Research carried out through the last 20 years gave us undeniable evidence that to learn anything we need to be active participants, not passive observers. One of the important aspects of learning physics is constructing explanations of physical phenomena. To support and guide students toward constructing their explanations, teachers need to be attentive and responsive to students’ explanations. To learn how physics teachers interpret and respond to students’ explanations we investigated pre- and in-service physics teachers’ responses to students’ written explanations of their answers to a complex physics problem. The survey administered to the participants included the problem statement and four authentic student explanations. The participants were asked to identify each student’s strengths and weaknesses and to provide a response to that student. We found that while the participants were successful in identifying productive and problematic aspects of student reasoning, they rarely built on student reasoning when responding to the students, mostly focusing on addressing problematic aspects. The paper discusses why this finding is important for physics teacher preparation programs and professional development programs.

A survey of 722 physics faculty conducted in 2008 found that many physics instructors had knowledge of research-based instructional strategies (RBISs), were interested in using more, but often discontinued use after trying. Considerable effort has been made during the decade following 2008 to develop and disseminate RBISs in physics as well as change the culture within the physics community to value RBIS use and other forms of student-centered instruction. This paper uses data from a 2019 survey of 1176 physics instructors to understand the current state of RBIS use in college-level introductory physics, thus allowing us to better understand some of the impacts of these efforts on physics instruction. Results show that self-reported knowledge and use of RBISs has increased considerably and discontinuation is now relatively low. However, although the percentage of time lecturing is less than 10 years ago, many instructors still engage in substantial lecturing (i.e., more than one-third of class time). Relatedly, we find that the majority of RBIS use centers on pedagogies designed to supplement a primarily lecture-based classroom rather than pedagogies designed to support a primarily active learning classroom. This suggests that the physics education research community and beyond has done well promoting knowledge about RBISs and inspiring instructors to try RBISs in their courses. But, there is still room to improve. Based on available evidence about effective instructional practices, we recommend that change agents focus on supporting instructors to increase the percent of class time in active learning and to implement higher impact strategies.

Female students, Latinx students, first-generation students, and transfer students often feel uncomfortable in science, technology, engineering, and mathematics (STEM) environments. However, some departments have been making progress in changing that. Guided by double consciousness and person-environment fit theory, we investigated the lived experiences of historically marginalized undergraduate and masters-level physics students at a large state university to understand how this particular department provides an environment encouraging all students they fit in physics. Graduated students and faculty were interviewed from California State University, Long Beach. Through the interviews, we gained an understanding of significant student experiences and their perceptions of fit in this physics environment. Department community members perceived the department environment to be open, which contributed to broadening fit and supporting diverse students to thrive. The importance of faculty agency in creating a welcoming and supportive physics environment is highlighted. Finally, we found students in this department take with them an approach to physics that they see applicable to other areas of study and their lives. We called this a physics state of mind. We include suggestions for other STEM departments based on the findings and previous research.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] Acknowledgement of the limited learning outcomes in our first-year physics lab course, strikingly similar to the observed and reported issues in literature, incited renewal of the course with a focus on developing students’ ability to engage in experimental physics research. The procedural and conceptual knowledge (PACKS) model—addressing different types of knowledge required for scientific investigation—was used as a “guide” in the transformation of the course. This educational design research study—distinguishing three stages—describes our approach in transforming the course and provides theoretical insights and practical solutions through the combined study of both the process of learning and the means that support that process. The merits and trade-offs of our approach and the effectiveness of the course transformation are evaluated through surveys, interviews, and assessment of students’ inquiry skills. The findings provide insights into the application of the PACKS model and its effectiveness in facilitating students’ development of physics inquiry abilities. The results reveal an alignment between perceived, attained and intended learning goals. The self-conceived experiment at the end of the course showcases students’ successful integration of the targeted knowledge types, previously addressed in isolated “preparatory” activities. We argue that the PACKS-model and the design principles are useful attributes when transforming a traditional lab activity, but also specify the limitations.

Recent advances in publicly available natural language processors (NLP) may enhance the efficiency of analyzing student short-answer responses in physics education research (PER). We train a state-of-the-art NLP, IBM’s Watson, and test its agreement with human coders using two different studies that gathered text responses in which students explain their reasoning on physics-related questions. The first study analyzes 479 student responses to a lab data analysis question and categorizes them by main idea. The second study analyzes 732 student answers to identify the presence or absence of each of the two conceptual themes. When training Watson with approximately one-third to half of the samples, we find that samples labeled with high confidence scores have similar accuracy to human agreement; yet for lower confidence scores, humans outperform the NLP’s labeling accuracy. In addition to studying Watson’s overall accuracy, we use this analysis to better understand factors that impact how Watson categorizes. Using the data from the categorization study, we find that Watson’s algorithm does not appear to be impacted by the disproportionate representation of categories in the training set, and we examine mislabeled statements to identify vocabulary and phrasing that may increase the rate of false positives. Based on this work, we find that, with careful consideration of the research study design and an awareness of the NLP’s limitations, Watson may present a useful tool for large-scale PER studies or classroom analysis tools.

We use the Survey of Thermodynamic Processes and First and Second Laws-Long, a research-based survey instrument with 78 items at the level of introductory physics, to investigate introductory and advanced students’ difficulties with internal energy, work, and heat transfer. We present analysis of data from 12 different introductory and advanced physics classes at four different higher education public institutions in the U.S. in which the survey was administered in person to more than 1000 students. We find that not only introductory but also advanced physics students have many common difficulties with these introductory thermodynamic concepts after traditional lecture-based instruction in relevant concepts. We utilize a wide variety of problem types and contexts and our sample includes large numbers of introductory algebra-based, calculus-based, and advanced students. Some of our findings are consistent with prior research in this area, but others expand upon them and reveal previously unreported aspects of students’ thinking. Findings related to common difficulties of students before and after traditional lecture-based instruction in college physics courses can help instructors of these courses plan instruction and curricula to improve student understanding. These findings can also be valuable for developing effective research-based curricula and pedagogies to address student difficulties and help students develop a functional understanding of these fundamental thermodynamic concepts.

The percentage of women receiving bachelor’s degrees in physics (25%) in the U.S. lags well behind that of men, and women leave the major at higher rates. Achieving equity in physics will mean that women stay in physics at the same rates as men, but this will require changes in the culture and support structures. A strong sense of belonging can lead to higher retention rates so interventions meant to increase dimensions of physics identity (interest, recognition, performance, and competence) may increase persistence overall and increase women’s retention differentially. We describe our model in which mentorship, an understanding of career options (career conceptualization), and leadership are inputs into the development of these dimensions of physics identity. This paper includes preliminary results from a qualitative study that aims to better understand how career conceptualization, leadership, and mentorship contribute to the development of physics identity and belonging. We report results from a survey of 15 undergraduate physics students which was followed up by interviews with 5 of those students. The students were from 2 institutions: a small private liberal arts college in the midwest region of the U.S. and a large public university in the southeast region of the U.S. classified as a Hispanic-serving institution (HSI). With respect to mentorship, consistent with the existing literature, we found that it could provide critical support for students’ engagement in the physics community. Leadership experiences have not previously been positioned as an important input into identity, yet we found that they helped women in physics feel more confident, contributing to their recognition of themselves as physics people. While the data on how career conceptualization contributed to the building of identity is limited, there are some connections to recognition and competence, and it will be an interesting avenue of future exploration.

Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing much larger and broader datasets to be analyzed than is practical with human coders. Existing work that uses these tools, however, does not investigate norms that allow for trustworthy quantitative claims without full reliance on cross-checking with human coding, which defeats the purpose of using these automated tools. Here we propose a four-part method for making such claims with supervised natural language processing: evaluating a trained model, calculating statistical uncertainty, calculating systematic uncertainty from the trained algorithm, and calculating systematic uncertainty from novel data sources. We provide evidence for this method using data from two distinct short response survey questions with two distinct coding schemes. We also provide a real-world example of using these practices to machine code a dataset unseen by human coders. We offer recommendations to guide physics education researchers who may use machine-coding methods in the future.

The notion of scientific visual literacy has been advocated in recent science curriculum reform documents and related learning outcomes are expected from students. However, few studies have been conducted to determine how it is tested in high-stakes examinations. This study utilized the Visualization Blooming Tool to examine the level of visual cognition involved in visual-based physics questions in the Senior High School Entrance Examination (SHSEE) in China. Content analysis was adopted as the research method and 12 sets of the SHSEE physics from four Chinese metropolises (Beijing, Shanghai, Hangzhou, and Suzhou) in 2020, 2021, and 2022 were targeted. The results indicate that although all four metropolises examined the higher-order visual cognitive skills, they placed more emphasis on the levels of apply and analyze but less on evaluate and create. Moreover, the examination items required students to interpret visual representations more often than to construct them, which may be detrimental to developing students’ scientific visual literacy. It is suggested that the examination of higher-order visual cognitive skills and encoded visual representation should be strengthened in future high-stakes physics examinations.

Science, technology, engineering, and mathematics (STEM) education research and physics education research, in particular, are currently struggling with a dearth of research into understanding the experiences and identity development of neurodivergent students. In addition, an even larger gap in research exists looking into nonacademic members who have left the field and still strongly identify with their disciplinary identity. As valued members of our physics community, these colleagues provide a unique perspective as to how identity and participation are nurtured and developed, particularly among rising disabled physicists. To resolve these current issues and aid in future research, we operationalize our new Critical Disability Physics Identity framework and present results from interviews with three neurodivergent post-baccalaureate nonacademic physicists (those who have left physics and retain a strong affinity toward their identity as a physicist). As the first paper in a four-part phenomenological study into the identity development of neurodivergent physicists, we also present an analysis of each interview through a Critical Disability Physics Identity lens and discuss the implications of their Critical Disability Physics Identity development. We find that neurodivergent students experience very little outright discrimination and violence but experience structural ableism in the form of assessment that is not constructed for how neurodivergent physicists perform physics-related tasks. Additionally, we find that neurodivergent physicists seem to ground identity in having a strong interest in physics, something that is only shaken by professors and others in power being neutral toward the discrimination experienced by neurodivergent people. We find that there are very large power imbalances between professors and neurodivergent students and that only when professors and others in power are actively anti-ableist is this power imbalance remedied and neurodivergent students begin to feel that they are physicists.

In the field of physics education research, numerous studies have been dedicated to investigating the relationship between gender identity and physics learning. However, these studies have predominantly employed binary gender measurement methods, which may limit the range of research questions that can be explored and impede the discovery of crucial insights. In this study, we adapted gradational measures from prior research to investigate students’ self-identified femininity, masculinity, and androgyny, as well as their reflected appraisal of femininity, masculinity, and androgyny (i.e., perceptions of how others perceive them) in both algebra-based and calculus-based introductory physics courses. The use of gradational measures revealed significant variation in students’ self-identified femininity, masculinity, and androgyny within the binary categories of women and men, providing new insights into gender dynamics in physics. We found that self-identified women in the calculus-based courses, where they are underrepresented, tend to perceive themselves as more masculine and less feminine than how they believe others perceive them. Similarly, students of color are also more likely than White students to perceive themselves as more masculine than they believe others perceive them. Using structural equation modeling, we found that students’ gender stigma consciousness plays an important role in mediating the effects of identifying as women and students of color on the observed discrepancies. Additionally, we found that women also exhibit a tendency to perceive themselves as more androgynous than they believe others perceive them in both algebra-based and calculus-based physics courses, and this phenomenon is also related to gender stigma consciousness. Moreover, our analyses revealed that students in the calculus-based courses tend to have a higher level of gender stigma consciousness even after controlling for gender and race. Our findings underscore the potential of gradational gender measurements in deepening our understanding of gender-related issues in physics education, shedding light on the complex interplay between students’ gender identity, perceptions from others, and their educational experiences in the field.

The well-known artificial intelligence-based chatbot ChatGPT-4 has become able to process image data as input in October 2023. We investigated its performance on the test of understanding graphs in kinematics to inform the physics education community of the current potential of using ChatGPT in the education process, particularly on tasks that involve graphical interpretation. We found that ChatGPT, on average, performed similarly to students taking a high-school level physics course, but with important differences in the distribution of the correctness of its responses, as well as in terms of the displayed “reasoning” and “visual” abilities. While ChatGPT was very successful at proposing productive strategies for solving the tasks on the test and expressed correct reasoning in most of its responses, it had difficulties correctly “seeing” graphs. We suggest that, based on its performance, caution and a critical approach are needed if one intends to use it in the role of a tutor, a model of a student, or a tool for assisting vision-impaired persons in the context of kinematics graphs.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] This manuscript presents a case study of an introductory physics student who, during the remote learning conditions imposed during the COVID-19 pandemic, found inspiration within a new, open-inquiry, project-based, laboratory curriculum designed at Portland State University. The phenomenon investigated by the study subject was intriguing to both the student and the lab instructors for its unfamiliar and instructive optical effect: a ring-shaped pattern or halo created by a laser diffusely reflected in a shallow body of water. Drawing on classwork and interview responses, this study shows that the subject achieved many expected curriculum outcomes, particularly with respect to experimental design and data analysis tasks, indicating that the course’s open-inquiry structure can be effective while offering students a free choice of what to investigate in a laboratory class. Additionally, the case study shows that the halo phenomenon is pedagogically rich as it combines refraction, diffuse reflection, and total internal reflection in a nontrivial way, thereby answering calls by physics education researchers for more complex, realistic examples in geometric optics instruction. Finally, this case also highlights challenges students may experience interpreting diffuse reflection and determining the position of optical features beyond image formation, not commonly a focus of introductory physics courses, textbooks, and education research.

Digital learning technologies have grown increasingly important in physics education, partly enforced through the COVID-19 pandemic. During the pandemic, digital technologies allowed for continued teaching and learning of students even when schools were closed. While research in psychology and educational technology has yielded many insights into the effectiveness of e-learning courses, fewer studies have examined the design of e-learning courses. Few studies have empirically investigated the design of learning tasks as a central element of e-learning courses. The present study analyzes how the design of tasks in e-learning courses, specifically with respect to their degree of openness as well as the relevance of their contexts, influences students’ behavioral engagement, learning outcomes, and situational interest. Due to the importance of e-learning courses during the COVID-19 pandemic, we also analyzed the extent to which specific learning settings (classroom learning, distance learning) influence the effects of e-learning course design on students’ behavioral engagement, learning outcomes, and situational interest. To investigate the research questions, we analyzed a total of $N=1060$ datasets for 12 different e-learning courses (3 to 5 lessons, middle school physics), of which $n=557$ were completed before and $n=503$ during the COVID-19 pandemic. The results suggest that e-learning courses with a high proportion of learning tasks that relate to meaningful real-world contexts appear to be more conducive to behavioral engagement, learning outcomes, and situational interest. Regarding the consideration of open-ended tasks, the results suggest that these appear to be more useful for classroom learning but should be used in a limited way when designing e-learning courses for distance education.

[This paper is part of the Focused Collection on Qualitative Methods in PER: A Critical Examination.] Epistemic beliefs about physics are most often investigated using quantitative instruments that reflect binary conceptualizations of those beliefs. This study reports from a qualitative study which used continua to represent the epistemic beliefs about physics knowledge of sixteen Western Canadian, high school physics teachers. Unlike other research, this study did not intend to compare epistemic beliefs to any specific epistemology of science. This article presents a novel, more nuanced means of analyzing interview data to construct profiles to describe epistemic beliefs. The epistemic belief profiles of the physics teachers in this study reflect each of four areas of a literature-derived theoretical framework regarding epistemic beliefs about physics knowledge. These four areas are individuals’ beliefs about the (a) source, (b) content, (c) certainty, and (d) structure of physics knowledge. The use of thematic analysis research methods and reasons for the placement of participants along continua are discussed. Potential classroom applications of this research include prompting discussions about student epistemic beliefs and collecting more nuanced representations of students’ epistemic beliefs to inform teaching.

Statistical mechanics has received limited attention in physics education research and remains a relatively underrepresented topic even in research on upper-division physics courses. The purpose of this study was to explore potential challenges that physics students encounter when they solve statistical mechanics problems in groups. Adopting a grounded approach, we video recorded and analyzed nine small student groups engaging in collaborative problem solving on the topic. The analysis involved iterative thematic coding, which gave rise to ten emergent categories of challenges. These were later divided into two broad groupings: challenges with concepts and challenges with problem-solving strategies. In the first grouping, we list seven identified categories related to the concepts of macrostates and microstates, distinguishable and indistinguishable particles, temperature, entropy, energy, equilibrium, heat bath, the Boltzmann distribution, and the partition function. In the second grouping, we list three categories related to the inappropriate application of common relations, difficulty managing tensions between calculated results and qualitative reasoning, and coming up with definitions of new and inconsistent concepts. Some of our findings are supported by existing research on the topic, and others are previously unreported. Based on our findings, we propose that future research should investigate the relations between the identified challenges on one hand, and students’ epistemological framing, reasoning, and use of multiple representations on the other. Finally, we suggest that teachers should spend time engaging students in a conceptual discussion of the central ideas of statistical mechanics, motivating the choice and pointing out limitations of commonly used toy models, and linking course content to real-world phenomena.

The Brief Electricity and Magnetism Assessment (BEMA) is a multiple-choice instrument commonly used to measure introductory undergraduate students’ conceptual understanding of electricity and magnetism. This study used a network analysis technique called modified module analysis-partial (MMA-P) to identify clusters of correlated responses, also known as communities, within 12214 BEMA responses. MMA-P identifies both communities related to the structure of the instrument and communities related to incorrect student reasoning. Every community resulting from MMA-P came from blocked items; groups of items that all refer to the same physical system. The most prevalent and consistently selected incorrect answers involved the relation of the electric field to the electric potential difference. The community structure identified in the Conceptual Survey of Electricity and Magnetism (CSEM) by a prior MMA-P study on items shared by the CSEM and BEMA differed because of the different incorrect responses available in the two instruments. One pair of items in the BEMA involving the induced electric field by a changing magnetic field showed evidence of students applying a variety of incorrect models; the scores on these items indicate their inclusion in the instrument should be reconsidered.

Social semiotic discussions about the role played by representations in effective teaching and learning in areas such as physics have led to theoretical proposals that have a strong common thread: in order to acquire an appropriate understanding of a particular object of learning, access to the disciplinary relevance aspects in the representations used calls for the attainment of representational competence across a particular critical constellation of systematically used semiotic resources (which are referred to as modes, see more on this later). However, an affirming empirical investigation into the relationship between a particular object of learning and different representational formulations, particularly with large numbers of students, is missing in the literature, especially in the context of university-level physics education. To start to address, this research shortfall the positioning for this article is that such studies need to embrace the complexities of student thinking and application of knowledge. To achieve this, both factor and network analyses were used. Even though both approaches are grounded in different frameworks, for the task at hand, both approaches are useful for analyzing clustering dynamics within the responses of a large number of participants. Both also facilitate an exploration of how such clusters may relate to the semiotic resource formulation of a representation. The data were obtained from a questionnaire given to 1368 students drawn from 12 universities across 7 countries. The questionnaire deals with the refraction of light in introductory-level physics and involves asking students to give their best prediction of the relative visual positioning of images and objects in different semiotically constituted situations. The results of both approaches revealed no one-to-one relationship between a particular representational formulation and a particular cluster of student responses. The factor analysis used correct answer responses to reveal clusters that brought to the fore three different complexity levels in relation to representation formulation. The network analysis used all responses (correct and incorrect) to reveal three structural patterns. What is evident from the results of both analyses is that they confirm two broad conclusions that have emerged from social semiotic explorations dealing with representations in relation to attempting to optimize teaching and learning. The first, which is linked to a facilitating-awareness perspective, is that any given disciplinary visual representation can be expected to evoke a dispersed set of knowledge structures, which is referred to as their relevance structure. Thus, the network analysis results can be seen as presenting a unique starting point for studies aiming to identify such relevance structure. The second broad conclusion is that disciplinary visual representation can and often does contain more disciplinary-relevant aspects than what may be directly visible in a given representation. These are referred to as the appresent aspects that need to become part of the total awareness needed by someone to constitute an intended meaning. The results of the factor analysis can then also be seen to be a way of capturing all the disciplinary-relevant aspects (both present and appresent). Educational implications are discussed.