Inviting Conversations in Discipline‐Based Science Education

Dados Bibliográficos

ID21392687
AutoresJulia Gouvea (0000-0002-2228-9066, Department of Education Tufts University Medford Massachusetts USA, autor correspondente), Hannah Sevian (0000-0001-7378-6786, Department of Chemistry (Retired) University of Massachusetts Boston Boston Massachusetts USA, autor correspondente), Ben Van Dusen (0000-0003-1264-0550, School of Education Iowa State University Ames Iowa USA, autor correspondente)
Ano2026
Volume110
Fascículo3
Páginas711-716
Data de publicação2026-05-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoScience Education (JOURNAL)
Identificadores do periódicoISSN: 0036-8326 • E-ISSN: 1098-237X
EditoraWiley (PUBLISHER • GB)
DOI10.1002/sce.70045
OpenAlexW4417506308
IdiomaEN
Citações recebidas1
Referências citadas54

A scholarly journal is a space for a community of researchers and practitioners to engage in conversations that expand knowledge, practice, and impact of a field. The new section of Science Education entitled “Discipline-Based Science Education” invites conversations within and among science education research communities that identify as “discipline-based.” Connections with disciplinary subfields such as biology, chemistry, physics, environmental science, and geosciences have long informed research in science education. In the United States, over the past century, interest and expertise in education research emerged and grew from within each discipline, especially as faculty from disciplinary departments transitioned to studying teaching and learning in colleges and universities (NRC 2012). Over the past decades, these discipline-specific communities, which have been grouped under the term “Discipline-Based Education Research” (DBER), have formed new scholarly societies, developed graduate programs, and launched new journals (Cooper and Stowe 2018; NRC 2012). In many other countries, education scholars often have primary appointments in disciplinary departments because this is where science teacher preparation is located. This structure allows education researchers to build and maintain strong disciplinary connections. What unites these communities is a combination of disciplinary expertise in the sciences and knowledge of the theory, methodologies, and analytical frameworks of education research. We use the term discipline-based science education (DBSE) research to refer to these communities. The growth of DBSE research has produced new knowledge about learning and teaching in specific disciplines and has expanded research on education at the post-secondary level. DBSE researchers, with their disciplinary expertise and positions in disciplinary departments, are well-positioned to study learning specific to disciplines and to lead departmental reforms (Coppola and Krajcik 2014). At the same time, specialization in DBSE has contributed to partitioning and isolation both from other disciplines and from the broader science education community (Talanquer 2014). This isolation is maintained by the location of DBSE researchers in disciplinary units, the independent origins and separate growth of each community within each sub-discipline, and the emphasis on disciplinary learning in higher education. Calls for increased communication among DBSE communities argue for the need to bring diverse perspectives into contact, negotiate areas of consensus, and identify open questions and areas of contention (Henderson et al. 2017; Peffer and Renken 2016). For example, Dolan (2015) called on the biology education research community to move beyond promoting active learning strategies to investigating the mechanisms of learning in both students and faculty. Cooper and Stowe (2018) chronicled shifts in the chemistry education research community and called for a need to examine the prevalence of deficit-based narratives of students. Conversations like these are critical because they invite researchers to reflect on and actively negotiate the aims, values, and practices of their community. We enthusiastically introduce this new section of Discipline-Based Science Education as a space in which to cultivate conversations among scholars who identify as working within and across DBSE. We invite any work that engages with conversations about teaching and learning in connection with disciplinary communities, including but not limited to scholarship from DBER communities, science education research that engages with the work of disciplines, and research that is interdisciplinary, both in its attention to learning at the intersection of disciplines and spanning multiple education research traditions. In this commentary, we outline three themes that we hope can seed conversations in this section of Science Education. First, we raise questions about definitions and purposes of “discipline” in discipline-based science education research. Next, we discuss the importance of theory in the contributions of discipline-based scholarship. Third, we invite transparency in discussions of methodological choices. Given the centrality of “discipline” in this new section, we feel that it is important to consider what discipline-based science education research has meant as well as how it is evolving and will continue to evolve. DBSE has been described as research that is grounded in the “priorities, worldview, knowledge, and practices” of specific scientific communities (NRC 2012). Researchers in these communities often are, or have been, practicing scientists and use their experiences and expertise to inform their research goals and approaches. Consider the following examples. One primary goal of DBSE has been to understand and promote science learning that uses the tools, ideas, and habits of mind of disciplinary communities—to learn to think or do science like scientists. Examples include the learning of specialized forms of discourse, practices such as modeling, and epistemological orientations towards sensemaking (e.g., Bolger et al. 2021; Hammer 2000; Hazari et al. 2010; Libarkin et al. 2007; Mortimer and Scott 2003; Sevian and Talanquer 2014). A second major goal has been to address inequities in access to disciplinary communities. Much of DBER, for example, has focused on expanding pathways into science by reforming introductory courses or increasing opportunities for students to engage in authentic research experiences (e.g., Dolan 2016; Matz et al. 2018; Oliver-Hoyo et al. 2004; Sevian et al. 2023; Theobald et al. 2020). Notice that both goals frame disciplinary learning as inherently good and desirable, and we agree that research that aims to understand and support learning that engages students in the practices, reasoning strategies, epistemologies, attitudes, identities, and emotions of disciplinary work is worthy. At the same time, we see a need for conversations that work to renegotiate, expand, and critique what counts as “disciplinary.” Such conversations are ongoing in the Science Education community, and in the DBSE section, we hope to involve researchers grappling with such questions. Below, we outline three examples of conversations about the role and purpose of grounding education research in disciplinarity. First, disciplinary learning has been strongly guided by conceptions of what experts do—what they know, how they think, and how they engage in scientific practice. While an understanding of expertise can provide ambitious learning targets, there are limitations to using normative descriptions of expertise to guide student learning. Such descriptions tend to focus attention on the ways in which students are not yet functioning as experts. Focusing on the gap between experts and novices can highlight misconceptions and other deficits in novices rather than building understanding of how students’ progress towards expertise (Cooper and Stowe 2018; Gupta and Elby 2011; Hammer 1996a, 1996b; Svoboda 2023). Additionally, descriptions of expertise tend to present it as a singular endpoint rather than appreciate the inherent variation and diversity of approaches that comprise expertise in scientific communities (Sevian and Talanquer 2014; Sikorski and Hammer 2017). Conversations about the relationship between experts and novices have been ongoing in K-12 science education, and we see a need for more research that examines the dynamics of disciplinary learning, including considerations such as: How can we broaden definitions of disciplinary expertise to encompass the variety of forms of expertise that are important in disciplinary communities? How can we understand the diversity of resources and experiences students bring and their continuity with that expertise? What needs to change to include critical conversations about the histories and cultures of disciplines in disciplinary learning? And how do students learn about these conversations? How does this learning influence students’ belonging, identities, and future participation in the disciplines? What is the value and relevance of disciplinary learning for students and society? How can disciplinary learning support transformation towards democracy and justice? Practices of theory use, application, and development are variable within and across DBSE communities. Our aim in this section is to invite authors to engage with theory and to cultivate conversations that deepen theory-building and theory-revising practices in DBSE. In this section, we provide a brief overview of the importance of theory work and conversations in DBSE. Whether a theory is applied or developed anew, theory enables us to interpret data through narratives, mechanisms, models, or similar frameworks that offer meaning. This use of theory is shared between science and DBSE. For example, Kinetic Molecular Theory explains matter's structure and dynamics by considering what occurs on the level of particles (atoms or molecules). It can explain the structure of matter and the processes of phase changes, for example. In education, Activity Theory (Engeström 1999) can be used to explain the patterns of activity that emerge from groups of people working together. Second-generation Activity Theory (Engeström and Sannino 2021) proposes that relationships between subjects and the objects (or purposes) they hope to achieve are mediated by relationships with other parts of an activity system, such as available tools, socially constructed community rules, and roles. This theoretical framework can help explain, for example, how partners in an informal science education research-practice partnership shifted power (Greenberg et al. 2025). In both science and DBSE, theories are based on assumptions that are important to examine both when the theories fit the phenomena and when those assumptions break down. Where assumptions break provides useful information that advances knowledge. When we encounter data that cannot be modeled by a theory, it invites us to examine the theory's structure, which affords us insights into the boundaries of assumptions. Kinetic Molecular Theory does a marvelous job of explaining many properties of gases, such as how pressure and volume relate to temperature. However, it must be modified to account for attractions and repulsions when particles are closer together in liquids and solids. Determining which assumption(s) must be modified lends tremendous insight into how gases differ from liquids and solids. Similarly, Activity Theory has evolved through multiple generations as researchers recognized that its assumptions constrained the theory and limited its usefulness (Engeström and Sannino 2021). The first generation of Activity Theory involved only the first three aspects: subject, object, and resources. The third generation recognizes that the assumption that activity is unidimensional fails, leading to elaboration of the theory by considering intersections and scales of activity to explain phenomena, for example, classroom activity at one scale, and department activity at a larger scale. The fourth generation considers the dynamics as well as the interdependency of activity, via cycles of expansive learning. Theory can also support design. Kinetic Molecular theory makes possible the design of a range of useful advances in science and engineering, including cellular biomechanics and how wind tunnels function. It also contributes to characterizing and controlling the functions of pharmaceutical inventions, which rely on understanding protein folding, interactions with water, and many other molecular-level dynamics at various scales. Activity Theory also facilitates the design of activities at a variety of levels, such as classroom talk, formative assessment tasks, teacher preparation and professional development, and interactive computer-based learning, by offering a structure for analysis and predictions of how different variables impact the ways phenomena will play out. For example, Activity Theory's expansive learning (the process of how the emergence and resolution of contradictions among aspects of activity drive new learning and activity) was employed to examine and improve the design of a video annotation tool used for peer feedback on presentation skills and knowledge of climate science in an undergraduate general education course (Gatrell et al. 2025). The theories we build and use also structure and constrain how we think about phenomena. The assumptions of Kinetic Theory constrain what researchers notice and what they decide to measure, and what kinds of knowledge are valued. In education, theories about people, social groups, and institutions similarly influence what is noticed and studied and valued. How “equity” is conceptualized shapes how researchers, and even how different fields, think about what equity problems are and how to study them (Calabrese Barton and Tan 2020; Grapin et al. 2023; Hand et al. 2013; Philip and Azevedo 2017; Russo-Tait 2022). For example, when equity is conceptualized as equal opportunities to “access” scientific learning and practice, research tends to focus on how to keep equal numbers of students in science classes, majors, and careers. Other theories of equity bound the problem differently, for example, by conceptualizing equity as requiring explicit attention to the forms of knowledge and practice that take place and are valued in science classrooms. Are students learning about diverse ways of engaging in science? Do they have opportunities to consider broad sets of purposes, including how science can improve their own communities? One way of theorizing equity lowers the barrier to entry into science learning as it is, the other asks researchers to consider how science learning itself should be transformed. In this brief overview, we have discussed how theory shapes what researchers notice, value, measure, and attempt to explain. In the DBSE section of Science Education, we ask authors to ground research in theory, clarify the assumptions of the theory, justify why the theory is a fit for the research that has been conducted, and show where assumptions break and how this expands knowledge in useful ways. In addition, we invite examination of how theory is useful in designing or improving science teaching and learning, as well as reflection on the ways in which theories shape the values and implications of DBSE research. We note that given the different trajectories of DBSE communities, DBSE researchers use and apply theories from a range of different disciplines and traditions, including psychology, anthropology, sociology, cognitive science, and the learning sciences. Theories from these traditions differ in their ability to explain and predict, in the assumptions they make, and in the values and implications they promote about education. Thus, we are particularly interested in bringing these theories into conversation with one another, either within or across articles to begin to explore areas of convergence and divergence. We welcome grappling with tensions in ways that uncover new or even opposing views that depend on modified or different assumptions, and we also welcome embracing dialectics that argue that seemingly opposed ideas can coexist. As DBSE research has grown, the types of knowledge claims and methods have expanded, creating a need for researchers to make intentional choices as they negotiate among alternatives. The DBSE section can provide a forum for conversations that interrogate research choices that can go unexamined. Such discussions can encourage researchers to reflect on how they define and practice depth, rigor, ethics, and transparency in their study design, analysis, and interpretation. All methodological decisions shape research outcomes—and those choices are never neutral. Researchers must be transparent with themselves and their readers about how these choices influence findings. Here, we raise considerations that can encourage reflective research practices. In qualitative research, conversations about subjectivity are common (Denzin and Lincoln 2011). Yet, quantitative methods also come with subjectivities. A common example is the misuse of p-values, which are often mistaken as objective measures of educational significance or used as arbitrary cutoffs for validating results (Cumming 2014; Wasserstein and Lazar 2016). Statistical uncertainty is a complex concept that no single metric can fully capture. Conversations critical of rigid and uncritical statistical practices are ongoing (Gigerenzer 2004). In response, the American Statistical Association curated a special issue of 43 papers offering alternative frameworks for interpreting statistical uncertainty with greater care and nuance (Wasserstein and Lazar 2016). Beyond p-values, researchers must thoughtfully consider other key issues such as generalizability (Kanim and Cid 2020), model specification (Li and Singh 2024; Van Dusen and Nissen 2022), causal inference (Adlakha and Kuo 2023), nested data structures (Van Dusen and Nissen 2019), and data aggregation (Shafer et al. 2021). These and other decisions require careful reflection to ensure rigor and relevance. Statistical software tools offer a growing range of packages and options. Without care, this proliferation can make it easier to apply inappropriate methods. Yet when used intentionally, it broadens access to more flexible and transparent approaches. For instance, Bayesian models offer an alternative to p-values and allow for greater statistical power by incorporating prior information (Bolstad and Curran 2016). This modeling framework supports innovations like Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), which enables researchers to model how multiple social identities interact to shape outcomes—offering a more nuanced approach to intersectional analysis (Evans et al. 2024). Simulation studies show that MAIHDA can outperform traditional fixed-effect models in predicting group-level outcomes (Van Dusen et al. 2024). As the field evolves, researchers will need to engage in discussions about how to adopt emerging methods with intention and discernment. Finally, thoughtful researchers must actively interpret and contextualize their findings. Researchers in QuantCrit have argued that the idea that “data speak for themselves” is a myth (Gillborn et al. 2023). When researchers withhold interpretation, they shift the burden of meaning-making to readers—heightening the risk of misinterpretation and reinforcing dominant narratives. Without intentional framing, findings are more likely to be interpreted through deficit-oriented or inequitable lenses (Castillo and Strunk 2025). Theory is useful here in clarifying assumptions, both in research design and analytical framing; and while it is more commonly recognized that qualitative methods are guided by theory (Collins and Stockton 2018), the same reasoning applies to the role of theory in quantitative research (Stage 2007; Zuberi and Bonilla-Silva 2008). We encourage authors to construct narratives that are grounded in theory, informed by evidence, and attentive to the study's boundaries and broader implications. In addition, we invite scholarly conversations about how DBSE constructs knowledge, what counts as evidence, and the implications of how findings are interpreted and positioned to inform practice and policy. DBSE research is shaped by the interplay of disciplinary commitments, methodological choices, and educational This section of Science Education is as a space where researchers working within and across disciplinary traditions can work that is and attentive to the assumptions and values both disciplinary and educational practice. how disciplinary knowledge, practices, and values shape learning, and the boundaries and assumptions of theoretical or methodological including where they break or require how students engage with disciplinary learning across of or prior Consider how DBSE with broader goals in education, such as or social between DBSE and other areas of science education research, such as teacher education, informal learning, or the learning sciences. How do disciplinary and histories influence what is how it is and who they In what ways do students’ experiences or with disciplinary How do the assumptions into commonly used methods or models shape findings and What can disciplinary learning play in educational or Our hope is that this section contributes to ongoing conversations in DBSE by a space for critical methodological and theoretical across disciplinary and Van Dusen are the of the Discipline-Based Science Education section of this contributed to aspects of this and three are

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