:

1. How does this framework relate to my research topic? 2. Can I use this framework to effectively address my research question(s)? 3. Does this framework resonate with the population and context I'm studying? 4. Can the constructs in this framework be feasibly operationalized in my study?

Steps in developing a conceptual framework

Developing your conceptual framework involves a few key steps:

1. Identify key constructs: Based on your theoretical perspective and research question(s) , what are the main constructs or variables that you need to explore in your study? 2. Clarify relationships among constructs: How do these constructs relate to each other? Are there presumed causal relationships, correlations, or other types of associations? 3. Define each construct: Clearly define what each construct means in the context of your study. This might also involve operationalizing each construct or defining the indicators you will use to measure or identify each construct. 4. Create a visual representation : It is often extremely helpful to create a visual representation of your conceptual framework to illustrate the constructs and their relationships. Map out the relationships among constructs to develop a holistic understanding of what you want to study.

Remember, your conceptual framework is not set in stone. You can start creating your conceptual framework based on your literature review and your own critical reflections. As you proceed with your study, you might need to refine or adapt your conceptual framework based on what you're learning from your data. Developing a robust framework is an iterative process that requires critical thinking, creativity, and flexibility.

A strong conceptual framework includes variables that refer to the constructs or characteristics that are being studied. They are the building blocks of your research study. It might be helpful to think about how the variables in your conceptual framework could be categorized as independent and dependent variables, which respectively influence and are influenced within the research study.

Independent variables and dependent variables

An independent variable is the characteristic or condition that is manipulated or selected by the researcher to determine its effect on the dependent variable. For example, in a study exploring the impact of classroom size on student engagement, classroom size would be the independent variable.

The dependent variable is the main outcome that the researcher is interested in studying or explaining. In the example given above, student engagement would be the dependent variable, as it's the outcome being observed for any changes in response to the independent variable (classroom size). In essence, defining these variables can help you identify the cause-and-effect relationships in your study. While it might be difficult to know beforehand exactly which variables will be important and how they relate to one another, this is a helpful thought exercise to flesh out potential relationships among variables you may want to study.

Relationships among variables

Within a conceptual framework, the dependent and independent variables are listed in addition to their proposed relationships to each other. The ways in which these variables influence one another form the crux of the propositions or assumptions that guide your research.

In a conceptual framework based on the theoretical perspective of constructivism, for instance, the independent variable might be a teaching method (as constructivists would argue that methods of instruction can shape learning), and the dependent variable could be the depth of student understanding. The proposed relationship between these variables might be that student-centered teaching methods lead to a deeper understanding, which would guide the data collection and analysis such that this proposition could be explored.

However, it is important to note that the terminology of independent and dependent variables is more typical of quantitative research , in which independent and dependent variables are operationalized in hypotheses that will be tested based on pre-established theory. In qualitative research , the relationships between variables are more fluid and open-ended because the focus is often more on understanding the phenomenon as a whole and building a contextualized understanding of the research problem. This can involve including new or unexpected variables and interrelationships that emerge during the study, thus extending previous theory or understanding that didn’t initially predict these relationships.

Thus, in your conceptual framework, rather than solely focusing on identifying independent and dependent variables, consider how various factors interact and influence one another within the context of your study. Your conceptual framework should provide a holistic picture of the complexity of the phenomenon you are studying.

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On using conceptual frameworks to guide a systematic review: a comment on Berger-Tal et al.

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Andrew Sih, Lea Pollack, Emily Zepeda, On using conceptual frameworks to guide a systematic review: a comment on Berger-Tal et al., Behavioral Ecology , Volume 30, Issue 1, January/February 2019, Pages 12–13, https://doi.org/10.1093/beheco/ary153

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The core idea of systematic reviews as described by Berger-Tal et al. (2019) is undeniably exciting. Clearly, it is wonderful to “maximize objectivity, transparency, and comprehensiveness…while minimizing the bias at all stages of the review process”. In addition, involving stakeholders in the process is highly laudable both for their valuable input, and for facilitating “the uptake of these findings by managers and policy makers.” Of course, because the process is so systematic and rigorous, it poses challenges. As freely acknowledged by the authors, the devil is in the many details. Our focus will be on a point that the authors discussed briefly, but that we think deserves more detailed discussion: the need to have a strong conceptual framework to guide step one—the formulation of the questions.

We suggest that the answer to all interesting questions that might be the subject of a systematic review (in any field) is—it depends. The goal is to figure out what “it” depends on. What are the major factors that mediate the outcome of interest, and how might those factors interact to govern the outcome? The authors asked, for example: what are the fitness consequences of cage diving operations to sharks? The answer likely depends on the shark species, perhaps its social system or foraging mode, or even the individual shark’s personality. It might also depend on various aspects of the habitat, time of day, season, and details of the diving operation.

More generally, outcomes often depend on: 1) the focal organisms’ traits; 2) components of the environmental context; 3) specific aspects of the intervention or exposure; and 4) interactions among these. When doing a systematic review or meta-analysis, to gain insight on the importance of a given factor (or interaction), a key is to identify beforehand which ones seem likely to be important enough to include in the review (i.e., what information should be extracted, if available, from each paper?). We suggest that ideally authors first develop a clear, conceptual framework and use that framework to guide the formulation of explicit hypotheses on mediating factors. While a conceptual framework is often implicit in the investigators’ approach, in many cases, the review would benefit from a more explicit, rigorous, perhaps even theory-based, implementation.

In behavioral ecology, one common conceptual framework for predicting behavior is the cost-benefit approach. In a nice example of a conservation-relevant meta-analysis guided by a conceptual framework, Stankowich (2008) examined factors that influence ungulate flight responses from human disturbance. Using a cost-benefit framework as a guide, he looked at characteristics of the focal organisms (sex, age, reproductive status, past experience with humans), of the context (group size, environmental factors), and of the human disturbance (speed and direction of approach). To address unexplained variance, he suggested that interactions among factors might play an important role, emphasizing the need for an expanded conceptual framework for predicting interactions. Of course, the optimality approach is not always best. For example, if some animals behave adaptively, but others exhibit apparently maladaptive behavioral responses (e.g., to novel situations associated with human-induced rapid environmental change), Sih et al. (2011 , 2016 ) suggested an alternative framework for generating predictions, but the point remains that a conceptual framework is crucial for guiding a systematic review.

In contrast, many reviews or meta-analyses test for impacts of factors that are easy to extract from every paper, even if not necessarily connected to theory-based hypotheses. Some, for example, have focused largely on comparing taxonomic groups (e.g., birds vs. mammals) and broad ecosystem types (e.g., marine, freshwater or terrestrial systems) without clearly stated a priori hypotheses. In general, many if not most of the original studies in these reviews had information on at least some potential mediating factors—information that would have been valuable to extract while conducting the review. Berger-Tal’s suggested step one—careful formulation of the questions with broad, stakeholder engagement—should help alleviate this issue. Our point is to strongly emphasize that this key first step can be, in principle, more effectively handled by building the questions/hypotheses around an explicit conceptual framework. If nothing else, this process would bring behavioral ecology’s conceptual thinkers into the systematic review process—a move that we think should often prove valuable.

This paper was supported by the National Science Foundation: NSF IOS 1456724 grant to A.S. and NSF GRFP fellowships to E.Z. and L.P.

Berger-Tal O , Greggor AL , Macura B , Adams CA , Blumenthal A , Bouskila A , Candolin U , Doran A , FernÁndez-Juricic E , Gotanda KM , et al.  2019 . Systematic reviews and maps as tools for applying behavioral ecology to management and policy . Behav Ecol . 30:1–8.

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Sih A , Ferrari MC , Harris DJ. 2011 . Evolution and behavioural responses to human-induced rapid environmental change . Evol Appl . 4 : 367 – 387

Sih A , Trimmer PC , Ehlman SM. 2016 . A conceptual framework for understanding behavioral responses to HIREC . Curr Opin Behav Sci . 12 : 109 – 114

Stankowich T. 2008 . Ungulate flight responses to human disturbance: a review and meta-analysis . Biol Cons . 141 : 2159 – 2173

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• UConn Library
• Literature Review: The What, Why and How-to Guide
• Introduction

Literature Review: The What, Why and How-to Guide — Introduction

• Getting Started
• How to Pick a Topic
• Strategies to Find Sources
• Evaluating Sources & Lit. Reviews
• Tips for Writing Literature Reviews
• Writing Literature Review: Useful Sites
• Citation Resources
• Other Academic Writings

What are Literature Reviews?

So, what is a literature review? "A literature review is an account of what has been published on a topic by accredited scholars and researchers. In writing the literature review, your purpose is to convey to your reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. As a piece of writing, the literature review must be defined by a guiding concept (e.g., your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries." Taylor, D.  The literature review: A few tips on conducting it . University of Toronto Health Sciences Writing Centre.

Goals of Literature Reviews

What are the goals of creating a Literature Review?  A literature could be written to accomplish different aims:

• To develop a theory or evaluate an existing theory
• To summarize the historical or existing state of a research topic
• Identify a problem in a field of research 

Baumeister, R. F., & Leary, M. R. (1997). Writing narrative literature reviews .  Review of General Psychology , 1 (3), 311-320.

What kinds of sources require a Literature Review?

• A research paper assigned in a course
• A thesis or dissertation
• A grant proposal
• An article intended for publication in a journal

All these instances require you to collect what has been written about your research topic so that you can demonstrate how your own research sheds new light on the topic.

Types of Literature Reviews

What kinds of literature reviews are written?

Narrative review: The purpose of this type of review is to describe the current state of the research on a specific topic/research and to offer a critical analysis of the literature reviewed. Studies are grouped by research/theoretical categories, and themes and trends, strengths and weakness, and gaps are identified. The review ends with a conclusion section which summarizes the findings regarding the state of the research of the specific study, the gaps identify and if applicable, explains how the author's research will address gaps identify in the review and expand the knowledge on the topic reviewed.

• Example : Predictors and Outcomes of U.S. Quality Maternity Leave: A Review and Conceptual Framework:  10.1177/08948453211037398  

Systematic review : "The authors of a systematic review use a specific procedure to search the research literature, select the studies to include in their review, and critically evaluate the studies they find." (p. 139). Nelson, L. K. (2013). Research in Communication Sciences and Disorders . Plural Publishing.

• Example : The effect of leave policies on increasing fertility: a systematic review:  10.1057/s41599-022-01270-w

Meta-analysis : "Meta-analysis is a method of reviewing research findings in a quantitative fashion by transforming the data from individual studies into what is called an effect size and then pooling and analyzing this information. The basic goal in meta-analysis is to explain why different outcomes have occurred in different studies." (p. 197). Roberts, M. C., & Ilardi, S. S. (2003). Handbook of Research Methods in Clinical Psychology . Blackwell Publishing.

• Example : Employment Instability and Fertility in Europe: A Meta-Analysis:  10.1215/00703370-9164737

Meta-synthesis : "Qualitative meta-synthesis is a type of qualitative study that uses as data the findings from other qualitative studies linked by the same or related topic." (p.312). Zimmer, L. (2006). Qualitative meta-synthesis: A question of dialoguing with texts .  Journal of Advanced Nursing , 53 (3), 311-318.

• Example : Women’s perspectives on career successes and barriers: A qualitative meta-synthesis:  10.1177/05390184221113735

Literature Reviews in the Health Sciences

• UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
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• Next: How to Pick a Topic >>
• Last Updated: Sep 21, 2022 2:16 PM
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• What Is a Conceptual Framework? | Tips & Examples

What Is a Conceptual Framework? | Tips & Examples

Published on 4 May 2022 by Bas Swaen and Tegan George. Revised on 18 March 2024.

A conceptual framework illustrates the expected relationship between your variables. It defines the relevant objectives for your research process and maps out how they come together to draw coherent conclusions.

Keep reading for a step-by-step guide to help you construct your own conceptual framework.

Table of contents

Developing a conceptual framework in research, step 1: choose your research question, step 2: select your independent and dependent variables, step 3: visualise your cause-and-effect relationship, step 4: identify other influencing variables, frequently asked questions about conceptual models.

A conceptual framework is a representation of the relationship you expect to see between your variables, or the characteristics or properties that you want to study.

Conceptual frameworks can be written or visual and are generally developed based on a literature review of existing studies about your topic.

Your research question guides your work by determining exactly what you want to find out, giving your research process a clear focus.

However, before you start collecting your data, consider constructing a conceptual framework. This will help you map out which variables you will measure and how you expect them to relate to one another.

In order to move forward with your research question and test a cause-and-effect relationship, you must first identify at least two key variables: your independent and dependent variables .

• The expected cause, ‘hours of study’, is the independent variable (the predictor, or explanatory variable)
• The expected effect, ‘exam score’, is the dependent variable (the response, or outcome variable).

Note that causal relationships often involve several independent variables that affect the dependent variable. For the purpose of this example, we’ll work with just one independent variable (‘hours of study’).

Now that you’ve figured out your research question and variables, the first step in designing your conceptual framework is visualising your expected cause-and-effect relationship.

It’s crucial to identify other variables that can influence the relationship between your independent and dependent variables early in your research process.

Some common variables to include are moderating, mediating, and control variables.

Moderating variables

Moderating variable (or moderators) alter the effect that an independent variable has on a dependent variable. In other words, moderators change the ‘effect’ component of the cause-and-effect relationship.

Let’s add the moderator ‘IQ’. Here, a student’s IQ level can change the effect that the variable ‘hours of study’ has on the exam score. The higher the IQ, the fewer hours of study are needed to do well on the exam.

Let’s take a look at how this might work. The graph below shows how the number of hours spent studying affects exam score. As expected, the more hours you study, the better your results. Here, a student who studies for 20 hours will get a perfect score.

But the graph looks different when we add our ‘IQ’ moderator of 120. A student with this IQ will achieve a perfect score after just 15 hours of study.

Below, the value of the ‘IQ’ moderator has been increased to 150. A student with this IQ will only need to invest five hours of study in order to get a perfect score.

Here, we see that a moderating variable does indeed change the cause-and-effect relationship between two variables.

Mediating variables

Now we’ll expand the framework by adding a mediating variable . Mediating variables link the independent and dependent variables, allowing the relationship between them to be better explained.

Here’s how the conceptual framework might look if a mediator variable were involved:

In this case, the mediator helps explain why studying more hours leads to a higher exam score. The more hours a student studies, the more practice problems they will complete; the more practice problems completed, the higher the student’s exam score will be.

Moderator vs mediator

It’s important not to confuse moderating and mediating variables. To remember the difference, you can think of them in relation to the independent variable:

• A moderating variable is not affected by the independent variable, even though it affects the dependent variable. For example, no matter how many hours you study (the independent variable), your IQ will not get higher.
• A mediating variable is affected by the independent variable. In turn, it also affects the dependent variable. Therefore, it links the two variables and helps explain the relationship between them.

Control variables

Lastly,  control variables must also be taken into account. These are variables that are held constant so that they don’t interfere with the results. Even though you aren’t interested in measuring them for your study, it’s crucial to be aware of as many of them as you can be.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

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

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

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

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Conceptual Framework and Literature Review

• First Online: 01 January 2014

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Part of the book series: Advances in Asian Human-Environmental Research ((AAHER))

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While ‘conceptual framework’ means a researcher’s own perceptions about the scope and structure of a problem, the literature review provides others’ ideas and work in areas close to that under study. With such a philosophy in mind, this chapter first constructs the author’s own thinking as to how the problem in question has originated, disseminated, and evolved; and how it can be resolved for sustainability if turned around. It also draws support from other like-minded models proposed in the fields of sustainable development. Next, the literature review thoroughly, but not exhaustively, scans the depth and breadth of the existing body of knowledge in the areas of sustainable agriculture, irrigation, and water resources, especially groundwater management. This chapter serves to elucidate the concept of sustainable development. It indicates the measurable indicators of sustainability in agriculture and irrigation systems, thus paving the way for designing the data tools at a subsequent stage. With the intention of giving due proportionate space to every significant prong of the aqua-agro issue, the whole conceptual discussion is organized under three sub-topics: (1) the general concepts of sustainability and sustainable development; (2) the focused area of sustainable agricultural development; and (3) the sustainable use of groundwater as an irrigation resource. To highlight the gap in indigenous research literature, the literature review is also organized in two levels of literature: international and national.

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Khattak, A.S. (2014). Conceptual Framework and Literature Review. In: Mutual Sustainability of Tubewell Farming and Aquifers. Advances in Asian Human-Environmental Research. Springer, Cham. https://doi.org/10.1007/978-3-319-02804-0_2

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29 Conceptualization in qualitative research

Chapter outline

• 15.1 Alternative paradigms: Interpretivism, critical paradigm, and pragmatism

15.2 Multiparadigmatic research: An example

15.3 idiographic causal relationships, 15.4 qualitative research questions.

Now let’s change things up! In the previous chapters, we explored steps to create and carry out a quantitative research study. Quantitative studies are great when we want to summarize or test relationships between ideas using numbers and the power of statistics. However, qualitative research offers us a different and equally important tool. Sometimes the aim of research projects is to explore meaning and lived experience. Instead of trying to arrive at generalizable conclusions for all people, some research projects establish a deep, authentic description of a specific time, place, and group of people.

Qualitative research relies on the power of human expression through words, pictures, movies, performance and other artifacts that represent these things. All of these tell stories about the human experience and we want to learn from them and have them be represented in our research. Generally speaking, qualitative research is about the gathering up of these stories, breaking them into pieces so we can examine the ideas that make them up, and putting them back together in a way that allows us to tell a common or shared story that responds to our research question. To do that, we need to discuss the assumptions underlying social science.

17.1 Alternative paradigms: Interpretivism, critical, and pragmatism

Learning objectives.

Students will be able to…

• Distinguish between the assumptions of positivism, interpretivism, critical, and pragmatist research paradigms.
• Use paradigm to describe how scientific thought changes over time.

In Chapter 10, we reviewed the assumptions that underly post-positivism (abbreviated hereafter as positivism for brevity). Quantitative methods are most often the choice for positivist research questions because they conform to these assumptions. Qualitative methods  can conform to these assumptions; however, they are limited in their generalizability.

Kivunja & Kuyini (2017) [1] describe the essential features of positivism as:

• A belief that theory is universal and law-like generalizations can be made across contexts
• The assumption that context is not important
• The belief that truth or knowledge is ‘out there to be discovered’ by research
• The belief that cause and effect are distinguishable and analytically separable
• The belief that results of inquiry can be quantified
• The belief that theory can be used to predict and to control outcomes
• The belief that research should follow the scientific method of investigation
• Rests on formulation and testing of hypotheses
• Employs empirical or analytical approaches
• Pursues an objective search for facts
• Believes in ability to observe knowledge
• The researcher’s ultimate aim is to establish a comprehensive universal theory, to account for human and social behavior
• Application of the scientific method

Because positivism is the dominant social science research paradigm, it can be easy to ignore or be confused by research that does not use these assumptions. We covered in Chapter 10 the table reprinted below when discussing the assumptions underlying positivistic social science.

As you consider your research project, keep these philosophical assumptions in mind. They are useful shortcuts to understanding the deeper ideas and assumptions behind the construction of knowledge. The purpose of exploring these philosophical assumptions isn’t to find out which is true and which is false. Instead, the goal is to identify the assumptions that fit with how you think about your research question. Choosing a paradigm helps you make those assumptions explicit.

Before we explore alternative paradigms, it’s important for us to review what paradigms are.

How do scientific ideas change over time?

Much like your ideas develop over time as you learn more, so does the body of scientific knowledge. Kuhn’s (1962) [2] The Structure of Scientific Revolutions is one of the most influential works on the philosophy of science, and is credited with introducing the idea of competing paradigms (or “disciplinary matrices”) in research. Kuhn investigated the way that scientific practices evolve over time, arguing that we don’t have a simple progression from “less knowledge” to “more knowledge” because the way that we approach inquiry is changing over time. This can happen gradually, but the process results in moments of change where our understanding of a phenomenon changes more radically (such as in the transition from Newtonian to Einsteinian physics; or from Lamarckian to Darwinian theories of evolution). For a social work practice example, Fleuridas & Krafcik (2019) [3] trace the development of the “four forces” of psychotherapy , from psychodynamics to behaviorism to humanism as well as the competition among emerging perspectives to establish itself as the fourth force to guide psychotherapeutic practice. But how did the problems in one paradigm inspire new paradigms? Kuhn presents us with a way of understanding the history of scientific development across all topics and disciplines.

As you can see in this video from Matthew J. Brown (CC-BY), there are four stages in the cycle of science in Kuhn’s approach. Firstly, a pre-paradigmatic state where competing approaches share no consensus. Secondly, the “normal” state where there is wide acceptance of a particular set of methods and assumptions. Thirdly, a state of crisis where anomalies that cannot be solved within the existing paradigm emerge and competing theories to address them follow. Fourthly, a revolutionary phase where some new paradigmatic approach becomes dominant and supplants the old. Shnieder (2009) [4] suggests that the Kuhnian phases are characterized by different kinds of scientific activity.

Newer approaches often build upon rather than replace older ones, but they also overlap and can exist within a state of competition. Scientists working within a particular paradigm often share methods, assumptions and values. In addition to supporting specific methods, research paradigms also influence things like the ambition and nature of research, the researcher-participant relationship and how the role of the researcher is understood.

Paradigm vs. theory

The terms ‘ paradigm ‘ and ‘ theory ‘ are often used interchangeably in social science. There is not a consensus among social scientists as to whether these are identical or distinct concepts. With that said, in this text, we will make a clear distinction between the two ideas because thinking about each concept separately is more useful for our purposes.

We define paradigm a set of common philosophical (ontological, epistemological, and axiological) assumptions that inform research. The four paradigms we describe in this section refer to patterns in how groups of researchers resolve philosophical questions. Some assumptions naturally make sense together, and paradigms grow out of researchers with shared assumptions about what is important and how to study it. Paradigms are like “analytic lenses” and a provide framework on top of which we can build theoretical and empirical knowledge (Kuhn, 1962). [5] Consider this video of an interview with world-famous physicist Richard Feynman in which he explains why “when you explain a ‘why,’ you have to be in some framework that you allow something to be true. Otherwise, you are perpetually asking why.” In order to answer basic physics question like “what is happening when two magnets attract?” or a social work research question like “what is the impact of this therapeutic intervention on depression,” you must understand the assumptions you are making about social science and the social world. Paradigmatic assumptions about objective and subjective truth support methodological choices like whether to conduct interviews or send out surveys, for example.

While paradigms are broad philosophical assumptions, theory is more specific, and refers to a set of concepts and relationships scientists use to explain the social world. Theories are more concrete, while paradigms are more abstract. Look back to Figure 7.1 at the beginning of this chapter. Theory helps you identify the concepts and relationships that align with your paradigmatic understanding of the problem. Moreover, theory informs how you will measure the concepts in your research question and the design of your project.

For both theories and paradigms, Kuhn’s observation of scientific paradigms, crises, and revolutions is instructive for understanding the history of science. Researchers inherit institutions, norms, and ideas that are marked by the battlegrounds of theoretical and paradigmatic debates that stretch back hundreds of years. We have necessarily simplified this history into four paradigms: positivism, interpretivism, critical, and pragmatism. Our framework and explanation are inspired by the framework of Guba and Lincoln (1990) [6] and Burrell and Morgan (1979). [7] while also incorporating pragmatism as a way of resolving paradigmatic questions. Most of social work research and theory can be classified as belonging to one of these four paradigms, though this classification system represents only one of many useful approaches to analyzing social science research paradigms.

Building on our discussion in section 7.1 on objective vs. subjective epistemologies and ontologies, we will start with the difference between positivism and interpretivism. Afterward, we will link our discussion of axiology in section 7.2 with the critical paradigm. Finally, we will situate pragmatism as a way to resolve paradigmatic questions strategically. The difference between positivism and interpretivism is a good place to start, since the critical paradigm and pragmatism build on their philosophical insights.

It’s important to think of paradigms less as distinct categories and more as a spectrum along which projects might fall. For example, some projects may be somewhat positivist, somewhat interpretivist, and a little critical. No project fits perfectly into one paradigm. Additionally, there is no paradigm that is more correct than the other. Each paradigm uses assumptions that are logically consistent, and when combined, are a useful approach to understanding the social world using science. The purpose of this section is to acquaint you with what research projects in each paradigm look like and how they are grounded in philosophical assumptions about social science.

You should read this section to situate yourself in terms of what paradigm feels most “at home” to both you as a person and to your project. You may find, as I have, that your research projects are more conventional and less radical than what feels most like home to you, personally. In a research project, however, students should start with their working question rather than their heart. Use the paradigm that fits with your question the best, rather than which paradigm you think fits you the best.

Interpretivism: Researcher as “empathizer”

Positivism is focused on generalizable truth. Interpretivism , by contrast, develops from the idea that we want to understand the truths of individuals, how they interpret and experience the world, their thought processes, and the social structures that emerge from sharing those interpretations through language and behavior. The process of interpretation (or social construction) is guided by the empathy of the researcher to understand the meaning behind what other people say.

Historically, interpretivism grew out of a specific critique of positivism: that knowledge in the human and social sciences cannot conform to the model of natural science because there are features of human experience that cannot objectively be “known”. The tools we use to understand objects that have no self-awareness may not be well-attuned to subjective experiences like emotions, understandings, values, feelings, socio-cultural factors, historical influences, and other meaningful aspects of social life. Instead of finding a single generalizable “truth,” the interpretivist researcher aims to generate understanding and often adopts a relativist position.

While positivists seek “the truth,” the social constructionist framework argues that “truth” varies. Truth differs based on who you ask, and people change what they believe is true based on social interactions. These subjective truths also exist within social and historical contexts, and our understanding of truth varies across communities and time periods. This is because we, according to this paradigm, create reality ourselves through our social interactions and our interpretations of those interactions. Key to the interpretivist perspective is the idea that social context and interaction frame our realities.

Researchers operating within this framework take keen interest in how people come to socially agree, or disagree, about what is real and true. Consider how people, depending on their social and geographical context, ascribe different meanings to certain hand gestures. When a person raises their middle finger, those of us in Western cultures will probably think that this person isn’t very happy (not to mention the person at whom the middle finger is being directed!). In other societies around the world, a thumbs-up gesture, rather than a middle finger, signifies discontent (Wong, 2007). [8] The fact that these hand gestures have different meanings across cultures aptly demonstrates that those meanings are socially and collectively constructed. What, then, is the “truth” of the middle finger or thumbs up? As we’ve seen in this section, the truth depends on the intention of the person making the gesture, the interpretation of the person receiving it, and the social context in which the action occurred.

Qualitative methods are preferred as ways to investigate these phenomena. Data collected might be unstructured (or “messy”) and correspondingly a range of techniques for approaching data collection have been developed. Interpretivism acknowledges that it is impossible to remove cultural and individual influence from research, often instead making a virtue of the positionality of the researcher and the socio-cultural context of a study.

One common objection positivists levy against interpretivists is that interpretivism tends to emphasize the subjective over the objective. If the starting point for an investigation is that we can’t fully and objectively know the world, how can we do research into this without everything being a matter of opinion? For the positivist, this risk for confirmation bias as well as invalid and unreliable measures makes interpretivist research unscientific. Clearly, we disagree with this assessment, and you should, too. Positivism and interpretivism have different ontologies and epistemologies with contrasting notions of rigor and validity (for more information on assumptions about measurement, see Chapter 11 for quantitative validity and reliability and Chapter 20 for qualitative rigor). Nevertheless, both paradigms apply the values and concepts of the scientific method through systematic investigation of the social world, even if their assumptions lead them to do so in different ways. Interpretivist research often embraces a relativist epistemology, bringing together different perspectives in search of a trustworthy and authentic understanding or narrative.

Kivunja & Kuyini (2017) [9] describe the essential features of interpretivism as:

• The belief that truths are multiple and socially constructed
• The acceptance that there is inevitable interaction between the researcher and his or her research participants
• The acceptance that context is vital for knowledge and knowing
• The belief that knowledge can be value laden and the researcher’s values need to be made explicit
• The need to understand specific cases and contexts rather deriving universal laws that apply to everyone, everywhere.
• The belief that causes and effects are mutually interdependent, and that causality may be circular or contradictory
• The belief that contextual factors need to be taken into consideration in any systematic pursuit of understanding

One important clarification: it’s important to think of the interpretivist perspective as not just about individual interpretations but the social life of interpretations. While individuals may construct their own realities, groups—from a small one such as a married couple to large ones such as nations—often agree on notions of what is true and what “is” and what “is not.” In other words, the meanings that we construct have power beyond the individuals who create them. Therefore, the ways that people and communities act based on such meanings is of as much interest to interpretivists as how they were created in the first place. Theories like social constructionism, phenomenology, and symbolic interactionism are often used in concert with interpretivism.

Is interpretivism right for your project?

An interpretivist orientation to research is appropriate when your working question asks about subjective truths. The cause-and-effect relationships that interpretivist studies produce are specific to the time and place in which the study happened, rather than a generalizable objective truth. More pragmatically, if you picture yourself having a conversation with participants like an interview or focus group, then interpretivism is likely going to be a major influence for your study.

Positivists critique the interpretivist paradigm as non-scientific. They view the interpretivist focus on subjectivity and values as sources of bias. Positivists and interpretivists differ on the degree to which social phenomena are like natural phenomena. Positivists believe that the assumptions of the social sciences and natural sciences are the same, while interpretivists strongly believe that social sciences differ from the natural sciences because their subjects are social creatures.

Similarly, the critical paradigm finds fault with the interpretivist focus on the status quo rather than social change. Although interpretivists often proceed from a feminist or other standpoint theory, the focus is less on liberation than on understanding the present from multiple perspectives. Other critical theorists may object to the consensus orientation of interpretivist research. By searching for commonalities between people’s stories, they may erase the uniqueness of each individual’s story. For example, while interpretivists may arrive at a consensus definition of what the experience of “coming out” is like for people who identify as lesbian, gay, bisexual, transgender, or queer, it cannot represent the diversity of each person’s unique “coming out” experience and what it meant to them. For example, see Rosario and colleagues’ (2009) [10] critique the literature on lesbians “coming out” because previous studies did not addressing how appearing, behaving, or identifying as a butch or femme impacted the experience of “coming out” for lesbians.

• From your literature search, identify an empirical article that uses qualitative methods to answer a research question similar to your working question or about your research topic.
• Review the assumptions of the interpretivist research paradigm.
• Discuss in a few sentences how the author’s conclusions are based on some of these paradigmatic assumptions. How might a researcher operating from a different paradigm (like positivism or the critical paradigm) critique the conclusions of this study?

Critical paradigm: Researcher as “activist”

As we’ve discussed a bit in the preceding sections, the critical paradigm focuses on power, inequality, and social change. Although some rather diverse perspectives are included here, the critical paradigm, in general, includes ideas developed by early social theorists, such as Max Horkheimer (Calhoun et al., 2007), [11] and later works developed by feminist scholars, such as Nancy Fraser (1989). [12] Unlike the positivist paradigm, the critical paradigm assumes that social science can never be truly objective or value-free. Furthermore, this paradigm operates from the perspective that scientific investigation should be conducted with the express goal of social change. Researchers in the critical paradigm foreground axiology, positionality and values . In contrast with the detached, “objective” observations associated with the positivist researcher, critical approaches make explicit the intention for research to act as a transformative or emancipatory force within and beyond the study.

Researchers in the critical paradigm might start with the knowledge that systems are biased against certain groups, such as women or ethnic minorities, building upon previous theory and empirical data. Moreover, their research projects are designed not only to collect data, but to impact the participants as well as the systems being studied. The critical paradigm applies its study of power and inequality to change those power imbalances as part of the research process itself. If this sounds familiar to you, you may remember hearing similar ideas when discussing social conflict theory in your human behavior in the social environment (HBSE) class. [13] Because of this focus on social change, the critical paradigm is a natural home for social work research. However, we fall far short of adopting this approach widely in our profession’s research efforts.

Is the critical paradigm right for your project?

Every social work research project impacts social justice in some way. What distinguishes critical research is how it integrates an analysis of power into the research process itself. Critical research is appropriate for projects that are activist in orientation. For example, critical research projects should have working questions that explicitly seek to raise the consciousness of an oppressed group or collaborate equitably with community members and clients to addresses issues of concern. Because of their transformative potential, critical research projects can be incredibly rewarding to complete. However, partnerships take a long time to develop and social change can evolve slowly on an issue, making critical research projects a more challenging fit for student research projects which must be completed under a tight deadline with few resources.

Positivists critique the critical paradigm on multiple fronts. First and foremost, the focus on oppression and values as part of the research process is seen as likely to bias the research process, most problematically, towards confirmation bias. If you start out with the assumption that oppression exists and must be dealt with, then you are likely to find that regardless of whether it is truly there or not. Similarly, positivists may fault critical researchers for focusing on how the world should be, rather than how it truly is . In this, they may focus too much on theoretical and abstract inquiry and less on traditional experimentation and empirical inquiry. Finally, the goal of social transformation is seen as inherently unscientific, as science is not a political practice.

Interpretivists often find common cause with critical researchers. Feminist studies, for example, may explore the perspectives of women while centering gender-based oppression as part of the research process. In interpretivist research, the focus is less on radical change as part of the research process and more on small, incremental changes based on the results and conclusions drawn from the research project. Additionally, some critical researchers’ focus on individuality of experience is in stark contrast to the consensus-orientation of interpretivists. Interpretivists seek to understand people’s true selves. Some critical theorists argue that people have multiple selves or no self at all.

• From your literature search, identify an article relevant to your working question or broad research topic that uses a critical perspective. You should look for articles where the authors are clear that they are applying a critical approach to research like feminism, anti-racism, Marxism and critical theory, decolonization, anti-oppressive practice, or other social justice-focused theoretical perspectives. To target your search further, include keywords in your queries to research methods commonly used in the critical paradigm like participatory action research and community-based participatory research. If you have trouble identifying an article for this exercise, consult your professor for some help. These articles may be more challenging to find, but reviewing one is necessary to get a feel for what research in this paradigm is like.
• Review the assumptions of the critical research paradigm.
• Discuss in a few sentences how the author’s conclusions are based on some of these paradigmatic assumptions. How might a researcher operating from different assumptions (like values-neutrality or researcher as neutral and unbiased) critique the conclusions of this study?

Pragmatism: Researcher as “strategist”

“Essentially, all models are wrong but some are useful.” (Box, 1976) [14]

Pragmatism is a research paradigm that suspends questions of philosophical ‘truth’ and focuses more on how different philosophies, theories, and methods can be used strategically to provide a multidimensional view of a topic. Researchers employing pragmatism will mix elements of positivist, interpretivist, and critical research depending on the purpose of a particular project and the practical constraints faced by the researcher and their research context. We favor this approach for student projects because it avoids getting bogged down in choosing the “right” paradigm and instead focuses on the assumptions that help you answer your question, given the limitations of your research context. Student research projects are completed quickly and moving in the direction of pragmatism can be a route to successfully completing a project. Your project is a representation of what you think is feasible, ethical, and important enough for you to study.

The crucial consideration for the pragmatist is whether the outcomes of research have any real-world application, rather than whether they are “true.” The methods, theories, and philosophies chosen by pragmatic researchers are guided by their working question. There are no distinctively pragmatic research methods since this approach is about making judicious use whichever methods fit best with the problem under investigation. Pragmatic approaches may be less likely to prioritize ontological, epistemological or axiological consistency when combining different research methods. Instead, the emphasis is on solving a pressing problem and adapting to the limitations and opportunities in the researchers’ context.

Adopt a multi-paradigmatic perspective

Believe it or not, there is a long literature of acrimonious conflict between scientists from positivist, interpretivist, and critical camps (see Heineman-Pieper et al., 2002 [15] for a longer discussion). Pragmatism is an old idea, but it is appealing precisely because it attempts to resolve the problem of multiple incompatible philosophical assumptions in social science. To a pragmatist, there is no “correct” paradigm. All paradigms rely on assumptions about the social world that are the subject of philosophical debate. Each paradigm is an incomplete understanding of the world, and it requires a scientific community using all of them to gain a comprehensive view of the social world. This multi-paradigmatic perspective is a unique gift of social work research, as our emphasis on empathy and social change makes us more critical of positivism, the dominant paradigm in social science.

We offered the metaphors of expert, empathizer, activist, and strategist for each paradigm. It’s important not to take these labels too seriously. For example, some may view that scientists should be experts or that activists are biased and unscientific. Nevertheless, we hope that these metaphors give you a sense of what it feels like to conduct research within each paradigm.

One of the unique aspects of paradigmatic thinking is that often where you think you are most at home may actually be the opposite of where your research project is. For example, in my graduate and doctoral education, I thought I was a critical researcher. In fact, I thought I was a radical researcher focused on social change and transformation. Yet, often times when I sit down to conceptualize and start a research project, I find myself squarely in the positivist paradigm, thinking through neat cause-and-effect relationships that can be mathematically measured. There is nothing wrong with that! Your task for your research project is to find the paradigm that best matches your research question. Think through what you really want to study and how you think about the topic, then use assumptions of that paradigm to guide your inquiry.

Another important lesson is that no research project fits perfectly in one paradigm or another. Instead, there is a spectrum along which studies are, to varying degrees, interpretivist, positivist, and critical. For example, all social work research is a bit activist in that our research projects are designed to inform action for change on behalf of clients and systems. However, some projects will focus on the conclusions and implications of projects informing social change (i.e., positivist and interpretivist projects) while others will partner with community members and design research projects collaboratively in a way that leads to social change (i.e. critical projects). In section 7.5, we will describe a pragmatic approach to research design guided by your paradigmatic and theoretical framework.

Key Takeaways

• Social work research falls, to some degree, in each of the four paradigms: positivism, interpretivism, critical, and pragmatist.
• Adopting a pragmatic, multi-paradigmatic approach to research makes sense for student researchers, as it directs students to use the philosophical assumptions and methodological approaches that best match their research question and research context.
• Research in all paradigms is necessary to come to a comprehensive understanding of a topic, and social workers must be able to understand and apply knowledge from each research paradigm.
• Describe which paradigm best fits your perspective on the world and which best fits with your project.
• Identify any similarities and differences in your personal assumptions and the assumption your research project relies upon. For example, are you a more critical and radical thinker but have chosen a more “expert” role for yourself in your research project?

Learners will be able to…

• Apply the assumptions of each paradigm to your project
• Summarize what aspects of your project stem from positivist, interpretivist, or critical assumptions

In the previous sections, we reviewed the major paradigms and theories in social work research. In this section, we will provide an example of how to apply theory and paradigm in research. This process is depicted in Figure 7.2 below with some quick summary questions for each stage. Some questions in the figure below have example answers like designs (i.e., experimental, survey) and data analysis approaches (i.e., discourse analysis). These examples are arbitrary. There are a lot of options that are not listed. So, don’t feel like you have to memorize them or use them in your study.

This diagram (taken from an archived Open University (UK) course entitled E89 ​- Educational Inquiry ) ​ shows one way to visualize the research design process. While research is far from linear, in general, this is how research projects progress sequentially. Researchers begin with a working question, and through engaging with the literature, develop and refine those questions into research questions (a process we will finalize in Chapter 9 ). But in order to get to the part where you gather your sample, measure your participants, and analyze your data, you need to start with paradigm. Based on your work in section 7.3, you should have a sense of which paradigm or paradigms are best suited to answering your question. The approach taken will often reflect the nature of the research question; the kind of data it is possible to collect; and work previously done in the area under consideration. When evaluating paradigm and theory, it is important to look at what other authors have done previously and the framework used by studies that are similar to the one you are thinking of conducting.

Once you situate your project in a research paradigm, it becomes possible to start making concrete choices about methods. Depending on the project, this will involve choices about things like:

• What is my final research question?
• What are the key variables and concepts under investigation, and how will I measure them?
• How do I find a representative sample of people who experience the topic I’m studying?
• What design is most appropriate for my research question?
• How will I collect and analyze data?
• How do I determine whether my results describe real patterns in the world or are the result of bias or error?

The data collection phase can begin once these decisions are made. It can be very tempting to start collecting data as soon as possible in the research process as this gives a sense of progress. However, it is usually worth getting things exactly right before collecting data as an error found in your approach further down the line can be harder to correct or recalibrate around.

Designing a study using paradigm and theory: An example

Paradigm and theory have the potential to turn some people off since there is a lot of abstract terminology and thinking about real-world social work practice contexts. In this section, I’ll use an example from my own research, and I hope it will illustrate a few things. First, it will show that paradigms are really just philosophical statements about things you already understand and think about normally. It will also show that no project neatly sits in one paradigm and that a social work researcher should use whichever paradigm or combination of paradigms suit their question the best. Finally, I hope it is one example of how to be a pragmatist and strategically use the strengths of different theories and paradigms to answering a research question. We will pick up the discussion of mixed methods in the next chapter.

Thinking as an expert: Positivism

In my undergraduate research methods class, I used an open textbook much like this one and wanted to study whether it improved student learning. You can read a copy of the article we wrote on based on our study . We’ll learn more about the specifics of experiments and evaluation research in Chapter 13 , but you know enough to understand what evaluating an intervention might look like. My first thought was to conduct an experiment, which placed me firmly within the positivist or “expert” paradigm.

Experiments focus on isolating the relationship between cause and effect. For my study, this meant studying an open textbook (the cause, or intervention) and final grades (the effect, or outcome). Notice that my position as “expert” lets me assume many things in this process. First, it assumes that I can distill the many dimensions of student learning into one number—the final grade. Second, as the “expert,” I’ve determined what the intervention is: indeed, I created the book I was studying, and applied a theory from experts in the field that explains how and why it should impact student learning.

Theory is part of applying all paradigms, but I’ll discuss its impact within positivism first. Theories grounded in positivism help explain why one thing causes another. More specifically, these theories isolate a causal relationship between two (or more) concepts while holding constant the effects of other variables that might confound the relationship between the key variables. That is why experimental design is so common in positivist research. The researcher isolates the environment from anything that might impact or bias the cause and effect relationship they want to investigate.

But in order for one thing to lead to change in something else, there must be some logical, rational reason why it would do so. In open education, there are a few hypotheses (though no full-fledged theories) on why students might perform better using open textbooks. The most common is the access hypothesis , which states that students who cannot afford expensive textbooks or wouldn’t buy them anyway can access open textbooks because they are free, which will improve their grades. It’s important to note that I held this theory prior to starting the experiment, as in positivist research you spell out your hypotheses in advance and design an experiment to support or refute that hypothesis.

Notice that the hypothesis here applies not only to the people in my experiment, but to any student in higher education. Positivism seeks generalizable truth, or what is true for everyone. The results of my study should provide evidence that  anyone  who uses an open textbook would achieve similar outcomes. Of course, there were a number of limitations as it was difficult to tightly control the study. I could not randomly assign students or prevent them from sharing resources with one another, for example. So, while this study had many positivist elements, it was far from a perfect positivist study because I was forced to adapt to the pragmatic limitations of my research context (e.g., I cannot randomly assign students to classes) that made it difficult to establish an objective, generalizable truth.

Thinking like an empathizer: Interpretivism

One of the things that did not sit right with me about the study was the reliance on final grades to signify everything that was going on with students. I added another quantitative measure that measured research knowledge, but this was still too simplistic. I wanted to understand how students used the book and what they thought about it. I could create survey questions that ask about these things, but to get at the subjective truths here, I thought it best to use focus groups in which students would talk to one another with a researcher moderating the discussion and guiding it using predetermined questions. You will learn more about focus groups in Chapter 18 .

Researchers spoke with small groups of students during the last class of the semester. They prompted people to talk about aspects of the textbook they liked and didn’t like, compare it to textbooks from other classes, describe how they used it, and so forth. It was this focus on  understanding and subjective experience that brought us into the interpretivist paradigm. Alongside other researchers, I created the focus group questions but encouraged researchers who moderated the focus groups to allow the conversation to flow organically.

We originally started out with the assumption, for which there is support in the literature, that students would be angry with the high-cost textbook that we used prior to the free one, and this cost shock might play a role in students’ negative attitudes about research. But unlike the hypotheses in positivism, these are merely a place to start and are open to revision throughout the research process. This is because the researchers are not the experts, the participants are! Just like your clients are the experts on their lives, so were the students in my study. Our job as researchers was to create a group in which they would reveal their informed thoughts about the issue, coming to consensus around a few key themes.

When we initially analyzed the focus groups, we uncovered themes that seemed to fit the data. But the overall picture was murky. How were themes related to each other? And how could we distill these themes and relationships into something meaningful? We went back to the data again. We could do this because there isn’t one truth, as in positivism, but multiple truths and multiple ways of interpreting the data. When we looked again, we focused on some of the effects of having a textbook customized to the course. It was that customization process that helped make the language more approachable, engaging, and relevant to social work practice.

Ultimately, our data revealed differences in how students perceived a free textbook versus a free textbook that is customized to the class. When we went to interpret this finding, the remix  hypothesis of open textbook was helpful in understanding that relationship. It states that the more faculty incorporate editing and creating into the course, the better student learning will be. Our study helped flesh out that theory by discussing the customization process and how students made sense of a customized resource.

In this way, theoretical analysis operates differently in interpretivist research. While positivist research tests existing theories, interpretivist research creates theories based on the stories of research participants. However, it is difficult to say if this theory was totally emergent in the dataset or if my prior knowledge of the remix hypothesis influenced my thinking about the data. Interpretivist researchers are encouraged to put a box around their prior experiences and beliefs, acknowledging them, but trying to approach the data with fresh eyes. Interpretivists know that this is never perfectly possible, though, as we are always influenced by our previous experiences when interpreting data and conducting scientific research projects.

Thinking like an activist: Critical

Although adding focus groups helped ease my concern about reducing student learning down to just final grades by providing a more rich set of conversations to analyze. However, my role as researcher and “expert” was still an important part of the analysis. As someone who has been out of school for a while, and indeed has taught this course for years, I have lost touch with what it is like to be a student taking research methods for the first time. How could I accurately interpret or understand what students were saying? Perhaps I would overlook things that reflected poorly on my teaching or my book. I brought other faculty researchers on board to help me analyze the data, but this still didn’t feel like enough.

By luck, an undergraduate student approached me about wanting to work together on a research project. I asked her if she would like to collaborate on evaluating the textbook with me. Over the next year, she assisted me with conceptualizing the project, creating research questions, as well as conducting and analyzing the focus groups. Not only would she provide an “insider” perspective on coding the data, steeped in her lived experience as a student, but she would serve as a check on my power through the process.

Including people from the group you are measuring as part of your research team is a common component of critical research. Ultimately, critical theorists would find my study to be inadequate in many ways. I still developed the research question, created the intervention, and wrote up the results for publication, which privileges my voice and role as “expert.” Instead, critical theorists would emphasize the role of students (community members) in identifying research questions, choosing the best intervention to used, and so forth. But collaborating with students as part of a research team did address some of the power imbalances in the research process.

Critical research projects also aim to have an impact on the people and systems involved in research. No students or researchers had profound personal realizations as a result of my study, nor did it lessen the impact of oppressive structures in society. I can claim some small victory that my department switched to using my textbook after the study was complete (changing a system), though this was likely the result of factors other than the study (my advocacy for open textbooks).

Social work research is almost always designed to create change for people or systems. To that end, every social work project is at least somewhat critical. However, the additional steps of conducting research with people rather than on people reveal a depth to the critical paradigm. By bringing students on board the research team, study had student perspectives represented in conceptualization, data collection, and analysis. That said, there was much to critique about this study from a critical perspective. I retained a lot of the power in the research process, and students did not have the ability to determine the research question or purpose of the project. For example, students might likely have said that textbook costs and the quality of their research methods textbook were less important than student debt, racism, or other potential issues experienced by students in my class. Instead of a ground-up research process based in community engagement, my research included some important participation by students on project created and led by faculty.

Conceptualization is an iterative process

I hope this conversation was useful in applying paradigms to a research project. While my example discusses education research, the same would apply for social work research about social welfare programs, clinical interventions, or other topics. Paradigm and theory are covered at the beginning of the conceptualization of your project because these assumptions will structure the rest of your project. Each of the research steps that occur after this chapter (e.g., forming a question, choosing a design) rely upon philosophical and theoretical assumptions. As you continue conceptualizing your project over the next few weeks, you may find yourself shifting between paradigms. That is normal, as conceptualization is not a linear process. As you move through the next steps of conceptualizing and designing a project, you’ll find philosophies and theories that best match how you want to study your topic.

Viewing theoretical and empirical arguments through this lens is one of the true gifts of the social work approach to research. The multi-paradigmatic perspective is a hallmark of social work research and one that helps us contribute something unique on research teams and in practice.

• Multi-paradigmatic research is a distinguishing hallmark of social work research. Understanding the limitations and strengths of each paradigm will help you justify your research approach and strategically choose elements from one or more paradigms to answer your question.
• Paradigmatic assumptions help you understand the “blind spots” in your research project and how to adjust and address these areas. Keep in mind, it is not necessary to address all of your blind spots, as all projects have limitations.
• Sketch out which paradigm applies best to your project. Second, building on your answer to the exercise in section 7.3, identify how the theory you chose and the paradigm in which you find yourself are consistent or are in conflict with one another. For example, if you are using systems theory in a positivist framework, you might talk about how they both rely on a deterministic approach to human behavior with a focus on the status-quo and social order.
• Define and provide an example of an idiographic causal explanation
• Differentiate between idiographic and nomothetic causal relationships
• Link idiographic and nomothetic causal relationships with the process of theory building and theory testing
• Describe how idiographic and nomothetic causal explanations can be complementary

As we transition away from positivism, it is important to highlight the assumptions it makes about the scientific process–the hypothetico-deductive method, sometimes referred to as the research circle.

The hypothetico-deductive method

The primary way that researchers in the positivist paradigm use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers choose an existing theory. Then, they make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary.

This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 8.8 shows, this approach meshes nicely with the process of conducting a research project—creating a more detailed model of “theoretically motivated” or “theory-driven” research. Together, they form a model of theoretically motivated research. 

Keep in mind the hypothetico-deductive method is only one way of using social theory to inform social science research. It starts with describing one or more existing theories, deriving a hypothesis from one of those theories, testing your hypothesis in a new study, and finally reevaluating the theory based on the results data analyses. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

But what if your research question is more interpretive? What if it is less about theory-testing and more about theory-building? This is what our next chapter covers: the process of inductively deriving theory from people’s stories and experiences. This process looks different than that depicted in Figure 8.8. It still starts with your research question and answering that question by conducting a research study. But instead of testing a hypothesis you created based on a theory, you will create a theory of your own that explain the data you collected. This format works well for qualitative research questions and for research questions that existing theories do not address.

Inductive reasoning is most commonly found in studies using qualitative methods, such as focus groups and interviews. Because inductive reasoning involves the creation of a new theory, researchers need very nuanced data on how the key concepts in their working question operate in the real world. Qualitative data is often drawn from lengthy interactions and observations with the individuals and phenomena under examination. For this reason, inductive reasoning is most often associated with qualitative methods, though it is used in both quantitative and qualitative research.

Whose truth does science establish?

Social work is concerned with the “isms” of oppression (ableism, ageism, cissexism, classism, heterosexism, racism, sexism, etc.), and so our approach to science must reconcile its history as both a tool of oppression and its exclusion of oppressed groups. Science grew out of the Enlightenment, a philosophical movement which applied reason and empirical analysis to understanding the world. While the Enlightenment brought forth tremendous achievements, the critiques of Marxian, feminist, and other critical theorists complicated the Enlightenment understanding of science. For this section, I will focus on feminist critiques of science, building upon an entry in the Stanford Encyclopedia of Philosophy (Crasnow, 2020). [16]

In its original formulation, science was an individualistic endeavor. As we learned in Chapter 1 , a basic statement of the scientific method is that a researcher studies existing theories on a topic, formulates a hypothesis about what might be true, and either confirms or disconfirms their hypothesis through experiment and rigorous observation. Over time, our theories become more accurate in their predictions and more comprehensive in their conclusions. Scientists put aside their preconceptions, look at the data, and build their theories based on objective rationality.

Yet, this cannot be perfectly true. Scientists are human, after all. As a profession historically dominated by white men, scientists have dismissed women and other minorities as being psychologically unfit for the scientific profession. While attitudes have improved, science, technology, engineering, mathematics (STEM) and related fields remain dominated by white men (Grogan, 2019). [17] Biases can persist in social work theory and research when social scientists do not have similar experiences to the populations they study.

Gender bias can influence the research questions scientists choose to answer. Feminist critiques of medical science drew attention to women’s health issues, spurring research and changing standards of care. The focus on domestic violence in the empirical literature can also be seen as a result of feminist critique. Thus, critical theory helps us critique what is on the agenda for science. If science is to answer important questions, it must speak to the concerns of all people. Through the democratization in access to scientific knowledge and the means to produce it, science becomes a sister process of social development and social justice.

The goal of a diverse and participatory scientific community lies in contrast to much of what we understand to be “proper” scientific knowledge. Many of the older, classic social science theories were developed based on research which observed males or from university students in the United States or other Western nations. How these observations were made, what questions were asked, and how the data were interpreted were shaped by the same oppressive forces that existed in broader society, a process that continues into the present. In psychology, the concept of hysteria or hysterical women was believed to be caused by a wandering womb (Tasca et al., 2012). [18] Even today, there are gender biases in diagnoses of histrionic personality disorder and racial biases in psychotic disorders (Klonsky et al., 2002) [19] because the theories underlying them were created in a sexist and racist culture. In these ways, science can reinforce the truth of the white Western male perspective.

Finally, it is important to note that social science research is often conducted on populations rather than with populations. Historically, this has often meant Western men traveling to other countries and seeking to understand other cultures through a Western lens. Lacking cultural humility and failing to engage stakeholders, ethnocentric research of this sort has led to the view of non-Western cultures as inferior. Moreover, the use of these populations as research subjects rather than co-equal participants in the research process privileges the researcher’s knowledge over that from other groups or cultures. Researchers working with indigenous cultures, in particular, had a destructive habit of conducting research for a short time and then leaving, without regard for the impact their study had on the population. These critiques of Western science aim to decolonize social science and dismantle the racist ideas the oppress indigenous and non-Western peoples through research (Smith, 2013). [20]

The central concept in feminist, anti-racist, and decolonization critiques (among other critical frames) is epistemic injustice. Epistemic injustice happens when someone is treated unfairly in their capacity to know something or describe their experience of the world. As described by Fricker (2011), [21] the injustice emerges from the dismissal of knowledge from oppressed groups, discrimination against oppressed groups in scientific communities, and the resulting gap between what scientists can make sense of from their experience and the experiences of people with less power who have lived experience of the topic. We recommend this video from Edinburgh Law School which applies epistemic injustice to studying public health emergencies, disabilities, and refugee services .

Positivism relies on nomothetic causality, or the idea that “one event, behavior, or belief will result in the occurrence of another, subsequent event, behavior, or belief.” Then, we described one kind of causality: a simple cause-and-effect relationship supported by existing theory and research on the topic, also known as a nomothetic causal relationship. But what if there is not a lot of literature on your topic? What if your question is more exploratory than explanatory? Then, you need a different kind of causal explanation, one that accounts for the complexity of human interactions.

How can we build causal relationships if we are just describing or exploring a topic? Recall the definitions of exploratory research , descriptive research , and explanatory research from Chapter 2. Wouldn’t we need to do explanatory research to build any kind of causal explanation? Explanatory research attempts to establish nomothetic causal relationships: an independent variable is demonstrated to cause change in a dependent variable. Exploratory and descriptive qualitative research contains some causal relationships, but they are actually descriptions of the causal relationships established by the study participants.

What do idiographic causal explanations look like?

An idiographic causal relationship   tries to identify the many, interrelated causes that account for the phenomenon the researcher is investigating. So, if idiographic causal explanations do not look like Figure 8.5, 8.6, or 8.7 what do they look like? Instead of saying “x causes y,” your participants will describe their experiences with “x,” which they will tell you was caused and influenced by a variety of other factors, as interpreted through their unique perspective, time, and environment. As we stated before, idiographic causal explanations are messy. Your job as a social science researcher is to accurately describe the patterns in what your participants tell you.

Let’s think about this using an example. If I asked you why you decided to become a social worker, what might you say? For me, I would say that I wanted to be a mental health clinician since I was in high school. I was interested in how people thought, and I was privileged enough to have psychology courses at my local high school. I thought I wanted to be a psychologist, but at my second internship in my undergraduate program, my supervisors advised me to become a social worker because the license provided greater authority for independent practice and flexibility for career change. Once I found out social workers were like psychologists who also raised trouble about social justice, I was hooked.

That’s not a simple explanation at all! But it’s definitely a causal explanation. It is my individual, subjective truth of a complex process. If we were to ask multiple social workers the same question, we might find out that many social workers begin their careers based on factors like personal experience with a disability or social injustice, positive experiences with social workers, or a desire to help others. No one factor is the “most important factor,” like with nomothetic causal relationships. Instead, a complex web of factors, contingent on context, emerge when you interpret what people tell you about their lives.

Understanding “why?”

In creating an idiographic explanation, you are still asking “why?” But the answer is going to be more complex. Those complexities are described in Table 8.1 as well as this short video comparing nomothetic and idiographic relationships .

Remember our question from the last section, “Are you trying to generalize or nah?” If you answered nah (or no, like a normal person), you are trying to establish an idiographic causal explanation. The purpose of that explanation isn’t to predict the future or generalize to larger populations, but to describe the here-and-now as it is experienced by individuals within small groups and communities. Idiographic explanations are focused less on what is generally experienced by all people but more on the particularities of what specific individuals in a unique time and place experience.

Researchers seeking idiographic causal relationships are not trying to generalize or predict, so they have no need to reduce phenomena to mathematics. In fact, only examining things that can be counted can rob a causal relationship of its meaning and context. Instead, the goal of idiographic causal relationships is understanding, rather than prediction. Idiographic causal relationships are formed by interpreting people’s stories and experiences. Usually, these are expressed through words. Not all qualitative studies use word data, as some can use interpretations of visual or performance art. However, the vast majority of qualitative studies do use word data, like the transcripts from interviews and focus groups or documents like journal entries or meeting notes. Your participants are the experts on their lives—much like in social work practice—and as in practice, people’s experiences are embedded in their cultural, historical, and environmental context.

Idiographic causal explanations are powerful because they can describe the complicated and interconnected nature of human life. Nomothetic causal explanations, by comparison, are simplistic. Think about if someone asked you why you wanted to be a social worker. Your story might include a couple of vignettes from your education and early employment. It might include personal experience with the social welfare system or family traditions. Maybe you decided on a whim to enroll in a social work course during your graduate program. The impact of each of these events on your career is unique to you.

Idiographic causal explanations are concerned with individual stories, their idiosyncrasies, and the patterns that emerge when you collect and analyze multiple people’s stories. This is the inductive reasoning we discussed at the beginning of this chapter. Often, idiographic causal explanations begin by collecting a lot of qualitative data, whether though interviews, focus groups, or looking at available documents or cultural artifacts. Next, the researcher looks for patterns in the data and arrives at a tentative theory for how the key ideas in people’s stories are causally related.

Unlike nomothetic causal relationships, there are no formal criteria (e.g., covariation) for establishing causality in idiographic causal relationships. In fact, some criteria like temporality and nonspuriousness may be violated. For example, if an adolescent client says, “It’s hard for me to tell whether my depression began before my drinking, but both got worse when I was expelled from my first high school,” they are recognizing that it may not so simple that one thing causes another. Sometimes, there is a reciprocal relationship where one variable (depression) impacts another (alcohol abuse), which then feeds back into the first variable (depression) and into other variables as well (school). Other criteria, such as covariation and plausibility, still make sense, as the relationships you highlight as part of your idiographic causal explanation should still be plausible and its elements should vary together.

Theory building and theory testing

As we learned in the previous section, nomothetic causal explanations are created by researchers applying deductive reasoning to their topic and creating hypotheses using social science theories. Much of what we think of as social science is based on this hypothetico-deductive method, but this leaves out the other half of the equation. Where do theories come from? Are they all just revisions of one another? How do any new ideas enter social science?

Through inductive reasoning and idiographic causal explanations!

Let’s consider a social work example. If you plan to study domestic and sexual violence, you will likely encounter the Power and Control Wheel, also known as the Duluth Model (Figure 8.9). The wheel is a model designed to depict the process of domestic violence. The wheel was developed based on qualitative focus groups conducted by sexual and domestic violence advocates in Duluth, MN. This video explains more about the Duluth Model of domestic abuse.

The Power and Control Wheel is an example of what an idiographic causal relationship looks like. By contrast, look back at the previous section’s Figure 8.5, 8.6, and 8.7 on nomothetic causal relationships between independent and dependent variables. See how much more complex idiographic causal explanations are?! They are complex, but not difficult to understand. At the center of domestic abuse is power and control, and while not every abuser would say that is what they were doing, that is the understanding of the survivors who informed this theoretical model. Their power and control is maintained through a variety of abusive tactics from social isolation to use of privilege to avoid consequences.

What about the role of hypotheses in idiographic causal explanations? In nomothetic causal explanations, researchers create hypotheses using existing theory and then test them for accuracy. Hypotheses in idiographic causality are much more tentative, and are probably best considered as “hunches” about what they think might be true. Importantly, they might indicate the researcher’s prior knowledge and biases before the project begins, but the goal of idiographic research is to let your participants guide you rather than existing social work knowledge. Continuing with our Duluth Model example, advocates likely had some tentative hypotheses about what was important in a relationship with domestic violence. After all, they worked with this population for years prior to the creation of the model. However, it was the stories of the participants in these focus groups that led the Power and Control Wheel explanation for domestic abuse.

As qualitative inquiry unfolds, hypotheses and hunches are likely to emerge and shift as researchers learn from what their participants share. Because the participants are the experts in idiographic causal relationships, a researcher should be open to emerging topics and shift their research questions and hypotheses accordingly. This is in contrast to hypotheses in quantitative research, which remain constant throughout the study and are shown to be true or false.

Over time, as more qualitative studies are done and patterns emerge across different studies and locations, more sophisticated theories emerge that explain phenomena across multiple contexts. Once a theory is developed from qualitative studies, a quantitative researcher can seek to test that theory. For example, a quantitative researcher may hypothesize that men who hold traditional gender roles are more likely to engage in domestic violence. That would make sense based on the Power and Control Wheel model, as the category of “using male privilege” speaks to this relationship. In this way, qualitatively-derived theory can inspire a hypothesis for a quantitative research project, as we will explore in the next section.

Complementary approaches

If idiographic and nomothetic still seem like obscure philosophy terms, let’s consider another example. Imagine you are working for a community-based non-profit agency serving people with disabilities. You are putting together a report to lobby the state government for additional funding for community support programs. As part of that lobbying, you are likely to rely on both nomothetic and idiographic causal relationships.

If you looked at nomothetic causal relationships, you might learn how previous studies have shown that, in general, community-based programs like yours are linked with better health and employment outcomes for people with disabilities. Nomothetic causal explanations seek to establish that community-based programs are better for everyone with disabilities, including people in your community.

If you looked at idiographic causal explanations, you would use stories and experiences of people in community-based programs. These individual stories are full of detail about the lived experience of being in a community-based program. You might use one story from a client in your lobbying campaign, so policymakers can understand the lived experience of what it’s like to be a person with a disability in this program. For example, a client who said “I feel at home when I’m at this agency because they treat me like a family member,” or “this is the agency that helped me get my first paycheck,” can communicate richer, more complex causal relationships.

Neither kind of causal explanation is better than the other. A decision to seek idiographic causal explanations means that you will attempt to explain or describe your phenomenon exhaustively, attending to cultural context and subjective interpretations. A decision to seek nomothetic causal explanations, on the other hand, means that you will try to explain what is true for everyone and predict what will be true in the future. In short, idiographic explanations have greater depth, and nomothetic explanations have greater breadth.

Most importantly, social workers understand the value of both approaches to understanding the social world. A social worker helping a client with substance abuse issues seeks idiographic explanations when they ask about that client’s life story, investigate their unique physical environment, or probe how their family relationships. At the same time, a social worker also uses nomothetic explanations to guide their interventions. Nomothetic explanations may help guide them to minimize risk factors and maximize protective factors or use an evidence-based therapy, relying on knowledge about what in general  helps people with substance abuse issues.

So, which approach speaks to you? Are you interested in learning about (a) a few people’s experiences in a great deal of depth, or (b) a lot of people’s experiences more superficially, while also hoping your findings can be generalized to a greater number of people? The answer to this question will drive your research question and project. These approaches provide different types of information and both types are valuable.

• Idiographic causal explanations focus on subjectivity, context, and meaning.
• Idiographic causal explanations are best suited to exploratory research questions and qualitative methods.
• Idiographic causal explanations are used to create new theories in social science.
• Explore the literature on the theory you identified in section 8.1.
• Read about the origins of your theory. Who developed it and from what data?
• See if you can find a figure like Figure 8.9 in an article or book chapter that depicts the key concepts in your theory and how those concepts are related to one another causally. Write out a short statement on the causal relationships contained in the figure.
• List the key terms associated with qualitative research questions
• Distinguish between qualitative and quantitative research questions

Qualitative research questions differ from quantitative research questions. Because qualitative research questions seek to explore or describe phenomena, not provide a neat nomothetic explanation, they are often more general and openly worded. They may include only one concept, though many include more than one. Instead of asking how one variable causes changes in another, we are instead trying to understand the experiences ,  understandings , and  meanings that people have about the concepts in our research question. These keywords often make an appearance in qualitative research questions.

Let’s work through an example from our last section. In Table 9.1, a student asked, “What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care?” In this question, it is pretty clear that the student believes that adolescents in foster care who identify as LGBTQ+ may be at greater risk for homelessness. This is a nomothetic causal relationship—LGBTQ+ status causes changes in homelessness.

However, what if the student were less interested in  predicting  homelessness based on LGBTQ+ status and more interested in  understanding  the stories of foster care youth who identify as LGBTQ+ and may be at risk for homelessness? In that case, the researcher would be building an idiographic causal explanation . The youths whom the researcher interviews may share stories of how their foster families, caseworkers, and others treated them. They may share stories about how they thought of their own sexuality or gender identity and how it changed over time. They may have different ideas about what it means to transition out of foster care.

Because qualitative questions usually center on idiographic causal relationships, they look different than quantitative questions. Table 9.3 below takes the final research questions from Table 9.1 and adapts them for qualitative research. The guidelines for research questions previously described in this chapter still apply, but there are some new elements to qualitative research questions that are not present in quantitative questions.

• Qualitative research questions often ask about lived experience, personal experience, understanding, meaning, and stories.
• Qualitative research questions may be more general and less specific.
• Qualitative research questions may also contain only one variable, rather than asking about relationships between multiple variables.

Qualitative research questions have one final feature that distinguishes them from quantitative research questions: they can change over the course of a study. Qualitative research is a reflexive process, one in which the researcher adapts their approach based on what participants say and do. The researcher must constantly evaluate whether their question is important and relevant to the participants. As the researcher gains information from participants, it is normal for the focus of the inquiry to shift.

For example, a qualitative researcher may want to study how a new truancy rule impacts youth at risk of expulsion. However, after interviewing some of the youth in their community, a researcher might find that the rule is actually irrelevant to their behavior and thoughts. Instead, their participants will direct the discussion to their frustration with the school administrators or the lack of job opportunities in the area. This is a natural part of qualitative research, and it is normal for research questions and hypothesis to evolve based on information gleaned from participants.

However, this reflexivity and openness unacceptable in quantitative research for good reasons. Researchers using quantitative methods are testing a hypothesis, and if they could revise that hypothesis to match what they found, they could never be wrong! Indeed, an important component of open science and reproducability is the preregistration of a researcher’s hypotheses and data analysis plan in a central repository that can be verified and replicated by reviewers and other researchers. This interactive graphic from 538 shows how an unscrupulous research could come up with a hypothesis and theoretical explanation  after collecting data by hunting for a combination of factors that results in a statistically significant relationship. This is an excellent example of how the positivist assumptions behind quantitative research and intepretivist assumptions behind qualitative research result in different approaches to social science.

• Qualitative research questions often contain words or phrases like “lived experience,” “personal experience,” “understanding,” “meaning,” and “stories.”
• Qualitative research questions can change and evolve over the course of the study.
• Using the guidance in this chapter, write a qualitative research question. You may want to use some of the keywords mentioned above.
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• Shneider, A. M. (2009). Four stages of a scientific discipline; four types of scientist. Trends in Biochemical Sciences 34 (5), 217-233. https://doi.org/10.1016/j.tibs.2009.02.00 ↵
• Burrell, G. & Morgan, G. (1979). Sociological paradigms and organizational analysis . Routledge. Guba, E. (ed.) (1990). The paradigm dialog . SAGE. ↵
• Routledge. Guba, E. (ed.) (1990). The paradigm dialog . SAGE. ↵
• Burrell, G. & Morgan, G. (1979). Sociological paradigms and organizational analysis . Here is a summary of Burrell & Morgan from Babson College , and our classification collapses radical humanism and radical structuralism into the critical paradigm, following Guba and Lincoln's three-paradigm framework. We feel this approach is more parsimonious and easier for students to understand on an introductory level. ↵
• For more about how the meanings of hand gestures vary by region, you might read the following blog entry: Wong, W. (2007). The top 10 hand gestures you’d better get right . Retrieved from: http://www.languagetrainers.co.uk/blog/2007/09/24/top-10-hand-gestures ↵
• Rosario, M., Schrimshaw, E. W., Hunter, J., & Levy-Warren, A. (2009). The coming-out process of young lesbian and bisexual women: Are there butch/femme differences in sexual identity development?. Archives of sexual behavior ,  38 (1), 34-49. ↵
• Calhoun, C., Gerteis, J., Moody, J., Pfaff, S., & Virk, I. (Eds.). (2007). Classical sociological theory  (2nd ed.). Malden, MA: Blackwell. ↵
• Fraser, N. (1989).  Unruly practices: Power, discourse, and gender in contemporary social theory . Minneapolis, MN: University of Minnesota Press. ↵
• Here are links to two HBSE open textbooks, if you are unfamiliar with social work theories and would like more background. https://uark.pressbooks.pub/hbse1/ and https://uark.pressbooks.pub/humanbehaviorandthesocialenvironment2/ ↵
• Box, G. E. P.. (1976). Science and statistics. Journal of the American Statistical Association, 71 (356), 791. ↵
• Heineman-Pieper, J., Tyson, K., & Pieper, M. H. (2002). Doing good science without sacrificing good values: Why the heuristic paradigm is the best choice for social work.  Families in Society ,  83 (1), 15-28. ↵
• Crasnow, S. (2020). Feminist perspectives on science. In E. N. Zalta (ed.), The Stanford Encyclopedia of Philosophy (Winter 2020 Edition). Retrieved from: https://plato.stanford.edu/entries/feminist-science/ ↵
• Grogan, K.E. (2019) How the entire scientific community can confront gender bias in the workplace. Nature Ecology & Evolution, 3 ,  3–6. doi:10.1038/s41559-018-0747-4 ↵
• Tasca, C., Rapetti, M., Carta, M. G., & Fadda, B. (2012). Women and hysteria in the history of mental health. Clinical practice and epidemiology in mental health: Clinical practice & epidemiology in mental health ,  8 , 110-119. ↵
• Klonsky, E. D., Jane, J. S., Turkheimer, E., & Oltmanns, T. F. (2002). Gender role and personality disorders.  Journal of personality disorders ,  16 (5), 464-476. ↵
• Smith, L. T. (2013). Decolonizing methodologies: Research and indigenous peoples . Zed Books Ltd. ↵
• Fricker, M. (2011). Epistemic injustice: Power and the ethics of knowing . Oxford University Press. ↵

The highest level of measurement. Denoted by mutually exclusive categories, a hierarchy (order), values can be added, subtracted, multiplied, and divided, and the presence of an absolute zero.

a paradigm based on the idea that social context and interaction frame our realities

a paradigm in social science research focused on power, inequality, and social change

a research paradigm that suspends questions of philosophical ‘truth’ and focuses more on how different philosophies, theories, and methods can be used strategically to resolve a problem or question within the researcher's unique context

A cyclical process of theory development, starting with an observed phenomenon, then developing or using a theory to make a specific prediction of what should happen if that theory is correct, testing that prediction, refining the theory in light of the findings, and using that refined theory to develop new hypotheses, and so on.

when someone is treated unfairly in their capacity to know something or describe their experience of the world

conducted during the early stages of a project, usually when a researcher wants to test the feasibility of conducting a more extensive study or if the topic has not been studied in the past

research that describes or defines a particular phenomenon

explains why particular phenomena work in the way that they do; answers “why” questions

attempts to explain or describe your phenomenon exhaustively, based on the subjective understandings of your participants

"Assuming that the null hypothesis is true and the study is repeated an infinite number times by drawing random samples from the same populations(s), less than 5% of these results will be more extreme than the current result" (Cassidy et al., 2019, p. 233).

Scientific Inquiry in Social Work (2nd Edition) Copyright © 2020 by Matthew DeCarlo, Cory Cummings, and Kate Agnelli is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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What is a Literature Review? How to Write It (with Examples)

A literature review is a critical analysis and synthesis of existing research on a particular topic. It provides an overview of the current state of knowledge, identifies gaps, and highlights key findings in the literature. 1 The purpose of a literature review is to situate your own research within the context of existing scholarship, demonstrating your understanding of the topic and showing how your work contributes to the ongoing conversation in the field. Learning how to write a literature review is a critical tool for successful research. Your ability to summarize and synthesize prior research pertaining to a certain topic demonstrates your grasp on the topic of study, and assists in the learning process. 

Table of Contents

What is the purpose of literature review , a. habitat loss and species extinction: , b. range shifts and phenological changes: , c. ocean acidification and coral reefs: , d. adaptive strategies and conservation efforts: .

• Choose a Topic and Define the Research Question: 
• Decide on the Scope of Your Review: 
• Select Databases for Searches: 
• Conduct Searches and Keep Track: 
• Review the Literature: 
• Organize and Write Your Literature Review: 
• How to write a literature review faster with Paperpal? 

Frequently asked questions 

What is a literature review .

A well-conducted literature review demonstrates the researcher’s familiarity with the existing literature, establishes the context for their own research, and contributes to scholarly conversations on the topic. One of the purposes of a literature review is also to help researchers avoid duplicating previous work and ensure that their research is informed by and builds upon the existing body of knowledge.

A literature review serves several important purposes within academic and research contexts. Here are some key objectives and functions of a literature review: 2  

1. Contextualizing the Research Problem: The literature review provides a background and context for the research problem under investigation. It helps to situate the study within the existing body of knowledge. 

2. Identifying Gaps in Knowledge: By identifying gaps, contradictions, or areas requiring further research, the researcher can shape the research question and justify the significance of the study. This is crucial for ensuring that the new research contributes something novel to the field.

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3. Understanding Theoretical and Conceptual Frameworks: Literature reviews help researchers gain an understanding of the theoretical and conceptual frameworks used in previous studies. This aids in the development of a theoretical framework for the current research. 

4. Providing Methodological Insights: Another purpose of literature reviews is that it allows researchers to learn about the methodologies employed in previous studies. This can help in choosing appropriate research methods for the current study and avoiding pitfalls that others may have encountered. 

5. Establishing Credibility: A well-conducted literature review demonstrates the researcher’s familiarity with existing scholarship, establishing their credibility and expertise in the field. It also helps in building a solid foundation for the new research. 

6. Informing Hypotheses or Research Questions: The literature review guides the formulation of hypotheses or research questions by highlighting relevant findings and areas of uncertainty in existing literature. 

Literature review example 

Let’s delve deeper with a literature review example: Let’s say your literature review is about the impact of climate change on biodiversity. You might format your literature review into sections such as the effects of climate change on habitat loss and species extinction, phenological changes, and marine biodiversity. Each section would then summarize and analyze relevant studies in those areas, highlighting key findings and identifying gaps in the research. The review would conclude by emphasizing the need for further research on specific aspects of the relationship between climate change and biodiversity. The following literature review template provides a glimpse into the recommended literature review structure and content, demonstrating how research findings are organized around specific themes within a broader topic. 

Literature Review on Climate Change Impacts on Biodiversity:  

Climate change is a global phenomenon with far-reaching consequences, including significant impacts on biodiversity. This literature review synthesizes key findings from various studies: 

Climate change-induced alterations in temperature and precipitation patterns contribute to habitat loss, affecting numerous species (Thomas et al., 2004). The review discusses how these changes increase the risk of extinction, particularly for species with specific habitat requirements. 

Observations of range shifts and changes in the timing of biological events (phenology) are documented in response to changing climatic conditions (Parmesan & Yohe, 2003). These shifts affect ecosystems and may lead to mismatches between species and their resources. 

The review explores the impact of climate change on marine biodiversity, emphasizing ocean acidification’s threat to coral reefs (Hoegh-Guldberg et al., 2007). Changes in pH levels negatively affect coral calcification, disrupting the delicate balance of marine ecosystems. 

Recognizing the urgency of the situation, the literature review discusses various adaptive strategies adopted by species and conservation efforts aimed at mitigating the impacts of climate change on biodiversity (Hannah et al., 2007). It emphasizes the importance of interdisciplinary approaches for effective conservation planning. 

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How to write a good literature review 

Writing a literature review involves summarizing and synthesizing existing research on a particular topic. A good literature review format should include the following elements. 

Introduction: The introduction sets the stage for your literature review, providing context and introducing the main focus of your review. 

• Opening Statement: Begin with a general statement about the broader topic and its significance in the field. 
• Scope and Purpose: Clearly define the scope of your literature review. Explain the specific research question or objective you aim to address. 
• Organizational Framework: Briefly outline the structure of your literature review, indicating how you will categorize and discuss the existing research. 
• Significance of the Study: Highlight why your literature review is important and how it contributes to the understanding of the chosen topic. 
• Thesis Statement: Conclude the introduction with a concise thesis statement that outlines the main argument or perspective you will develop in the body of the literature review. 

Body: The body of the literature review is where you provide a comprehensive analysis of existing literature, grouping studies based on themes, methodologies, or other relevant criteria. 

• Organize by Theme or Concept: Group studies that share common themes, concepts, or methodologies. Discuss each theme or concept in detail, summarizing key findings and identifying gaps or areas of disagreement. 
• Critical Analysis: Evaluate the strengths and weaknesses of each study. Discuss the methodologies used, the quality of evidence, and the overall contribution of each work to the understanding of the topic. 
• Synthesis of Findings: Synthesize the information from different studies to highlight trends, patterns, or areas of consensus in the literature. 
• Identification of Gaps: Discuss any gaps or limitations in the existing research and explain how your review contributes to filling these gaps. 
• Transition between Sections: Provide smooth transitions between different themes or concepts to maintain the flow of your literature review. 

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Conclusion: The conclusion of your literature review should summarize the main findings, highlight the contributions of the review, and suggest avenues for future research. 

• Summary of Key Findings: Recap the main findings from the literature and restate how they contribute to your research question or objective. 
• Contributions to the Field: Discuss the overall contribution of your literature review to the existing knowledge in the field. 
• Implications and Applications: Explore the practical implications of the findings and suggest how they might impact future research or practice. 
• Recommendations for Future Research: Identify areas that require further investigation and propose potential directions for future research in the field. 
• Final Thoughts: Conclude with a final reflection on the importance of your literature review and its relevance to the broader academic community. 

Conducting a literature review 

Conducting a literature review is an essential step in research that involves reviewing and analyzing existing literature on a specific topic. It’s important to know how to do a literature review effectively, so here are the steps to follow: 1  

Choose a Topic and Define the Research Question:  

• Select a topic that is relevant to your field of study. 
• Clearly define your research question or objective. Determine what specific aspect of the topic do you want to explore? 

Decide on the Scope of Your Review:  

• Determine the timeframe for your literature review. Are you focusing on recent developments, or do you want a historical overview? 
• Consider the geographical scope. Is your review global, or are you focusing on a specific region? 
• Define the inclusion and exclusion criteria. What types of sources will you include? Are there specific types of studies or publications you will exclude? 

Select Databases for Searches:  

• Identify relevant databases for your field. Examples include PubMed, IEEE Xplore, Scopus, Web of Science, and Google Scholar. 
• Consider searching in library catalogs, institutional repositories, and specialized databases related to your topic. 

Conduct Searches and Keep Track:  

• Develop a systematic search strategy using keywords, Boolean operators (AND, OR, NOT), and other search techniques. 
• Record and document your search strategy for transparency and replicability. 
• Keep track of the articles, including publication details, abstracts, and links. Use citation management tools like EndNote, Zotero, or Mendeley to organize your references. 

Review the Literature:  

• Evaluate the relevance and quality of each source. Consider the methodology, sample size, and results of studies. 
• Organize the literature by themes or key concepts. Identify patterns, trends, and gaps in the existing research. 
• Summarize key findings and arguments from each source. Compare and contrast different perspectives. 
• Identify areas where there is a consensus in the literature and where there are conflicting opinions. 
• Provide critical analysis and synthesis of the literature. What are the strengths and weaknesses of existing research? 

Organize and Write Your Literature Review:  

• Literature review outline should be based on themes, chronological order, or methodological approaches. 
• Write a clear and coherent narrative that synthesizes the information gathered. 
• Use proper citations for each source and ensure consistency in your citation style (APA, MLA, Chicago, etc.). 
• Conclude your literature review by summarizing key findings, identifying gaps, and suggesting areas for future research. 

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How to write a literature review faster with Paperpal?  

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• Ask a question: Get started with a new document on paperpal.com. Click on the “Research | Cite” feature and type your question in plain English. Paperpal will scour over 250 million research articles, including conference papers and preprints, to provide you with accurate insights and citations. 

• Review and Save: Paperpal summarizes the information, while citing sources and listing relevant reads. You can quickly scan the results to identify relevant references and save these directly to your built-in citations library for later access. 
• Cite with Confidence: Paperpal makes it easy to incorporate relevant citations and references in 10,000+ styles into your writing, ensuring your arguments are well-supported by credible sources. This translates to a polished, well-researched literature review. 

The literature review sample and detailed advice on writing and conducting a review will help you produce a well-structured report. But remember that a good literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. By combining effortless research with an easy citation process, Paperpal Research streamlines the literature review process and empowers you to write faster and with more confidence. Try Paperpal Research now and see for yourself.  

A literature review is a critical and comprehensive analysis of existing literature (published and unpublished works) on a specific topic or research question and provides a synthesis of the current state of knowledge in a particular field. A well-conducted literature review is crucial for researchers to build upon existing knowledge, avoid duplication of efforts, and contribute to the advancement of their field. It also helps researchers situate their work within a broader context and facilitates the development of a sound theoretical and conceptual framework for their studies.

Literature review is a crucial component of research writing, providing a solid background for a research paper’s investigation. The aim is to keep professionals up to date by providing an understanding of ongoing developments within a specific field, including research methods, and experimental techniques used in that field, and present that knowledge in the form of a written report. Also, the depth and breadth of the literature review emphasizes the credibility of the scholar in his or her field.  

Before writing a literature review, it’s essential to undertake several preparatory steps to ensure that your review is well-researched, organized, and focused. This includes choosing a topic of general interest to you and doing exploratory research on that topic, writing an annotated bibliography, and noting major points, especially those that relate to the position you have taken on the topic. 

Literature reviews and academic research papers are essential components of scholarly work but serve different purposes within the academic realm. 3 A literature review aims to provide a foundation for understanding the current state of research on a particular topic, identify gaps or controversies, and lay the groundwork for future research. Therefore, it draws heavily from existing academic sources, including books, journal articles, and other scholarly publications. In contrast, an academic research paper aims to present new knowledge, contribute to the academic discourse, and advance the understanding of a specific research question. Therefore, it involves a mix of existing literature (in the introduction and literature review sections) and original data or findings obtained through research methods. 

Literature reviews are essential components of academic and research papers, and various strategies can be employed to conduct them effectively. If you want to know how to write a literature review for a research paper, here are four common approaches that are often used by researchers.  Chronological Review: This strategy involves organizing the literature based on the chronological order of publication. It helps to trace the development of a topic over time, showing how ideas, theories, and research have evolved.  Thematic Review: Thematic reviews focus on identifying and analyzing themes or topics that cut across different studies. Instead of organizing the literature chronologically, it is grouped by key themes or concepts, allowing for a comprehensive exploration of various aspects of the topic.  Methodological Review: This strategy involves organizing the literature based on the research methods employed in different studies. It helps to highlight the strengths and weaknesses of various methodologies and allows the reader to evaluate the reliability and validity of the research findings.  Theoretical Review: A theoretical review examines the literature based on the theoretical frameworks used in different studies. This approach helps to identify the key theories that have been applied to the topic and assess their contributions to the understanding of the subject.  It’s important to note that these strategies are not mutually exclusive, and a literature review may combine elements of more than one approach. The choice of strategy depends on the research question, the nature of the literature available, and the goals of the review. Additionally, other strategies, such as integrative reviews or systematic reviews, may be employed depending on the specific requirements of the research.

The literature review format can vary depending on the specific publication guidelines. However, there are some common elements and structures that are often followed. Here is a general guideline for the format of a literature review:  Introduction:   Provide an overview of the topic.  Define the scope and purpose of the literature review.  State the research question or objective.  Body:   Organize the literature by themes, concepts, or chronology.  Critically analyze and evaluate each source.  Discuss the strengths and weaknesses of the studies.  Highlight any methodological limitations or biases.  Identify patterns, connections, or contradictions in the existing research.  Conclusion:   Summarize the key points discussed in the literature review.  Highlight the research gap.  Address the research question or objective stated in the introduction.  Highlight the contributions of the review and suggest directions for future research.

Both annotated bibliographies and literature reviews involve the examination of scholarly sources. While annotated bibliographies focus on individual sources with brief annotations, literature reviews provide a more in-depth, integrated, and comprehensive analysis of existing literature on a specific topic. The key differences are as follows: 

References 

• Denney, A. S., & Tewksbury, R. (2013). How to write a literature review.  Journal of criminal justice education ,  24 (2), 218-234. 
• Pan, M. L. (2016).  Preparing literature reviews: Qualitative and quantitative approaches . Taylor & Francis. 
• Cantero, C. (2019). How to write a literature review.  San José State University Writing Center . 

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• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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Literature Review, Theoretical Review or Conceptual Review?

I was researching and refreshing what I learned about literature reviews and research methodology in the 6625 ESLTECH class and came across this post in ResearchGate:

While  I was interested in finding out how to conduct a lit review,  and what methodologies fit with my “Begin With the End in mind” framework, I remembered that I was actually conducting a conceptual analysis of the Hackathon through two instruments:  the opportunistic interviews and my observations.  Applying Backward Design as research methodology has been used in the biological sciences.  It is called Backward Design for Education Research (BDER) and basically it instructs how to apply teaching-as-research (based on the Scholarship of Teaching and Learning(SoTL) model) to see what works in “providing evidence-based pedagogy and a deeper understanding of causal mechanisms for the broader education community.” (Jenkins, Bailey, Kummer & Weber, 2017). My approach was  more like “Backward Market Research,”  which consists of eight steps that ultimately resemble Wiggins and McTighe’s Backward Design for curriculum development. The key to backward market research lies in identifying the desired outcome (i.e., what data would answer the question you are asking) before embarking on the project …” (Jenkins, Bailey, Kummer & Weber, 2017). My question is broad  – what insights come out of the Hackathon – and the results are formative – data reports generate more questions and identify the need to code certain responses,  or to add a new question next year (as with the multitude of comments about Judging from 2017) – but a body or knowledge is being formed.

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Concept Review

A stage in product development where a team evaluates the viability and desirability of a product idea before investing significant resources in its creation. product glossary concept review also called: concept check, concept refresher, concept summary, concept overview, concept recap, concept assessment, concept evaluation, and concept analysis see also: assumptions collection , business model mapping , empathy mapping , fishbone diagram , five whys , market of skills , prototype persona , service blueprint , stakeholder mapping , starbursting , touchpoint mapping , user story mapping , value proposition mapping , continuous discovery , dual track agile relevant metrics: conversion rate, customer retention rate, average order value, customer lifetime value, and return on investment in this article what is concept review.

Concept review is a process used in product management and user experience to evaluate the viability, desirability, and feasibility of a product concept. It involves a thorough review of the concept, including its features, benefits, and potential market. The review is conducted by a team of experts, including product managers, user experience designers, and other stakeholders.

By understanding the key components of a successful concept review, evaluating the viability, feasibility, and desirability of a product idea, and gathering feedback from key stakeholders, teams can make informed decisions about whether to pursue a product idea or not.

The goal of the review is to identify any potential issues or risks associated with the concept, and to provide feedback on how to improve it. The review process typically includes a review of the concept’s user experience, usability, and marketability. The review team may also provide feedback on the concept’s design, development, and implementation. The concept review process is an important step in the product development process, as it helps to ensure that the product concept is viable and meets the needs of the target market.

Where did Concept Review come from?

Concept review is a term used in education to refer to the process of reviewing and reinforcing a concept or idea. It is a way of ensuring that students have a thorough understanding of a concept before moving on to the next topic. The term was first used in the early 20th century, when educators began to recognize the importance of reviewing and reinforcing concepts in order to ensure that students had a strong understanding of the material.

Within the context of product development, the origin is not well documented. “Concept reviews” are a common and important step in the process of developing and refining product ideas, and the term has been adopted by many organizations and product development experts to describe this process.

Key Components of a Successful Concept Review

Concept reviews play a critical role in the product development process, helping teams to assess the viability, feasibility, and desirability of a product idea. A successful concept review can make all the difference in determining whether a product idea is worth pursuing or not. In this blog post, we’ll explore the key components that make up a successful concept review.

The Key Components of a Successful Concept Review

The success of a concept review depends on several key components, including:

• A clear understanding of the product idea . Before a concept review can be conducted, it’s important to have a clear and detailed understanding of the product idea being evaluated. This includes information on the product’s target audience, its unique features and benefits, and the problem it’s trying to solve.
• A thorough evaluation of viability, feasibility, and desirability . During a concept review, it’s important to evaluate the viability, feasibility, and desirability of the product idea. Viability refers to whether the product can be developed and brought to market. Feasibility refers to whether the product can be developed within the given budget and timeline. Desirability refers to whether the product will meet the needs and wants of its target audience.
• Feedback from key stakeholders . Feedback from key stakeholders is critical to the success of a concept review. This feedback can come from internal teams, such as product managers, designers, and engineers, as well as external stakeholders, such as customers and other subject matter experts.

Evaluating the Viability, Feasibility, and Desirability of a Product Idea

To evaluate the viability, feasibility, and desirability of a product idea, it’s important to consider several key factors, including:

• Market demand . Does the product idea have a viable market, and is there enough demand for it?
• Competition . Is the product idea unique enough to stand out in a crowded market, and what are the key competitors?
• Budget and timeline . Are the resources available to develop the product within the given budget and timeline?
• Target audience . Does the product idea meet the needs and wants of its target audience, and is there enough demand from this audience?
• Technical feasibility . Is the product idea technically feasible, and can it be developed within the given budget and timeline?

Gathering Feedback from Key Stakeholders

To gather feedback from key stakeholders, it’s important to:

• Identify key stakeholders . Identify all key stakeholders who can provide valuable feedback on the product idea, including internal teams, customers, and other subject matter experts.
• Reach out to stakeholders . Reach out to these stakeholders and invite them to participate in the concept review. This can be done through email, phone, or in-person meetings.
• Ask the right questions . Make sure to ask the right questions to get the feedback you need to make informed decisions. This includes asking about the strengths and weaknesses of the product idea, what needs to be improved, and any other feedback they have to offer.

Common Challenges and How to Overcome Them

Despite their importance, concept reviews are not without their challenges. Here are some of the common challenges faced during concept reviews and how to overcome them.

• Lack of clarity about the product idea . One of the most common challenges faced during concept reviews is a lack of clarity about the product idea being evaluated. This can make it difficult for stakeholders to provide meaningful feedback and can lead to misunderstandings and disagreements.
• Conflicting opinions and subjectivity . Concept reviews often involve multiple stakeholders with differing opinions and perspectives. This can result in conflicting opinions and subjectivity, making it difficult to reach a consensus on the viability, feasibility, and desirability of the product idea.
• Insufficient data and information . Without sufficient data and information, it can be challenging to evaluate the viability, feasibility, and desirability of a product idea. This can result in decisions being based on incomplete information, leading to costly mistakes and setbacks.

You might consider the following to try to overcome these challenges

• Clearly define the product idea . To overcome the challenge of a lack of clarity about the product idea, it’s important to clearly define the product idea and provide stakeholders with a detailed understanding of what is being evaluated.
• Gather data and information . To overcome the challenge of insufficient data and information, it’s important to gather as much data and information as possible about the product idea, including market research, customer feedback, and technical feasibility assessments.
• Encourage open and honest feedback . Encourage open and honest feedback from all stakeholders, and provide a safe and neutral environment where everyone feels comfortable sharing their opinions and perspectives.

As concepts are reviewed, disagreements among stakeholders are likely to happen. Here are good ways to handle disagreements or conflicting opinions under concept reviews.

• Facilitate open and honest discussions . To handle disagreements and conflicting opinions, it’s important to facilitate open and honest discussions between all stakeholders. This can help to uncover the root causes of disagreements and find mutually acceptable solutions.
• Encourage active listening . Encourage all stakeholders to actively listen to one another and understand each other’s perspectives. This can help to reduce subjectivity and find common ground.
• Seek outside help if necessary . If disagreements and conflicting opinions cannot be resolved through open and honest discussions, it may be necessary to seek outside help, such as from a neutral third party or mediator.

By handling disagreements and conflicting opinions through open and honest discussions and active listening, teams can reach a consensus on the viability, feasibility, and desirability of a product idea, leading to more successful product development outcomes.

Concept Review Best Practices

Get a head start and make your concept review session a success. Here are few tips to make them work well:

• Clearly define the goals of the review . It’s important to clearly define the goals of the concept review and what the team hopes to achieve. This can help to ensure that everyone is aligned and focused on the same objectives.
• Gather data and information . To ensure that the concept review is informed and productive, it’s important to gather as much data and information as possible about the product idea, including market research, customer feedback, and technical feasibility assessments.

Prioritizing ideas emerging during concept reviews

With numerous ideas to choose from, it can be difficult to decide which ones to pursue further. In this segment, we will explore best practices for prioritizing ideas and selecting the best ones for development.

• Assess the potential impact of each idea . Including market size, frequency of solved problem, potential income, customer demand, and technical feasibility.
• Consider the resources required for each idea . It’s also important to consider the resources required for each idea, including time, money, and staffing.
• Seek outside help if necessary . If it’s challenging to prioritize ideas and select the best ones for further development, it may be necessary to seek outside help, such as from a neutral third party or advisor.

Communicating the results of the Concept Review effectively

Ensure that all stakeholders understand and can act on the outcomes of the review by being strategic about how you communicate its results.

• Present the results in a clear and concise manner . To communicate the results of the concept review effectively, it’s important to present the results in a clear and concise manner, including a summary of the key findings, recommendations, and next steps.
• Ensure that all stakeholders understand the results . It’s also important to ensure that all stakeholders understand the results of the concept review, including any disagreements or conflicting opinions.
• Document the results for future reference . To ensure that the results of the concept review are easily accessible for future reference, it’s important to document the results, including a summary of the key findings, recommendations, and next steps.
• What is the purpose of the concept review? Hint The purpose of the concept review is to evaluate the feasibility of a proposed concept or idea. It is used to assess the potential risks, benefits, and challenges associated with the concept, and to determine whether it is worth pursuing.
• What is the scope of the concept review? Hint The scope of the concept review will depend on the complexity of the concept and the resources available. It may include research into the concept, analysis of the potential risks and benefits, and evaluation of the potential challenges.
• What are the expected outcomes of the concept review? Hint The expected outcomes of the concept review are to determine whether the concept is feasible and worth pursuing.
• What resources are available to support the concept review? Hint Resources available to support the concept review may include research materials, expert opinions, and financial analysis.
• What criteria will be used to evaluate the concept review? Hint Criteria used to evaluate the concept review may include the potential risks, benefits, and challenges associated with the concept, as well as the potential return on investment.
• What timeline is available for the concept review? Hint The timeline for the concept review will depend on the complexity of the concept and the resources available.
• What are the potential risks associated with the concept review? Hint Potential risks associated with the concept review may include financial losses, delays in implementation, and legal issues.
• What are the potential benefits of the concept review? Hint Potential benefits of the concept review may include cost savings, improved efficiency, and increased customer satisfaction.
• What are the potential challenges associated with the concept review? Hint Potential challenges associated with the concept review may include a lack of resources, difficulty in obtaining accurate data, and difficulty in obtaining expert opinions.
• How will the concept review be documented and communicated? Hint The concept review will be documented and communicated through reports, presentations, and other forms of communication.

You might also be interested in reading up on:

• Assumptions Collection
• Business Model Mapping
• Empathy Mapping
• Fishbone Diagram
• Market of Skills
• Prototype Persona
• Service Blueprint
• Stakeholder Mapping
• Starbursting
• Touchpoint Mapping
• User Story Mapping
• Value Proposition Mapping
• Continuous Discovery
• Dual Track Agile
• Eric Ries @ericries
• Steve Blank @sgblank
• Ash Maurya @ashmaurya
• Marty Cagan @cagan
• Teresa Torres @ttorres
• Cracking Creativity : The Secrets of Creative Genius by Michael Michalko (2001)
• The Lean Product Playbook : How to Innovate with Minimum Viable Products and Rapid Customer Feedback by Dan Olsen (2015)
• Inspired : How to Create Tech Products Customers Love by Marty Cagan (2007)
• Empowered : Ordinary People, Extraordinary Products by Marty Cagan (2007)
• Business Model Generation : A Handbook for Visionaries, Game Changers, and Challengers by Alexander Osterwalder and Yves Pigneur (2010)
• The Innovator's Dilemma : When New Technologies Cause Great Firms to Fail by Clayton M. Christensen (1997)

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