research framework adalah

An official website of the United States government

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

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

• Publications
• Account settings

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

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

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

Julie a. luft.

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

Sophia Jeong

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

Robert Idsardi

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

Grant Gardner

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

Associated Data

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

INTRODUCTION

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

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

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

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

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

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

Comparison of literature reviews, theoretical frameworks, and conceptual reviews

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

LITERATURE REVIEWS

Purpose of a literature review.

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

Building Literature Reviews

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

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

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

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

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

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

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

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

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

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

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

Suggestions and Advice

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

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

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

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

THEORETICAL FRAMEWORKS

Purpose of theoretical frameworks.

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

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

Selecting Theoretical Frameworks

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

CONCEPTUAL FRAMEWORKS

Purpose of a conceptual framework.

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

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

Constructing Conceptual Frameworks

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

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

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

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

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

Conceptual framework from Sabel et al. (2017) .

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

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

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

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

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

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

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

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

CONCLUDING THOUGHTS

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

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

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

Supplementary Material

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

• Privacy Policy

Buy Me a Coffee

Home » Theoretical Framework – Types, Examples and Writing Guide

Theoretical Framework – Types, Examples and Writing Guide

Table of Contents

Theoretical Framework

Definition:

Theoretical framework refers to a set of concepts, theories, ideas , and assumptions that serve as a foundation for understanding a particular phenomenon or problem. It provides a conceptual framework that helps researchers to design and conduct their research, as well as to analyze and interpret their findings.

In research, a theoretical framework explains the relationship between various variables, identifies gaps in existing knowledge, and guides the development of research questions, hypotheses, and methodologies. It also helps to contextualize the research within a broader theoretical perspective, and can be used to guide the interpretation of results and the formulation of recommendations.

Types of Theoretical Framework

Types of Types of Theoretical Framework are as follows:

Conceptual Framework

This type of framework defines the key concepts and relationships between them. It helps to provide a theoretical foundation for a study or research project .

Deductive Framework

This type of framework starts with a general theory or hypothesis and then uses data to test and refine it. It is often used in quantitative research .

Inductive Framework

This type of framework starts with data and then develops a theory or hypothesis based on the patterns and themes that emerge from the data. It is often used in qualitative research .

Empirical Framework

This type of framework focuses on the collection and analysis of empirical data, such as surveys or experiments. It is often used in scientific research .

Normative Framework

This type of framework defines a set of norms or values that guide behavior or decision-making. It is often used in ethics and social sciences.

Explanatory Framework

This type of framework seeks to explain the underlying mechanisms or causes of a particular phenomenon or behavior. It is often used in psychology and social sciences.

Components of Theoretical Framework

The components of a theoretical framework include:

• Concepts : The basic building blocks of a theoretical framework. Concepts are abstract ideas or generalizations that represent objects, events, or phenomena.
• Variables : These are measurable and observable aspects of a concept. In a research context, variables can be manipulated or measured to test hypotheses.
• Assumptions : These are beliefs or statements that are taken for granted and are not tested in a study. They provide a starting point for developing hypotheses.
• Propositions : These are statements that explain the relationships between concepts and variables in a theoretical framework.
• Hypotheses : These are testable predictions that are derived from the theoretical framework. Hypotheses are used to guide data collection and analysis.
• Constructs : These are abstract concepts that cannot be directly measured but are inferred from observable variables. Constructs provide a way to understand complex phenomena.
• Models : These are simplified representations of reality that are used to explain, predict, or control a phenomenon.

How to Write Theoretical Framework

A theoretical framework is an essential part of any research study or paper, as it helps to provide a theoretical basis for the research and guide the analysis and interpretation of the data. Here are some steps to help you write a theoretical framework:

• Identify the key concepts and variables : Start by identifying the main concepts and variables that your research is exploring. These could include things like motivation, behavior, attitudes, or any other relevant concepts.
• Review relevant literature: Conduct a thorough review of the existing literature in your field to identify key theories and ideas that relate to your research. This will help you to understand the existing knowledge and theories that are relevant to your research and provide a basis for your theoretical framework.
• Develop a conceptual framework : Based on your literature review, develop a conceptual framework that outlines the key concepts and their relationships. This framework should provide a clear and concise overview of the theoretical perspective that underpins your research.
• Identify hypotheses and research questions: Based on your conceptual framework, identify the hypotheses and research questions that you want to test or explore in your research.
• Test your theoretical framework: Once you have developed your theoretical framework, test it by applying it to your research data. This will help you to identify any gaps or weaknesses in your framework and refine it as necessary.
• Write up your theoretical framework: Finally, write up your theoretical framework in a clear and concise manner, using appropriate terminology and referencing the relevant literature to support your arguments.

Theoretical Framework Examples

Here are some examples of theoretical frameworks:

• Social Learning Theory : This framework, developed by Albert Bandura, suggests that people learn from their environment, including the behaviors of others, and that behavior is influenced by both external and internal factors.
• Maslow’s Hierarchy of Needs : Abraham Maslow proposed that human needs are arranged in a hierarchy, with basic physiological needs at the bottom, followed by safety, love and belonging, esteem, and self-actualization at the top. This framework has been used in various fields, including psychology and education.
• Ecological Systems Theory : This framework, developed by Urie Bronfenbrenner, suggests that a person’s development is influenced by the interaction between the individual and the various environments in which they live, such as family, school, and community.
• Feminist Theory: This framework examines how gender and power intersect to influence social, cultural, and political issues. It emphasizes the importance of understanding and challenging systems of oppression.
• Cognitive Behavioral Theory: This framework suggests that our thoughts, beliefs, and attitudes influence our behavior, and that changing our thought patterns can lead to changes in behavior and emotional responses.
• Attachment Theory: This framework examines the ways in which early relationships with caregivers shape our later relationships and attachment styles.
• Critical Race Theory : This framework examines how race intersects with other forms of social stratification and oppression to perpetuate inequality and discrimination.

When to Have A Theoretical Framework

Following are some situations When to Have A Theoretical Framework:

• A theoretical framework should be developed when conducting research in any discipline, as it provides a foundation for understanding the research problem and guiding the research process.
• A theoretical framework is essential when conducting research on complex phenomena, as it helps to organize and structure the research questions, hypotheses, and findings.
• A theoretical framework should be developed when the research problem requires a deeper understanding of the underlying concepts and principles that govern the phenomenon being studied.
• A theoretical framework is particularly important when conducting research in social sciences, as it helps to explain the relationships between variables and provides a framework for testing hypotheses.
• A theoretical framework should be developed when conducting research in applied fields, such as engineering or medicine, as it helps to provide a theoretical basis for the development of new technologies or treatments.
• A theoretical framework should be developed when conducting research that seeks to address a specific gap in knowledge, as it helps to define the problem and identify potential solutions.
• A theoretical framework is also important when conducting research that involves the analysis of existing theories or concepts, as it helps to provide a framework for comparing and contrasting different theories and concepts.
• A theoretical framework should be developed when conducting research that seeks to make predictions or develop generalizations about a particular phenomenon, as it helps to provide a basis for evaluating the accuracy of these predictions or generalizations.
• Finally, a theoretical framework should be developed when conducting research that seeks to make a contribution to the field, as it helps to situate the research within the broader context of the discipline and identify its significance.

Purpose of Theoretical Framework

The purposes of a theoretical framework include:

• Providing a conceptual framework for the study: A theoretical framework helps researchers to define and clarify the concepts and variables of interest in their research. It enables researchers to develop a clear and concise definition of the problem, which in turn helps to guide the research process.
• Guiding the research design: A theoretical framework can guide the selection of research methods, data collection techniques, and data analysis procedures. By outlining the key concepts and assumptions underlying the research questions, the theoretical framework can help researchers to identify the most appropriate research design for their study.
• Supporting the interpretation of research findings: A theoretical framework provides a framework for interpreting the research findings by helping researchers to make connections between their findings and existing theory. It enables researchers to identify the implications of their findings for theory development and to assess the generalizability of their findings.
• Enhancing the credibility of the research: A well-developed theoretical framework can enhance the credibility of the research by providing a strong theoretical foundation for the study. It demonstrates that the research is based on a solid understanding of the relevant theory and that the research questions are grounded in a clear conceptual framework.
• Facilitating communication and collaboration: A theoretical framework provides a common language and conceptual framework for researchers, enabling them to communicate and collaborate more effectively. It helps to ensure that everyone involved in the research is working towards the same goals and is using the same concepts and definitions.

Characteristics of Theoretical Framework

Some of the characteristics of a theoretical framework include:

• Conceptual clarity: The concepts used in the theoretical framework should be clearly defined and understood by all stakeholders.
• Logical coherence : The framework should be internally consistent, with each concept and assumption logically connected to the others.
• Empirical relevance: The framework should be based on empirical evidence and research findings.
• Parsimony : The framework should be as simple as possible, without sacrificing its ability to explain the phenomenon in question.
• Flexibility : The framework should be adaptable to new findings and insights.
• Testability : The framework should be testable through research, with clear hypotheses that can be falsified or supported by data.
• Applicability : The framework should be useful for practical applications, such as designing interventions or policies.

Advantages of Theoretical Framework

Here are some of the advantages of having a theoretical framework:

• Provides a clear direction : A theoretical framework helps researchers to identify the key concepts and variables they need to study and the relationships between them. This provides a clear direction for the research and helps researchers to focus their efforts and resources.
• Increases the validity of the research: A theoretical framework helps to ensure that the research is based on sound theoretical principles and concepts. This increases the validity of the research by ensuring that it is grounded in established knowledge and is not based on arbitrary assumptions.
• Enables comparisons between studies : A theoretical framework provides a common language and set of concepts that researchers can use to compare and contrast their findings. This helps to build a cumulative body of knowledge and allows researchers to identify patterns and trends across different studies.
• Helps to generate hypotheses: A theoretical framework provides a basis for generating hypotheses about the relationships between different concepts and variables. This can help to guide the research process and identify areas that require further investigation.
• Facilitates communication: A theoretical framework provides a common language and set of concepts that researchers can use to communicate their findings to other researchers and to the wider community. This makes it easier for others to understand the research and its implications.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

How to Cite Research Paper – All Formats and...

Data Collection – Methods Types and Examples

Delimitations in Research – Types, Examples and...

Research Paper Format – Types, Examples and...

Research Process – Steps, Examples and Tips

Research Design – Types, Methods and Examples

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• 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.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

Swaen, B. & George, T. (2024, March 18). What Is a Conceptual Framework? | Tips & Examples. Scribbr. Retrieved 22 April 2024, from https://www.scribbr.co.uk/research-methods/conceptual-frameworks/

Is this article helpful?

Other students also liked

Mediator vs moderator variables | differences & examples, independent vs dependent variables | definition & examples, what are control variables | definition & examples.

• Library databases
• Library website

Theories and Frameworks: Introduction

Theoretical & conceptual frameworks.

The terms theoretical framework and conceptual framework are often used interchangeably to mean the same thing. Although they are both used to understand a research problem and guide the development, collection, and analysis of research, it's important to understand the difference between the two. When working on coursework or dissertation research, make sure to clarify what is being asked and any specific course or program requirements. 

Theoretical framework 

A theoretical framework is a single formal theory. When a study is designed around a theoretical framework, the theory is the primary means in which the research problem is understood and investigated. Although theoretical frameworks tend to be used in quantitative studies, you will also see this approach in qualitative research.  

Conceptual framework

A conceptual framework includes one or more formal theories (in part or whole) as well as other concepts and empirical findings from the literature. It is used to show relationships among these ideas and how they relate to the research study. Conceptual frameworks are commonly seen in qualitative research in the social and behavioral sciences, for example, because often one theory cannot fully address the phenomena being studied.

Investigate theory

Identifying and learning about theories requires a different search strategy than other types of research. Even though the steps are different, you will still use many of the same skills and tools you’ve used for other library research.

• psychology:  human development, cognition, personality, motivation
• sociology:  social change, race, class, gender
• business:  leadership, management
• health:  patient care, well-being, environment
• course textbooks
• encyclopedias and handbooks
• credible websites

Theory in doctoral research

Identifying a theory that aligns with your dissertation or doctoral study takes time. It’s never too early to start exploratory research. The process of identifying an appropriate theory can seem daunting, so try breaking down the process into smaller steps.

• your theory courses
• completed dissertations and doctoral studies
• the scholarly literature on your topic
• Keep a list of theories and take notes on how and why they were used.
• Identify and learn more about relevant theories.
• Locate influential and seminal works  related to those theories.
• Next Page: Discover Theories
• Office of Student Disability Services

Walden Resources

Departments.

• Academic Residencies
• Academic Skills
• Career Planning and Development
• Customer Care Team
• Field Experience
• Military Services
• Student Success Advising
• Writing Skills

Centers and Offices

• Center for Social Change
• Office of Academic Support and Instructional Services
• Office of Degree Acceleration
• Office of Research and Doctoral Services
• Office of Student Affairs

Student Resources

• Doctoral Writing Assessment
• Form & Style Review
• Quick Answers
• ScholarWorks
• SKIL Courses and Workshops
• Walden Bookstore
• Walden Catalog & Student Handbook
• Student Safety/Title IX
• Legal & Consumer Information
• Website Terms and Conditions
• Cookie Policy
• Accessibility
• Accreditation
• State Authorization
• Net Price Calculator
• Contact Walden

Walden University is a member of Adtalem Global Education, Inc. www.adtalem.com Walden University is certified to operate by SCHEV © 2024 Walden University LLC. All rights reserved.

Doing Research: A New Researcher’s Guide pp 51–75 Cite as

Building and Using Theoretical Frameworks

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  
• Open Access
• First Online: 03 December 2022

14k Accesses

1 Citations

Part of the book series: Research in Mathematics Education ((RME))

Theoretical frameworks can be confounding. They are supposed to be very important, but it is not always clear what they are or why you need them. Using ideas from Chaps. 1 and 2 , we describe them as local theories that are custom-designed for your study. Although they might use parts of larger well-known theories, they are created by individual researchers for particular studies. They are developed through the cyclic process of creating more precise and meaningful hypotheses. Building directly on constructs from the previous chapters, you can think of theoretical frameworks as equivalent to the most compelling, complete rationales you can develop for the predictions you make. Theoretical frameworks are important because they do lots of work for you. They incorporate the literature into your rationale, they explain why your study matters, they suggest how you can best test your predictions, and they help you interpret what you find. Your theoretical framework creates an essential coherence for your study and for the paper you are writing to report the study.

You have full access to this open access chapter,  Download chapter PDF

Part I. What Are Theoretical Frameworks?

As the name implies, a theoretical framework is a type of theory. We will define it as the custom-made theory that focuses specifically on the hypotheses you want to test and the research questions you want to answer. It is custom-made for your study because it explains why your predictions are plausible. It does no more and no less. Building directly on Chap. 2 , as you develop more complete rationales for your predictions, you are actually building a theory to support your predictions. Our goal in this chapter is for you to become comfortable with what theoretical frameworks are, with how they relate to the general concept of theory, with what role they play in scientific inquiry, and with why and how to create one for your study.

As you read this chapter, it will be helpful to remember that our definitions of terms in this book, such as theoretical framework, are based on our view of scientific inquiry as formulating, testing, and revising hypotheses. We define theoretical framework in ways that continue the coherent story we lay out across all phases of scientific inquiry and all the chapters this book. You are likely to find descriptions of theoretical frameworks in other sources that differ in some ways from our description. In addition, you are likely to see other terms that we would include as synonyms for theoretical framework, including conceptual framework. We suggest that when you encounter these special terms, make sure you understand how the authors are defining them.

Definitions of Theories

We begin by stepping back and considering how theoretical frameworks fit within the concept of theory, as usually defined. There are many definitions of theory; you can find a huge number simply by googling “theory.” Educational researchers and theorists often propose their own definitions but many of these are quite similar. Praetorius and Charalambous ( 2022 ) reviewed a number of definitions to set the stage for examining theories of teaching. Here are a few, beginning with a dictionary definition:

Lexico.com Dictionary (Oxford University Press, 2021 ): “A supposition or a system of ideas intended to explain something, especially one based on general principles independent of the thing to be explained.”

Biddle and Anderson ( 1986 ): “By scientific theory we mean the system of concepts and propositions that is used to represent, think about, and predict observable events. Within a mature science that theory is also explanatory and formalized. It does not represent ultimate ‘truth,’ however; indeed, it will be superseded by other theories presently. Instead, it represents the best explanation we have, at present, for those events we have so far observed” (p. 241).

Kerlinger ( 1964 ): “A theory is a set of interrelated constructs (concepts), definitions and propositions which presents a systematic view of phenomena by specifying relations among variables, with the purpose of explaining and predicting phenomena” (p. 11).

Colquitt and Zapata-Phelan ( 2007 ): The authors say that theories allow researchers to understand and predict outcomes of interest, describe and explain a process or sequence of events, raise consciousness about a specific set of concepts as well as prevent scholars from “being dazzled by the complexity of the empirical world by providing a linguistic tool for organizing it” (p. 1281).

For our purposes, it is important to notice two things that most definitions of theories share: They are descriptions of a connected set of facts and concepts, and they are created to predict and/or explain observed events. You can connect these ideas to Chaps. 1 and 2 by noticing that the language for the descriptors of scientific inquiry we suggested in Chap. 1 are reflected in the definitions of theories. In particular, notice in the definitions two of the descriptors: “Observing something and trying to explain why it is the way it is” and “Updating everyone’s thinking in response to more and better information.” Notice also in the definitions the emphasis on the elements of a theory similar to the elements of a rationale described in Chap. 2 : definitions, variables, and mechanisms that explain relationships.

Exercise 3.1

Before you continue reading, in your own words, write down a definition for “theoretical framework.”

Theoretical Frameworks Are Local Theories

There are strong similarities between building theories and doing scientific inquiry (formulating, testing, and revising hypotheses). In both cases, the researcher (or theorist) develops explanations for phenomena of interest. Building theories involves describing the concepts and conjectures that predict and later explain the events, and specifying the predictions by identifying the variables that will be measured. Doing scientific inquiry involves many of the same activities: formulating predictions for answers to questions about the research problem and building rationales to explain why the predictions are appropriate and reasonable.

As you move through the cycles described in Chap. 2 —cycles of asking questions, making predictions, writing out the reasons for these predictions, imagining how you would test the predictions, reading more about what scholars know and have hypothesized, revising your predictions (and maybe your questions), and so on—your theoretical rationales will become both more complete and more precise. They will become more complete as you find new arguments and new data in the literature and through talking with others, and they will become sharper as you remove parts of the rationales that originally seemed relevant but now create mostly distractions and noise. They will become increasingly customized local theories that support your predictions.

In the end, your framework should be as clean and frugal as possible without missing arguments or data that are directly relevant. In the language of mathematics, you should use an idea if and only if it makes your framework stronger, more convincing. On the one hand, including more than you need becomes a distraction and can confuse both you, as you try to conceptualize and conduct your research, and others, as they read your reports of your research. On the other hand, including less than you need means your rationale is not yet as convincing as it could be.

The set of rationales, blended together, constitute a precisely targeted custom-made theory that supports your predictions. Custom designing your rationales for your specific predictions means you probably will be drawing ideas from lots of sources and combining them in new ways. You are likely to end up with a unique local theory, a theoretical framework that has not been proposed in exactly the same way before.

A common misconception among beginning researchers is that they should borrow a theoretical framework from somewhere else, especially from well-known scholars who have theories named after them or well-known general theories of learning or teaching. You are likely to use ideas from these theories (e.g., Vygotsky’s theory of learning, Maslow’s theory of motivation, constructivist theories of learning), but you will combine specific ideas from multiple sources to create your own framework. When someone asks, “What theoretical framework are you using?” you would not say, “A Vygotskian framework.” Rather, you would say something like, “I created my framework by combining ideas from different sources so it explains why I am making these predictions.”

You should think of your theoretical framework as a potential contribution to the field, all on its own. Although it is unique to your study, there are elements of your framework that other researchers could draw from to construct theoretical frameworks for their studies, just as you drew from others’ frameworks. In rare cases, other researchers could use your framework as is. This might happen if they want to replicate your study or extend it in very specific ways. Usually, however, researchers borrow parts of frameworks or modify them in ways that better fit their own studies. And, just as you are doing with your own theoretical framework, those researchers will need to justify why borrowing or modifying parts of your framework will help them explain the predictions they are making.

Considering your theoretical framework as a contribution to the field means you should treat it as a central part of scientific inquiry, not just as a required step that must be completed before moving to the next phase. To be useful, the theoretical framework should be constructed as a critical part of conceptualizing and carrying out the research (Cai et al., 2019c ). This also means you should write out your framework as you are developing it. This will be a key part of your evolving research paper. Because your framework will be adjusted multiple times, your written document will go through many drafts.

If you are a graduate student, do not think of the potential audience for your written framework as only your advisor and committee members. Rather, consider your audience to be the larger community of education researchers. You will need to be sure all the key terms are defined and each part of your argument is clear, even to those who are not familiar with your study. This is one place where writing out your framework can benefit your study—it is easy to assume key terms are clear, but then you find out they are not so clear, even to you, when trying to communicate them. Failing to notice this lack of clarity can create lots of problems down the road.

Exercise 3.2

Researchers have used a number of different metaphors to describe theoretical frameworks. Maxwell (2005) referred to a theoretical framework as a “coat closet” that provides “places to ‘hang’ data, showing their relationship to other data,” although he cautioned that “a theory that neatly organizes some data will leave other data disheveled and lying on the floor, with no place to put them” (p. 49). Lester (2005) referred to a framework as a “scaffold” (p. 458), and others have called it a “blueprint” (Grant & Osanloo, 2014). Eisenhart (1991) described the framework as a “skeletal structure of justification” (p. 209). Spangler and Williams (2019) drew an analogy to the role that a house frame provides in preventing the house from collapsing in on itself. What aspects of a theoretical framework does each of these metaphors capture? What aspects does each fail to capture? Which metaphor do you find best fits your definition of a theoretical framework? Why? Can you think of another metaphor to describe a theoretical framework?

Part II. Why Do You Need Theoretical Frameworks?

Theoretical frameworks do lots of work for you. They have four primary purposes. They ensure (1) you have sound reasons to expect your predictions will be accurate, (2) you will craft appropriate methods to test your predictions, (3) you can interpret appropriately what you find, and (4) your interpretations will contribute to the accumulation of a knowledge base that can improve education. How do they do this?

Supporting Your Predictions

In previous chapters and earlier in this chapter, we described how theoretical frameworks are built along with your predictions. In fact, the rationales you develop for convincing others (and yourself) that your predictions are accurate are used to refine your predictions, and vice versa. So, it is not surprising that your refined framework provides a rationale that is fully aligned with your predictions. In fact, you could think of your theoretical framework as your best explanation, at any given moment during scientific inquiry, for why you will find what you think you will find.

Throughout this book, we are using “explanation” in a broad sense. As we noted earlier, an explanation for why your predictions are accurate includes all the concepts and definitions about mechanisms (Kerlinger’s, 1964 definition of “theory”) that help you describe why you think the predictions you are making are the best predictions possible. The explanation also identifies and describes all the variables that make up your predictions, variables that will be measured to test your predictions.

Crafting Appropriate Methods

Critical decisions you make to test your hypotheses form the methods for your scientific inquiry. As we have noted, imagining how you will test your hypotheses helps you decide whether the empirical observations you make can be compared with your predictions or whether you need to revise the methods (or your predictions). Remember, the theoretical framework is the coherent argument built from the rationales you develop as part of each hypothesis you formulate. Because each rationale explains why you make that prediction, it contains helpful cues for which methods would provide the fairest and most complete test of that prediction. In fact, your theoretical framework provides a logic against which you can check every aspect of the methods you imagine using.

You might find it helpful to ask yourself two questions as you think about which methods are best aligned with your theoretical framework. One is, “After reading my theoretical framework, will anyone be surprised by the methods I use?” If so, you should look back at your framework and make sure the predictions are clear and the rationales include all the reasons for your predictions. Your framework should telegraph the methods that make the most sense. The other question is, “Are there some predictions for which I can’t imagine appropriate methods?” If so, we recommend you return to your hypotheses—to your predictions and rationales (theoretical framework)—to make sure the predictions are phrased as precisely as possible and your framework is fully developed. In most cases, this will help you imagine methods that could be used. If not, you might need to revise your hypotheses.

Exercise 3.3

Kerlinger ( 1964 ) stated, “A theory is a set of interrelated constructs (concepts), definitions and propositions which presents a systematic view of phenomena by specifying relations among variables, with the purpose of explaining and predicting phenomena” (p. 11). What role do definitions play in a theoretical framework and how do they help in crafting appropriate methods?

Exercise 3.4

Sarah is in the beginning stages of developing a study. Her initial prediction is: There is a relationship between pedagogical content knowledge and ambitious teaching. She realizes that in order to craft appropriate measures, she needs to develop definitions of these constructs. Sarah’s original definitions are: Pedagogical content knowledge is knowledge about subject matter that is relevant to teaching. Ambitious teaching is teaching that is responsive to students’ thinking and develops a deep knowledge of content. Sarah recognizes that her prediction and her definitions are too broad and too general to work with. She wants to refine the definitions so they can guide the refinement of her prediction and the design of the study. Develop definitions of these two constructs that have clearer implications for the design and that would help Sarah to refine her prediction. (tip: Sarah may need to reduce the scope of her prediction by choosing to focus only on one aspect of pedagogical content knowledge and one aspect of ambitious teaching. Then, she can more precisely define those aspects.)

Guiding Interpretations of the Data

By providing rationales for your predictions, your theoretical framework explains why you think your predictions will be accurate. In education, researchers almost always find that if they make specific predictions (which they should), the predictions are not entirely accurate. This is a consequence of the fact that theoretical frameworks are never complete. Recall the definition of theories from Biddle and Anderson ( 1986 ): A theory “does not represent ultimate ‘truth,’ however; indeed, it will be superseded by other theories presently. Instead, it represents the best explanation we have, at present, for those events we have so far observed” (p. 241). If you have created your best developed and clearly stated theoretical framework that explains why you expected certain results, you can focus your interpretation on the ways in which your theoretical framework should be revised.

Focusing on realigning your theoretical framework with the data you collected produces the richest interpretation of your results. And it prevents you from making one of the most common errors of beginning researchers (and veteran researchers, as well): claiming that your results say more than they really do. Without this anchor to ground your interpretation of the data, it is easy to overgeneralize and make claims that go beyond the evidence.

In one of the definitions of theory presented earlier, Colquitt and Zapata-Phelan ( 2007 ) say that theories prevent scholars from “being dazzled by the complexity of the empirical world” (p. 1281). Theoretical frameworks keep researchers grounded by setting parameters within which the empirical world can be interpreted.

Exercise 3.5

Find two published articles that explicitly present theoretical frameworks (not all articles do). Where do you see evidence of the researchers using their theoretical frameworks to inform, shape, and connect other parts of their articles?

Showing the Contribution of Your Study

Theoretical frameworks contain the arguments that define the contribution of research studies. They do this in two ways, by showing how your study extends what is known and by setting the parameters for your contribution.

Showing How Your Study Extends What Is Known

Because your theoretical framework is built from what is already known or has been proposed, it situates your study in work that has occurred before. A clearly written framework shows readers how your study will take advantage of what is known to extend it further. It reveals what is new about what you are studying. The predictions that are generated from your framework are predictions that have never been made in quite the same way. They predict you will find something that has not been found previously in exactly this way. Your theoretical framework allows others to see the contributions that your study is likely to make even before the study has been conducted.

Setting the Parameters for Your Contribution

Earlier we noted that theoretical frameworks keep researchers grounded by setting parameters within which they should interpret their data. They do this by providing an initial explanation for why researchers expect to find particular results. The explanation is custom-built for each study. This means it uniquely explains the expected results. The results will almost surely turn out somewhat differently than predicted. Interpreting the data includes revising the initial explanation. So, you will end up with two versions of your theoretical framework, one that explains what you expected to find plus a second, updated framework that explains what you actually found.

The two frameworks—the initial version and the updated version—define the parameters of your study’s contribution. The difference between the two frameworks is what can be learned from your study. The first framework is a claim about what is known before you conduct your study about the phenomenon you are studying; the updated framework is a claim about how what is known has changed based on your results. It is the new aspects of the updated framework that capture the important contribution of your work.

Here is a brief example. Suppose you study the errors fourth graders make after receiving ordinary instruction on adding and subtracting decimal fractions. Based on empirical findings from past research, on theories of student learning, and on your own experience, you develop a rationale which predicts that a common error on “ragged” addition problems will be adding the wrong numerals. One of the reasons for this prediction is that students are likely to ignore the values of the digit positions and “line up” the numerals as they do with whole numbers. For instance, if they are asked to add 53.2 + .16, they are likely to answer either 5.48 or 54.8.

When you conduct your study, you present problems, handwritten, in both horizontal and vertical form. The horizontal form presents the numbers using the format shown above. The vertical form places one numeral over the other but not carefully aligned:

You find the predicted error occurs, but only for problems written in vertical form. To interpret these data, you look back at your theoretical framework and realize that students might ignore the value of the digits if the format reminded them of the way they lined up digits for whole number addition but might consider the value of the digits if they are forced to align the digits themselves, either by rewriting the problem or by just adding in their heads. A measure of what you (and others) learned from this study is the change in possible explanations (your theoretical frameworks). This does not mean your updated theoretical framework is “correct” or will make perfectly accurate predictions next time. But, it does mean that you are very likely moving toward more accurate predictions and toward a deeper understanding of how students think about adding decimal fractions.

Anchoring the Coherence of Your Study (and Your Evolving Research Paper)

Your theoretical framework serves as the anchor or center point around which all other aspects of your study should be aligned. This does not mean it is created first or that all other aspects are changed to align with the framework after it is created. The framework also changes as other aspects are considered. However, it is useful to always check alignment by beginning with the framework and asking whether other aspects are aligned and, if not, adjusting one or the other. This process of checking alignment is equally true when writing your evolving research paper as when planning and conducting your study.

Part III. How Do You Construct a Theoretical Framework for Your Study?

How do you start the process? Because constructing a theoretical framework is a natural extension of constructing rationales for your predictions, you already started as soon as you began formulating hypotheses: making predictions for what you will find and writing down reasons for why you are making these predictions. In Chap. 2 , we talked about beginning this process. In this section, we will explore how you can continue building out your rationales into a full-fledged theoretical framework.

Building a Theoretical Framework in Phases

Building your framework will occur in phases and proceed through cycles of clarifying your questions, making more precise and explicit your predictions, articulating reasons for making these predictions, and imagining ways of testing the predictions. The major source for ideas that will shape the framework is the research literature. That said, conversations with colleagues and other experts can help clarify your predictions and the rationales you develop to justify the predictions.

As you read relevant literature, you can ask: What have researchers found that help me predict what I will find? How have they explained their findings, and how might those explanations help me develop reasons for my predictions? Are there new ways to interpret past results so they better inform my predictions? Are there ways to look across previous results (and claims) and see new patterns that I can use to refine my predictions and enrich my rationales? How can theories that have credibility in the research community help me understand what I might find and help me explain why this is the case? As we have said, this process will go back and forth between clarifying your predictions, adjusting your rationales, reading, clarifying more, adjusting, reading, and so on.

One Researcher’s Experience Constructing a Theoretical Framework: The Continuing Case of Martha

In Chap. 2 , we followed Martha, a doctoral student in mathematics education, as she was working out the topic for her study, asking questions she wanted to answer, predicting the answers, and developing rationales for these predictions. Our story concluded with a research question, a sample set of predictions, and some reasons for Martha’s predictions. The question was: “Under what conditions do middle school teachers who lack conceptual knowledge of linear functions benefit from five 2-hour learning opportunity (LO) sessions that engage them in conceptual learning of linear functions as assessed by changes in their teaching toward a more conceptual emphasis of linear functions?” Her predictions focused on particular conditions that would affect the outcomes in particular ways. She was beginning to build rationales for these predictions by returning to the literature and identifying previous research and theory that were relevant. We continue the story here.

Imagine Martha continuing to read as she develops her theoretical framework—the rationales for her predictions. She tweaks some of her predictions based on what other researchers have already found. As she continues reading, she comes across some related literature on learning opportunities for teachers. A number of articles describe the potential of another form of LOs that might help teachers teach mathematics more conceptually—analyzing videos of mathematics lessons.

The data suggested that teachers can improve their teaching by analyzing videos of other teachers’ lessons as well as their own. However, the results were mixed so researchers did not seem to know exactly what makes the difference. Martha also read that teachers who already can analyze videos of lessons and spontaneously describe the mathematics that students are struggling with and offer useful suggestions for how to improve learning opportunities for students teach toward more conceptual learning goals, and their students learn more (Kersting et al., 2010 , 2012 ). These findings caught Martha’s attention because it is unusual to find correlates with conceptual teaching and better achievement. What is not known, realized Martha, is whether teachers who learn to analyze videos in this way, through specially designed LOs, would look like the teachers who already could analyze them. Would teachers who learned to analyze videos teach more conceptually?

It occurred to Martha she could bring these lines of research together by extending what is known along both lines. Recall our earlier suggestion of looking across the literature and noticing new patterns that can inform your work. Martha thought about studying how, exactly, these two skills are related: analyzing videos in particular ways and teaching conceptually. Would the relationships reported in the literature hold up for teachers who learn to describe the mathematics students are struggling with and make useful suggestions for improving students’ LOs?

Martha was now conflicted. She was well on her way to developing a testable hypothesis about the effects of learning about linear functions, but she was really intrigued by the work on analyzing videos of teaching. In addition, she saw several advantages of switching to this new topic:

The research question could be formulated quite easily. It would be something like: “What are the relationships between learning to analyze videos of mathematics teaching in particular ways (specified from prior research) and teaching for conceptual understanding?”

She could imagine predicting the answers to this question based directly on previous research. She would predict connections between particular kinds of analysis skills and levels of conceptual teaching of mathematics in ways that employed these skills.

The level of conceptual teaching, a challenging construct to define with her previous topic (the effects of professional development on the teaching of linear functions), was already defined in the work on analyzing videos of mathematics teaching, so that would solve a big problem. The definition foregrounded particular sets of behaviors and skills such as identifying key learning moments in a lesson and focusing on students’ thinking about the key mathematical idea during these moments. In other words, Martha saw ways to adapt a definition that had already been used and tested.

The issue of transfer—another challenging issue in her original hypothesis—was addressed more directly in this setting because the learning environment—analyzing videos of classroom teaching—is quite close to the classroom environment in which participants’ conceptual teaching would be observed.

Finally, the nature of learning opportunities, an aspect of her original idea she still needed to work through, had been explored in previous studies on this new topic, and connections were found between studying videos and changes in teaching.

Given all these advantages, Martha decided to change her topic and her research question. We applaud this decision for two major reasons. First, Martha’s interest grew as she explored this new topic. She became excited about conducting a study that might answer the research question she posed. It is always good to be passionate about what you study. Second, Martha was more likely to contribute important new insights if she could extend what is already known rather than explore a new area. Exploring something quite new requires lots of effort defining terms, creating measures, making new predictions, developing reasons for the predictions, and so on. Sometimes, exploring a new area has payoffs. But, as a beginning researcher, we suggest you take advantage of work that has already been done and extend it in creative ways.

Although Martha’s idea of extending previous work came with real advantages, she still faced a number of challenges. A first, major challenge was to decide whether she could build a rationale that would predict learning to analyze videos caused more conceptual teaching. Or, could she only build a rationale that would predict that there was a relationship between changes in analyzing videos and level of conceptual teaching? Perhaps a cause-effect relationship existed but in the opposite direction: If teachers learned to teach more conceptually, their analysis of teaching videos would improve. Although most of the literature described learning to analyze videos as the potential cause of teaching conceptually, Martha did not believe there was sufficient evidence to build a rationale for this prediction. Instead, she decided to first determine if a relationship existed and, if so, to understand the relationship. Then, if warranted, she could develop and test a hypothesis of causation in a future study. In fact, the direction of the causation might become clearer when she understood the relationship more clearly.

A second major challenge was whether to study the relationship as it existed or as one (or both) of the constructs was changing. Past research had explored the relationship as it existed, without inducing changes in either analyzing videos or teaching conceptually. So, Martha decided she could learn more about the relationship if one of the constructs was changing in a planned way. Because researchers had argued that teachers’ analysis of video could be changed with appropriate LOs, and because changing teachers’ teaching practices has resisted simple interventions, Martha decided to study the relationship as she facilitated changes in teachers’ analysis of videos. This would require gathering data on the relationship at more than one point in time.

Even after resolving these thorny issues, Martha faced many additional challenges. Should she predict a closer relationship between learning to analyze video and teaching for conceptual understanding before teachers began learning to analyze videos or after? Perhaps the relationship increases over time because conceptual teaching often changes slowly. Should she predict a closer relationship if the content of the videos teachers analyzed was the same as the content they would be teaching? Should she predict the relationship will be similar across pairs of similar topics? Should she predict that some analysis skills will show closer relationships to levels of conceptual teaching than others? These questions and others occurred to Martha as she was formulating her predictions, developing justifications for her predictions, and considering how she would test the predictions.

Based on her reading and discussions with colleagues, Martha phrased her initial predictions as follows:

There will be a significant positive correlation between teachers’ performance on analysis of videos and the extent to which they create conceptual learning opportunities for their students both before and after proposed learning experiences.

The relationship will be stronger:

Before the proposed opportunities to learn to analyze videos of teaching;

When the videos and the instruction are about similar mathematical topics; and,

When the videos analyzed display conceptual misunderstandings among students.

Of the video analysis skills that will be assessed, the two that will show the strongest relationship are spontaneously describing (1) the mathematics that students are struggling with and (2) useful suggestions for how to improve the conceptual learning opportunities for students.

Martha’s rationales for these predictions—her theoretical framework—evolved along with her predictions. We will not detail the framework here, but we will note that the rationale for the first prediction was based on findings from past research. In particular, the prediction is generated by reasoning that if there has been no special intervention, the tendency to analyze videos in particular ways and to teach conceptually develop together. This might explain Kersting’s findings described earlier. The second and third predictions were based on the literature on teachers’ learning, especially their learning from analyzing videos of teaching.

Before leaving Martha at this point in her journey, we want to make an important point about the change she made to her research topic. Changes like this occur quite often as researchers do the hard intellectual work of developing testable hypotheses that guide research studies. When this happens to you, it can feel like you have lost ground. You might feel like you wasted your time on the original topic. In Chap. 1 , we described inevitable “failure” when engaged in scientific inquiry. Failure is often associated with realizing the data you collected do not come close to supporting your predictions. But a common kind of failure occurs when researchers realize the direction they have been pursuing should change before they collect data. This happened in Martha’s case because she came across a topic that was more intriguing to her and because it helped solve some problems she was facing with the previous topic. This is an example of “failing productively” (see Chap. 1 ). Martha did not succeed in pursuing her original idea, but while she was recognizing the problems, she was also seeing new possibilities.

Constantly Improving Your Framework

We will use Martha’s experience to be more specific about the back-and-forth process in which you will engage as you flesh out your framework. We mentioned earlier your review of the literature as a major source of ideas and evidence that will affect your framework.

Reviewing Published Empirical Evidence

One of the best sources for helping you specify your predictions are studies that have been conducted on related topics. The closer to your topic, the more helpful will be the evidence for anticipating what you will find. Many beginning researchers worry they will locate a study just like the one they are planning. This (almost) never happens. Your study will be different in some ways, and a study that is very similar to yours can be extraordinarily helpful in specifying your predictions. Be excited instead of terrified when you come across a study with a title similar to yours.

Try to locate all the published research that has been conducted on your topic. What does “on your topic” mean? How widely should you cast your net? There are no rules here; you will need to use your professional judgment. However, here is a general guide: If the study does not help you clarify your predictions, change your confidence in them, or strengthen your rationale, then it falls outside your net.

In addition to helping specify your predictions, prior research studies can be a goldmine for developing and strengthening your theoretical framework. How did researchers justify their predictions or explain why they found what they did? How can you use these ideas to support (or change) your own predictions?

By reading research on similar topics, you might also imagine ways of testing your predictions. Maybe you learn of ways you could design your study, measures you could use to collect data, or strategies you could use to analyze your data. As you find helpful ideas, you will want to keep track of where you found these ideas so you can cite the appropriate sources as you write drafts of your evolving research paper.

Examining Theories

You will read a wide range of theories that provide insights into why things might work like they do. When the phenomena addressed by the theory are similar to those you will study, the associated theories can help you think through your own predictions and why you are making them. Returning to Martha’s situation, she could benefit from reading theories on adult learning, especially teacher learning, on transferring knowledge from one setting to another, on professional development for teachers, on the role of videos in learning, on the knowledge needed to teach conceptually, and so on.

Focusing on Variables and Mechanisms

As you review the literature and search for evidence and ideas that could strengthen your predictions and rationales, it is useful to keep your eyes on two components: the variables you will attend to and the mechanisms that might explain the relationships between the variables. Predictions could be considered statements about expected behaviors of the variables. The theoretical framework could be thought of as a description of all the variables that will be deliberately attended to plus the mechanisms conjectured to account for these relationships.

In Martha’s case, the most obvious variables are the responses teachers give to questions about their analysis of the videos and the features observed in their teaching practices. The mechanism of primary interest is the (mental and social) process that transforms the skills, knowledge, and attention involved in analyzing videos into particular kinds of teaching practices—or vice versa. The definition of conceptual teaching she adopted from previous studies gave her a clue about the mechanisms—about how and why learning to analyze videos might affect classroom teaching. The definition included attending to key learning moments in a lesson and tracking students’ thinking during these moments. Martha predicted that if teachers learned to attend to these aspects of teaching when viewing videos, they might attend to them when planning and implementing their own teaching.

As Martha reviewed the literature, she identified a number of variables that might affect the likelihood and extent of this translation. Here are some examples: how well teachers understand the mathematics in the videos and the mathematics they will teach; the nature of the videos themselves; the number of opportunities teachers have to analyze videos and the ways in which these opportunities are structured; teachers’ analysis of videos and their teaching practices before the learning opportunities begin; and how much time they have to apply what they learn to their own teaching.

Martha identified these additional variables because she learned they might have a direct influence on the mechanisms that could explain the relationship between analyzing videos and teaching. Some variables might support these mechanisms, and some might interfere. Martha’s task at this point in her work is to identify and describe all the variables that could play a meaningful role in the outcome of her study. This means to identify each variable for which it is possible to establish a clear and direct connection between the variable and the relationship she planned to investigate. Using the outcome of this task, Martha then needs to update her description of the mechanisms that could account for the relationships she expects to see and review her predictions and theoretical framework with these variables and mechanisms in mind.

Exercise 3.6

Review the predictions that Martha made and identify the variables that play a role in these predictions. Even though you might not be immersed in this literature, think about the alignment between the variables included in the predictions and those that could impact the relationships in which Martha is interested. Are there other missing variables that should be included in her predictions?

How Do You Know When You Have Finished Building Your Theoretical Framework?

The question of when your theoretical framework is finished could be answered in several ways. First, it is never really finished. As you continue to write your evolving research paper, you will continue strengthening your framework. You might even refine the framework as you write the final draft of your paper, after you have collected and analyzed your data. Furthermore, if you do follow-up studies, you will continue to build your framework.

A second answer is that you should invest the time and effort to build a theoretical framework that is as finished as possible at each point in the research process. As you write each draft of your evolving research paper, you should feel as if you have the strongest, most robust rationale you can have for your current predictions. In other words, you should feel that with each succeeding draft you have finished building your framework, even though you are quite sure you have not.

A third answer addresses a common, related question: “How do I know when I have included enough ideas and borrowed from enough sources? Would including another idea or citing another source be useful?” The answer is that you should include only those ideas that contribute to building a stronger framework. When you wonder whether you should include another idea or reference, ask yourself whether doing so would make your framework stronger in all the ways we described earlier.

Exercise 3.7

In 2–3 pages (single spaced), write out the plan for your study. The plan should include your research questions, your predictions of the answers, your rationale for the predictions (i.e., your theoretical framework), and your imagined plan for testing the predictions. Be as explicit and precise as you can. Be sure you have identified the critical variables and described the mechanism(s) that could explain the phenomena, the relationships, and/or the changes you predict. Look back to see if the logic connecting the parts is obvious. Ask yourself whether the tests you plan are what anyone familiar with your framework would expect (i.e., there should be no surprises).

Part IV. Refining a Theoretical Framework: A Scholarly Dialogue

As we noted above, conversations with colleagues and other experts can help you refine your theoretical framework by clarifying your predictions and digging into the details of the rationales you develop to justify those predictions. This is as true for experienced researchers as it is for beginning researchers. The dialogue below is an example of how two colleagues, Adrian (A) and Corin (C), work together to gradually formulate a testable hypothesis. Some of their conversation will look familiar as they refine their prediction through multiple steps of discussion:

Narrowing the focus of their prediction.

Making their prediction more testable.

Being more specific about what they want to study.

Engaging their prediction in cycles of refinements.

Determining the appropriate level/grainsize of their prediction (zoom in, zoom out).

Adding more predictions.

Thinking about underlying mechanisms (i.e., what explains the relationships between their variables).

Putting their predictions on a continuum (going from black and white to grey).

In addition, they construct their theoretical framework to match their hypotheses through multiple steps:

Defining and rationalizing their variables.

Re-evaluating their initial rationales in response to changes in their initial predictions.

Asking themselves “why” questions about predictions and rationales.

Finding empirical evidence and theory that better supports their evolving predictions.

Keeping in mind what they are going to be measuring.

Making sure their rationales support each link in their chain of reasoning.

Identifying underlying mechanisms.

Making sure that statements are included in their rationale if and only if they directly support their predictions and are essential to the argument.

They begin with the following hypothesis:

Prediction: Students will exhibit more persistence in mathematical course taking in high school if they work in groups.

Brief Description of Rationale: When people work in groups, they feel more competent and learn better (Cohen & Lotan, 2014 ; Jansen, 2012). When people feel more competent, they persist in additional mathematical course taking (Bandura & Schunk, 1981 ; Dweck, 1986 ).

So, do we think this hypothesis is testable?

Well actually, who these students are is probably something we need to be more specific about.

Good point, and also, since Algebra 2 is the bridge to additional course taking (i.e., the first course students don’t have to take), perhaps we should target Algebra 2. How about if we change our prediction to the following: Algebra 2 students will exhibit more mathematical persistence in mathematical course taking in high school if they work in groups in Algebra 2.

Okay, but another problem is that it would take a long time to collect data that would inform a prediction about the courses students take, and over that amount of time I’m not sure we could even tell if groupwork was responsible. What if we limited our prediction to: Algebra 2 students will exhibit more mathematical persistence in Algebra 2 if they work in groups.

Good idea! But when we talk about persistence, do we mean students don’t quit, or that they don’t drop the course, or productively struggle during class, or turn in their homework, or is it something else we mean? To me, what would be testable about mathematical persistence would be persistence at the problem level, such as when students get stuck on a problem, but they don’t give up.

I agree. So, let’s predict the following: Algebra 2 students will exhibit more mathematical persistence in Algebra 2 when they get stuck on problems if they work in groups. That’s something I think we could test.

Yes, but I think we need to be even more specific about what we mean by mathematical persistence when students get stuck on problems.

Hmm, what if we focused specifically on mathematical persistence that involves staying engaged in trying to solve a problem for the duration of a problem-solving session or until the problem gets solved? But that also makes me wonder if we want to be focusing on persistence at the individual level or at the group level?

Umm, I think we should focus on persistence at the individual level, because that’s more consistent with our original interest in persistence in course taking, which is about individual students, not about groups.

Okay, that makes sense. So then how about this for a prediction: If Algebra 2 students work in groups, they will be more likely to stay engaged in trying to solve problems for the duration of a problem-solving session or until they solve the problem.

To this point in the dialogue, Adrian and Corin are developing a theoretical framework by sharpening what they mean by their prediction and making sure their prediction is testable. In the next part, they return to their original idea to make sure they have not strayed too far by making their prediction more precise. The dialogue illustrates how making predictions should support the goal of understanding the relationship between variables and the mechanisms for change.

Yes, I’m liking the way this prediction is evolving. However, I also feel like our prediction is now so focused that we’ve lost a bit of our initial idea of competence and learning, which is what we were initially interested in. Could we do something to bring those ideas back? Perhaps we could create more predictions to get at more of those ideas?

Great idea! Okay, so to help us see what we are missing now, let’s look back at the initial links in our chain of reasoning. We initially said that Working in Groups leads to Feeling Competent & Learning Better leads to Persistence in Math Course Taking. But our chain of reasoning has changed. I think it’s more like this: Working in Groups on Problems leads to Staying Engaged in Problem Solving leads to Greater Sense of Competence and Learning Better leads to More Persistence in Course Taking.

Okay, so if that’s the case, it looks like our new prediction just tests the first link in this chain, the link between Working in Groups on Problems and Staying Engaged in Problem Solving. It looks like there are three other potential predictions we could make; we could make a prediction about the relationship between Staying Engaged in Problem Solving and having a Greater Sense of Competence, between Staying Engaged in Problem Solving and Learning Better, and between having a Greater Sense of Competence/Learning Better and More Persistence in Course Taking.

Clearly that’s too many predictions for us to tackle in one study and actually I am aware of several studies that already address the third prediction. So, we can use those studies as part of our rationale and don’t need to study that link.

I agree. Let’s just add one prediction, one about the link between Staying Engaged and Sense of Competence. In our initial prediction, we just had a vague connection between Working in Groups and Sense of Competence. But in our new prediction, we were more specific that working in groups helps students stay engaged until the end of a problem-solving session. So, I guess we could say for a second prediction then that When Algebra 2 students stay engaged in problem solving until the end of a problem-solving session, they develop a greater sense of competence.

Okay so we will have two predictions to examine with our study: Prediction 1 is: If Algebra 2 students work in groups, they will be more likely to stay engaged in trying to solve problems for the duration of a problem-solving session or until they solve the problem. This prediction deals with the first link in our chain of reasoning. And then Prediction 2 is: If Algebra 2 students try to solve problems for the duration of a problem-solving session or until they solve the problem, they will be more likely to develop a sense of competence. Oh, as soon as I finished stating that prediction, the thought just came to me, “sense of competence about what?”

How about if we focused on sense of competence in being able to solve similar problems in the future? Actually, maybe that’s too limited. Maybe we should expand our prediction a bit more so we include a sense of competence that’s at least somewhat closer to more course taking? Something like sense of competence that involves feeling capable of understanding future Algebra 2 concepts. That’s at least bigger than sense of competence at solving similar problems. If students feel they’re capable of understanding future Algebra 2 concepts, then they will probably be more likely to persist in course taking too.

Okay, that makes sense. So, then our Prediction 2 could be: If Algebra 2 students try to solve problems for the duration of a problem-solving session or until they solve the problem, they will be more likely to feel they will be capable of understanding future Algebra 2 concepts.

Oh, I just had an additional idea! What if we changed the two predictions one more time to allow for more or less of the variables? For example, Prediction 1 could be: The more Algebra 2 students work in groups, the more likely they will stay engaged in trying to solve problems for the duration of a problem-solving session or until they solve the problem.

Yes, great. So, that would mean Prediction 2 could be: The more Algebra 2 students try to solve problems for the duration of a problem-solving session or until they solve the problem, the more likely they will feel they are capable of understanding future Algebra 2 concepts.

So, I think we’re happy with our predictions for now, but I think we need to work on our rationales for those predictions because they no longer apply very well.

Okay, to recap, our original chain of reasoning was Working in Groups leads to Feeling Competent & Learning Better leads to Persistence in Math Course Taking. Our initial rationales were the following: For the link between working in groups and feeling competent, we based that link on Cohen and Lotan’s ( 2014 ) book on Designing Groupwork, in which they explain why and how all students can feel competent through their engagement in groupwork. We also based this link on that 2012 Jansen study that found that groupwork helped students enact their competence in math. Then, for the link between competence and persistence, we based that link on the Bandura and Schunk ( 1981 ) study and on the work by Carol Dweck ( 1986 ) that show that children who feel more competent in arithmetic, tend to persist more.

Corin and Adrian have looked back at their initial research idea. In doing so, they illustrated how developing a theoretical framework involves developing and refining a chain of reasoning. They continue by working on developing rationales for their predictions.

Okay, so let’s think if any of our previous rationales still work. How about Elizabeth Cohen’s work? I still think her work applies because it shows that groupwork can affect engagement. But now that I think about it, another part of her work indicates that groupwork needs particular norms in order to be effective. So maybe we should tighten up our predictions to focus just on groupwork that has particular norms?

But, on the other hand, what about Jo Boaler’s ( 1998 ) “Open and Closed Mathematics” article? In that study, students at the Phoenix Park School did not have much structure, and in spite of that, groupwork worked quite well for those students, better than individual work did for students at the Amber Hill School who had highly structured instruction.

That’s a good point. So maybe we should leave our predictions about groupwork as is (i.e., not focus on particular norms). Also, the ideas in the Boaler article would be good to add to our theoretical framework because it deals with secondary students, which aligns better with the ages of the Algebra 2 students we are planning on studying.

Okay, so we’re adding the ideas in the Boaler article. I also think we need to find literature that specifies the kind of engagement we want to focus on. Looking at the engagement literature would sharpen our thinking about the engagement we are most interested in. We should consider Brigid Barron’s ( 2003 ) study, “When Smart Groups Fail.” In her study, students produced better products if they engaged with each other and with the content. But that makes me think that we are mostly just focused on the latter, namely on how individuals engage with the content.

I agree we’re focused on individuals’ engagement with the content. Come to think of it, the fact that we’re focused on how individuals engage with content rather than how groups engage further justifies why we’re not looking at groupwork norms. But let me ask a question we need to answer. Why are we focusing on how individuals engage with content? It’s not just a preference. It’s because we think individual engagement with content is related to feeling capable. So, our decision to focus on individual engagement aligns with our predictions. And even though we’re not including Barron’s work in our framework, considering her work helped sharpen our thinking about what we’re focusing on.

You know, we are kind of in a weird space because we’re focusing on individual engagement with content at the same time as we are predicting that groupwork leads to more engagement. In other words, we are and aren’t taking a social perspective. But what this reminds me of is how, from the perspective of the theory of constructivism, even though individuals have to make sense of things for themselves, social interactions are what drives sense making. In fact, here’s a quote from von Glasersfeld ( 1995 ): “Piaget has stressed many times that the most frequent cause of accommodation is the interaction” (p. 66). So, I think we can use constructivism as a theoretical justification for predicting that the social activity of groupwork is what is related to individual engagement with content.

Interesting! Yes, makes sense. When you were describing that, I had another insight from constructivism. You know how when someone experiences a perturbation, it also creates a need in them to resolve the perturbation, right? So maybe perturbations are the mechanism explaining why groupwork leads to more individual engagement with content. Groupwork potentially generates perturbations, meaning the person engages more to try to resolve those perturbations.

Okay, now that we have brought in the idea of perturbations as potentially being the mechanism that drives how working in groups leads to staying more engaged, perhaps we need to reconsider what we will be measuring in our study. Will it be perturbations, or will it be staying engaged that we should be measuring?

I think what we are saying is that the need to resolve perturbations is part of the underlying mechanism, but measuring the need to resolve perturbations would be difficult if not impossible. So, instead, I think we should focus on measuring the variable staying engaged , a variable we can measure. And then if we find that more working in groups leads to more staying engaged, that also gives us more evidence that our theoretical framework with perturbations as a mechanism is viable. In other words, mechanisms are part of our framework and by testing our prediction, we are testing our theoretical framework (i.e., our rationales) too.

This final part of the dialogue illustrates that the rationale for a study continues to develop as the predictions continue to be refined and testability continues to be considered. In other words, the development of the predictions and rationale (i.e., the theoretical framework) should be iterative and ongoing.

Through their discussion, Adrian and Corin have refined both their predictions and their rationales. In the process, the key ideas they have drawn on contributed to their rationales and thus to constructing their theoretical framework.

Part V. Distinctions Between Rationales, Theoretical Frameworks, and Literature Reviews

We have introduced a number of terms that play critical roles in the scientific inquiry process. Because they refer to related and sometimes overlapping ideas, keeping straight their meanings and uses can be challenging. It might be helpful to revisit each of them briefly to describe how they are similar to, and different from, each other.

To distinguish between rationales, theoretical frameworks, and literature reviews, it is useful to consider the roles they play as you plan and conduct a study compared to the roles they play when you write the report of your study.

Thinking Through a Study

The chronology of the thinking process often moves through many cycles of identifying a research problem or asking a question, and then reading the literature to learn more about the problem, and then refining and narrowing the scope of a question that would add to or extend what is known, and then predicting (guessing) an answer to the question and asking yourself why you predicted this answer and writing a first draft of your rationale, and then reading the literature to improve your rationale, and then realizing you can refine the question further along with specifying a clearer and more targeted prediction, and then reading the literature to further improve your rationale, and then realizing you can refine the question further along with a clearer and more targeted prediction, and so on.

The primary activity that generates more specific and clearer hypotheses is searching and reviewing literature . You can return to the literature as often as you need to build your rationales . As your rationales develop, they morph into your theoretical framework . The theoretical framework is a coherent argument that threads together the individual rationales and explains why your predictions are the best predictions the field can make at this time.

If you have one research question and one prediction you will have one rationale. In this case, your rationale is essentially the same as your theoretical framework. If you have more than one research question, you will have multiple predictions and multiple rationales. As you develop rationales for each prediction, you might find lots of overlap. Maybe the literatures you read to refine each prediction and develop each rationale overlap, and maybe the arguments you piece together include many of the same elements. Your theoretical framework emerges from weaving the rationales together into one coherent argument. Although this process is more complicated than the thinking process for one prediction, it is more common. If you find few connections among the rationales for each prediction, we recommend stepping back and asking whether you are conducting more than one study. It might make more sense to sort the questions into two or more studies because the rationales for the predicted answers are drawing from different literatures.

Writing the Evolving Research Paper

We recommend that you write drafts of the research report as you think through your study and make decisions about how to proceed. Although your thinking will be fluid and evolving, we recommend that you follow the conventions of academic writing as you write drafts. For example, we recommend that you structure the paper using the five typical major sections of a journal article: introduction, theoretical framework, methods, results, and discussion. Each of these sections will go through multiple drafts as you plan your study, collect the data, analyze the data, and interpret the results.

In the introduction, you will present the research problem you are studying. This includes describing the problem, explaining why it is significant, defining the special terms you use, and often presenting the research questions you will address along with the answers you predict. Sometimes the questions and predictions are part of the next section—the theoretical framework.

In the theoretical framework, you will present your best arguments for expecting the predicted answers to the research questions. You will not trace the many cycles in which you engaged to get to the best versions of your arguments but rather present the latest and best version. The report of a study does not describe the chronology of the back-and-forth messiness always involved in thinking through all aspects of the study. What you learned from reviewing the literature will be an integral part of your arguments. In other words, the review of research will be included in the presentation of your theoretical framework rather than in a separate section.

The literature you choose to include to present your theoretical framework is not all the literature you reviewed for conducting your study. Rather, the literature cited in your paper should be the literature that contributed to building your theoretical framework, and only that literature. In other words, the theoretical framework places the boundaries on what you should review in the paper.

Beginning researchers are often tempted to review much of what they read. Researchers put lots of time into reading, and leaving lots of it out when writing the paper can make all that reading feel like a waste of time. It is not a waste of time; it is always part of the research process. But, reviewing more than you need in the paper becomes a distraction and diverts the reader from the main points.

What should you do if the editor of the journal requires, or recommends, a section titled “review of research”? We recommend you create a somewhat more elaborated review for this section and then show exactly how you used the literature to build your rationale in the theoretical framework section.

Reviewers notice when the theoretical framework and the literature reviewed do not provide sufficient justification for the research questions (or the hypotheses). We found that about 13% of JRME reviews noted an especially important gap—the research questions in a paper were not sufficiently motivated. We expect the same would be true for other research journals. Reviewers also note when manuscripts either do not have an explicit theoretical framework or when they seem to be juggling more than one theoretical framework.

Part VI. Moving to Methods

A significant benefit of building rich and precise theoretical frameworks is the guidance they provide for selecting and creating the methods you will use to test your hypotheses. The next phase in the process of scientific inquiry is crafting your methods: choosing your research design, selecting your sample, developing your measures, deciding on your data analysis strategies, and so on. In Chap. 4 , we discuss how you can do this in ways that keep your story coherent.

Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41 , 586–598. https://doi.org/10.1037/0022-3514.41.3.586

Article   Google Scholar  

Barron, B. (2003). When smart groups fail. Journal of the Learning Sciences, 12 (3), 307–359. https://doi.org/10.1207/S15327809JLS1203_1

Biddle, B. J., & Anderson, D. S. (1986). Theory, methods, knowledge, and research on teaching. In M. C. Wittrock (Ed.), Handbook of research on teaching: A project of the American Educational Research Association . Macmillan.

Google Scholar  

Boaler, J. (1998). Open and closed mathematics: Student experiences and understandings. Journal for Research in Mathematics Education, 29 , 41–62.

Cai, J., Morris, A., Hohensee, C., Hwang, S., Robison, V., Cirillo, M., Kramer, S. L., & Hiebert, J. (2019c). Theoretical framing as justifying. Journal for Research in Mathematics Education, 50 (3), 218–224. https://doi.org/10.5951/jresematheduc.50.3.0218

Cohen, E. G., & Lotan, R. A. (2014). Designing groupwork: Strategies for the heterogenous classroom (3rd ed.). Teachers College Press.

Colquitt, J. A., & Zapata-Phelan, C. P. (2007). Trends in theory building and theory testing: A five-decade study of the academy of management journal. The Academy of Management Journal, 50 (6), 1281–1303.

Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41 , 1040–1048. https://doi.org/10.1037/0003-066X.41.10.1040

Kerlinger, F. N. (1964). Foundations of behavioral research: Educational and psychological inquiry . Holt, Rinehardt, & Winston.

Kersting, N. B., Givvin, K., Sotelo, F., & Stigler, J. W. (2010). Teacher’s analysis of classroom video predicts student learning of mathematics: Further explorations of a novel measure of teacher knowledge. Journal of Teacher Education , 61(1–2), 172–181. https://doi.org/10.1177/0022487109347875 , 172.

Kersting, N. B., Givvin, K. B., Thompson, B., Santagata, R., & Stigler, J. (2012). Developing measures of usable knowledge: Teachers’ analyses of mathematics classroom videos predict teaching quality and student learning. American Educational Research Journal, 49 (3), 568–590. https://doi.org/10.3102/0002831212437853

Oxford University Press. (2021). Theory. In Lexico.com dictionary . Lexico.com . https://www.lexico.com/en/definition/theory

Praetorius, A.-K., & Charalambous, C. (2022). Moving the field forward with respect to theorizing teaching: An introduction. In A.-K. Praetorius & C. Charalmabous (Eds.), Expert perspectives on theorizing teaching: Current status, problematic issues, and aspirations . Springer.

von Glasersfeld, E. (1995). Radical constructivism: A way of knowing and learning . Falmer Press.

Download references

Author information

Authors and affiliations.

School of Education, University of Delaware, Newark, DE, USA

James Hiebert, Anne K Morris & Charles Hohensee

Department of Mathematical Sciences, University of Delaware, Newark, DE, USA

Jinfa Cai & Stephen Hwang

You can also search for this author in PubMed   Google Scholar

Rights and permissions

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Reprints and permissions

Copyright information

© 2023 The Author(s)

About this chapter

Cite this chapter.

Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). Building and Using Theoretical Frameworks. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_3

Download citation

DOI : https://doi.org/10.1007/978-3-031-19078-0_3

Published : 03 December 2022

Publisher Name : Springer, Cham

Print ISBN : 978-3-031-19077-3

Online ISBN : 978-3-031-19078-0

eBook Packages : Education Education (R0)

Share this chapter

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

What is a good example of a conceptual framework?

Last updated

18 April 2023

Reviewed by

Miroslav Damyanov

A well-designed study doesn’t just happen. Researchers work hard to ensure the studies they conduct will be scientifically valid and will advance understanding in their field.

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

• 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.

Get started today

Go from raw data to valuable insights with a flexible research platform

Editor’s picks

Last updated: 21 December 2023

Last updated: 16 December 2023

Last updated: 6 October 2023

Last updated: 25 November 2023

Last updated: 12 May 2023

Last updated: 15 February 2024

Last updated: 11 March 2024

Last updated: 12 December 2023

Last updated: 18 May 2023

Last updated: 6 March 2024

Last updated: 10 April 2023

Last updated: 20 December 2023

Latest articles

Related topics, log in or sign up.

Get started for free

What is a Conceptual Framework?

A conceptual framework sets forth the standards to define a research question and find appropriate, meaningful answers for the same. It connects the theories, assumptions, beliefs, and concepts behind your research and presents them in a pictorial, graphical, or narrative format.

Updated on August 28, 2023

What are frameworks in research?

Both theoretical and conceptual frameworks have a significant role in research.  Frameworks are essential to bridge the gaps in research. They aid in clearly setting the goals, priorities, relationship between variables. Frameworks in research particularly help in chalking clear process details.

Theoretical frameworks largely work at the time when a theoretical roadmap has been laid about a certain topic and the research being undertaken by the researcher, carefully analyzes it, and works on similar lines to attain successful results. 

It varies from a conceptual framework in terms of the preliminary work required to construct it. Though a conceptual framework is part of the theoretical framework in a larger sense, yet there are variations between them.

The following sections delve deeper into the characteristics of conceptual frameworks. This article will provide insight into constructing a concise, complete, and research-friendly conceptual framework for your project.

Definition of a conceptual framework

True research begins with setting empirical goals. Goals aid in presenting successful answers to the research questions at hand. It delineates a process wherein different aspects of the research are reflected upon, and coherence is established among them. 

A conceptual framework is an underrated methodological approach that should be paid attention to before embarking on a research journey in any field, be it science, finance, history, psychology, etc. 

A conceptual framework sets forth the standards to define a research question and find appropriate, meaningful answers for the same. It connects the theories, assumptions, beliefs, and concepts behind your research and presents them in a pictorial, graphical, or narrative format. Your conceptual framework establishes a link between the dependent and independent variables, factors, and other ideologies affecting the structure of your research.

A critical facet a conceptual framework unveils is the relationship the researchers have with their research. It closely highlights the factors that play an instrumental role in decision-making, variable selection, data collection, assessment of results, and formulation of new theories.

Consequently, if you, the researcher, are at the forefront of your research battlefield, your conceptual framework is the most powerful arsenal in your pocket.

What should be included in a conceptual framework?

A conceptual framework includes the key process parameters, defining variables, and cause-and-effect relationships. To add to this, the primary focus while developing a conceptual framework should remain on the quality of questions being raised and addressed through the framework. This will not only ease the process of initiation, but also enable you to draw meaningful conclusions from the same. 

A practical and advantageous approach involves selecting models and analyzing literature that is unconventional and not directly related to the topic. This helps the researcher design an illustrative framework that is multidisciplinary and simultaneously looks at a diverse range of phenomena. It also emboldens the roots of exploratory research. 

Fig. 1: Components of a conceptual framework

How to make a conceptual framework

The successful design of a conceptual framework includes:

• Selecting the appropriate research questions
• Defining the process variables (dependent, independent, and others)
• Determining the cause-and-effect relationships

This analytical tool begins with defining the most suitable set of questions that the research wishes to answer upon its conclusion. Following this, the different variety of variables is categorized. Lastly, the collected data is subjected to rigorous data analysis. Final results are compiled to establish links between the variables. 

The variables drawn inside frames impact the overall quality of the research. If the framework involves arrows, it suggests correlational linkages among the variables. Lines, on the other hand, suggest that no significant correlation exists among them. Henceforth, the utilization of lines and arrows should be done taking into cognizance the meaning they both imply.

Example of a conceptual framework

To provide an idea about a conceptual framework, let’s examine the example of drug development research. 

Say a new drug moiety A has to be launched in the market. For that, the baseline research begins with selecting the appropriate drug molecule. This is important because it:

• Provides the data for molecular docking studies to identify suitable target proteins
• Performs in vitro (a process taking place outside a living organism) and in vivo (a process taking place inside a living organism) analyzes

This assists in the screening of the molecules and a final selection leading to the most suitable target molecule. In this case, the choice of the drug molecule is an independent variable whereas, all the others, targets from molecular docking studies, and results from in vitro and in vivo analyses are dependent variables.

The outcomes revealed by the studies might be coherent or incoherent with the literature. In any case, an accurately designed conceptual framework will efficiently establish the cause-and-effect relationship and explain both perspectives satisfactorily.

If A has been chosen to be launched in the market, the conceptual framework will point towards the factors that have led to its selection. If A does not make it to the market, the key elements which did not work in its favor can be pinpointed by an accurate analysis of the conceptual framework.

Fig. 2: Concise example of a conceptual framework

Important takeaways

While conceptual frameworks are a great way of designing the research protocol, they might consist of some unforeseen loopholes. A review of the literature can sometimes provide a false impression of the collection of work done worldwide while in actuality, there might be research that is being undertaken on the same topic but is still under publication or review. Strong conceptual frameworks, therefore, are designed when all these aspects are taken into consideration and the researchers indulge in discussions with others working on similar grounds of research.

Conceptual frameworks may also sometimes lead to collecting and reviewing data that is not so relevant to the current research topic. The researchers must always be on the lookout for studies that are highly relevant to their topic of work and will be of impact if taken into consideration. 

Another common practice associated with conceptual frameworks is their classification as merely descriptive qualitative tools and not actually a concrete build-up of ideas and critically analyzed literature and data which it is, in reality. Ideal conceptual frameworks always bring out their own set of new ideas after analysis of literature rather than simply depending on facts being already reported by other research groups.

So, the next time you set out to construct your conceptual framework or improvise on your previous one, be wary that concepts for your research are ideas that need to be worked upon. They are not simply a collection of literature from the previous research.

Final thoughts

Research is witnessing a boom in the methodical approaches being applied to it nowadays. In contrast to conventional research, researchers today are always looking for better techniques and methods to improve the quality of their research. 

We strongly believe in the ideals of research that are not merely academic, but all-inclusive. We strongly encourage all our readers and researchers to do work that impacts society. Designing strong conceptual frameworks is an integral part of the process. It gives headway for systematic, empirical, and fruitful research.

Vridhi Sachdeva, MPharm

See our "Privacy Policy"

Get an overall assessment of the main focus of your study from AJE

Our Presubmission Review service will provide recommendations on the structure, organization, and the overall presentation of your research manuscript.

Help | Advanced Search

Computer Science > Computer Vision and Pattern Recognition

Title: vasa-1: lifelike audio-driven talking faces generated in real time.

Abstract: We introduce VASA, a framework for generating lifelike talking faces with appealing visual affective skills (VAS) given a single static image and a speech audio clip. Our premiere model, VASA-1, is capable of not only producing lip movements that are exquisitely synchronized with the audio, but also capturing a large spectrum of facial nuances and natural head motions that contribute to the perception of authenticity and liveliness. The core innovations include a holistic facial dynamics and head movement generation model that works in a face latent space, and the development of such an expressive and disentangled face latent space using videos. Through extensive experiments including evaluation on a set of new metrics, we show that our method significantly outperforms previous methods along various dimensions comprehensively. Our method not only delivers high video quality with realistic facial and head dynamics but also supports the online generation of 512x512 videos at up to 40 FPS with negligible starting latency. It paves the way for real-time engagements with lifelike avatars that emulate human conversational behaviors.

Submission history

Access paper:.

• HTML (experimental)
• Other Formats

References & Citations

• Google Scholar
• Semantic Scholar

BibTeX formatted citation

Bibliographic and Citation Tools

Code, data and media associated with this article, recommenders and search tools.

• Institution

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .