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What is a framework? Understanding their purpose, value, development and use

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• Stefan Partelow   ORCID: orcid.org/0000-0002-7751-4005 1 , 2  

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Many frameworks exist across the sciences and science-policy interface, but it is not always clear how they are developed or can be applied. It is also often vague how new or existing frameworks are positioned in a theory of science to advance a specific theory or paradigm. This article examines these questions and positions the role of frameworks as integral but often vague scientific tools, highlighting benefits and critiques. While frameworks can be useful for synthesizing and communicating core concepts in a field, they often lack transparency in how they were developed and how they can be applied. Positioning frameworks within a theory of science can aid in knowing the purpose and value of framework use. This article provides a meta-framework for visualizing and engaging the four mediating processes for framework development and application: (1) empirical generalization, (2) theoretical fitting, (3) application, and (4) hypothesizing. Guiding points for scholars and policymakers using or developing frameworks in their research are provided in closing.

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Introduction

Reflections on Methodological Issues

Looking Back

Avoid common mistakes on your manuscript.

The development of ‘frameworks’ is at present probably the most common strategy in the field of natural resources management to achieve integration and interdisciplinarity. Mollinga , 2008

…it is not clear what the role of a scientific framework should be, and relatedly, what makes for a successful scientific framework. Ban and Cox, 2017

Frameworks are important research tools across nearly all fields of science. They are critically important for structuring empirical inquiry and theoretical development in the environmental social sciences, governance research and practice, the sustainability sciences and fields of social-ecological systems research in tangent with the associated disciplines of those fields (Binder et al. 2013 ; Pulver et al. 2018 ; Colding and Barthel 2019 ). Many well-established frameworks are regularly applied to collect new data or to structure entire research programs such as the Ecosystem Services (ES) framework (Potschin-Young et al. 2018 ), the Social-Ecological Systems Framework (SESF) (McGinnis and Ostrom 2014a ), Earth Systems Governance (ESG) (Biermann et al. 2010 ), the Driver-Impact-Pressure-State-Response (DIPSR) framework, and the Life Cycle Assessment (LCA) framework. Frameworks are also put forth by major scientific organizing bodies to steer scientific and policy agendas at regional and global levels such as the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) (Díaz et al. 2015 ) and the Global Sustainable Development Report’s transformational levers and fields (UN 2019 ).

Despite the countless frameworks, it is not always clear how a framework can be developed or applied (Ban and Cox 2017 ; Partelow 2018 ; Nagel and Partelow 2022 ). Development may occur through empirically backed synthesis or by scholars based on their own knowledge, values, or interests. These diverse development pathways do, however, result in common trends. The structure of most frameworks is the identification of a set of concepts and their general relationships — often in the form box-and-arrow diagrams — that are loosely defined or unspecified. This hallmark has both benefits and challenges. On one hand, this is arguably the purpose of frameworks, to structure the basic ideas of theory or conceptual thinking, and if they were more detailed they would be models. On the other hand, there is often a “black box” nature to frameworks. It is often unclear why some sets of concepts and relationships are chosen for integration into frameworks, and others not. As argued below, these choices are often the result of the positionality of the framework’s creators. Publications of frameworks, furthermore, often lack descriptions of their value and potential uses compared to other frameworks or analytical tools that exist in the field.

Now shifting focus to how frameworks are applied. Some frameworks provide measureable indicators as the key variables in the framework, but many only suggest general concepts. This creates the need to link concepts and their relationships to data through other more tangible indicators. Methods to measure such indicators will also be needed in new empirical studies. These methodological and study design steps necessary to associate data to framework concepts is often referred to as “operationalizing” a framework. However, without guidance on how to do this, scholars are often left with developing their own strategies, which can lead to heterogeneous and idiosyncratic methods and data. These challenges can be referred to as methodological gaps (Partelow 2018 ), where the details of how to move from concept to indicator to measurement to data transformation, are not always detailed in a way that welcomes replicability or learning. This is not necessarily a problem if the purpose of a framework is to only guide the analysis of individual cases or synthesis activities in isolation, for example to inform local management, but it hinders meta-analyses, cross-case learning and data interpretability for others.

In this article, a brief overview of framework definitions and current synthesis literature are reviewed in the “ What is a framework? ” section. This is coupled with the argument that frameworks often lack clarity in their development and application because their positioning within a theory of science is unclear. In the “ Mechanisms of framework development and use: a meta-framework ” section, a meta-framework is proposed to assist in clarifying the four major levers with which frameworks are developed and applied: (1) empirical generalization, (2) theoretical fitting, (3) hypothesizing, and (4) application. The meta-framework aims to position individual frameworks into a theory of science, which can enable scholars to take a conceptual “step back” in order to view how their engagement with a framework contributes to their broader scientific goal and field. Two case studies of different frameworks are provided to explore how the meta-framework can aid in comparing them. This is followed by a discussion of what makes a good framework, along with explicit guiding points for the use of frameworks in research and policy practice.

What is a framework?

The definition and purpose of a framework is likely to vary across disciplines and thematic fields (Cox et al. 2016 ). There is no universal definition of a framework, but it is useful to provide a brief overview of different definitions for orientation. The Cambridge Dictionary states that frameworks are “a supporting structure around which something can be built; a system of rules, ideas, or beliefs that is used to plan or decide something.” Schlager ( 2007 , 293) states that “frameworks provide a foundation for inquiry,” and Cumming ( 2014 , 5) adds that this “does not necessarily depend on deductive logic to connect different ideas.” Importantly, Binder et al., ( 2013 , 2) note that “a framework provides a set of assumptions, concepts, values and practices,” emphasizing the normative or inherently subjective logic to framework development. A core theme being plurality and connectivity. Similarly, McGinnis and Ostrom ( 2014a , 1) define frameworks as “the basic vocabulary of concepts and terms that may be used to construct the kinds of causal explanations expected of a theory. Frameworks organize diagnostic, descriptive, and prescriptive inquiry.” In a review comparing ten commonly used frameworks in social-ecological systems (SES) research, Binder et al., ( 2013 , 1) state that frameworks are useful for developing “a common language, to structure research on SES, and to provide guidance toward a more sustainable development of SES.” In a similar review, Pulver et al., ( 2018 , 1) suggest that frameworks “assist scholars and practitioners to analyze the complex, nonlinear interdependencies that characterize interactions between biophysical and social arenas and to navigate the new epistemological, ontological, analytical, and practical horizons of integrating knowledge for sustainability solutions.” It is important to recognize that the above claims often suggest the dualistic or bridging positions held by frameworks, in both theory building and for guiding empirical observations. However, there is relatively little discussion in the above literature on how frameworks act as bridging tools within a theory of science or how frameworks add value as positioning tools in a field.

Every framework has a position, meaning it is located within a specific context of a scientific field. As positioning tools, frameworks seem to “populate the scientist’s world with a set of conceptual objects and (non-causal) relationships among them,” shaping (and sometimes limiting) the way we think about problems and potential solutions (Cox et al. 2016 , 47). Thus, using a specific framework helps in part to position the work of a researcher in a field and its related concepts, theories and paradigms.

Four factors can be considered to evaluate the positioning of a framework: (a) who developed it, (b) the values being put forth by those researchers, (c) the research questions engaged with, and (d) the field in which it is embedded. For example, the Social-Ecological Systems Framework (SESF) (Ostrom 2009 ) was developed by (a) Elinor Ostrom who developed the framework studying common-pool resource and public goods governance from the 1960s until the 2000s. Ostrom’s overall goal was (b) to examine the hindering and enabling conditions for governance to guide the use and provision common goods towards sustainability outcomes. Her primary research questions (c) related to collective action theory, unpacking how and why people cooperate with each other or not. The field her work is embedded in (d) is an interdisciplinary mix between public policy, behavioral and institutional economics. Scholars who use Ostrom’s SESF today, carry this history with them and therefore position themselves, whether implicitly or explicitly, as part of this research landscape as systems thinkers and interdisciplinarians, even if they have other scholarly positions.

Frameworks are positioned within a theory of science. Understanding this positioning can guide scholars in comprehending how their engagement with frameworks contributes to the overall advancement of their field. To do this, taking a conceptual “step back” is necessary, to distinguish between different levels of theory in science. From the conceptually broadest to the most empirically specific, we can identify the following levels of theory: paradigms, frameworks, specific theories, models/archetypes and cases (Table 1 ). Knowledge production processes flow up and down these levels of theory. For example, as argued by Kuhn ( 1962 ), the purpose of a scientific field is to advance its paradigm. Thus, the study of empirical observations (e.g., case studies) — and the development of models or theories resulting from those data — are aimed at advancing the overarching paradigm. Such paradigms could be conservation, democracy, sustainable development or social-ecological systems.

There is a need to connect cases, models and specific theory up to the overall paradigms of a field to make aggregate knowledge gains. Here, the role of frameworks becomes more clear, as bridging tools that enable connections between levels of knowledge. From the top down, frameworks can specify paradigms with more tangible conceptual features and relationships, which can then guide empirical inquiry. For example, the Driver-Pressure-State-Impact-Response (DPSIR) framework (Smeets and Weterings 1999 ; Ness, Anderberg, and Olsson 2010 ) specifies how to evaluate policy options and their effects by focusing on the five embedded concepts in a relational order. Scholars can then generate more specific indicators and methods to measure the five specified features of the framework, and their relationships, to generate empirical insights that now have a direct link to the paradigm of sustainable policy development via the framework.

Furthermore, frameworks can also emerge from the bottom up, by distilling empirical data across cases and thus creating a knowledge bridge of more specified conceptual features and relationships that connect to a paradigm. In both top-down and bottom-up mechanism, frameworks can play a vital role in synthesizing and communicating ideas among scholars in a field — from empirical data to a paradigm. A challenge may be, however, that multiple frameworks have emerged attempting to specify the core conceptual features and relationships in a paradigm. A mature scientific field is likely to have many frameworks to guide research and debate. There is, however, a lack of research and tools available to compare frameworks and their added value.

Beyond their use as positioning tools, frameworks make day-to-day science easier. They can guide researchers in designing new empirical research by indicating which core concepts and relationships are of interest to be measured and compared. Scientific fields also need common fires to huddle around, meaning that we need reference points to initiate scholarly debates, coordinate disparate empirical efforts and to communicate findings and novel advancements through a common language (McGinnis and Ostrom 2014a ; Ban and Cox 2017 ). As such, frameworks are useful for synthesis research, focusing the attention of reviews and meta-analyses around core sets of concepts and relationships.

There is, however, a tension between frameworks that aim to capture complexity and those that aim to simplify core principles. Complexity oriented frameworks often advance systems thinking at the risk of including too many variables. They often have long lists of variables which makes empirical orientation and synthesis difficult. On the other hand, simplification frameworks face the challenge of leaving important things out, with the benefit of clarifying what may be important and giving clear direction.

From a more critical perspective, the “criteria for comparing frameworks are not well developed,” (Schlager, 2007 , 312), and the positionality of frameworks has not been rigorously explored outside of smaller studies. Nonetheless, numerous classifications or typologies of frameworks within specific fields have been suggested (Table 2 ), although not with reference to positionality (Spangenberg 2011 ; Binder et al. 2013 ; Cumming 2014 ; Schlager 2007 ; Ness et al. 2007 ; Potschin-Young et al. 2018 ; Cox et al. 2021 ; Louder et al. 2021 ; Chofreh and Goni 2017 ; Alaoui et al. 2022 ; Tapio and Willamo 2008 ). These studies point to the question of: what makes a good framework? Are there certain quality criteria that make some frameworks more useful than others? There has undoubtedly been a rise in the number of frameworks, but as expressed by Ban and Cox ( 2017 , 2), “it is not clear what the role of a scientific framework should be, and relatedly, what makes for a successful scientific framework. Although there are many frameworks […] there is little discussion on what their scientific role ought to be, other than providing a common scientific language.” The meta-framework presented below serves as a tool for answering these questions and provides guidance for developing and implementing frameworks in a range of settings.

Mechanisms of framework development and use: a meta-framework

This section presents a meta-framework detailing the mechanisms of framework development and use (Fig. 1 ). The meta-framework illustrates the role of frameworks as bridging tools for knowledge synthesis and communication. Therefore, the purpose of the meta-framework is to demonstrate how the mechanisms of framework development and use act as levers of knowledge flow across levels within a theory of science, doing so by enabling the communication and synthesis of knowledge. Introducing the meta-framework has two parts, outlined below.

A meta-framework outlining the central role frameworks play in scientific advancement through their development and use. In the center, frameworks provide two core bridging values: knowledge synthesis and knowledge communication. Three modes of logical reasoning contribute to framework development: induction, deduction and abduction. Frameworks are used and developed through four mediating processes: (1) empirical generalization, (2) theoretical fitting, (3) application, and (4) hypothesizing

First, the meta-framework visualizes the levels along the scale of scientific theory including paradigms, frameworks, specific theory and empirical observations, introduced above. Along this scale, three mechanisms of logical reasoning are typical: induction, deduction, and abduction. Induction is a mode of logical reasoning based on sets of empirical observations, which, when patterns within those observations emerge, can inform more generalized theory formation. Induction, in its pure form, is reasoning without prior assumptions about what we think is happening. In contrast, deduction is a mode of logical reasoning based on testing a claim or hypothesis, often based on a body of theory, against an observation to infer whether or not a claim is true. In contrast to induction, which always leads to probable or fuzzy conclusions, deductive logic provides true or false conclusions. A third mode of logical reasoning is abduction. Abduction starts with a single or limited set of observations, and assumes the most likely cause as a conclusion. Abduction can only provide probable conclusions. Knowledge claims from all three modes of logical reasoning are part of the nexus of potential framework creation or modification.

Second, the meta-framework has four iterative mediating processes that directly enable the development and/or application of frameworks (Fig. 1 ). Two of the four mediating processes relate to framework development: (1) empirical generalization and (2) theoretical fitting. The other two relate to framework application: (3) hypothesizing, and (4) application (Fig. 1 , Table 3 ). The details of the specific mediating pathways are outlined in Table 3 , including the processes involved in each. There are numerous potential benefits and challenges associated with each (Table 3 ).

The value of a meta-framework

The presented meta-framework (Fig. 1 ) allows us to assess the values different frameworks can provide. If a framework provides a novel synthesis of key ideas or new developments in a field, and communicates those insights well in its composition, it likely adds notable value. If a framework coordinates scientific inquiry across the 1 or more of the four mediating processes, it likely acts as an important gatekeeper and boundary object for what may otherwise be disparate or tangential research. If it contributes substantial advances in 3 or 4 of the mediating processes, the value of the framework is likely higher.

The meta-framework can further help identify the positioning of framework such as the type of logical reasoning processes used to create it, as well as help clarify the role of a framework along the scale of knowledge production (i.e., from data to paradigm). It might be clear, for example, what paradigm or specific theory a framework contributes to. The meta-framework can add value by guiding the assessment of how frameworks fit into the bigger picture of knowledge contribution in their field. Furthermore, many scholars and practitioners are interested in developing new frameworks. The meta-framework outlines the mechanisms that can be considered in creating the framework as well as help developers of new frameworks communicate how their frameworks add value. For example, to link empirical data collection to theoretical work in their field.

The meta-framework can help compare frameworks, to assess strengths and weaknesses in terms of their positioning and knowledge production mechanisms. It can also help elucidate the need for, or value of, new frameworks. This challenge is noted by Cumming ( 2014 , 18) in the field of social-ecological systems, reflecting that “the tendency of researchers to develop “new” frameworks without fully explaining how they relate to other existing frameworks and what new elements they bring to the problem is another obvious reason for the lack of a single dominant, unifying framework.” To showcase such as comparison, two brief examples are provided. The first example features the Driver-Pressure-State-Impact-Response (DPSIR) framework developed by the European Environmental Agency (EEA) (Box 1 ) (Smeets and Weterings 1999 ; Ness, Anderberg, and Olsson 2010 ). The DPSIR framework exemplifies a framework developed from the top-down (theoretical fitting) approach, to better organize the policy goal and paradigm of environmental sustainability to the indicators collected by EU member states. The second example highlights the Social-Ecological Systems Framework (SESF) developed by Elinor Ostrom (Box 2 ) (Ostrom 2009 ; McGinnis and Ostrom 2014a ). The SESF exemplifies a framework developed from the bottom up (empirical generalization) to aggregate data into common variables to enable data standardization and comparison towards theory building to improve environmental governance. In the case examples (Box 1 ; Box 2 ), we can see the value of both frameworks from different perspectives. The examples briefly illustrate how the positionality of each framework dictates how others use them to produce knowledge towards a paradigm. In the case of the DPSIR framework, from the top-down towards a policy goal, and with the SESF, from the bottom-up towards a theoretical goal.

Drivers – Pressures – State – Impact - Response (DPSIR) framework

Social-Ecological Systems Framework (SESF)

Discussion and directions forward

Frameworks are commons objects to huddle around in academic and practitioner communities, providing identity and guiding our effort. They focus scholarly attention on important issues, stimulate cognitive energy and provide fodder for discussion. However, reflection on the role and purpose of the frameworks we use needs to be a more common practice in science. The proposed meta-framework aims to showcase the role of frameworks as boundary objects that connect ideas and concepts to data in constructive and actionable ways, enabling knowledge to be built up and aggregated within scientific fields through using common languages and concepts (Mollinga 2008 ; Klein 1996 ).

Boundary objects such as frameworks can be especially important for inter- and transdisciplinary collaboration, where there may be few prior shared points of conceptual understanding or terminology beyond a problem context. Mollinga ( 2008 , 33) reflects that “frameworks are typical examples of boundary objects, building connections between the worlds of science and that of policy, and between different knowledge domains,” and that “the development of frameworks is at present probably the most common strategy in the field of natural resources management to achieve integration and interdisciplinarity,” (Mollinga, 2008 , 31). They are, however, critically important for both disciplinary specific fundamental research, as well as for bridging science-society gaps through translating often esoteric academic concepts and findings into digestible and often visual objects. For example, the DPSIR framework (Box 1 ) attempts to better organize the analysis of environmental indicators for policy evaluation processes in the EU. Furthermore, Partelow et al., ( 2019 ) and Gurney et al., ( 2019 ) both use Ostrom’s SESF (Box 2 ) as a boundary object at the science-society interface to visually communicate systems thinking and social-ecological interactions to fishers and coastal stakeholders involved in local management decision-making.

An important feature of frameworks is that the very contestation over their nature is perhaps their main value. A framework can only be an effective boundary object if it catalyzes deliberation and scholarly debate — thus contestation over what it is and its value is seeded into the toolbox and identity of a scholarly field. Although most frameworks are likely to have shortcomings, flaws or controversial features, the fact that they motivate engagement around common problems and stimulate scholarly engagement is a value of its own. In doing so, frameworks often become symbols of individual and community identity in contested spaces. This is evidenced in how frameworks are often used to stamp our research as valid, relevant and important to the field, even if done passively. Citing a framework both communicates the general purpose of what a scholar is attempting to achieve to others, and orients science towards a common synthetic object for future knowledge synthesis and debate. These positioning actions are essential for science and practitioner communities to understand a research or policy project, its aims and assumptions. Historically, disciplines have provided this value – signaling the problems, methods and theories one is likely to engage with. Frameworks can act as tools for bridging disciplines, helping to catalyze interdisciplinary engagement (Mollinga 2008 ; Klein 1996 ). As many scientific communities shift focus towards solving real-world problems (e.g., climate change, gender equality), tools that can help scientists’ cooperate and communicate, such as a framework, will continue to play a vital role in achieving knowledge co-production goals.

Guiding points for framework engagement

An aim of this article is not only to reflect on the purpose, value and positioning of frameworks, but to provide some take-away advice for engaging with frameworks in current or future work. Over the course of this article, the question of “What makes a good framework?” has been explored. The meta-framework outlines mechanisms of useful frameworks and can help understand the positioning of frameworks. Nonetheless, more detailed guiding points can be specified for both the use and development of frameworks going forward. A series of guiding points are outlined in Table 4 , generated from the literature cited throughout this article, feedback from colleagues and personal experiences applying and developing numerous frameworks. The guiding points focus on the two types of mediating processes, framework development and use (Table 4 ).

In conclusion, we need to know our academic tools in order make the best use of them in our own research, practice and knowledge communities. Frameworks have gained substantial popularity for the communication and synthesis of academic ideas, and as tools we all have the ability to create and perhaps the responsibility to steward. However, frameworks have struggled to find roots in a theory of science which grounds their contributions in relation to other scientific tools such as models, specific theories and empirical data. There is also a lack of discussion about what makes a good framework and how to apply frameworks in a way to makes those applications of integrative value to an overall community of scholars positioned around it. The meta-framework provided in this article offers insights into how to understand the purpose and positionality of frameworks, as well as the mechanisms for understanding the creation and application of frameworks. The meta-framework further allows for the comparison of frameworks to assess their value.

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Acknowledgements

I would like to thank Michael Cox and Achim Schlüter for their helpful feedback on previous versions of the manuscript and the ideas within it. I am grateful to the Leibniz Centre for Tropical Marine Research (ZMT) in Bremen, and the Center for Life Ethics at the University of Bonn for support.

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Partelow, S. What is a framework? Understanding their purpose, value, development and use. J Environ Stud Sci 13 , 510–519 (2023). https://doi.org/10.1007/s13412-023-00833-w

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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

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How to Use a Conceptual Framework for Better Research

A conceptual framework in research is not just a tool but a vital roadmap that guides the entire research process. It integrates various theories, assumptions, and beliefs to provide a structured approach to research. By defining a conceptual framework, researchers can focus their inquiries and clarify their hypotheses, leading to more effective and meaningful research outcomes.

What is a Conceptual Framework?

A conceptual framework is essentially an analytical tool that combines concepts and sets them within an appropriate theoretical structure. It serves as a lens through which researchers view the complexities of the real world. The importance of a conceptual framework lies in its ability to serve as a guide, helping researchers to not only visualize but also systematically approach their study.

Key Components and to be Analyzed During Research

• Theories: These are the underlying principles that guide the hypotheses and assumptions of the research.
• Assumptions: These are the accepted truths that are not tested within the scope of the research but are essential for framing the study.
• Beliefs: These often reflect the subjective viewpoints that may influence the interpretation of data.
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Together, these components help to define the conceptual framework that directs the research towards its ultimate goal. This structured approach not only improves clarity but also enhances the validity and reliability of the research outcomes. By using a conceptual framework, researchers can avoid common pitfalls and focus on essential variables and relationships.

For practical examples and to see how different frameworks can be applied in various research scenarios, you can Explore Conceptual Framework Examples .

Different Types of Conceptual Frameworks Used in Research

Understanding the various types of conceptual frameworks is crucial for researchers aiming to align their studies with the most effective structure. Conceptual frameworks in research vary primarily between theoretical and operational frameworks, each serving distinct purposes and suiting different research methodologies.

Theoretical vs Operational Frameworks

Theoretical frameworks are built upon existing theories and literature, providing a broad and abstract understanding of the research topic. They help in forming the basis of the study by linking the research to already established scholarly works. On the other hand, operational frameworks are more practical, focusing on how the study’s theories will be tested through specific procedures and variables.

• Theoretical frameworks are ideal for exploratory studies and can help in understanding complex phenomena.
• Operational frameworks suit studies requiring precise measurement and data analysis.

Choosing the Right Framework

Selecting the appropriate conceptual framework is pivotal for the success of a research project. It involves matching the research questions with the framework that best addresses the methodological needs of the study. For instance, a theoretical framework might be chosen for studies that aim to generate new theories, while an operational framework would be better suited for testing specific hypotheses.

Benefits of choosing the right framework include enhanced clarity, better alignment with research goals, and improved validity of research outcomes. Tools like Table Chart Maker can be instrumental in visually comparing the strengths and weaknesses of different frameworks, aiding in this crucial decision-making process.

Real-World Examples of Conceptual Frameworks in Research

Understanding the practical application of conceptual frameworks in research can significantly enhance the clarity and effectiveness of your studies. Here, we explore several real-world case studies that demonstrate the pivotal role of conceptual frameworks in achieving robust research conclusions.

• Healthcare Research: In a study examining the impact of lifestyle choices on chronic diseases, researchers used a conceptual framework to link dietary habits, exercise, and genetic predispositions. This framework helped in identifying key variables and their interrelations, leading to more targeted interventions.
• Educational Development: Educational theorists often employ conceptual frameworks to explore the dynamics between teaching methods and student learning outcomes. One notable study mapped out the influences of digital tools on learning engagement, providing insights that shaped educational policies.
• Environmental Policy: Conceptual frameworks have been crucial in environmental research, particularly in studies on climate change adaptation. By framing the relationships between human activity, ecological changes, and policy responses, researchers have been able to propose more effective sustainability strategies.

Adapting conceptual frameworks based on evolving research data is also critical. As new information becomes available, it’s essential to revisit and adjust the framework to maintain its relevance and accuracy, ensuring that the research remains aligned with real-world conditions.

For those looking to visualize and better comprehend their research frameworks, Graphic Organizers for Conceptual Frameworks can be an invaluable tool. These organizers help in structuring and presenting research findings clearly, enhancing both the process and the presentation of your research.

Step-by-Step Guide to Creating Your Own Conceptual Framework

Creating a conceptual framework is a critical step in structuring your research to ensure clarity and focus. This guide will walk you through the process of building a robust framework, from identifying key concepts to refining your approach as your research evolves.

Building Blocks of a Conceptual Framework

• Identify and Define Main Concepts and Variables: Start by clearly identifying the main concepts, variables, and their relationships that will form the basis of your research. This could include defining key terms and establishing the scope of your study.
• Develop a Hypothesis or Primary Research Question: Formulate a central hypothesis or question that guides the direction of your research. This will serve as the foundation upon which your conceptual framework is built.
• Link Theories and Concepts Logically: Connect your identified concepts and variables with existing theories to create a coherent structure. This logical linking helps in forming a strong theoretical base for your research.

Visualizing and Refining Your Framework

Using visual tools can significantly enhance the clarity and effectiveness of your conceptual framework. Decision Tree Templates for Conceptual Frameworks can be particularly useful in mapping out the relationships between variables and hypotheses.

Map Your Framework: Utilize tools like Creately’s visual canvas to diagram your framework. This visual representation helps in identifying gaps or overlaps in your framework and provides a clear overview of your research structure.

Analyze and Refine: As your research progresses, continuously evaluate and refine your framework. Adjustments may be necessary as new data comes to light or as initial assumptions are challenged.

By following these steps, you can ensure that your conceptual framework is not only well-defined but also adaptable to the changing dynamics of your research.

Practical Tips for Utilizing Conceptual Frameworks in Research

Effectively utilizing a conceptual framework in research not only streamlines the process but also enhances the clarity and coherence of your findings. Here are some practical tips to maximize the use of conceptual frameworks in your research endeavors.

• Setting Clear Research Goals: Begin by defining precise objectives that are aligned with your research questions. This clarity will guide your entire research process, ensuring that every step you take is purposeful and directly contributes to your overall study aims. \
• Maintaining Focus and Coherence: Throughout the research, consistently refer back to your conceptual framework to maintain focus. This will help in keeping your research aligned with the initial goals and prevent deviations that could dilute the effectiveness of your findings.
• Data Analysis and Interpretation: Use your conceptual framework as a lens through which to view and interpret data. This approach ensures that the data analysis is not only systematic but also meaningful in the context of your research objectives. For more insights, explore Research Data Analysis Methods .
• Presenting Research Findings: When it comes time to present your findings, structure your presentation around the conceptual framework . This will help your audience understand the logical flow of your research and how each part contributes to the whole.
• Avoiding Common Pitfalls: Be vigilant about common errors such as overcomplicating the framework or misaligning the research methods with the framework’s structure. Keeping it simple and aligned ensures that the framework effectively supports your research.

By adhering to these tips and utilizing tools like 7 Essential Visual Tools for Social Work Assessment , researchers can ensure that their conceptual frameworks are not only robust but also practically applicable in their studies.

How Creately Enhances the Creation and Use of Conceptual Frameworks

Creating a robust conceptual framework is pivotal for effective research, and Creately’s suite of visual tools offers unparalleled support in this endeavor. By leveraging Creately’s features, researchers can visualize, organize, and analyze their research frameworks more efficiently.

• Visual Mapping of Research Plans: Creately’s infinite visual canvas allows researchers to map out their entire research plan visually. This helps in understanding the complex relationships between different research variables and theories, enhancing the clarity and effectiveness of the research process.
• Brainstorming with Mind Maps: Using Mind Mapping Software , researchers can generate and organize ideas dynamically. Creately’s intelligent formatting helps in brainstorming sessions, making it easier to explore multiple topics or delve deeply into specific concepts.
• Centralized Data Management: Creately enables the importation of data from multiple sources, which can be integrated into the visual research framework. This centralization aids in maintaining a cohesive and comprehensive overview of all research elements, ensuring that no critical information is overlooked.
• Communication and Collaboration: The platform supports real-time collaboration, allowing teams to work together seamlessly, regardless of their physical location. This feature is crucial for research teams spread across different geographies, facilitating effective communication and iterative feedback throughout the research process.

Moreover, the ability t Explore Conceptual Framework Examples directly within Creately inspires researchers by providing practical templates and examples that can be customized to suit specific research needs. This not only saves time but also enhances the quality of the conceptual framework developed.

In conclusion, Creately’s tools for creating and managing conceptual frameworks are indispensable for researchers aiming to achieve clear, structured, and impactful research outcomes.

Join over thousands of organizations that use Creately to brainstorm, plan, analyze, and execute their projects successfully.

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Chiraag George is a communication specialist here at Creately. He is a marketing junkie that is fascinated by how brands occupy consumer mind space. A lover of all things tech, he writes a lot about the intersection of technology, branding and culture at large.

Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

The purpose of a field report in the social sciences is to describe the deliberate observation of people, places, and/or events and to analyze what has been observed in order to identify and categorize common themes in relation to the research problem underpinning the study. The content represents the researcher's interpretation of meaning found in data that has been gathered during one or more observational events.

Flick, Uwe. The SAGE Handbook of Qualitative Data Collection . London: SAGE Publications, 2018; Lofland, John, David Snow, Leon Anderson, and Lyn H. Lofland. Analyzing Social Settings: A Guide to Qualitative Observation and Analysis. Long Grove, IL: Waveland Press, 2022; Baker, Lynda. "Observation: A Complex Research Method." Library Trends 55 (Summer 2006): 171-189.; Kellehear, Allan. The Unobtrusive Researcher: A Guide to Methods . New York: Routledge, 2020.

How to Approach Writing a Field Report

How to Begin

Field reports are most often assigned in disciplines of the applied social sciences [e.g., social work, anthropology, gerontology, criminal justice, education, law, the health care services] where it is important to build a bridge of relevancy between the theoretical concepts learned in the classroom and the practice of actually doing the work you are being taught to do. Field reports are also common in certain science disciplines [e.g., geology] but these reports are organized differently and serve a different purpose than what is described below.

Professors will assign a field report with the intention of improving your understanding of key theoretical concepts by applying methods of careful and structured observation of, and reflection about, people, places, or phenomena existing in their natural settings. Field reports facilitate the development of data collection techniques and observation skills and they help you to understand how theory applies to real world situations. Field reports are also an opportunity to obtain evidence through methods of observing professional practice that contribute to or challenge existing theories.

We are all observers of people, their interactions, places, and events; however, your responsibility when writing a field report is to conduct research based on data generated by the act of designing a specific study, deliberate observation, synthesis of key findings, and interpretation of their meaning.

When writing a field report you need to:

• Systematically observe and accurately record the varying aspects of a situation . Always approach your field study with a detailed protocol about what you will observe, where you should conduct your observations, and the method by which you will collect and record your data.
• Continuously analyze your observations . Always look for the meaning underlying the actions you observe. Ask yourself: What's going on here? What does this observed activity mean? What else does this relate to? Note that this is an on-going process of reflection and analysis taking place for the duration of your field research.
• Keep the report’s aims in mind while you are observing . Recording what you observe should not be done randomly or haphazardly; you must be focused and pay attention to details. Enter the observation site [i.e., "field"] with a clear plan about what you are intending to observe and record in relation to the research problem while, at the same time, being prepared to adapt to changing circumstances as they may arise.
• Consciously observe, record, and analyze what you hear and see in the context of a theoretical framework . This is what separates data gatherings from reporting. The theoretical framework guiding your field research should determine what, when, and how you observe and act as the foundation from which you interpret your findings in relation to the underlying assumptions embedded in the theoretical framework .

Techniques to Record Your Observations Although there is no limit to the type of data gathering techniques you can use, these are the most frequently used methods:

Note Taking This is the most common and easiest method of recording your observations. Tips for taking notes include: organizing some shorthand symbols beforehand so that recording basic or repeated actions does not impede your ability to observe, using many small paragraphs, which reflect changes in activities, who is talking, etc., and, leaving space on the page so you can write down additional thoughts and ideas about what’s being observed, any theoretical insights, and notes to yourself that are set aside for further investigation. See drop-down tab for additional information about note-taking.

Photography With the advent of smart phones, an almost unlimited number of high quality photographs can be taken of the objects, events, and people observed during a field study. Photographs can help capture an important moment in time as well as document details about the space where your observation takes place. Taking a photograph can save you time in documenting the details of a space that would otherwise require extensive note taking. However, be aware that flash photography could undermine your ability to observe unobtrusively so assess the lighting in your observation space; if it's too dark, you may need to rely on taking notes. Also, you should reject the idea that photographs represent some sort of "window into the world" because this assumption creates the risk of over-interpreting what they show. As with any product of data gathering, you are the sole instrument of interpretation and meaning-making, not the object itself. Video and Audio Recordings Video or audio recording your observations has the positive effect of giving you an unfiltered record of the observation event. It also facilitates repeated analysis of your observations. This can be particularly helpful as you gather additional information or insights during your research. However, these techniques have the negative effect of increasing how intrusive you are as an observer and will often not be practical or even allowed under certain circumstances [e.g., interaction between a doctor and a patient] and in certain organizational settings [e.g., a courtroom]. Illustrations/Drawings This does not refer to an artistic endeavor but, rather, refers to the possible need, for example, to draw a map of the observation setting or illustrating objects in relation to people's behavior. This can also take the form of rough tables, charts, or graphs documenting the frequency and type of activities observed. These can be subsequently placed in a more readable format when you write your field report. To save time, draft a table [i.e., columns and rows] on a separate piece of paper before an observation if you know you will be entering data in that way.

NOTE:   You may consider using a laptop or other electronic device to record your notes as you observe, but keep in mind the possibility that the clicking of keys while you type or noises from your device can be obtrusive, whereas writing your notes on paper is relatively quiet and unobtrusive. Always assess your presence in the setting where you're gathering the data so as to minimize your impact on the subject or phenomenon being studied.

ANOTHER NOTE:   Techniques of deliberate observation and data gathering are not innate skills; they are skills that must be learned and practiced in order to achieve proficiency. Before your first observation, practice the technique you plan to use in a setting similar to your study site [e.g., take notes about how people choose to enter checkout lines at a grocery store if your research involves examining the choice patterns of unrelated people forced to queue in busy social settings]. When the act of data gathering counts, you'll be glad you practiced beforehand.

YET ANOTHER NOTE:   An issue rarely discussed in the literature about conducting field research is whether you should move around the study site while observing or remaining situated in one place. Moving around can be intrusive, but it facilitates observing people's behavior from multiple vectors. However, if you remain in one place throughout the observation [or during each observation], you will eventually blend into the background and diminish the chance of unintentionally influencing people's behavior. If the site has a complex set of interactions or interdependent activities [e.g., a play ground], consider moving around; if the study site is relatively fixed [e.g., a classroom], then consider staying in one place while observing.

Examples of Things to Document While Observing

• Physical setting . The characteristics of an occupied space and the human use of the place where the observation(s) are being conducted.
• Objects and material culture . This refers to the presence, placement, and arrangement of objects that impact the behavior or actions of those being observed. If applicable, describe the cultural artifacts representing the beliefs [i.e., the values, ideas, attitudes, and assumptions] of the individuals you are observing [e.g., the choice of particular types of clothing in the observation of family gatherings during culturally specific holidays].
• Use of language . Don't just observe but  listen to what is being said, how is it being said, and the tone of conversations among participants.
• Behavior cycles . This refers to documenting when and who performs what behavior or task and how often they occur. Record at which stage this behavior is occurring within the setting.
• The order in which events unfold . Note sequential patterns of behavior or the moment when actions or events take place and their significance. Also, be prepared to note moments that diverge from these sequential patterns of behavior or actions.
• Physical characteristics of subjects. If relevant, document personal characteristics of individuals being observed. Note that, unless this data can be verified in interviews or from documentary evidence, you should only focus on characteristics that can be clearly observed [e.g., clothing, physical appearance, body language].
• Expressive body movements . This would include things like body posture or facial expressions. Note that it may be relevant to also assess whether expressive body movements support or contradict the language used in conversation [e.g., detecting sarcasm].

Brief notes about all of these examples contextualize your observations; however, your observation notes will be guided primarily by your theoretical framework, keeping in mind that your observations will feed into and potentially modify or alter these frameworks.

Sampling Techniques

Sampling refers to the process used to select a portion of the population for study . Qualitative research, of which observation is one method of data gathering, is generally based on non-probability and purposive sampling rather than probability or random approaches characteristic of quantitatively-driven studies. Sampling in observational research is flexible and often continues until no new themes emerge from the data, a point referred to as data saturation.

All sampling decisions are made for the explicit purpose of obtaining the richest possible source of information to answer the research questions. Decisions about sampling assumes you know what you want to observe, what behaviors are important to record, and what research problem you are addressing before you begin the study. These questions determine what sampling technique you should use, so be sure you have adequately answered them before selecting a sampling method.

Ways to sample when conducting an observation include:

• Ad Libitum Sampling -- this approach is not that different from what people do at the zoo; they observe whatever seems interesting at the moment. There is no organized system of recording the observations; you just note whatever seems relevant at the time. The advantage of this method is that you are often able to observe relatively rare or unusual behaviors that might be missed by more deliberately designed sampling methods. This method is also useful for obtaining preliminary observations that can be used to develop your final field study. Problems using this method include the possibility of inherent bias toward conspicuous behaviors or individuals, thereby missing mundane or repeated patterns of behavior, and that you may miss brief interactions in social settings.
• Behavior Sampling -- this involves watching the entire group of subjects and recording each occurrence of a specific behavior of interest and with reference to which individuals were involved. The method is useful in recording rare behaviors missed by other sampling methods and is often used in conjunction with focal or scan methods [see below]. However, sampling can be biased towards particular conspicuous behaviors.
• Continuous Recording -- provides a faithful record of behavior including frequencies, durations, and latencies [the time that elapses between a stimulus and the response to it]. This is a very demanding method because you are trying to record everything within the setting and, thus, measuring reliability may be sacrificed. In addition, durations and latencies are only reliable if subjects remain present throughout the collection of data. However, this method facilitates analyzing sequences of behaviors and ensures obtaining a wealth of data about the observation site and the people within it. The use of audio or video recording is most useful with this type of sampling.
• Focal Sampling -- this involves observing one individual for a specified amount of time and recording all instances of that individual's behavior. Usually you have a set of predetermined categories or types of behaviors that you are interested in observing [e.g., when a teacher walks around the classroom] and you keep track of the duration of those behaviors. This approach doesn't tend to bias one behavior over another and provides significant detail about a individual's behavior. However, with this method, you likely have to conduct a lot of focal samples before you have a good idea about how group members interact. It can also be difficult within certain settings to keep one individual in sight for the entire period of the observation without being intrusive.
• Instantaneous Sampling -- this is where observation sessions are divided into short intervals divided by sample points. At each sample point the observer records if predetermined behaviors of interest are taking place. This method is not effective for recording discrete events of short duration and, frequently, observers will want to record novel behaviors that occur slightly before or after the point of sampling, creating a sampling error. Though not exact, this method does give you an idea of durations and is relatively easy to do. It is also good for recording behavior patterns occurring at a specific instant, such as, movement or body positions.
• One-Zero Sampling -- this is very similar to instantaneous sampling, only the observer records if the behaviors of interest have occurred at any time during an interval instead of at the instant of the sampling point. The method is useful for capturing data on behavior patterns that start and stop repeatedly and rapidly, but that last only for a brief period of time. The disadvantage of this approach is that you get a dimensionless score for an entire recording session, so you only get one one data point for each recording session.
• Scan Sampling -- this method involves taking a census of the entire observed group at predetermined time periods and recording what each individual is doing at that moment. This is useful for obtaining group behavioral data and allows for data that are evenly representative across individuals and periods of time. On the other hand, this method may be biased towards more conspicuous behaviors and you may miss a lot of what is going on between observations, especially rare or unusual behaviors. It is also difficult to record more than a few individuals in a group setting without missing what each individual is doing at each predetermined moment in time [e.g., children sitting at a table during lunch at school]. The use of audio or video recording is useful with this type of sampling.

Alderks, Peter. Data Collection. Psychology 330 Course Documents. Animal Behavior Lab. University of Washington; Emerson, Robert M. Contemporary Field Research: Perspectives and Formulations . 2nd ed. Prospect Heights, IL: Waveland Press, 2001; Emerson, Robert M. et al. “Participant Observation and Fieldnotes.” In Handbook of Ethnography . Paul Atkinson et al., eds. (Thousand Oaks, CA: Sage, 2001), 352-368; Emerson, Robert M. et al. Writing Ethnographic Fieldnotes . 2nd ed. Chicago, IL: University of Chicago Press, 2011; Ethnography, Observational Research, and Narrative Inquiry. Writing@CSU. Colorado State University; Hazel, Spencer. "The Paradox from Within: Research Participants Doing-Being-Observed." Qualitative Research 16 (August 2016): 446-457; Pace, Tonio. Writing Field Reports. Scribd Online Library; Presser, Jon and Dona Schwartz. “Photographs within the Sociological Research Process.” In Image-based Research: A Sourcebook for Qualitative Researchers . Jon Prosser, editor (London: Falmer Press, 1998), pp. 115-130; Pyrczak, Fred and Randall R. Bruce. Writing Empirical Research Reports: A Basic Guide for Students of the Social and Behavioral Sciences . 5th ed. Glendale, CA: Pyrczak Publishing, 2005; Report Writing. UniLearning. University of Wollongong, Australia; Wolfinger, Nicholas H. "On Writing Fieldnotes: Collection Strategies and Background Expectancies.” Qualitative Research 2 (April 2002): 85-95; Writing Reports. Anonymous. The Higher Education Academy.

Structure and Writing Style

How you choose to format your field report is determined by the research problem, the theoretical framework that is driving your analysis, the observations that you make, and/or specific guidelines established by your professor. Since field reports do not have a standard format, it is worthwhile to determine from your professor what the preferred structure and organization should be before you begin to write. Note that field reports should be written in the past tense. With this in mind, most field reports in the social sciences include the following elements:

I.  Introduction The introduction should describe the research problem, the specific objectives of your research, and the important theories or concepts underpinning your field study. The introduction should describe the nature of the organization or setting where you are conducting the observation, what type of observations you have conducted, what your focus was, when you observed, and the methods you used for collecting the data. Collectively, this descriptive information should support reasons why you chose the observation site and the people or events within it. You should also include a review of pertinent literature related to the research problem, particularly if similar methods were used in prior studies. Conclude your introduction with a statement about how the rest of the paper is organized.

II.  Description of Activities

Your readers only knowledge and understanding of what happened will come from the description section of your report because they were not witnesses to the situation, people, or events that you are writing about. Given this, it is crucial that you provide sufficient details to place the analysis that will follow into proper context; don't make the mistake of providing a description without context. The description section of a field report is similar to a well written piece of journalism. Therefore, a useful approach to systematically describing the varying aspects of an observed situation is to answer the "Five W’s of Investigative Reporting." As Dubbels notes [p. 19], these are:

• What -- describe what you observed. Note the temporal, physical, and social boundaries you imposed to limit the observations you made. What were your general impressions of the situation you were observing. For example, as a student teacher, what is your impression of the application of iPads as a learning device in a history class; as a cultural anthropologist, what is your impression of women's participation in a Native American religious ritual?
• Where -- provide background information about the setting of your observation and, if necessary, note important material objects that are present that help contextualize the observation [e.g., arrangement of computers in relation to student engagement with the teacher].
• When -- record factual data about the day and the beginning and ending time of each observation. Note that it may also be necessary to include background information or key events which impact upon the situation you were observing [e.g., observing the ability of teachers to re-engage students after coming back from an unannounced fire drill].
• Who -- note background and demographic information about the individuals being observed e.g., age, gender, ethnicity, and/or any other variables relevant to your study]. Record who is doing what and saying what, as well as, who is not doing or saying what. If relevant, be sure to record who was missing from the observation.
• Why -- why were you doing this? Describe the reasons for selecting particular situations to observe. Note why something happened. Also note why you may have included or excluded certain information.

III.  Interpretation and Analysis

Always place the analysis and interpretations of your field observations within the larger context of the theoretical assumptions and issues you described in the introduction. Part of your responsibility in analyzing the data is to determine which observations are worthy of comment and interpretation, and which observations are more general in nature. It is your theoretical framework that allows you to make these decisions. You need to demonstrate to the reader that you are conducting the field work through the eyes of an informed viewer and from the perspective of a casual observer.

Here are some questions to ask yourself when analyzing your observations:

• What is the meaning of what you have observed?
• Why do you think what you observed happened? What evidence do you have for your reasoning?
• What events or behaviors were typical or widespread? If appropriate, what was unusual or out of the ordinary? How were they distributed among categories of people?
• Do you see any connections or patterns in what you observed?
• Why did the people you observed proceed with an action in the way that they did? What are the implications of this?
• Did the stated or implicit objectives of what you were observing match what was achieved?
• What were the relative merits of the behaviors you observed?
• What were the strengths and weaknesses of the observations you recorded?
• Do you see connections between what you observed and the findings of similar studies identified from your review of the literature?
• How do your observations fit into the larger context of professional practice? In what ways have your observations possibly changed or affirmed your perceptions of professional practice?
• Have you learned anything from what you observed?

NOTE:   Only base your interpretations on what you have actually observed. Do not speculate or manipulate your observational data to fit into your study's theoretical framework.

IV.  Conclusion and Recommendations

The conclusion should briefly recap of the entire study, reiterating the importance or significance of your observations. Avoid including any new information. You should also state any recommendations you may have based on the results of your study. Be sure to describe any unanticipated problems you encountered and note the limitations of your study. The conclusion should not be more than two or three paragraphs.

V.  Appendix

This is where you would place information that is not essential to explaining your findings, but that supports your analysis [especially repetitive or lengthy information], that validates your conclusions, or that contextualizes a related point that helps the reader understand the overall report. Examples of information that could be included in an appendix are figures/tables/charts/graphs of results, statistics, pictures, maps, drawings, or, if applicable, transcripts of interviews. There is no limit to what can be included in the appendix or its format [e.g., a DVD recording of the observation site], provided that it is relevant to the study's purpose and reference is made to it in the report. If information is placed in more than one appendix ["appendices"], the order in which they are organized is dictated by the order they were first mentioned in the text of the report.

VI.  References

List all sources that you consulted and obtained information from while writing your field report. Note that field reports generally do not include further readings or an extended bibliography. However, consult with your professor concerning what your list of sources should be included and be sure to write them in the preferred citation style of your discipline or is preferred by your professor [i.e., APA, Chicago, MLA, etc.].

Alderks, Peter. Data Collection. Psychology 330 Course Documents. Animal Behavior Lab. University of Washington; Dubbels, Brock R. Exploring the Cognitive, Social, Cultural, and Psychological Aspects of Gaming and Simulations . Hershey, PA: IGI Global, 2018; Emerson, Robert M. Contemporary Field Research: Perspectives and Formulations . 2nd ed. Prospect Heights, IL: Waveland Press, 2001; Emerson, Robert M. et al. “Participant Observation and Fieldnotes.” In Handbook of Ethnography . Paul Atkinson et al., eds. (Thousand Oaks, CA: Sage, 2001), 352-368; Emerson, Robert M. et al. Writing Ethnographic Fieldnotes . 2nd ed. Chicago, IL: University of Chicago Press, 2011; Ethnography, Observational Research, and Narrative Inquiry. Writing@CSU. Colorado State University; Pace, Tonio. Writing Field Reports. Scribd Online Library; Pyrczak, Fred and Randall R. Bruce. Writing Empirical Research Reports: A Basic Guide for Students of the Social and Behavioral Sciences . 5th ed. Glendale, CA: Pyrczak Publishing, 2005; Report Writing. UniLearning. University of Wollongong, Australia; Wolfinger, Nicholas H. "On Writing Fieldnotes: Collection Strategies and Background Expectancies.” Qualitative Research 2 (April 2002): 85-95; Writing Reports. Anonymous. The Higher Education Academy.

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Home » Methodological Framework – Types, Examples and Guide

Methodological Framework – Types, Examples and Guide

Table of Contents

Methodological Framework

Definition:

Methodological framework is a set of procedures, methods, and tools that guide the research process in a systematic and structured manner. It provides a structure for conducting research, collecting and analyzing data, and drawing conclusions. The framework outlines the steps to be taken in a research project, including the research question, hypothesis, data collection methods, data analysis techniques, and the interpretation of the results.

Types of Methodological Framework

There are different types of methodological frameworks that researchers can use depending on the nature of their research question, the type of data they want to collect, and the research methodology they want to employ. Some common types of methodological frameworks include:

Quantitative Research Framework

This type of framework uses numerical data and statistical analysis to test hypotheses and draw conclusions. It involves the collection of structured data through surveys, experiments, or other quantitative methods.

Qualitative Research Framework

This framework is used to explore complex social phenomena and involves the collection of non-numerical data through methods such as interviews, observation, and document analysis. Qualitative research typically involves the use of open-ended questions and in-depth analysis of data.

Mixed Methods Research Framework

This framework combines quantitative and qualitative research methods to address research questions from multiple angles. It involves collecting both numerical and non-numerical data and using both statistical analysis and interpretive techniques to analyze the data.

Action Research Framework

This framework involves the collaboration between researchers and participants to identify and address practical problems in real-world settings. It involves a cyclical process of planning, action, reflection, and evaluation to improve a specific situation or practice.

Case Study Research Framework

This framework involves the in-depth investigation of a specific case or phenomenon, often using qualitative methods. It aims to understand the complexity of the case and draw generalizations from the findings.

How to Develop a Methodological Framework

Developing a methodological framework involves a series of steps that help to guide the research process in a systematic and structured manner. Here are the general steps involved in developing a methodological framework:

• Define the research problem: The first step is to clearly define the research problem or question. This involves identifying the purpose of the research, the research objectives, and the scope of the study.
• Select an appropriate research methodology: The research methodology selected should align with the research problem and research question. Common research methodologies include quantitative, qualitative, mixed-methods, case study, or action research.
• Develop the research design: Once the research methodology is selected, the research design should be developed. This involves identifying the data collection methods, sampling strategy, and data analysis techniques.
• Identify and justify the data collection methods: The data collection methods should be chosen based on the research methodology and research design. For example, if the research methodology is qualitative, data collection methods such as interviews, observation, or document analysis may be used.
• Identify and justify the data analysis techniques: The data analysis techniques should also be chosen based on the research methodology and research design. For quantitative research, this may include statistical analysis techniques, while for qualitative research, this may include interpretive techniques such as thematic analysis.
• Consider ethical considerations: Ethical considerations should be taken into account throughout the research process. This includes obtaining informed consent, ensuring confidentiality and privacy, and protecting the rights of participants.
• Identify potential limitations: It is important to identify potential limitations or biases that may affect the research findings. This includes discussing potential sources of error or bias in the research design, data collection methods, or data analysis techniques.
• Consider the significance and implications of the research: The significance and implications of the research findings should be considered, including their potential contributions to theory, practice, or policy.
• Refine the framework: The methodological framework should be refined based on feedback from peers, experts, or other stakeholders. This involves identifying any areas for improvement in the research design, data collection methods, or data analysis techniques.

Applications of Methodological Framework

Here are some examples of how a methodological framework can be applied in various fields:

• Social sciences: In social sciences, a methodological framework can be used to conduct research on various topics, such as psychology, sociology, and anthropology. For example, a researcher may use a qualitative research methodology to investigate the experiences and perceptions of individuals living in poverty.
• Natural sciences: In natural sciences, a methodological framework can be used to conduct research on various topics, such as biology, chemistry, and physics. For example, a researcher may use a quantitative research methodology to investigate the effects of different fertilizers on crop yield.
• Engineering : In engineering, a methodological framework can be used to design and test new technologies or systems. For example, a researcher may use a mixed-methods research methodology to investigate the usability and effectiveness of a new software application.
• Business : In business, a methodological framework can be used to conduct research on various topics, such as marketing, management, and finance. For example, a researcher may use a quantitative research methodology to investigate the relationship between customer satisfaction and customer loyalty.

When to use Methodological Framework

Here are some specific situations when a methodological framework can be particularly useful:

• When conducting original research: If you are conducting original research, a methodological framework can help ensure that your study is designed in a structured and systematic manner, which increases the reliability and validity of the findings.
• When conducting a literature review: A methodological framework can be used when conducting a literature review to ensure that the review is conducted in a structured and systematic manner. This helps to identify relevant studies and synthesize the findings from multiple studies.
• When replicating previous research: If you are replicating previous research, a methodological framework can help ensure that the replication is conducted in a rigorous and systematic manner. This helps to ensure that the findings are consistent with the original study.
• When developing a research proposal : A methodological framework can be used when developing a research proposal to ensure that the proposal is designed in a structured and systematic manner. This helps to convince reviewers that the study is well-designed and likely to produce valid and reliable findings.
• When teaching research methods: A methodological framework can be used when teaching research methods to provide students with a structured approach to designing and conducting research. This helps to ensure that students understand the research process and are able to conduct research in a rigorous and systematic manner.

Examples of Methodological Framework

Here are some real-time examples of how methodological frameworks are used in various fields:

• In healthcare research, a mixed-methods research framework can be used to evaluate the effectiveness of a new treatment approach. The quantitative component may involve measuring the changes in patient outcomes, while the qualitative component may involve interviewing patients and healthcare providers to understand their perspectives on the treatment.
• In engineering, a design science research framework can be used to develop and test a new software application. The researchers may identify a problem with existing software, develop a new solution, and test it in a real-world setting.
• In business, a case study research framework can be used to understand the impact of a new marketing strategy on a particular company. The researcher may analyze data from the company’s financial statements, conduct interviews with key stakeholders, and observe the implementation of the strategy in order to understand its effectiveness.
• In education, an action research framework can be used to improve teaching practices. A teacher may identify a problem in their classroom, develop a plan to address the problem, implement the plan, and reflect on the results in order to improve their teaching practices.
• In social science research, a grounded theory framework can be used to develop a theory from qualitative data. A researcher may collect data from interviews or observations and use that data to develop a theory about a particular phenomenon.

Purpose of Methodological Framework

The purpose of a methodological framework is to provide a structured and systematic approach to designing, conducting, and analyzing research. The framework serves as a guide for researchers to follow, ensuring that the research is conducted in a rigorous and transparent manner, and that the results are reliable, valid, and generalizable. Some key purposes of a methodological framework are:

• To provide a clear and concise description of the research process: The framework outlines the steps involved in conducting the research, including the research question, data collection methods, data analysis, and interpretation of results.
• To ensure that the research is conducted in a systematic and rigorous manner : The framework provides a structured approach to the research, helping to ensure that the research is conducted in a way that minimizes bias and maximizes the accuracy and reliability of the results.
• To improve the quality of the research: The framework helps to ensure that the research is of high quality and meets the standards of the field. This can help to increase the impact and relevance of the research.
• To increase transparency and replicability: The framework provides a clear and transparent description of the research process, making it easier for others to understand and replicate the research.
• To facilitate communication and collaboration: The framework provides a common language and structure for researchers to communicate their research findings and collaborate with others in the field.

Characteristics of Methodological Framework

Here are some common characteristics of a methodological framework:

• Systematic : A methodological framework is a systematic approach to research that provides a clear and structured guide for researchers to follow. It outlines the steps involved in conducting research, from developing a research question to analyzing and interpreting data.
• Transparent : A methodological framework promotes transparency in research by providing a clear and concise description of the research process. This helps to ensure that others can understand and replicate the research.
• Flexible : A methodological framework should be flexible enough to accommodate different research designs and methodologies. It should allow for modifications based on the specific research question, data collection methods, and analysis techniques.
• Contextual : A methodological framework should take into account the contextual factors that may impact the research. This includes the cultural, social, and historical context of the research, as well as the research setting and the characteristics of the participants.
• Rigorous : A methodological framework promotes rigor in research by ensuring that the research is conducted in a systematic and unbiased manner. It includes strategies for minimizing bias and ensuring the validity and reliability of the findings.
• Theory-driven: A methodological framework should be grounded in theoretical concepts and principles that guide the research. This helps to ensure that the research is relevant and meaningful, and that the findings can be applied to broader theoretical frameworks.

Advantages of Methodological Framework

There are several advantages to using a methodological framework in research:

• Structured approach: A methodological framework provides a clear and structured approach to conducting research, which helps to ensure that the research is conducted in a systematic and rigorous manner.
• Increased efficiency: A methodological framework can increase the efficiency of the research process by providing a clear roadmap for researchers to follow, reducing the time and resources required to conduct the research.
• Reproducibility: A methodological framework promotes reproducibility by providing a clear and transparent description of the research process, making it easier for others to replicate the research.
• Improved quality : A methodological framework can improve the quality of research by ensuring that the research is conducted in a rigorous and transparent manner, and that the results are reliable and valid.
• Standardization : A methodological framework promotes standardization in research, helping to ensure that the research meets the standards of the field and is comparable to other research studies.
• Better communication : A methodological framework provides a common language and structure for researchers to communicate their research findings, facilitating communication and collaboration among researchers.
• Theory development: A methodological framework can contribute to the development of theory by providing a structured approach to data collection and analysis that is grounded in theoretical concepts and principles.

Limitations of Methodological Framework

While there are many advantages to using a methodological framework in research, there are also some limitations to be aware of:

• Flexibility : While a methodological framework can provide a structured approach to research, it may also limit flexibility in the research process. Researchers may feel constrained by the framework and unable to deviate from the prescribed steps, which may limit their ability to adapt to unexpected findings or changes in the research context.
• Applicability : Methodological frameworks may not be equally applicable to all research questions and contexts. Some frameworks may be more suitable for certain types of research than others, and researchers may need to modify or adapt the framework to fit their specific research question and context.
• Complexity : Some methodological frameworks can be complex and difficult to understand, particularly for novice researchers. This may limit their usefulness in certain contexts or for certain types of research.
• Time and resource constraints : Using a methodological framework may require additional time and resources to fully implement, which may not be feasible for all researchers or research projects.
• Overemphasis on methodology: While a methodological framework can provide a structured approach to research methodology, it may overemphasize the importance of methodology over other aspects of research, such as theoretical frameworks or ethical considerations.

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Home » Introduction to Research Frameworks

Introduction to Research Frameworks

What are research frameworks, research frameworks provide us with, frameworks content, using research frameworks, contributing to the research frameworks.

In 1996 the English Heritage (now Historic England) publication ‘ Frameworks for our Past ‘ highlighted the need for research frameworks for the historic environment as a tool for establishing long-term objectives. The DCMS document ‘ Historic Environment: a Force for our Future’ (2001) stated that English Heritage had been ‘ commissioned to frame a co-ordinated approach to research across the historic environment sector’ .

Research Frameworks for many areas and specialisms have now been developed, with more in production, some of the earlier Frameworks are already being reviewed and updated.

The development of this Research Frameworks Network also addresses a number of the recommendations of the Pye Tait Review of Research Frameworks report (2014), including the need to ‘ Pursue the development of a dynamic and interactive web-based system for hosting a new generation of Research Frameworks’ .

As new Research Frameworks are developed, and older documents are reviewed, the plan is for them to be published here on the Network as a central location. We are also working on making older Research Frameworks (originally published as monographs) available through the Network.

How do we assess if sites or areas are important or significant? 

What research questions can we ask?

How do we go about co-ordinating this research?

Research Frameworks help us to identify what is important or significant archaeologically. They are normally organised by;

• Geographical areas such as Regional, County, or World Heritage Site (e.g. the South West Regional Research Framework)
• Periods (eg the Mesolithic)
• Themes (eg Roman pottery)

They provide research questions and objectives to help co-ordinate and focus our research effort.

They are created by bringing together people across the sector to create a shared framework, including:

• Local authorities
• Contractors
• Voluntary groups

Guided by a Steering Group, meetings of local stakeholders from across the historic environment spectrum come together to discuss and identify priorities. These take the form of a mixture of workshops and meetings, with sections of the Frameworks being written by specialists.

1. An up to date overview of current understanding – ie “what we currently know” .

Usually created by synthesising information from lots of different sources, eg Historic Environment Records (HERs), reports from planning-led investigations, academic and society journals. This provides an overview of a specific period, place or theme – eg The Bronze Age in the West Midlands.

2. A Research Agenda – identifying gaps in our knowledge and providing questions to fill these gaps .

An agreed set of research areas and questions that is used to help co-ordinate research – they help focus what the sector wants to know more about. Research agendas can help to coordinate academic and community research as well as provide a research focus for planning-led projects.

3. Strategies to carry out this research .

These strategies provide the framework within which the research can be carried out – promoting potential ways forward and partnerships.

This Regional Steering Group model means that Frameworks differ in content. They can cover archaeology, the built environment, landscapes, environmental information, and maritime heritage. However, generally they all contain similar components such as the following:-

• Defining the region – defining the area covered by the framework
• Time periods – summary of the time periods
• Research Agenda Topics – list of key research questions for each period and synthesis of research themes spanning multiple periods
• Research Strategy – strategies for advancing understanding of the Agenda Topics
• Overarching questions – region or specialism wide questions
• Environmental information (if relevant) – details of the palaeoenvironmental remains
• Resources/bibliography – these vary in detail and scope across the network, but often contain lists of publications used in the production of the framework, online resources and other relevant information.

A table of existing research Frameworks can be found  here , we are working to make more available on the network.

Research Frameworks play an important role in providing an overview of current understanding, coordinating research and informing decision making – particularly planning related. They have many different uses:

1. Local authority staff:

• As a reference to provide context for assessing the significance of heritage assets and proposed sites.
• To provide a research focus for planning-led investigations.

2. Contractors:

• As a reference resource to help write desk-based assessments and environmental impact assessments.
• Referred to when writing Written Schemes of Investigation (WSIs) in response to project briefs.

3. Academics:

• To scope out research projects and provide direction for postgraduate research.
• To assess the ‘impact’ of their research, eg in relation to Research Excellence Framework (REF) impact assessments.

4. Local Societies:

• To improve their knowledge and scope out research projects.
• To establish research priorities linking into the regional and national picture.

Frameworks rely on local research to keep up to date – everyone is encouraged to add to the value of the Frameworks by contributing to these online documents via the commenting facility.

To find out how to get involved please visit the How to use the Research Framework Site page to find out how to register and contribute to the historical and archaeological knowledge on these sites.

Research Framework

Ai generator.

A framework is an essential idea that humans have been using to build something effectively. This structure is widespread in various fields. In web development, for example, web developers use a framework called Model-View-Controller(MVC) to develop a web application.  MVC framework  is one of the most common software design patterns that web developers use to build user-interfaces. This type of structure allows them to create a more organized and understandable set of codes, making it an essential tool in developing an object-oriented program using programming languages, such as Javascript. Aside from web development, you can use frameworks in executing research methodologies, such as quantitative and qualitative research .

What is the Research Framework?

A research framework is a precise representation of the structure of a research project plan . Through this structure, you can determine the critical areas of the study. It also allows you to come up with relevant research questions and research objectives. To develop a research framework, you have to team up with the individuals within your organization or community. These people may include local authorities, contractors, voluntary groups, and other affecting individuals.

What are the Contributions that Research Framework Can Offer?

Developing a framework for your study is crucial to obtain the following benefits.

1. Timely Knowledge

Whether you are conducting marketing research or nursing research, you will need to gather the relevant information that surrounds your study for a better understanding of your research. You can collect this type of information by scanning related reports and writings from a public library, publications, and other sources.

2. Knowledge Gaps

After receiving the relevant information, you will be able to determine the holes of the data between the existing information and your current study. To close the gap, use this knowledge difference to come up with questions, which you will be focusing on for the rest of your project.

3. Research Strategy

If you can develop an action research framework, market research framework, or any other research framework, it will be easier for you to plan on how to carry out your project.

10+ Research Framework Examples

To give you a better understanding of research frameworks, we collated a list of samples that you can easily download in PDF formats.

1. Disaster Management Research Framework Example

Size: 227 KB

2. Research Framework Plan Example

Size: 270 KB

3. Research Framework Policy Example

4. Research Framework Methodology Example

Size: 308 KB

5. Feminist Research Framework Example

6. Basic Research Framework Example

7. research methodology and analysis framework example.

Size: 197 KB

8. Research Evaluation Framework Example

Size: 215 KB

9. Framework for Assessing Research Example

Size: 76 KB

10. Research Training Framework Example

Size: 159 KB

11. Research Strategic Framework Example

How to Apply Research Framework?

In applying the framework to research projects such as experimental investigations for the first time, following a guide can be essential to prevent your research from going astray. Read the following instructions to ensure that you are doing your research correctly.

1. Take Note of the Observation

When researching with a set framework, the first thing that you must do is to observe the research surroundings. There are many ways to do your observation. You can take note of the indicators that will reveal the hidden matters during your study. In the process, you may notice unusual activities that may need further examination. You can also uncover a connection between one or two matters, which the existing information didn’t cover.

2. Develop Research Questions

By following the previous step, you should be able to take note of remarkable observations. Through these remarks, you will formulate the research questions. In doing so, make sure that the items that you have come up with will interest you and your audience. Aside from that, it would help if you were the first individual who will answer the questions. However, you also have to ensure that these questions are answerable given the time and the resources that you have.

3. Determine the Study Objectives

Once you have gathered the research questions, you can easily create the objectives of your project. Develop answerable, predictive, and clear assertions.

4. Assign the Most Appropriate Design

By choosing a research method, you can determine how to gather the necessary data, which is crucial to come up with a conclusion of your research. Case study, open-label, parallel design, cross-sectional, and case-control are a few of the vast array of the research designs that you can choose from to apply in your project.

5. Describe the Data Collection Process

Explain all the procedures for gathering the necessary information for your study. This essay should cover the process involved in collecting and storing the data. Specify the individuals or organizations that can retrieve the data and the steps that you are going to take in ensuring the subject and the data confidentiality.

6. Analyze the Data

Once you have all the necessary information, analyze it using statistical methods to come up with the best solution, and conclusion for your research project. Lastly, present the results to the target audience.

Before conducting a research project, it is essential to learn the use of research frameworks. Just like software development frameworks, this type of tool will ensure that you are executing the research process of your project systematically. We created this article to ensure that you are not going to conduct your research project aimlessly.

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New Report: Framework for AI Transparency

Recommendations for Practitioners & Context for Policymakers

Sarah Newman

Kasia Chmielinski

Chris N. Kranzinger

With growing attention to AI regulation, rights-based principles, data equity, and risk mitigation, this is a pivotal moment to think about the social impact of AI, including its risks and harms, and the implementation of accountability and transparency. Transparency can be realized, in part, by providing information about how the data used to develop and evaluate the AI system was collected and processed, how AI models were built, trained, and fine-tuned, and how models and AI systems were evaluated and deployed. Towards this end, documentation has emerged as an essential component of AI transparency and a foundation for responsible AI development. The full report, co-authored by experts across academia, industry, and civil society, is available at the Shorenstein Center website .  

This report introduces the CLeAR Documentation Framework, designed to help practitioners and policymakers understand what principles should guide the process and content of AI documentation. The report introduces four principles for documentation and offers definitions, recommends approaches, explains tradeoffs, highlights open questions, and helps guide the implementation of documentation.

The CLeAR Principles state that documentation should be:

• Comparable : Able to be compared; having similar components to documentation of other datasets, models, or systems to permit or suggest comparison; enabling comparison by following a discrete, well-defined format in process, content, and presentation.
• Legible : Able to be read and understood; clear and accessible for the intended audience.
• Actionable : Able to be acted on; having practical value, useful for the intended audience.
• Robust : Able to be sustained over time; up to date.

Kasia Chmielinski* (Data Nutrition Project & Harvard University) Sarah Newman* (Data Nutrition Project & Harvard University) Chris N. Kranzinger* (Data Nutrition Project) Michael Hind (IBM Research) Jennifer Wortman Vaughan (Microsoft Research) Margaret Mitchell (Hugging Face) Julia Stoyanovich (New York University) Angelina McMillan-Major (independent researcher) Emily McReynolds (independent researcher) Kathleen Esfahany (Data Nutrition Project & Harvard University) Mary L. Gray (Microsoft Research, Indiana University & Harvard University) Maui Hudson (TKRI, University of Waikato) Audrey Chang (Data Nutrition Project & Harvard University)

*Joint first authors

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During Fiscal Year 2023 (FY 2023) – from October 1, 2022, through September 30, 2023 –the NIST Information Technology Laboratory (ITL) Cybersecurity and Privacy Program successfully responded to numerous challenges and opportunities in security and privacy. This Annual Report highlights the FY 2023 research activities for the ITL Cybersecurity and Privacy Program, including the ongoing participation and development of international standards; research and practical applications in several key priority areas (e.g., Post Quantum Cryptography, updating the NIST Cybersecurity Framework (CSF 2.0) and some new CSF profiles); accomplishments in the area of improving software and supply chain cybersecurity; IoT cybersecurity guidelines work; National Cybersecurity Center of Excellence (NCCoE) projects, and setting up a new comment site for NIST’s Risk Management Framework work; release of a Phish scale; progress in the Identity and Access Management program; Strategic and Emerging Research Initiatives (SERI) for autonomous vehicles.

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• About Adverse Childhood Experiences
• Risk and Protective Factors
• Program: Essentials for Childhood: Preventing Adverse Childhood Experiences through Data to Action
• Adverse childhood experiences can have long-term impacts on health, opportunity and well-being.
• Adverse childhood experiences are common and some groups experience them more than others.

What are adverse childhood experiences?

Adverse childhood experiences, or ACEs, are potentially traumatic events that occur in childhood (0-17 years). Examples include: 1

• Experiencing violence, abuse, or neglect.
• Witnessing violence in the home or community.
• Having a family member attempt or die by suicide.

Also included are aspects of the child’s environment that can undermine their sense of safety, stability, and bonding. Examples can include growing up in a household with: 1

• Substance use problems.
• Mental health problems.
• Instability due to parental separation.
• Instability due to household members being in jail or prison.

The examples above are not a complete list of adverse experiences. Many other traumatic experiences could impact health and well-being. This can include not having enough food to eat, experiencing homelessness or unstable housing, or experiencing discrimination. 2 3 4 5 6

Quick facts and stats

ACEs are common. About 64% of adults in the United States reported they had experienced at least one type of ACE before age 18. Nearly one in six (17.3%) adults reported they had experienced four or more types of ACEs. 7

Preventing ACEs could potentially reduce many health conditions. Estimates show up to 1.9 million heart disease cases and 21 million depression cases potentially could have been avoided by preventing ACEs. 1

Some people are at greater risk of experiencing one or more ACEs than others. While all children are at risk of ACEs, numerous studies show inequities in such experiences. These inequalities are linked to the historical, social, and economic environments in which some families live. 5 6 ACEs were highest among females, non-Hispanic American Indian or Alaska Native adults, and adults who are unemployed or unable to work. 7

ACEs are costly. ACEs-related health consequences cost an estimated economic burden of $748 billion annually in Bermuda, Canada, and the United States. 8

ACEs can have lasting effects on health and well-being in childhood and life opportunities well into adulthood. 9 Life opportunities include things like education and job potential. These experiences can increase the risks of injury, sexually transmitted infections, and involvement in sex trafficking. They can also increase risks for maternal and child health problems including teen pregnancy, pregnancy complications, and fetal death. Also included are a range of chronic diseases and leading causes of death, such as cancer, diabetes, heart disease, and suicide. 1 10 11 12 13 14 15 16 17

ACEs and associated social determinants of health, such as living in under-resourced or racially segregated neighborhoods, can cause toxic stress. Toxic stress, or extended or prolonged stress, from ACEs can negatively affect children’s brain development, immune systems, and stress-response systems. These changes can affect children’s attention, decision-making, and learning. 18

Children growing up with toxic stress may have difficulty forming healthy and stable relationships. They may also have unstable work histories as adults and struggle with finances, jobs, and depression throughout life. 18 These effects can also be passed on to their own children. 19 20 21 Some children may face further exposure to toxic stress from historical and ongoing traumas. These historical and ongoing traumas refer to experiences of racial discrimination or the impacts of poverty resulting from limited educational and economic opportunities. 1 6

Adverse childhood experiences can be prevented. Certain factors may increase or decrease the risk of experiencing adverse childhood experiences.

Preventing adverse childhood experiences requires understanding and addressing the factors that put people at risk for or protect them from violence.

Creating safe, stable, nurturing relationships and environments for all children can prevent ACEs and help all children reach their full potential. We all have a role to play.

• Merrick MT, Ford DC, Ports KA, et al. Vital Signs: Estimated Proportion of Adult Health Problems Attributable to Adverse Childhood Experiences and Implications for Prevention — 25 States, 2015–2017. MMWR Morb Mortal Wkly Rep 2019;68:999-1005. DOI: http://dx.doi.org/10.15585/mmwr.mm6844e1 .
• Cain KS, Meyer SC, Cummer E, Patel KK, Casacchia NJ, Montez K, Palakshappa D, Brown CL. Association of Food Insecurity with Mental Health Outcomes in Parents and Children. Science Direct. 2022; 22:7; 1105-1114. DOI: https://doi.org/10.1016/j.acap.2022.04.010 .
• Smith-Grant J, Kilmer G, Brener N, Robin L, Underwood M. Risk Behaviors and Experiences Among Youth Experiencing Homelessness—Youth Risk Behavior Survey, 23 U.S. States and 11 Local School Districts. Journal of Community Health. 2022; 47: 324-333.
• Experiencing discrimination: Early Childhood Adversity, Toxic Stress, and the Impacts of Racism on the Foundations of Health | Annual Review of Public Health https://doi.org/10.1146/annurev-publhealth-090419-101940 .
• Sedlak A, Mettenburg J, Basena M, et al. Fourth national incidence study of child abuse and neglect (NIS-4): Report to Congress. Executive Summary. Washington, DC: U.S. Department of Health an Human Services, Administration for Children and Families.; 2010.
• Font S, Maguire-Jack K. Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse Negl. 2016;51:390-399.
• Swedo EA, Aslam MV, Dahlberg LL, et al. Prevalence of Adverse Childhood Experiences Among U.S. Adults — Behavioral Risk Factor Surveillance System, 2011–2020. MMWR Morb Mortal Wkly Rep 2023;72:707–715. DOI: http://dx.doi.org/10.15585/mmwr.mm7226a2 .
• Bellis, MA, et al. Life Course Health Consequences and Associated Annual Costs of Adverse Childhood Experiences Across Europe and North America: A Systematic Review and Meta-Analysis. Lancet Public Health 2019.
• Adverse Childhood Experiences During the COVID-19 Pandemic and Associations with Poor Mental Health and Suicidal Behaviors Among High School Students — Adolescent Behaviors and Experiences Survey, United States, January–June 2021 | MMWR
• Hillis SD, Anda RF, Dube SR, Felitti VJ, Marchbanks PA, Marks JS. The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial consequences, and fetal death. Pediatrics. 2004 Feb;113(2):320-7.
• Miller ES, Fleming O, Ekpe EE, Grobman WA, Heard-Garris N. Association Between Adverse Childhood Experiences and Adverse Pregnancy Outcomes. Obstetrics & Gynecology . 2021;138(5):770-776. https://doi.org/10.1097/AOG.0000000000004570 .
• Sulaiman S, Premji SS, Tavangar F, et al. Total Adverse Childhood Experiences and Preterm Birth: A Systematic Review. Matern Child Health J . 2021;25(10):1581-1594. https://doi.org/10.1007/s10995-021-03176-6 .
• Ciciolla L, Shreffler KM, Tiemeyer S. Maternal Childhood Adversity as a Risk for Perinatal Complications and NICU Hospitalization. Journal of Pediatric Psychology . 2021;46(7):801-813. https://doi.org/10.1093/jpepsy/jsab027 .
• Mersky JP, Lee CP. Adverse childhood experiences and poor birth outcomes in a diverse, low-income sample. BMC pregnancy and childbirth. 2019;19(1). https://doi.org/10.1186/s12884-019-2560-8 .
• Reid JA, Baglivio MT, Piquero AR, Greenwald MA, Epps N. No youth left behind to human trafficking: Exploring profiles of risk. American journal of orthopsychiatry. 2019;89(6):704.
• Diamond-Welch B, Kosloski AE. Adverse childhood experiences and propensity to participate in the commercialized sex market. Child Abuse & Neglect. 2020 Jun 1;104:104468.
• Shonkoff, J. P., Garner, A. S., Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care, & Section on Developmental and Behavioral Pediatrics (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246. https://doi.org/10.1542/peds.2011-2663
• Narayan AJ, Kalstabakken AW, Labella MH, Nerenberg LS, Monn AR, Masten AS. Intergenerational continuity of adverse childhood experiences in homeless families: unpacking exposure to maltreatment versus family dysfunction. Am J Orthopsych. 2017;87(1):3. https://doi.org/10.1037/ort0000133 .
• Schofield TJ, Donnellan MB, Merrick MT, Ports KA, Klevens J, Leeb R. Intergenerational continuity in adverse childhood experiences and rural community environments. Am J Public Health. 2018;108(9):1148-1152. https://doi.org/10.2105/AJPH.2018.304598 .
• Schofield TJ, Lee RD, Merrick MT. Safe, stable, nurturing relationships as a moderator of intergenerational continuity of child maltreatment: a meta-analysis. J Adolesc Health. 2013;53(4 Suppl):S32-38. https://doi.org/10.1016/j.jadohealth.2013.05.004 .

Adverse Childhood Experiences (ACEs)

ACEs can have a tremendous impact on lifelong health and opportunity. CDC works to understand ACEs and prevent them.

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Is College Worth It?

As economic outcomes for young adults with and without degrees have improved, americans hold mixed views on the value of college, table of contents.

• Labor force trends and economic outcomes for young adults
• Economic outcomes for young men
• Economic outcomes for young women
• Wealth trends for households headed by a young adult
• The importance of a four-year college degree
• Getting a high-paying job without a college degree
• Do Americans think their education prepared them for the workplace?
• Is college worth the cost?
• Acknowledgments
• The American Trends Panel survey methodology
• Current Population Survey methodology
• Survey of Consumer Finances methodology

Pew Research Center conducted this study to better understand public views on the importance of a four-year college degree. The study also explores key trends in the economic outcomes of young adults among those who have and have not completed a four-year college degree.

The analysis in this report is based on three data sources. The labor force, earnings, hours, household income and poverty characteristics come from the U.S. Census Bureau’s Annual Social and Economic Supplement of the Current Population Survey. The findings on net worth are based on the Federal Reserve’s Survey of Consumer Finances.

The data on public views on the value of a college degree was collected as part of a Center survey of 5,203 U.S. adults conducted Nov. 27 to Dec. 3, 2023. Everyone who took part in the survey is a member of Pew Research Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. Address-based sampling ensures that nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this report , along with responses, and the survey’s methodology .

Young adults refers to Americans ages 25 to 34.

Noncollege adults include those who have some college education as well as those who graduated from high school but did not attend college. Adults who have not completed high school are not included in the analysis of noncollege adults. About 6% of young adults have not completed high school. Trends in some labor market outcomes for those who have not finished high school are impacted by changes in the foreign-born share of the U.S. population. The Census data used in this analysis did not collect information on nativity before 1994.

Some college includes those with an associate degree and those who attended college but did not obtain a degree.

The some college or less population refers to adults who have some college education, those with a high school diploma only and those who did not graduate high school.

A full-time, full-year worker works at least 50 weeks per year and usually 35 hours a week or more.

The labor force includes all who are employed and those who are unemployed but looking for work.

The labor force participation rate is the share of a population that is in the labor force.

Young adults living independently refers to those who are not living in the home of either of their parents.

Household income is the sum of incomes received by all members of the household ages 15 and older. Income is the sum of earnings from work, capital income such as interest and dividends, rental income, retirement income, and transfer income (such as government assistance) before payments for such things as personal income taxes, Social Security and Medicare taxes, union dues, etc. Non-cash transfers such as food stamps, health benefits, subsidized housing and energy assistance are not included. As household income is pretax, it does not include stimulus payments or tax credits for earned income and children/dependent care.

Net worth, or wealth, is the difference between the value of what a household owns (assets) and what it owes (debts).

All references to party affiliation include those who lean toward that party. Republicans include those who identify as Republicans and those who say they lean toward the Republican Party. Democrats include those who identify as Democrats and those who say they lean toward the Democratic Party.

At a time when many Americans are questioning the value of a four-year college degree, economic outcomes for young adults without a degree are improving.

After decades of falling wages, young U.S. workers (ages 25 to 34) without a bachelor’s degree have seen their earnings increase over the past 10 years. Their overall wealth has gone up too, and fewer are living in poverty today.

Things have also improved for young college graduates over this period. As a result, the gap in earnings between young adults with and without a college degree has not narrowed.

The public has mixed views on the importance of having a college degree, and many have doubts about whether the cost is worth it, according to a new Pew Research Center survey.

• Only one-in-four U.S. adults say it’s extremely or very important to have a four-year college degree in order to get a well-paying job in today’s economy. About a third (35%) say a college degree is somewhat important, while 40% say it’s not too or not at all important.
• Roughly half (49%) say it’s less important to have a four-year college degree today in order to get a well-paying job than it was 20 years ago; 32% say it’s more important, and 17% say it’s about as important as it was 20 years ago.
• Only 22% say the cost of getting a four-year college degree today is worth it even if someone has to take out loans. Some 47% say the cost is worth it only if someone doesn’t have to take out loans. And 29% say the cost is not worth it.

These findings come amid rising tuition costs and mounting student debt . Views on the cost of college differ by Americans’ level of education. But even among four-year college graduates, only about a third (32%) say college is worth the cost even if someone has to take out loans – though they are more likely than those without a degree to say this.

Four-year college graduates (58%) are much more likely than those without a college degree (26%) to say their education was extremely or very useful in giving them the skills and knowledge they needed to get a well-paying job. (This finding excludes the 9% of respondents who said this question did not apply to them.)

Views on the importance of college differ widely by partisanship. Republicans and Republican-leaning independents are more likely than Democrats and Democratic leaners to say:

• It’s not too or not at all important to have a four-year college degree in order to get a well-paying job (50% of Republicans vs. 30% of Democrats)
• A college degree is less important now than it was 20 years ago (57% vs. 43%)
• It’s extremely or very likely someone without a four-year college degree can get a well-paying job (42% vs. 26%)

At the same time that the public is expressing doubts about the value of college, a new Center analysis of government data finds young adults without a college degree are doing better on some key measures than they have in recent years.

A narrow majority of workers ages 25 to 34 do not have a four-year college degree (54% in 2023). Earnings for these young workers mostly trended downward from the mid-1970s until roughly a decade ago.

Outcomes have been especially poor for young men without a college degree. Other research has shown that this group saw falling labor force participation and sagging earnings starting in the early 1970s , but the last decade has marked a turning point.

This analysis looks at young men and young women separately because of their different experiences in the labor force.

Trends for young men

• Labor force participation: The share of young men without a college degree who were working or looking for work dropped steadily from 1970 until about 2014. Our new analysis suggests things have stabilized somewhat for this group over the past decade. Meanwhile, labor force participation among young men with a four-year degree has remained mostly flat.
• Full-time, full-year employment: The share of employed young men without a college degree who are working full time and year-round has varied somewhat over the years – trending downward during recessions. It’s risen significantly since the Great Recession of 2007-09, with the exception of a sharp dip in 2021 due to the COVID-19 pandemic. For employed young men with a college degree, the share working full time, full year has remained more stable over the years.

• Median annual earnings: Since 2014, earnings have risen for young men with some college education and for those whose highest attainment is a high school diploma. Even so, earnings for these groups remain below where they were in the early 1970s. Earnings for young men with a bachelor’s degree have also trended up, for the most part, over the past 10 years.
• Poverty: Among young men without a college degree who are living independently from their parents, the share in poverty has fallen significantly over the last decade. For example, 12% of young men with a high school diploma were living in poverty in 2023, down from a peak of 17% in 2011. The share of young men with a four-year college degree who are in poverty has also fallen and remains below that of noncollege young men.

Trends for young women

• Labor force participation: The shares of young women with and without a college degree in the labor force grew steadily from 1970 to about 1990. Among those without a college degree, the share fell after 2000, and the drop-off was especially sharp for young women with a high school diploma. Since 2014, labor force participation for both groups of young women has increased.
• Full-time, full-year employment: The shares of employed young women working full time and year-round, regardless of their educational attainment, have steadily increased over the decades. There was a decline during and after the Great Recession and again (briefly) in 2021 due to the pandemic. Today, the shares of women working full time, full year are the highest they’ve ever been across education levels.

• Median annual earnings: Median earnings for young women without a college degree were relatively flat from 1970 until about a decade ago. These women did not experience the steady decline in earnings that noncollege young men did over this period. By contrast, earnings have grown over the decades for young women with a college degree. In the past 10 years, earnings for women both with and without a college degree have risen.
• Poverty: As is the case for young men without a college degree, the share of noncollege young women living in poverty has fallen substantially over the past decade. In 2014, 31% of women with a high school diploma who lived independently from their parents were in poverty. By 2023, that share had fallen to 21%. Young women with a college degree remain much less likely to be in poverty than their counterparts with less education.

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Half of Latinas Say Hispanic Women’s Situation Has Improved in the Past Decade and Expect More Gains

From businesses and banks to colleges and churches: americans’ views of u.s. institutions, fewer young men are in college, especially at 4-year schools, key facts about u.s. latinos with graduate degrees, private, selective colleges are most likely to use race, ethnicity as a factor in admissions decisions, most popular, report materials.

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The world’s benchmark climate monitoring station passes a major milestone

• May 20, 2024
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On May 17, 1974, staff of the new National Oceanographic and Atmospheric Administration’s Geophysical Monitoring for Climatic Change program took their first atmospheric measurements for what would become one of the most scientifically significant records of humanity’s impact on Earth’s climate.

Since then, NOAA’s Global Monitoring Laboratory’s continuous measurements of atmospheric carbon dioxide (CO 2 ) at the Mauna Loa Observatory have contributed to the longest modern datasets of this important greenhouse gas. NOAA’s daily measurements provide independent observations that complement measurements taken by the University of California San Diego’s Scripps Institution of Oceanography, which started sampling in 1958. The sustained, collaborative effort has helped educate scientists and the public about the relentless rise of CO 2 caused primarily by fossil fuel pollution. 

The concentration of carbon dioxide, or CO 2 , in that first sample was 333.46 parts per million (ppm). This month, as the annual CO 2 cycle peaks, concentrations have been averaging 427 ppm, more than 90 ppm above the 1974 level.  

“The long-term measurements at Mauna Loa have given us an accurate and unmistakable record of humans’ impact on the only atmosphere we have,” said Vanda Grubišić, director of the Global Monitoring Laboratory (GML).

This graph shows the full record of monthly mean carbon dioxide measured at Mauna Loa Observatory, Hawaii, by NOAA and the Scripps Institution of Oceanography. Credit: NOAA Global Monitoring Laboratory

Perched high on the barren slopes of the Mauna Loa volcano in the middle of the Pacific Ocean, the observatory protrudes through the strong marine boundary layer temperature inversion that separates the more polluted lower portions of the atmosphere from the much cleaner free troposphere. The 11,135-foot elevation above sea level is ideal for sampling well-mixed air undisturbed by the influence of local pollution sources or vegetation, producing measurements that represent the average state of the atmosphere in the northern hemisphere. 

The characteristics that make the site ideal for measuring CO 2 also provide ideal conditions for a wide variety of other atmospheric research efforts. The observatory’s 10 buildings house instruments that collected up to 250 climatological measurements for NOAA and partner agency scientists and engineers every day before the eruption of the volcano cut off access to the site in November 2022. 

In the beginning

The Mauna Loa Observatory was established by the U.S. Weather Bureau , the precursor to NOAA’s National Weather Service, on June 28th, 1956, but not to monitor climate. Instead, scientists made routine weather observations and studied atmospheric circulation. They also made observations of solar radiation, cosmic radiation, fallout from atomic tests, snow crystals, meteors, the Sun’s corona, even the atmosphere of Mars. 

Charles David Keeling was the first to observe that CO 2 levels rose and fell every year in concert with the seasons, a dynamic which is now known as the Keeling Curve . The highest monthly mean CO 2 value of the year occurs in May, just before plants in the northern hemisphere start to remove large amounts of CO 2 from the atmosphere during the growing season. In the northern fall, winter, and early spring, plants and soils give off CO 2, causing levels to rise through May. 

Keeling was also the first to recognize that despite the seasonal fluctuation, average CO 2 levels were increasing every year. Not only has that trend continued, but the rate of the annual increase has also risen – sharply – in recent decades. (Keeling’s son, geochemist Ralph Keeling, runs the Scripps program at Mauna Loa.)

This aerial photograph shows the dominant fissure erupting on the Northeast Rift Zone of Mauna Loa, taken at approximately 8 a.m. Hawaii Standard Time on November 29, 2022. Lava fountains were up to 25 m (82 ft) that morning as the vent was feeding the main lava flow to the northeast. Credit: M. Patrick/USGS photo

The volcano awakes

On Nov. 27, 2022, lava flows from the erupting Mauna Loa volcano buried more than a mile of the access road and destroyed power poles, temporarily interrupting all scientific activity at the observatory. NOAA and Scripps scientists were able to quickly set up alternative sampling sites for some measurements, including CO 2 , at Maunakea. 

In 2023, MLO staff visiting the site once a week via helicopter restored limited power to four key observatory buildings by augmenting existing solar generation and adding battery systems. Approximately 33 percent of the atmospheric measurements on the mountain site have been restored, including consistent measurements for greenhouse gases, halocarbons and trace gases, ozone, aerosols and global radiation. Reconstruction of the access road to the observatory is anticipated in 2025.

The Mauna Loa Observatory is one of four NOAA atmospheric baseline observatories strategically situated from the Arctic to the South Pole, each of which collects numerous daily in situ and remote atmospheric and solar measurements. Continuous measurements of atmospheric CO 2 at the Barrow Observatory near the ​​village of Utqiaġvik, Alaska began in July 1973, at the South Pole Atmospheric Research Observatory in January 1975, and at the American Samoa Atmospheric Baseline Observatory in January 1976.

To explore more information about the CO 2 record at Mauna Loa Observatory, visit the GML website’s Trends in CO2 page. 

For more information, contact Theo Stein, NOAA Communications: [email protected] .

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Journal of Materials Chemistry C

Functionalised al( iii ) metal organic frameworks for fluorescence sensing of nitroaromatic vapours †.

* Corresponding authors

a Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece E-mail: [email protected]

b Department of Materials Science and Engineering, University of Crete, Vassilika Vouton, 70013 Heraklion, Greece

The employment of fluorescence sensors provides a platform for rapid and efficient in-field detection of nitroaromatic compounds and is gaining increasing research ground. Herein, we report the synthesis and characterisation of three new fluorescent Al( III ) MOFs, structurally analogous to MIL-53, with the assigned formula {Al(OH)(bdc) 1− n ( L-1 ) n }·xsolv (bdc 2− = terephthalate; L-1 = 2-((benzyl)amino)-terephthalate). L-1 is a strongly fluorescent dicarboxylic ligand with a pendant π-electron rich aromatic group suitable for donor–acceptor interactions with electron-deficient nitroaromatic guests. Our MOFs show strong fluorescence quenching upon exposure to vapours of nitrobenzene, 1,3-dinitrobenzene, 4-nitrotoluene, and 2,4-dinitrotoluene. Additionally, we prepare and study MOF-polymer composites in the form of thin films that are strongly quenched in the presence of nitrobenzene vapours.

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Functionalised Al( III ) metal organic frameworks for fluorescence sensing of nitroaromatic vapours

A. Haj-Yahya, D. Kouskouki, A. G. Margellou, E. K. Andreou, G. S. Armatas and T. Lazarides, J. Mater. Chem. C , 2024, Advance Article , DOI: 10.1039/D4TC00862F

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