Since 2022, artificial intelligence (AI) tools have become publicly available, thereby enabling physics teachers to employ them in a multitude of ways. The aim of this research is to evaluate the potential of AI in assisting physics teachers in lesson planning. The objective is to identify which cognitive demands of lesson planning can be carried out by the AI, therefore reducing the workload for teachers. To compare teachers with different backgrounds, we examine three groups: prospective, out-of-field, and experienced physics teachers. The participants planned a lesson on Newton’s third law using an AI tool. To analyze the participants’ lesson planning process, we employed evaluative qualitative content analysis. Each of the groups presented a different approach to lesson planning using AI. For example, out-of-field physics teachers focused on the physics content, while experienced physics teachers were more prone to asking how to adapt the learning materials to the students’ cognitive level. One of the key findings was that the AI tools considered the clarity of the learning objectives and phasing of the lessons without necessarily being prompted, in all three groups. Moreover, in general, the experienced physics teachers were more critical about using AI for lesson planning than the other two groups. The findings of this study might inform teacher professional development courses focused on the use of AI in physics education.

Upper-secondary education has been identified as a critical period for understanding young people’s (non)continuation in physics, as well as their broader trajectories into science, technology, engineering, and mathematics (STEM). This paper illuminates the longitudinal identity negotiations within upper secondary school physics and mathematics by focusing on two students, Kristi and Svea, who embody a paradox: Despite entering upper secondary school with strong science and mathematics identities and pursuing advanced coursework in both disciplines, they consistently refrained from considering futures in STEM. Central to our analysis is the concept of disciplinary and celebrated identities, which we integrate with perspectives from narrative psychology. This study draws on three rounds of semistructured narrative interviews with each student ($n=6$). The analysis was carried out by applying an in-depth reflexive thematic approach, focusing on how gendered identities and power dynamics shaped the young women’s negotiations within these masculine fields. The analysis showed how the two young women were presented with challenges in (i) aligning their interests and identity work with the disciplines’ norms and practices, and that facing such narrative disturbances was a gendered experience; (ii) bonding with the teachers enabled recognition, even though it involved applying narrow masculine strategies; and (iii) having to submit themselves to a “sink or swim” culture amplified their sense of inadequacy and unfitness for evolving strong disciplinary identities. Our findings show that these factors together discouraged the young women from maintaining sustainable narratives and negotiating positive choice considerations for a future in STEM. From a diversity perspective, our findings illustrate that inclusion is not only about access to participation but also about whose interests and ways of meaning-making are valued and legitimized within disciplinary practices. In doing so, this study advances research on diversity and inclusion in STEM by showing how disciplinary identities are shaped through sedimented practices of recognition over time. The implications call for rethinking participation to embrace and foster gender-inclusive teaching and learning environments, for example, through reforms in teacher training. Finally, we argue for moving away from deficit framings that describe young women as lacking confidence in physics and mathematics. Instead, feelings of not being “clever enough” should be understood as a product of the field itself, shaped by disciplinary practices in school physics and mathematics.

Large language models (LLMs) can now generate physics practice problems in real time, yet the educational value of these items hinges on rapid, reliable postgeneration vetting. In this exploratory study, we investigated which automated checks are both technically feasible and pedagogically meaningful when exercises are produced on demand within a chatbot interface. A cohort of 34 introductory-physics students generated and attempted 543 practice problems during exam preparation. Each item was labeled by an expert on a wide range of quality attributes and presented to the learners in pairs to record their preference. We then (i) benchmarked three commodity LLMs as “judges” against the expert labels, (ii) quantified which attributes predict student choice via random-forest models, and (iii) triangulated these results with free-form exit surveys. Only a small subset of the original metric items proved necessary to reliably address student preferences either directly or by proxy. The study demonstrates that scalable formative assessment does not require exhaustive scoring: a carefully curated core of structural and learner-visible checks is sufficient to ensure both technical soundness and user appeal. The findings provide a practical blueprint for deploying real-time, AI-generated practice in physics and other quantitative disciplines.

Diagnosing students’ mastery of physics concepts alongside their misconceptions is important for guiding effective physics instruction. Prior studies have analyzed distractor choices to identify misconceptions, and recent research has applied cognitive diagnostic modeling to obtain more fine-grained insights into student understanding. Building on this progress, we first proposed the two-stage multiple-choice deterministic inputs, noisy “and” gate with hierarchy (TS-MC-DINA-H) model, which estimates the probabilities of both conceptual mastery and misconceptions through option-level response coding. On the basis of this model, we developed a cognitive diagnostic assessment tool for forces and motion. An analysis of data from 492 high school students validated the assessment tool. Moreover, the diagnostic results revealed that students with identical total scores often exhibited different mastery-misconception profiles, thus suggesting that diagnostic information can complement traditional score-based evaluation. The key goal of this study is to provide a new approach for simultaneously diagnosing concept mastery and a wide range of misconceptions at the individual level. This dual diagnostic perspective provides a more comprehensive picture of student learning and offers practical implications for targeted instruction and personalized remediation.

Education literature recommends many different strategies for structuring student group work in labs. Many of these strategies, however, have not been sufficiently evaluated for their effects on student outcomes. One prior study suggested that sharing roles, rather than splitting roles, in lab groups can boost students’ physics interest and self-efficacy. Here, we expand upon this literature by evaluating the effects of a broader range of role distributions across several student outcomes in a large sample at two different institutions. We developed a survey item to probe the ways in which students distribute their roles in lab groups. The item asks for the percent of time in lab that students spent working together on lab roles (sharing), working alone on roles but rotating each session (rotating), and working alone in the same role throughout the semester (splitting). We employed hierarchical linear modeling to measure the effects of these role distributions on student critical thinking, self-efficacy, perceived agency, sense of belonging, and recognition based on survey items specific to physics lab contexts. We found that role distributions did not differentially impact student critical thinking. We also found that sharing roles tended to have a positive impact on student attitudes; splitting had a negative effect on attitudes; and rotating fell in between. Statistical significance varied across these attitudinal outcomes. Our findings invite further research and controlled studies to better understand the apparent benefits of sharing, rotating, and splitting roles in introductory physics labs.

We report on a profession-oriented course we offered at the University of Vienna, aimed at physics education teacher students. The course on theoretical classical mechanics was conceived and designed from the outset with the explicit goal of bridging the gap between the abstract, mathematical notions employed in theoretical physics and the concrete future needs of prospective teachers in their profession. We aimed to counter both the negative attitudes of students toward theoretical physics and the interrelated skepticism of professors regarding the students’ mathematical proficiency. Our main findings are that these goals can indeed be achieved through a careful selection of course material and the associated mathematical tools, through closely interwoven lecture topics and exercises, and through thorough planning according to principles for high-school teaching known from science education research. Establishing close connections between the material taught in the course and the students’ future occupation as high-school teachers has proven to be of utmost importance. This is possible without any sacrifice of mathematical rigor or the quality of physics presented.

Metarepresentational competence (MRC) is a theoretical framework that is used to analyze how people create and interact with external representations. Within quantum mechanics, problems may be approached or perceived differently based on the notation used (such as Dirac, Matrix, or Spinor notation) in the problem statement or by the person working on the problem. Semistructured interviews were conducted to present physics students with change of basis content problems in the context of quantum mechanics. These content questions were paired with MRC-focused follow-up questions for the explicit purpose of asking students about MRC concepts directly. Student statements were coded to confirm previously identified MRC concepts and to identify MRC concepts that are novel in this data. Our analysis of three student interviews demonstrates an array of MRC concepts, the usefulness of asking direct questions about MRC concepts as part of an interview, and solidifies MRC as a useful lens for investigating student thinking.

Tablets and smartphones provide compact and relatively inexpensive tools for measuring many physical quantities, and numerous applications of these “mobile devices as experimental tools” (MDETs) have been published over the last decade, covering a broad range of topics. According to the literature, MDETs can offer educational benefits by creating authentic, real-life contexts for physics learning, enhancing student motivation through the use of familiar technology, and supporting cognitive processes by providing multiple representations (videos, tables, and graphs) of physical phenomena. On the other hand, serious concerns have been raised about potential distractions and cognitive overload. Regarding these conflicting perspectives, few empirical studies on the impact of MDETs in real classroom settings of regular, full-length physics courses are available, and—to the best of our knowledge—none focus on a nonspecialized high-school target group. The purpose of this contribution is to present a study of a mechanics course in such a setting, addressing the tight curricular, material, and practical constraints inherent to it. A quasiexperimental pre- and post-test design comparing a treatment group using MDETs and a control group without (same content, lesson plan, and teacher) was used. The 19-week teaching sequence focused on conceptual learning and motivational outcomes (e.g., interest, self-concept, and curiosity), controlled by several predictor variables. Findings reveal substantial pre- and post-test learning gains for both groups (Cohen’s $d=0.9$) and small gains for perceived relation to reality ($d=0.29$). However, no significant differences between treatments were found, indicating that the use of MDETs does not outperform conventional approaches under the given constraints. On the other hand, no evidence of negative effects such as distraction or cognitive overload was observed. Moreover, little to no interactions with predictors such as gender or prior knowledge were found. In conclusion, MDETs show considerable potential as a viable and effective option for integrating technology into physics teaching, offering learning outcomes comparable to those of successful conventional teaching, but not better. Furthermore, no evidence of negative effects from distraction or cognitive overload was found, nor of strong interactions with gender and other predictors. The MDETs approach thus appears suitable for both sexes and different kinds of learners. This leads to suggestions for future utilization of MDETs as a component of physics education, which are discussed as potential perspectives.

How students use mathematics in their physics classes has been studied extensively in the physics education literature. In addition to specific mathematical methods in specific physics contexts, possible effects of more general “cultural” differences between the two disciplines have also been explored. However, there has been little examination of students’ own awareness and interpretations of these differences. We explore the undergraduate student experience of these cultural contrasts, and how students think they affect their learning. Through a qualitative exploratory study, including surveys and interviews with students double majoring in mathematics and physics (or majoring in one and minoring in the other), we investigate students’ awareness of distinct pedagogical approaches, mathematical justifications, and organization of concepts in mathematics versus physics classes. We find that students do recognize and navigate these cultural differences, often employing specific coping strategies. We identify specific themes from our data and comment on how students feel that these themes impact their learning. We suggest that increased faculty and student awareness of the identified differences in educational practice could facilitate knowledge transfer between mathematics and physics.

Understanding the parallelism between electric and magnetic phenomena can be challenging for students in introductory physics courses. This study compares students’ understanding of electric and magnetic fields and forces using parallel multiple-choice questions. Most of the electricity items were drawn from our previously published Test of Understanding of Electric Field, Force, and Flux (TU-E3F), while the magnetism items were newly developed as parallel questions based on the results of our earlier studies. The participants in the present study were 232 engineering students enrolled in a calculus-based electricity and magnetism course at a private university in the northeast of Mexico. We administered a five-item electricity test and a parallel five-item magnetism test to two independent groups of 116 students each and analyzed item difficulty and response patterns using chi-square tests. In this article, we compare students’ performance on parallel items and identify significant differences in the selection of the correct answers and incorrect answers. We also analyze the items by level of difficulty and identify the most frequent incorrect answers. Analysis of incorrect-answer categories highlighted recurrent difficulties with field representations, superposition, and “larger implies larger” reasoning, as well as interference between electric and magnetic ideas. Based on these results, we provide specific recommendations for improving instruction on these concepts. The analyses and recommendations can serve as valuable resources for physics education researchers and instructors teaching these topics. This study offers insights into how context influences students’ conceptual understanding, with implications for enhancing electricity and magnetism education.

Quantum information science (QIS) is a vast, diverse, and abstract field. In consequence, learners face many challenges. Science, technology, engineering, and mathematics education research has found that visualizations are valuable for aiding learners in complex matters. The conditions under which visualizations pose benefits are largely unexplored in QIS education. In this eye-tracking study, we examine the conditions under which the visualization of multiqubit systems with the dimensional circle notation (DCN) in addition to the mathematical symbolic Dirac notation (DN) is associated with a benefit for solving problems on the ubiquitously used hadamard gate operation, in terms of performance, extraneous cognitive load (ECL) and intrinsic cognitive load (ICL). We find that DCN increases performance and reduces cognitive load for participants with little experience in quantum physics. In addition, representational competence predicts reductions in ECL with DCN, but not performance or ICL. Analysis of the eye-tracking results indicates that task solvers with more transitions between DN and DCN benefit less from the visualization. We discuss the generalizability of the results and practical implications.

Introductory physics instruction emphasizes fluency with routine problem-solving procedures. However, even when applying these procedures, students frequently encounter challenges. This paper investigates how students navigate such moments when answering qualitative electricity and magnetism problems in interviews. Students frequently noted they had partially forgotten a key equation on a problem involving RC circuits. We present focal cases that show how coherence-seeking approaches were employed to overcome this problem-solving challenge. In attempts to reconstruct these equations, participants identified and chained qualitative dependencies and sought coherence between qualitative and mathematical understanding of the physical system. These moments of forgetting and reconstructing equations are a useful site for studying broader physics learning goals. While prior work investigates the use of mathematical sensemaking by examining how students respond to explicit prompts, our cases illustrate how students can spontaneously use mathematical sensemaking strategies. We reflect on these cases to consider how such adaptive reasoning can be a target for instruction and assessment.

Recent research indicates that the use of Multiple External Representations (MERs) has the potential to support learning, especially in complex scientific areas, such as quantum physics. In particular, the provision of informationally redundant external representations can have advantageous effects on learning outcomes. This is of special relevance for quantum education, where various external representations are available, and their effective use is recognized as crucial to student learning. However, research on the effects of informationally redundant external representations in quantum learning is limited. The present study aims to contribute to the development of effective learning materials by investigating the effects of informationally redundant external representations on students’ learning of quantum physics. Using a between-subjects design, 113 students were randomly assigned to one of four conditions. The control group learnt with a traditional multimedia learning unit on the behavior of a single photon in a Mach-Zehnder interferometer. The three intervention groups received redundant essential information in the Dirac formalism, the Bloch sphere, or both. The use of eye tracking enabled insight into the learning process, depending on the external representations provided. While the results indicate no effect of the study condition on learning outcomes (content knowledge and cognitive load), the analysis of visual behavior reveals decreased learning efficiency with the addition of the Bloch sphere to the multimedia learning unit. The results are discussed based on current insights into learning with MERs. The study emphasizes the need for careful instructional design to balance the associated cognitive load when learning with informationally redundant external representations.

The current work aims to better understand student course experiences for those who reported negative perceptions in introductory physics. We conducted semistructured interviews with 24 students who reported negative perceptions of their class on a screening survey. Participants were asked to share general reflections on challenges and successes they experienced, as well as their reflections on specific aspects of the course (e.g., experiences with instructors and peers). Interview transcripts were then coded to identify the types of experiences students reported, whether they were experienced as positive or negative, as well as the themes and features associated with those experiences. Experiences with the classroom, course structure, instructors, and exams were most frequently reported as negative. Experiences with peers, help-seeking, course curriculum, and specific learning activities were the most positive, although only experiences with peers had more positive than negative reports. We then used a resources vs demands framework [M. D. Seery, The biopsychosocial model of challenge and threat: Using the heart to measure the mind, Soc. Pers. Psychol. Compass. 7, 637 (2013)] to interpret the common instructional, cognitive, and motivational themes and features reported across multiple contexts. We discuss the implications of the results for theory and practice.

The ideal gas law is a fundamental concept in physics, yet students often struggle to develop a deep understanding of its principles. Despite its central role in secondary school physics and introductory college thermodynamics, research indicates that, even after instruction, students frequently retain fragmented knowledge structures and fail to achieve deep conceptual understanding. To address these challenges, this study develops a conceptual framework to model features of knowledge integration in students’ learning of the ideal gas law. The conceptual framework identifies essential concepts and their interrelationships, which are used to guide the development of a diagnostic tool that targets knowledge integration and deep learning. Administered to cohorts of Chinese high school and college students, the assessment revealed four distinct knowledge integration levels, including novice, lower-intermediate, upper-intermediate, and expertlike, through a combination of quantitative test results and qualitative interview data. Findings indicate that the conceptual framework can effectively capture features of integration in students’ knowledge structures, which can provide valuable insights for developing educational interventions that help students to establish critical connections within their knowledge structures and thereby deepen their understanding of the ideal gas law.

Analyzing and understanding the differences between novices and experts in domains such as physics has been proven to be important for enhancing competence acquisition in that field. This study investigates these differences through an expert-novice comparison by analyzing visual attention, cognitive strategies, and behavior during scientific diagram interpretation. A total of 23 participants (11 novices and 12 experts) completed 10 diagram-based tasks, while their eye movements and verbalizations were recorded. Experts outperformed novices across several dimensions: higher task success (86% vs 70%), significantly greater visual efficiency (23% vs 17%), and longer dwell times in task-relevant areas. Their shorter, more structured scan paths reflected goal-directed, conceptually driven strategies. In contrast, novices showed disoriented gaze behavior, frequent shifts between the diagram and task text, and relied on surface-level reverse-matching strategies, indicating higher extraneous cognitive load. Think-aloud data revealed qualitative reasoning differences: experts used precise, technical language and referenced diagrams accurately, while novices were vague, hesitant, and uncertain. Emotional expressions in novice protocols aligned with signs of cognitive overload. These findings support cognitive load theory, suggesting experts draw on schemas to manage intrinsic load, while novices struggle with element interactivity. Unexpectedly, some experts in the study showed novicelike behavior, whereas some novices exhibited patterns typically associated with expert performance. Novicelike experts often lacked recent exposure to diagram-related coursework. Conversely, some novices demonstrated efficient gaze patterns and structured scanning but still made conceptual errors. To contextualize human performance, two large language models (ChatGPT-4 and DeepSeek-R1) were tested on the same tasks. ChatGPT-4 reached an overall success rate of 50%, handling simple extractions but failing with visual relationships. DeepSeek-R1 performed poorly (10%), revealing current AI limitations in visual interpretation. These results underscore the uniquely human capacity for visual reasoning, schema activation, and metacognitive monitoring, which AI still lacks. The findings emphasize the critical role of graph literacy, representational competence, and cognitive strategy use in diagram interpretation. They highlight the need for explicit instructional interventions to help novices develop expertlike visual attention patterns and reasoning skills.

We investigated sustained departmental change catalyzed by three Departmental Action Teams (DATs) that worked on change projects independently following an initial period of external facilitation. Using qualitative analysis of interview data, we documented four main categories of change catalyzed by DATs, three categories of supports for change, and four categories of constraints on change. DATs accomplished a wide variety of sustained changes, and DAT members frequently leveraged their individual learning to benefit the work in departmental groups outside of their DAT. Change was documented at the levels of the individual, the group, and the organization (i.e., department or university), suggesting that the DAT model is capable of supporting organizational learning at all of these levels. Additionally, DATs successfully used levers of project prioritization and positional power to generate sustained change. DATs did not rely heavily on support outside of their departments to accomplish sustained change. This study provides insight into the mechanisms by which departmentally based change teams accomplish change in departmental cultures, practices, and processes influencing science, technology, engineering, and mathematics education.

Integrating problem-posing activities into instruction fosters students’ critical and creative thinking while deepening their understanding of problem solving. However, complementing the problem-solving process with direct mental processes such as recalling memorized information will make a limited contribution to meaningful learning. In this context, having students construct their own problems and use metacognitive strategies while doing so will increase their cognitive awareness in the problem-solving process. Drawing on this perspective, the present study investigates the processes through which preservice physics teachers pose nonroutine physics problems, focusing on the metacognitive strategies they employ and the pedagogical beliefs they hold during these processes. The study was conducted with 20 volunteer preservice physics teachers from different grade levels at a public university. Data were collected through a five-item problem-posing task, a metacognition-oriented reflection form, and a process-based opinion form, and were analyzed qualitatively. The findings indicated that nonroutine problem-posing performance generally increased with grade level and that preservice physics teachers actively used metacognitive strategies such as ease of learning, decision making about learning, experiencing a sense of knowing, and confidence in the answer during the problem-posing process. Nevertheless, participants faced difficulties, particularly in evaluating alternative solutions and engaging in creative thinking. Despite these challenges, they maintained a positive attitude toward problem-posing activities, highlighting the potential of nonroutine problem posing as an effective pedagogical tool in physics teacher education.

Learners often struggle to develop expandable mental models of polarization due to its abstract nature and the multitude of models used to describe it. A closer examination of the structure of mental models for linear polarization is therefore worthwhile in order to gain insight into mental abstraction processes. Existing research has largely documented misconceptions, leaving the underlying cognitive structures of mental models insufficiently explored. To address this gap, we employed the Fidelities Model of Conceptual Development (FMCD) to investigate learners’ cognitions of linear polarization. The framework, distinguishes two dimensions of students’ mental models: Gestalt, which refers to visual and structural representations, and Functionality, which captures how well a model explains underlying processes. The degrees to which these dimensions align with reality allow for a typification of learners’ reasoning patterns. We developed a test instrument based on established students’ mental models and validated it through expert review and think-aloud studies. In a cross-sectional survey with $N=178$ German secondary school and university students, confirmatory factor analysis confirmed a robust two-factor structure ($\mathrm{CFI}=0.96$, $\mathrm{RMSEA}=0.03$, $\mathrm{SRMR}=0.07$) with solid factor-reliability (${\omega }_{\text{FF}}=0.71$, ${\omega }_{\text{FG}}=0.81$). Descriptive results showed developmental trends: while secondary students often exhibited “dual” models combining both FG and FF, university students increasingly relied on functionally oriented reasoning. The findings validate the FMCD in the domain of polarization and provide a diagnostic tool that informs instructional design for supporting students’ conceptual development in optics.