Student learning in upper-division thermal physics has not been studied to the same extent as in other courses like electromagnetism and quantum mechanics. Studies addressing reasoning and learning at the graduate level are even more limited. In this study, we conducted think-aloud interviews with eight graduate students involving questions centered around a set of entropy related conceptual tasks, two of which are similar to tasks presented to undergraduates in other studies. We discuss patterns in student reasoning on each question then discuss themes that appeared across questions. We identify conceptual resources that students frequently used to reason about the interview tasks and compare them to prior work. We observed graduate students commonly thinking about entropy in relationship to a number of states, even in situations where such a connection was not directly relevant. Graduate students also frequently made direct associations between entropy and temperature, despite there being no general, explicit relationship between the two quantities. On the whole, graduate students demonstrated adaptability and metacognitive awareness in their approach to reasoning about entropy.

Sound educational policy recommendations require valid estimates of causal effects, but observational studies in physics education research sometimes have loosely specified causal hypotheses. The connections between the observational data and the explicit or implicit causal conclusions are sometimes misstated. The link between the causal conclusions reached and the policy recommendations made is also sometimes loose. Causal graphs are used to illustrate these issues in several papers from Physical Review Physics Education Research. For example, the core causal conclusion of one paper rests entirely on the choice of a causal direction although an unstated plausible alternative gives an exactly equal fit to the data.

Science knowledge is reflected in mental models that students tend to form when dealing with science phenomena. One way to identify students’ mental models about scientific concepts is the use of diagnostic tests (inventories). Even though several statistical approaches and tools intended for the analysis of such inventories’ results exist in the literature, there are certain inventories for which analysis might require the development of more convenient tools. Thus, there seems to be no simple way to handle the results of inventories whose items include different numbers of statements, the number of statements relating to the same mental model within an item is not fixed, and neutral distractors are possible. This exploratory study aims at meeting this challenge and suggests a relatively simple statistic $F_{2m}$ for estimating the mental model state of a subject or a group of subjects in the case of two mental models under consideration, providing a preliminary estimation of $F_{2m}$ consistency using the results of the sound concept inventory instrument.

There are studies of students’ understanding of the concept of the electric field, the magnetic field, and the use of the superposition principle that have contributed to the creation of both educational strategies and assessment tools. However, the difficulties of these two concepts have not been compared comprehensively. Therefore, this study aims to compare students’ conceptual understanding of electric and magnetic fields in questions regarding the field created by one source and the field produced by a system of two sources. We focus our study on students’ explanations about the magnitude and direction of the field and their application of the superposition principle in both contexts (electric and magnetic). We conducted this study with 322 engineering students in a Mexican university. We designed two versions of an open-ended questionnaire, one with the context of electricity and the other with magnetism. We created the questions using the parallelism between electricity and magnetism and used schematic representations with similar surface features to represent this parallelism. Analyzing the data through a phenomenographic approach, the students’ drawings and explanations gave insight into their understanding of the concept of field and the superposition principle application in the context of electricity and magnetism. We found that students have similar categories of understanding the concept of the electric and the magnetic field. In both contexts, there is an evident relationship between applying the principle of superposition and understanding the concept of field. We found that there is a greater tendency that a student correctly applies the superposition principle if that student has a robust representation of the field. We found evidence that students consistently merge two different representations (vector plots and field lines) in electricity and magnetism. We named this category of representation “hybrid vectors and field lines.” We also found that some students who draw hybrid representations of the field can still apply the superposition principle correctly. However, some conceptual understanding difficulties are dependent on the context: the known difficulty of confusion between forces and fields is more attached to the electricity context. The confusion between electricity and magnetism concepts is more relevant in the magnetism context. As in other literature, we found more evidence that the correct answer in multiple-choice questions may lead students who have mild difficulties (such as memorization and creating a hybrid representation) to choose a correct answer. We recommend that teachers and researchers of electricity and magnetism acknowledge the relationship between the conceptual understanding of the field and applying the superposition principle. We suggest that instructors be attentive to how they approach using representations of electric and magnetic fields.

Newton’s third law is one of the most important concepts learned early in introductory mechanics courses; however, ample studies have documented a wide range of students’ misconceptions and fragmented understandings of this concept that are difficult to change through traditional instruction. This research develops a conceptual framework model to investigate students’ understanding of Newton’s third law through the knowledge integration perspective. The conceptual framework is established with a central idea emphasizing forces as quantitative measures of physical interactions instead of using the common action-reaction language. Guided by the conceptual framework, assessment and interview results reveal that students’ concepts of Newton’s third law are fragmented without deep understanding. Specifically, three main issues within students’ understanding have been identified: (i) students have a disconnect between time order of events and causal reasoning, (ii) students rely on a memorized equal-and-opposite rule to identify interaction forces, and (iii) students directly link action-reaction language to the belief in a causal relation between the interaction forces. The framework is then applied to develop a new instruction intervention that explicitly targets the central idea of Newton’s third law. Results from pre- and post-testing show that the intervention is effective in helping students develop more integrated understandings of Newton’s third law. Overall, this study shows the potential benefits of applying the conceptual framework method to model student knowledge structures and guide assessment and instruction for promoting knowledge integration and deep learning.

An analysis of 1955 physics graduate students from 19 Ph.D. programs shows that undergraduate grade point average predicts graduate grades and Ph.D. completion more effectively than GRE scores. Students’ undergraduate GPA (UGPA) and GRE Physics (GRE-P) scores are small but statistically significant predictors of graduate course grades, while GRE quantitative and GRE verbal scores are not. We also find that males and females score equally well in their graduate coursework despite a statistically significant 18 percentile point gap in median GRE-P scores between genders. A counterfactual mediation analysis demonstrates that among admission metrics tested only UGPA is a significant predictor of overall Ph.D. completion, and that UGPA predicts Ph.D. completion indirectly through graduate grades. Thus UGPA measures traits linked to graduate course grades, which in turn predict graduate completion. Although GRE-P scores are not significantly associated with Ph.D. completion, our results suggest that any predictive effect they may have is also linked indirectly through graduate GPA. Overall our results indicate that among commonly used quantitative admissions metrics, UGPA offers the most insight into two important measures of graduate school success, while posing fewer concerns for equitable admissions practices.

The COVID-19 pandemic has made conducting in-person research a health risk for interviewers and participants. Near the start of the pandemic, many universities pivoted to emergency remote teaching where courses were delivered remotely in observance of safety guidelines. The safety guidelines also necessitated that research be done remotely. We designed a remote interview protocol for a computational physics based qualitative interview. Using Zoom’s features, we created an interview that allowed participants many modes of interacting with the interviewer and the interview task materials. We present the interview methods and evaluate the utility of remote interviews. We then generalize the experiences from designing and conducting remote interviews for contexts outside of computational physics and describe how task design choices were influenced by technology. We find that conducting interactive remote interviews can be an effective method for physics education researchers even outside of the pandemic.

This work describes the implementation of a hierarchical team model, the Integrated Peer Leadership Program (IPLP), in a calculus-based college introductory physics classroom. Using this model, in which students in the course engage with their peers throughout the semester, we observe a significant increase in the students’ likelihood of successfully completing the course. The model also reduces the gap between underrepresented minority (URM) and non-URM students. Learning gains using the IPLP format are improved as compared to previous data for traditional classes. The model transforms a traditional lecture style class into a student-centered class without additional time requirement or cost to the instructor or institution, and we anticipate that it will be portable to other large section introductory college science courses.

Concept inventories are commonly used tools in physics education research (PER) for evaluating teaching methods. Student responses to concept inventories have been studied using classical test theoretical methods such as factor analysis and network methods such as module analysis. The results of these studies have been used to evaluate the instruments and to find aggregate patterns that may be used to infer how students’ think about the concepts on the inventory. In this work, we apply modified model analysis using partial correlations, a network based method using partial correlations, to evaluate the Quantum Mechanics Concept Assessment (QMCA). The QMCA is designed to measure student understanding of upper-division quantum mechanics in both the spatial wave function and the spins contexts. This represents the first time a network-based analysis has been applied to an upper-division concept inventory. The modules we found are related to the structure of the instrument. There were two broad classes of modules: those that connected responses (either both correct or both incorrect) to isomorphic pairs questions written to probe the same concept in the spatial wave function and the spin contexts. The second class of modules were explain pairs, where the first question asked about a concept and the second question asked students to explain their choice, again either both correct or both incorrect. This structure resembles the structure of the Force Concept Inventory where there are a common correct and a common incorrect pair for many concepts, compared to the Force and Motion Conceptual Evaluation, which has larger and more varied communities reflecting a smaller number of topics.

With the adoption of instructional laboratories that require students to make their own decisions, there is a need to better understand students’ activities as they make sense of their data and decide how to proceed. In particular, understanding when students do not engage productively with unexpected data may provide insights into how to better support students in more open-ended labs. We examine video and audio data from groups within a lab session where students were expected to find data inconsistent with the predictions of two models. In prior work, we examined the actions of the four groups that productively grapple with this designed problem. Here, we analyze the engagement of the three groups that do not. We conducted three phases of analysis: (1) documenting large scale behaviors and time spent in on-topic discussion, (2) analyzing interactions with the teaching assistant, and (3) identifying students’ framing—their expectations for what is taking place—when they were discussing their data. Our phase 1 and 2 analyses show only minor differences between the groups that engaged with the problem and those that did not. Our phase 3 analysis demonstrated that the groups that did not engage with the problem framed the lab activity as about confirming a known result or as a series of hoops to jump through to fulfill assignment requirements. Implications for instruction include supporting teaching assistants to attend to students’ framing and agency within laboratory classrooms.

The rapid transition to remote teaching in the spring of 2020 posed particular challenges for laboratory courses, which often involve students working hands-on with equipment in collaborative environments. Replicating in-person experiments was especially challenging for advanced lab courses that utilize specialized apparatus, which could not be accessed by students at home. However, physics lab instructors employed a variety of creative strategies to overcome these barriers and provide students access to lab-like learning in a remote setting. We report on one advanced lab course that used the transition to remote teaching to completely redefine the course goals and transition from traditional prescriptive labs to more open-ended projects. We conduct a case study analysis, triangulating among several data sources—survey responses and interviews from both instructor and students—to construct an in-depth understanding of the remote course and how students experienced it. Although we cannot necessarily generalize the results of this analysis to the entire student experience in the course due to the student response rate, the feedback that the course did receive from both students and the instructor was overwhelmingly positive, and the instructors are planning to retain the open-ended projects when the course returns to an in-person format. We find that the new open-ended projects afforded students opportunities to make decisions and think deeply about their experiments, which students report as contributing to their enjoyment and satisfaction with the course. Students had mixed group work experiences, with some describing positive and meaningful interactions and others describing group work as a source of frustration and stress. Additionally, some students missed being able to work hands-on with equipment, and some reported a high workload that made the course stressful. We discuss these student experiences and provide implications for both in-person and remote lab courses.

Physics outreach programs provide a critical context for informal experiences that promote the transition from new student to contributing physicist. Prior studies have suggested a positive link between participation in informal physics outreach programs and the development of a student’s physics identity. In this study, we adopt a student-focused investigation to explore the effects of informal programs on dimensions of physics identity, sense of community, 21st century skill development, and motivation. We employed a mixed methods study combining a survey instrument (117 responses) and interviews (35) with current and former undergraduate and graduate students who participated in five programs through a physics and astronomy department at a large land-grant university. To examine interviews, we employed a framework based on situated learning theory, transformative learning theory, and the dynamic systems model of role identity. Our findings, based on self-reported data, show that students who facilitated informal physics programs positively developed their physics identity, experienced increased sense of belonging to the physics community, and developed 21st century career skills. Specifically, students reported positive benefits to their communication, teamwork and networking, and design skills. The benefits of these programs can be achieved by departments of any size without significant commitment of funds or changes to curriculum.

We investigated physics students’ behavior in a second-year laboratory by analyzing transcribed audio recordings of laboratory sessions. One student group was given both a problem and procedure and asked to analyze and explain their results. Another was provided with only the problem and asked to design and execute the experiment, interpret the data, and draw conclusions. These two approaches involved different levels of student inquiry and they have been described as guided and open inquiry, respectively. The latter gave students more opportunities to practice “designing experiments,” one of the six major learning outcomes in the recommendations for the undergraduate physics laboratory curriculum by the American Association of Physics Teachers. Qualitative analysis was performed of the audio transcripts to identify emergent themes and it was augmented by quantitative analysis for a richer understanding of student behavior. An important finding is that significant improvements can be made to undergraduate laboratories impacting student behavior by increasing the level of inquiry in laboratory experiments. This is most easily achieved by requiring students to design their own experimental procedures.

This study aims to examine the effectiveness of metacognitive scaffolding in different inquiry tasks related to optics. Two high school classes participated in this study. One class, the treatment group ($n=33$), which integrated metacognitive prompts into the simulation-based inquiry, was compared to the other class, the control group ($n=34$), which received only simulation-based inquiry. Students’ conceptual understanding, integrated science process skills, confidence judgment, and inquiry performance were measured using a multiple-choice pretest and post-test and worksheets. The results show that the students’ conceptual understanding and confidence judgments on conceptual understanding in both groups significantly increased from the pretest to the post-test. Incorporating metacognitive scaffolds into inquiry-based learning better facilitated the improvement of integrated science process skills as well as the confidence judgment on the process skills, especially in the more complex tasks. The metacognitive scaffolding could be applied to various inquiry activities to enhance students’ control of variables, data interpretation, and graph comprehension.

Despite the growing presence of students as partners (SAP) in education research and the overlap of goals with learning assistant (LA) programs, there is little research done on pedagogy- and curriculum-focused student partnerships that involve LAs. LAs have expertise as both teachers and learners, so why not leverage this expertise to improve the underlying structure and teaching philosophy of future offerings of a course? We intend to investigate this idea in the case of a flipped, introductory physics course at Michigan State University by conceptualizing its LA program as a model for enacting SAP using the communities of practice (COP) framework. Using an interpretivist case study approach, we found in this environment that (i) the LAs experienced a learning trajectory within P-Cubed that resembled attainment of central membership in a COP, (ii) the development of a specific practice among LAs resembled the evolution of practice in a community of practice, and (3) LAs have a strong level of influence over decision making on curriculum and pedagogy in P-Cubed in a way that is indicative of authentic student partnership. This input is particularly important for a specific type of partnership: curriculum design and pedagogic consultancy, which requires significant participation and say so from LAs. Reconceiving LA programs as student partnerships opens a path to incorporate students into and reinforce sustainable curriculum change.

Research in undergraduate physics and in K–12 science education has demonstrated challenges and successes in facilitating student engagement with reasoning practices associated with professional physicists. Here we focus on one important dimension of physics reasoning, using evidence to revise models. While this topic has been explored at the undergraduate level, less is known about younger students’ physics reasoning, especially within the context of modeling and model revision, where measurement tools are less emphasized and where evidence is often observational qualitative data. Here we examine 7th graders’ conversations about pieces of observational scientific evidence in their conceptual models of magnetism. We present a series of cases from a whole class discussion to illustrate students’ productive reasoning using evidence while revising, challenging, and testing their scientific models. These cases illustrate how students reason about evidence in the context of canonical and noncanonical models of magnetism, specifically when different pieces of evidence contradict each other and when running the model is inconclusive. The results capture a variety of complex ways evidence can be productively used in reasoning with models, and, more importantly, show that middle school students’ reasoning shares important similarities with more advanced physics reasoning, which can be leveraged when designing and building future instruction.

Access and performance in advanced high school physics have been persistently inequitable when considering student ethnicity and gender. This quasiexperimental, observational study examined access and performance of students in four Advanced Placement (AP) Physics courses in 2018–2019: AP Physics 1 ($N=150451$), AP Physics 2 ($N=20466$), AP Physics C Mechanics ($N=49951$), and AP Physics C Electricity & Magnetism ($N=21602$); this analysis utilized an intersectional lens of ethnicity and gender in identifying enrollment and performance disparities. Descriptive and inferential analyses were conducted to determine whether the distribution of student ethnicities and genders of students who took the examinations was similar to that of U.S. schools. Further analyses were conducted to determine whether achievement on AP Physics examinations varied by 14 unique intersectional groups characterized by gender and ethnicity. Results indicated that AP Physics 1 was a relatively accessible course, though enrollment disparities among genders, ethnicities, and intersectional groups grew as the AP Physics courses became more advanced with physics and/or calculus prerequisites or corequisites. There were large decreases in course enrollments from first- to second-year AP Physics courses, particularly for women who were also underrepresented ethnic minorities. In terms of performance, AP Physics 1 had the lowest overall weighted average, with the majority of students failing the examination. Women who were traditionally underrepresented ethnic minorities were found to have failure rates of over 80% on the AP Physics 1 examination, and failure rates near 50% for AP Physics 2 and the AP Physics C courses compared to nonminority men who had approximately half the failure rates. In most cases, men outperformed women who shared their ethnicities. These results present opportunities for physics education policy makers and researchers to design interventions for students in intersecting marginalized social groups, many of whom have disproportionately low representation and achievement in advanced high school physics, which occurs at a critical juncture in the physics pipeline.

Across the field of education research there has been an increased focus on the development, critique, and evaluation of statistical methods and data usage due to recently created, very large datasets and machine learning techniques. In physics education research (PER), this increased focus has recently been shown through the 2019 Physical Review PER Focused Collection examining quantitative methods in PER. Quantitative PER has provided strong arguments for reforming courses by including interactive engagement, demonstrated that students often move away from scientistlike views due to science education, and has injected robust assessment into the physics classroom via concept inventories. The work presented here examines the impact that machine learning may have on physics education research, presents a framework for the entire process including data management, model evaluation, and results communication, and demonstrates the utility of this framework through the analysis of two types of survey data.

We surveyed a national sample of United States physics faculty about the COVID-19 transition to online learning. Most faculty had 1–2 weeks to prepare and no experience with teaching online. They relied on department peers to discuss approaches and used lecture adaptations such as video conferencing rather than new curricular elements. Their responses were empathetic to the students’ situation, and 90% believed they were average or above at implementing online instruction. Faculty’s preference for local resources and existing methods suggests that in a crisis, strong network ties will dominate as information sources, with consequences for professional development and instructional change.