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.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] This review article provides an overview of research on the topic of gender equity in educational physics labs. As many institutions and instructors seek to evolve or transform physics lab learning, it is important that changes are made that improve equity for all students along multiple axes of identity, including gender. The studies highlighted in this review article describe the existence of complex gender-based differences, e.g., in opportunities to tinker with lab equipment, as well as differences in grades, conceptual understanding, and motivational outcomes across a broad range of lab curricula and contexts. The studies also illustrate and explore social interactions and structures that can impact students’ experiences based on their gender identities. Although there has been less scholarship focused on proposals to reduce gender-based inequities in labs, this review article also provides an overview of some relevant proposals as well as associated research results. This overview of research on gender equity in physics labs helps to make clear that future scholarship on equity in physics labs should adopt gender frameworks that allow researchers to transcend binary gender identities and student deficit framing of research results. Likewise, a case is made that future research is needed on equity along other axes of identity, as well as research that accounts for the intersectionality of different identities, in the physics lab context.

Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying the proposed model, as there are statistically equivalent models with distinct causal structures that equally well fit the data. Therefore, it is crucial for researchers using SEM to consider statistically equivalent models and to clarify why the proposed model is more accurate than the equivalent ones. However, many SEM studies did not explicitly address this important step, and no prior study in physics education research has delved into potential methods for distinguishing statistically equivalent models with differing causal structures. In this study, we use a physics identity model as an example to discuss the importance of considering statistically equivalent models and how other data can help to distinguish them. Previous research has identified three dimensions of physics identity: perceived recognition, self-efficacy, and interest. However, the relationships between these dimensions have not been thoroughly understood. In this paper, we specify a model with perceived recognition predicting self-efficacy and interest, which is inspired by individual interviews with students in physics courses to make physics learning environments equitable and inclusive. We test our model with fit indices and discuss its statistically equivalent models with different causal inferences among perceived recognition, self-efficacy, and interest. We then discuss potential experiments that could further empirically test the causal inferences underlying the models, aiding the refinement to a more accurate causal model for guiding educational improvements.

This small-scale, qualitative study uses educational design research to explore how focusing on argumentation may contribute to students’ learning to engage in inquiry independently. Understanding inquiry as the construction of a scientifically cogent argument in support of a claim may encourage students to develop personal reasons for adhering to scientific criteria and to use these with understanding rather than by rote. An understanding of the characteristics of scientific evidence may clarify why doing inquiry in specific ways is important, in addition to the how. On the basis of five design principles—derived from literature—that integrate argumentation in inquiry and enhance learning through practical activities, we developed a teaching-learning sequence of five activities aimed at developing inquiry knowledge in lower secondary school students. By means of observations of a grade 9 physics class ($N=23$, aged 14–15), students’ answers to worksheets, and self-reflection questions, we explored whether the design principles resulted in the intended students’ actions and attitudes. We studied whether the activities stimulated students to engage in argumentation and to develop the targeted inquiry knowledge. The focus on argumentation, specifically through critical evaluation of the quality of evidence, persuaded students to evaluate whether what they thought, said, or claimed was “scientifically” justifiable and convincing. They gradually uncovered key characteristics of scientific evidence, understandings of what counts as convincing in science, and why. Rather than adopting and practicing the traditional inquiry skills, students in these activities developed a cognitive need and readiness for learning such skills. Of their own accord, they used their gained insights to make deliberate decisions about collecting reliable and valid data and substantiating the reliability of their claims. This study contributes to our understanding of how to enable students to successfully engage in inquiry by extending the theoretical framework for argumentation toward teaching inquiry and by developing a tested educational approach derived from it.

When learning about the particulate nature of matter (PNM), students tend to attribute the same properties to both particles and to the substances they compose. It has been argued that this might be explained by them categorizing the wrong ontological category. To explain the relationships between submicroscopic and macroscopic levels of matter, students need to understand the concept of emergence. Building on prior work, the authors propose that crystal structures might be a suitable context for the introduction of the PNM. As there is a close connection between the behavior of the particles and the properties of crystals, students can learn the concept of emergence and therefore gain a deeper understanding of the PNM. This study investigates students’ learning about the PNM within the context of crystal structures following the methodological framework of design-based research. The aim of the study is the development of a prototypical teaching-learning sequence (TLS) on the PNM and to help developing local theories for teaching that subject. Throughout several cycles of designing and refining the TLS, a total of 40 interviews were conducted using the method of probing acceptance. Evaluative qualitative content analysis led to new insights into students’ thinking about the PNM and allowed for further development of the TLS. For example, we found that salt and snow crystals were a more effective learning context than a scanning tunnel microscopy image of graphite for students to come to understand the connection between macroscopic and submicroscopic levels of matter.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] Physics instructional labs have long been an area of pedagogical innovation and educational research. While current stakeholders in instructional labs are undoubtedly aware of the day’s concerns, reform efforts, and empirical research within lab settings, likely less apparent are the deep-rooted connections today’s deliberations have with those from multiple educational eras across the last 200 years. To this end, this paper provides a historical analysis of instructional laboratories in undergraduate physics education in the United States, with the goal of elucidating recurring themes in educational reform and research aimed at improving these learning environments. This work aims to synthesize the recursive themes present in the instructional laboratory landscape while summarizing how new research and pedagogical trends can promote further growth in this important learning environment. Through this analysis, commonly recurring themes are identified related to the longitudinal criticism of confirmatory, “cookbook” lab structures, the community’s skepticism of instructional labs’ abilities to reinforce lecture content, and the possibility of technological and societal obstructions which may implicitly limit innovative ideas, pedagogy, and research. By bringing to light these latent recursive themes, this work hopes to work toward helping break the cycle of criticism and stifled innovation alongside recent positive movements in evidence-based reforms and promising empirical research into student learning and engagement in instructional labs.

Self-efficacy is an important measure in science education as it is predictive of persistence and success in science, technology, engineering, and mathematics (STEM) courses and is an influential factor in students’ decisions to major in STEM fields. It is unclear what effect active teaching strategies have on students’ self-efficacy, which is typically measured with a pretest at the beginning of the semester and a post-test at the end of the semester. To better understand what happens to self-efficacy over the course of an actively taught physics class, in addition to the typical pretest and post-test, we used a reflective pretest. At the end of the semester, we asked students to reflect on their abilities at the beginning of the semester and we compared this “reflective” self-efficacy to both their presemester and postsemester self-efficacy. We found that students’ reflective self-efficacy was systematically lower than their self-efficacy at the beginning of the semester. Interviews reveal that discrepancies between presemester self-efficacy and reflective self-efficacy are the result of response-shift bias. Because of students’ limited experience with active learning environments, response-shift bias makes it difficult to accurately measure students’ change in self-efficacy over the semester of an actively taught physics course. We conclude that reflective pretests in combination with interviews can help educators and researchers understand if changes in self-efficacy are being masked by response-shift bias.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] National organizations set goals of engaging students in experimentation and authentic scientific reasoning while developing normative concepts to help them develop essential skills and competencies necessary to succeed in our rapidly changing world. One framework that meets these goals is the investigative science learning environment (ISLE) approach to teaching and learning physics. While studies have been conducted on student development of scientific abilities in ISLE-based classrooms, little is known about how formative assessment helps promote student growth in this setting. This paper presents on the findings from an empirical study on how the revision of written laboratory reports positively impacts first-year high school student development of scientific abilities in an ISLE-approach classroom. We argue that the opportunity to revise written work provides students with additional exposures that are necessary to support their scientific ability development. Furthermore, we explore positive correlations between student involvement in the collaborative writing process and attitudes regarding experimental physics.

Research in astronomy education has uncovered that many learners possess limited and fragmented understanding of stars. The corresponding misconceptions manifest in various areas such as star formation, size, the relationship between stars and planets, and their position in space and have been shown to persist across different age groups and educational settings, highlighting the need for further investigation. This paper presents the findings of an empirical study that examines secondary students’ views of stars and their evolution throughout their secondary school education. We designed and evaluated an instrument for assessing students’ views of stars in five domains (stars and the solar system, formation and evolution of stars, general properties and motion of stars, (sub-)stellar objects, as well as color and brightness). The instrument creation process involved several steps, including literature-based item development, an expert survey with faculty members, and a quantitative pilot study with a sample of $N=390$ secondary school and college students. This process led to a final version of the instrument that exhibits good psychometric properties. We used this new instrument in a cross-age study to investigate the alignment of secondary students’ ideas about stars with scientific views across different stages of secondary education. The sample of this main study comprised a total of $N=366$ learners, including 148 lower (aged 13–14 years), 151 middle (aged 15–16 years), and 67 upper (aged 17–18 years) secondary school students. Our study findings reveal a progressive development of students’ perspectives on star-related topics throughout their school education: Using analyses of variance and conducting pairwise post hoc comparisons, we observed a statistically significant increase in the proportion of responses aligning with scientific views across all aspects of stars examined in this study, as students progressed from lower secondary to upper secondary levels. We further report on widely held views of stars among our study participants that do not align with the scientific views and discuss the implications of our findings for both educational research and practice.

This paper presents the results of a confirmatory factor analysis on two self-efficacy scales designed to probe the self-efficacy of college-level introductory astronomy (Astro-101) students ($n=1381$) from 22 institutions across the United States of America and Canada. The students undertook a course based on similar curriculum materials, which involved students using robotic telescopes to support their learning of astronomical concepts covered in the “traditional” Astro-101 courses. Previous research by the authors using these self-efficacy scales within a pre-/post-test approach showed both high reliabilities and very high construct validities. However, the scale purporting to measure students’ self-efficacy in relation to their use of the astronomical instrumentation associated with online robotic telescopes was particularly skewed and required further investigation. This current study builds on the previous work and shows how a slight adjustment of the survey items presents an improved and robust scale for measuring self-efficacy.