Teaching assistants have a very important role in physics education as they interact with students and guide them in different contexts. A multitude of research has focused on how to prepare teaching assistants to implement high-quality, research-based teaching techniques. Video clubs, i.e., working with a group of teachers to watch and discuss excerpts of videos recorded from their own teaching, is a novel approach to teaching assistant training that draws from teacher education. This study reports on the experiences of five physics teaching assistants as they participated in a semester long series of video clubs as a part of the implementation of a new introductory lab course. Data were collected through interviews ($N=5$). The interview data were analyzed through reflexive thematic analysis. Five themes for the experiences were constructed from the data. Participation in the video clubs enabled the teaching assistants to uptake teaching practices from each other and spurred a wish for more coplanning of teaching. There was tension in the experiences as some teaching assistants appreciated the positive feedback but others would have preferred more constructive feedback. As the teaching assistants’ experiences were positive, the use of video clubs in teaching assistant training warrants more research. This research could focus on, e.g., the type of feedback the teaching assistants receive in the video clubs.

Wave optics is a mandatory part of Croatian secondary school physics curriculum for students in the final year of secondary school (age 18–19). Many physics education research studies have shown that it is a difficult physics topic for both university and secondary school students. An inquiry-based teaching sequence on wave optics, designed for eight 45-min teaching periods, was developed by the authors. The sequence included four investigative students’ experiments on the topics of interference, diffraction, and polarization of light, as well as several teacher demonstrations. The experimental group included six classes of students from six different Croatian urban secondary schools, who underwent the teaching intervention with the new inquiry-based sequence on wave optics, whereas the control group consisted of six classes from the same schools, taught in a predominantly lecturing way. Both groups were post-tested with the same instrument, the Conceptual Survey on Wave Optics (CSWO), to evaluate the research hypothesis that the new sequence might improve students’ conceptual understanding better than the traditional teaching. The results of the experimental and control groups were analyzed and compared using the Rasch analysis. The results show that the experimental group outperformed the control group in four out of five conceptual areas probed by the CSWO, suggesting that the new inquiry-based teaching sequence may contribute to stronger development of secondary school students’ conceptual understanding of wave optics, especially concerning typical wave optics patterns, reasoning from experiments, and explaining basic wave optics phenomena. A questionnaire on attitudes toward the teaching intervention was administered to students and it was found that students generally liked the inquiry-based teaching intervention and expressed positive attitudes to interactive, experimental, and collaborative aspects of physics teaching. The results are very promising, but their generalization may be limited by the selection of the students, as well as by the short duration of the teaching intervention and the relatively small breadth of the covered topics.

Although researchers have extensively studied student conceptions of radioactivity, the conceptions held by preservice teachers on this subject are largely absent from the literature. We conducted a qualitative content analysis of problem-centered interviews with preservice teachers ($N=13$) to establish which conceptions are held by preservice teachers and to examine these conceptions’ structure in coordination classes. As has already been observed in students, some preservice teachers inadequately differentiate between radioactive matter and ionizing radiation and between fission and decay. We also observed that preservice teachers tend to describe the activation of materials due to ionizing radiation despite having previously denied an activation, thus showing that the conception of activation of materials can reemerge in particular framings. Within the interviews conducted, the concept of energy emerged as a central coordination class regarding radioactivity. This coordination class appeared across contexts and proved fruitful in explaining preservice teachers’ conceptions about radioactivity. We will use the results from this study to develop a teaching-learning laboratory for preservice teachers in which they can actively study high school students’ conceptions while reflecting on their own. In this way, these findings will contribute to improving the structure of nuclear physics courses at the university.

Previous research on student thinking about experimental measurement and uncertainty has primarily focused on students’ procedural reasoning: Given some data, what should students calculate or do next? This approach, however, cannot tell us what beliefs or conceptual understanding leads to students’ procedural decisions. To explore this relationship, we first need to understand the range of students’ beliefs and conceptual understanding of measurement. In this work, we explored students’ philosophical beliefs about the existence of a true value in experimental measurement. We distributed a survey to students from 12 universities in which we presented two viewpoints on the existence of a true definite position resulting from an experiment, asking participants to indicate which view they agreed with more and asking them to explain their choice. We found that participants, both students and experts, varied in their beliefs about the existence of a true definite position and discussed a range of concepts related to quantum mechanics and the experimental process to explain their answers, regardless of whether or not they agreed with the existence of a true value. From these results, we postulate that students who exhibit similar procedural reasoning may hold widely varying philosophical views about measurement. We recommend that future work investigates this potential relationship and whether and how instruction should attend to these philosophical views in addition to students’ procedural decisions.

As part of an effort to examine students’ mathematical sensemaking (MSM) in a spins-first quantum mechanics course during the transition from discrete (spin) to continuous (position) systems, students were asked to construct an eigenvalue equation for a one-dimensional position operator. A subset of responses took the general form of an eigenvalue equation written in Dirac notation. Symbolic blending, a combination of symbolic forms and conceptual blending, as well as a categorical framework for MSM, were used in the analysis. The data suggest two different symbolic forms for an eigenvalue equation that share a symbol template but have distinct conceptual schemata: A transformation that reproduces the original and to operate is to act. These symbolic forms, when blended with two sets of contextual knowledge, form the basis of three different interpretations of eigenvalue equations modeled here as conceptual blends. The analysis in this study serves as a novel example of, and preliminary evidence for, student engagement in sensemaking activities in the transition from discrete to continuous systems in a spins-first quantum mechanics course.

Instructor’s feedback plays a critical role in students’ development of conceptual understanding and reasoning skills. However, grading student written responses and providing personalized feedback can take a substantial amount of time, especially in large enrollment courses. In this study, we explore using GPT-3.5 to write feedback on students’ written responses to conceptual questions with prompt engineering and few-shot learning techniques. In stage I, we used a small portion ($n=20$) of the student responses on one conceptual question to iteratively train GPT to generate feedback. Four of the responses paired with human-written feedback were included in the prompt as examples for GPT. We tasked GPT to generate feedback for another 16 responses and refined the prompt through several iterations. In stage II, we gave four student researchers (one graduate and three undergraduate researchers) the 16 responses as well as two versions of feedback, one written by the authors and the other by GPT. Students were asked to rate the correctness and usefulness of each feedback and to indicate which one was generated by GPT. The results showed that students tended to rate the feedback by human and GPT equally on correctness, but they all rated the feedback by GPT as more useful. Additionally, the success rates of identifying GPT’s feedback were low, ranging from 0.1 to 0.6. In stage III, we tasked GPT to generate feedback for the rest of the students’ responses ($n=65$). The feedback messages were rated by four instructors based on the extent of modification needed if they were to give the feedback to students. All four instructors rated approximately 70% (ranging from 68% to 78%) of the feedback statements needing only minor or no modification. This study demonstrated the feasibility of using generative artificial intelligence (AI) as an assistant to generate feedback for student written responses with only a relatively small number of examples in the prompt. An AI assistant can be one of the solutions to substantially reduce time spent on grading student written responses.

This project aims to understand physics faculty responses to transitioning to online teaching during the COVID-19 pandemic. We surveyed 662 physics faculty from the United States following the Spring 2020 term; of these, 258 completed a follow-up survey after the Fall 2020 term. We used natural language processing to measure the sentiment scores of 364 Spring 2020 responses and another 134 Fall 2020 responses of physics faculty who completed an optional written prompt. Additionally, we determined the change in sentiment scores of the 100 individuals who responded to both surveys. These sentiment scores measured between $-1$ and 1 for completely negative and completely positive, respectively. Sentiment scores after Spring 2020 were slightly positive with a median value of 0.2347. The distribution of sentiment changes was approximately normally distributed with a mean centered near zero. Analysis suggests the average sentiment did not change from the initial to follow-up surveys. To identify major topics within the responses for both surveys, latent Dirichlet allocation analysis was applied to the data. The topic distribution for the initial survey is given as course modifications and technology, negative aspects of the transition—primarily with labs and cheating, exam and evaluation difficulties, and difficulties with student understanding. The topics were noticeably different in the follow-up survey with differences between Fall and Spring, cooperative learning strategies, strategies that worked in the remote space, and benefits of in-person labs.

Vector fields are a highly abstract physical concept that is often taught using visualizations. Although vector representations are particularly suitable for visualizing quantitative data, they are often confusing, especially when describing real fields such as magnetic and electric fields, as the vector arrows can overlap. The present study investigates vector understanding at the end of secondary education. In particular, the extent to which the geometry of the field can be derived from conventional unit vector representations and representations with centered unit vectors was examined. To support this understanding, two exercises were compared. The unirepresentational exercise argued within the conventional unit vector representation, while the multirepresentational exercise attempted to support the link between centered and conventional unit vectors. The results show that almost all test subjects solved the items for generating vector representations correctly, but significant difficulties were encountered in interpreting vector representations. Drawing and interpreting vector representations therefore appear to be different skills that should be practiced intensively and in an integrated way. Various problems could be identified when interpreting vector representations. For example, the number of vectors is often erroneously used to estimate the strength of the field, although more vectors per surface element actually only increase the resolution of the representation. Here, however, the results suggest that the longitudinal density and the transverse density of the drawn vectors are perceived differently by the learners. Furthermore, the learners recognized the field’s geometry much more readily from centered unit vectors than from conventional unit vectors. Errors occur especially when interpreting the geometry of conventional unit vector representations of rotational fields and fields containing both sources and sinks while the geometries of fields containing only sinks were interpreted quite well. The comparison between the two training exercises showed that a promising approach to deepen students’ understanding would be to use an exercise that contrasts conventional and centered unit vector representations and explains how to translate from one representation to the other, rather than describing the main elements of only a single representation. Finally, based on the results of the study, we propose a strategy for teaching vector representations in schools. Given the significantly improved readability of the representation with centered unit vectors, the results even raise the question of whether this type of representation could possibly replace the conventional representation in textbooks and learning materials in the future.

Machine learning models were constructed to predict student performance in an introductory mechanics class at a large land-grant university in the United States using data from 2061 students. Students were classified as either being at risk of failing the course (earning a D or F) or not at risk (earning an A, B, or C). The models focused on variables available in the first few weeks of the class which could potentially allow for early interventions to help at-risk students. Multiple types of variables were used in the model: in-class variables (average homework and clicker quiz scores), institutional variables [college grade point average (GPA)], and noncognitive variables (self-efficacy). The substantial imbalance between the pass and fail rates of the course, with only about 10% of students failing, required modification to the machine learning algorithms. Decision threshold tuning and upsampling were successful in improving performance for at-risk students. Logistic regression combined with a decision threshold tuned to maximize balanced accuracy yielded the strongest classifier, with a DF accuracy of 83% and an ABC accuracy of 81%. Measures of variable importance involving changes in balanced accuracy identified homework grades, clicker grades, college GPA, and the fraction of college classes successfully completed as the most important variables in predicting success in introductory physics. Noncognitive variables added little predictive power to the models. Classification models with performance near the best-performing models using the full set of variables could be constructed with very few variables (homework average, clicker scores, and college GPA) using straightforward to implement algorithms, suggesting the application of these technologies may be fairly easy to include in many physics classes.

In physics education, a number of studies have developed assessments of teachers’ knowledge of student understanding (KSU) of specific physics concepts with modified versions of existing concept inventories, in which teachers were asked to predict the popular incorrect answers from students. The results provide useful but indirect information to make inferences about teachers’ knowledge of the misconceptions that students may be using in answering the questions. To improve the assessment of teachers’ KSU, a new instrument is developed using a three-tier item design. The items were adapted from 17 questions from the Force Concept Inventory on force and motion. Each item was designed in three tiers, with tier 1 asking for teachers’ own answers to the question to test their content knowledge, tier 2 asking for teachers’ predictions of popular students’ incorrect answers, and tier 3 asking for teachers’ explanations of students’ incorrect answers in an open-ended form. The three-tier design captures teachers’ content knowledge, predictions, and explanations in a single item to allow explicit measures of teachers’ own content knowledge and their KSU on students’ misconceptions. The instrument was validated with preservice physics teachers, who were master-level graduate students in a normal university in China. The assessment results also suggest that the preservice teachers’ KSU of force and motion was only moderately developed, and their content knowledge was uncorrelated with their KSU. In addition, a four-level progression scale of KSU was also developed, which categorized the preservice teachers into five proficiency groups.

Over the course of the introductory calculus-based physics course, students are often expected to build conceptual understanding and develop and refine skills in problem solving and qualitative inferential reasoning. Many of the research-based materials developed over the past 30 years by the physics education research community use sequences of scaffolded questions to step students through a qualitative inferential reasoning chain. It is often tacitly assumed that, in addition to building conceptual understanding, such materials improve qualitative reasoning skills. However, clear documentation of the impact of such materials on qualitative reasoning skills is critical. New methodologies are needed to better study reasoning processes and to disentangle, to the extent possible, processes related to physics content from processes general to all human reasoning. As a result, we have employed network analysis methodologies to examine student responses to reasoning-related tasks in order to gain deeper insight into the nature of student reasoning in physics. In this paper, we show that network analysis metrics are both interpretable and valuable when applied to student reasoning data generated from reasoning chain construction tasks. We also demonstrate that documentation of improvements in the articulation of specific lines of reasoning can be obtained from a network analysis of responses to reasoning chain construction tasks.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] We report on a study of the effects of laboratory activities that model fictitious laws of physics in a virtual reality environment on (i) students’ epistemology about the role of experimental physics in class and in the world; (ii) students’ self-efficacy; and (iii) the quality of student engagement with the lab activities. We create opportunities for students to practice physics as a means of creating and validating new knowledge by simulating real and fictitious physics in virtual reality (VR). This approach seeks to steer students away from a confirmation mindset in labs by eliminating any form of prior or outside models to confirm. We refer to the activities using this approach as Novel Observations in Mixed Reality (NOMR) labs. We examined NOMR’s effects in 100-level and 200-level undergraduate courses. Using pre-post measurements, we find that after NOMR labs, students in both populations were more expertlike in their epistemology about experimental physics and held stronger self-efficacy about their abilities to do the kinds of things experimental physicists do. Through the lens of the psychological theory of flow, we found that students engage as productively with NOMR labs as with traditional hands-on labs. This engagement persisted after the novelty of VR in the classroom wore off, suggesting that these effects were due to the pedagogical design rather than the medium of the intervention. We conclude that these NOMR labs offer an approach to physics laboratory instruction that centers the development of students’ understanding of and comfort with the authentic practice of science.

As a result of the pandemic, many physics courses moved online. Alongside, the popularity of Internet-based problem-solving sites and forums rose. With the emergence of large language models, another shift occurred. One year into the public availability of these models, how has online help-seeking behavior among introductory physics students changed, and what is the effect of different patterns of online resource usage? In a mixed-method approach, we investigate student choices and their impact on assessment components of an online introductory physics course for scientists and engineers. We find that students still mostly rely on traditional Internet resources and that their usage strongly influences the outcome of low-stake unsupervised quizzes. We empirically found distinct clusters of help-seeking and resource-usage patterns among the students; the impact of students’ cluster membership on the supervised assessment components of the course, however, is nonsignificant.

Reforming the professionalization experiences of future faculty members, including their undergraduate experience, provides a possible means to create scalable change in higher education. However, this requires an understanding of where faculty undergraduate training occurs. We analyze data from 7748 tenure-line faculty members across 611 U.S. physics departments, including their undergraduate alma mater and their employer university. The resulting undergraduate professionalization network reveals a prestige hierarchy similar in strength to those previously found in hiring networks at the Ph.D. level, indicating that the road to faculty jobs begins during undergraduate admissions. Furthermore, 42% of physics faculty members earned their undergraduate degrees from institutions outside of the United States. These results reinforce the importance of institutional prestige in academia and offer a potential strategy for driving systemic change.

We investigate learning difficulties among second-year students in electromagnetism courses when they apply Ampère-Maxwell’s law. Using phenomenography, we analyzed written answers from 65 undergraduate physics students to four questions on Ampère’s and Ampère-Maxwell’s laws. We complemented our research by interviewing 12 students. To design the questionnaire, we ran an epistemological analysis of classical electromagnetism which helped us to identify a set of key essential concepts to understand this theory, guided the definition of learning objectives, and drew up the questions. The results revealed that the students found it hard to recognize the validity framework from Ampère’s law and to apply Ampère-Maxwell’s law. They face particular difficulties to recognize the appearance of the displacement current and the relationship between the circulation of the magnetic field and an electric field that is variable over time.

Photovoice is a type of participatory action research in which individuals document their experiences through photography. Through the taking, captioning, and reflecting on photographs that they have taken, participants are able to affect change within their communities. Participants also take part in an interview or focus group about their photos at the end of the photovoice process in which they determine themes that appear in their photos, allowing them to participate in the research being done. We used the photovoice methodology in a small, project-based, upper-division, physics capstone course at the University of Colorado Boulder, in which students worked on an authentic industry project in partnership with a company in the quantum industry. As an example of the types of research results and benefits one could obtain using photovoice, we present a discussion of how we implemented the photovoice process within this course and present some of our results, including students’ experiences with the photovoice process. Photovoice may be particularly useful in understanding new, unique courses, as it allows students to co-create research that highlights ideas about the course that researchers would not know to ask about in more traditional research methodologies such as reflection questions.

We present two studies to investigate the extent to which attending a planetarium presentation increases secondary school students’ understanding of the apparent motion of the Sun and stars. In the first study, we used the Apparent Motion of Sun and Stars (AMoSS) test in a pretest/post-test/retention test setting to measure learning gains and improved insight of 404 students (16- to 17-year-olds) after attending a classical planetarium presentation at the Brussels Planetarium. The AMoSS test is a questionnaire on the daily and yearly apparent motion and the observer’s position. It consists of six multiple-choice questions about the Sun and six similar multiple-choice questions about the stars. We asked the students to explain their choices. The learning gains are rather small and the scores improve more on the Sun questions than on the star questions. This difference is largest for questions about the yearly apparent motion. We found that this is due to the fact that many students copy their knowledge about the Sun to the stars. Based on the results of this survey, we developed a new planetarium presentation with particular attention to the use of the celestial sphere model. We also developed a learning module that prepares students at school for this planetarium presentation. In a second study, we measured the learning gains after attending this new planetarium presentation among 339 students, also 16- to 17-year-olds. Some school groups had worked through the preparatory learning module at school and others had not. We find that the learning gains on the star questions are significantly higher than in the first study, due to better scores on the yearly apparent motion questions. In this regard, it is notable that we do not see significant differences between those students who prepared the presentation at school and those who did not. In the second study, the number of students who answer all questions correctly after attending the planetarium presentation or working through the learning module increases, but only significantly for those students who worked through the learning module at school.

While many previous studies have indicated that encouraging a growth mindset can improve student learning outcomes, this conclusion’s applicability to college-level astronomy classrooms remains poorly understood owing to the variation in students’ overall and domain-specific learning attitudes. To address this, we surveyed undergraduate students in an introductory astronomy class about their attitudes towards learning astronomy over the course of five semesters. Overall, students felt an affinity for astronomy, felt moderately competent, perceived astronomy to be intermediate in terms of difficulty, and agreed strongly with standard statements reflecting a “growth mindset,” i.e., the belief that intelligence is malleable rather than fixed from birth. Their responses were stable over the course of the semester and did not appear to depend strongly on student demographics. The unexpected start of the COVID-19 pandemic and the associated shift to all-virtual learning correlated with a drop in their affinity for astronomy, a small decrease in their perceived competence, and an increase in the perceived difficulty of the topic. Their overall learning mindset showed negligible change during this time, emphasizing the stability of their belief in a growth mindset as compared to other measured learning attitudes. However, more nuanced questions about their behaviors and interpretations in the classroom, about how they felt “in the moment,” and about what factors were most important for their success in the class revealed significantly lower alignment with a growth mindset. This suggests that while introductory astronomy students may believe that they have a growth mindset, this mindset is not necessarily reflected in their self-reported classroom behaviors or measured responses to actual learning challenges.