Course-Based Undergraduate Research Experiences (CUREs) have been shown to provide students with a variety of learning benefits including better conceptual understanding, improved critical thinking and data literacy skills, and increased interest in pursuing scientific careers. Additionally, CUREs provide students with opportunities to participate in authentic research experiences that have a broader impact outside of the classroom. Despite the numerous benefits, the field of astronomy has lagged behind disciplines like biology and chemistry when it comes to including CUREs in the curriculum. Not limited to astronomy, however, is the lack of research opportunities and courses offered to students enrolled in undergraduate degree programs online. In the Fall of 2020, Arizona State University (ASU) introduced the nation’s first online bachelor’s degree program in astronomy and planetary sciences (APS). To make research accessible to a more diverse population of learners, it is imperative that students in this program have access to the same opportunities to participate in authentic research as those in the parallel in-person program. In this work, we describe the development, implementation, and assessment of a fully online CURE for astronomy majors as part of the APS program. We conducted a mixed methods analysis consisting of a Likert style survey administered pre- and postcourse as well as student interviews at the conclusion of the semester. Survey results from the course’s first two offerings ($N=24$) indicated that students’ research self-efficacy and science identity both improved. An exoplanet-specific multiple-choice assessment ($N=26$) showed statistically significant improvements in conceptual understanding postcourse. Additionally, student interview ($N=11$) responses relayed that students felt a stronger sense of belonging to both ASU and the larger astronomy community after participation in the course. The results from this study are encouraging and suggest that student participation in this online CURE led to similar improvements across a variety of outcomes previously identified in studies of in-person CUREs spanning multiple disciplines.

Social learning, the ability to perceive, interpret, and assess the behavior of one’s peers, is crucial for forming meaningful relationships and succeeding in various learning environments. Yet, the rise of online and hybrid settings poses new challenges to socialization. Here, we study the social interactions among 191 high school physics students in Chile, comparing online and hybrid classrooms that were assigned in the COVID-19 pandemic context. We found that students in hybrid settings were more connected and more likely to form casual relationships outside their immediate friend groups, which allowed them to gather new information from diverse sources. Along the same lines, in online classrooms, students who excelled in physics occupied more central positions in social networks. This trend was not evident in hybrid settings, suggesting that when social cues are limited, academic performance gains greater importance in establishing social hierarchies and potentially limiting access to diverse information. Our study highlights the importance of social interactions in educational contexts and raises questions about the impact of relational inaccessibility on virtual learning.

To explore the self-efficacy and physics identity of students across various physics career trajectories, as well as to delve into the motivations of male and female students in choosing to major in physics and pursue teaching, we conducted a survey within the Department of Physics at East China Normal University. This institution offers undergraduate physics programs with both teaching and nonteaching trajectories. The teaching trajectory caters to preservice teachers who will receive certifications to teach physics at the middle or high school level upon completing their degree. A total of 266 undergraduate students participated in the survey, ensuring a balanced representation of both genders and both teaching and nonteaching trajectories. A gender disparity was evident for self-efficacy, while no such gap emerged for physics identity. Conversely, distinct disparities emerged between different career trajectories, with significant differences observed in physics identity between students in the teaching and nonteaching trajectories. A predominant motivation for majoring in physics was “interest,” and the top two reasons for choosing the teaching career were consistent for both genders, with women assigning higher priority to job security.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] This study investigated the development of four new novice graduate teaching assistants (GTAs) and one nontenure track (NTT) faculty member assigned to teach an introductory physics laboratory course based on the investigative science learning environment (ISLE) approach. We describe the training that these instructors received and the progress that they made over their first semester of instruction. We used classroom observations scored using the Danielson Framework and the Reform Teaching Observation Protocol (RTOP) to assess each instructor’s teaching multiple times throughout the semester. All four GTAs demonstrated improvement of various degrees while the NTT did not. Classroom observations and debriefs improved the GTAs’ teaching and were used to tailor weekly training meetings to their needs. Our results suggest that new instructor training should feature specific, tangible teaching actions which new instructors can implement easily in their own classrooms. When these actions directly address issues that instructors have had, as indicated by conversations with the instructors and classroom observations, they were more likely to be adopted and have a noticeable effect on the quality of teaching.

The increasing and diversifying student enrollments in introductory physics courses make reliable, valid, and usable instruments for measuring student skills and gains ever more important. In introductory physics, in addition to teaching facts about mechanics, we also seek to teach our students the skills of “thinking like a physicist,” or expertise in and intuition for physical problem solving. How and when these expert, intuitive problem-solving skills emerge during a STEM education, or what the most effective teaching methods might be, are not certain. A facile survey to measure students’ “physics-thinking” skills in a pretest and post-test format is therefore desirable to measure and evaluate different pedagogical approaches. Prior investigators codified these skills as “epistemic games” (e.g., order-of-magnitude estimation, evaluating extreme cases) and developed and validated the math epistemic games survey (MEGS) to measure students’ ability to employ these techniques. The original survey instrument is reliable and valid but has drawbacks in its length and in students’ ability to recall questions between administrations. We employed factor analysis to split the MEGS into two mutually exclusive subtests and measured them to be equivalently reliable and valid as the full-length MEGS as originally formulated. The “split MEGS” is well suited for use as a pretest and post-test instrument to measure gains in expertise in problem solving in introductory physics courses.

Course-based undergraduate research experiences (CUREs) have emerged as a promising approach to enhance undergraduate STEM education by engaging students in authentic discovery. CUREs integrate genuine research projects into undergraduate courses, providing students with a real research experience while earning academic credit. While CUREs offer similar benefits to traditional research experiences, they have the advantage of reaching a larger student population and being accessible to all enrolled students. In this study, we assess the outcomes of the first reported large-enrollment physics CURE within an introductory physics laboratory. One of the primary learning objectives of this CURE, which took place at the University of Colorado Boulder from 2020 to 2021, was to foster the development of more expertlike attitude and beliefs about experimental physics among the students. To evaluate the impact of the CURE along this dimension, we employed the Colorado Learning Attitudes about Science Survey for Experimental Physics (E-CLASS). Precourse and postcourse E-CLASS responses were collected from the CURE participants and compared with data from 363 other first-year physics labs, representing over 20 000 students. We found that students enrolled in the C-PhLARE CURE led to significantly higher scores on many of the E-CLASS items, even when controlling for precourse scores, students’ majors, and students’ genders. In particular, we observed that the C-PhLARE CURE had a significant effect on many of the E-CLASS items aligned with the objectives of the course; notably, students had more expertlike views in areas such as communicating scientific findings to peers, understandings of authentic research practices, and students’ belief in their own research capabilities. Additionally, we found no statistically significant negative impacts on any of the E-CLASS items as compared to the effects of other first-year physics labs. These results demonstrate the efficacy of this CURE in impacting students’ views of experimental physics.

Generative AI technologies such as large language models show novel potential to enhance educational research. For example, generative large language models were shown to be capable of solving quantitative reasoning tasks in physics and concept tests such as the Force Concept Inventory (FCI). Given the importance of such concept inventories for physics education research, and the challenges in developing them such as field testing with representative populations, this study seeks to examine to what extent a generative large language model could be utilized to generate a synthetic dataset for the FCI that exhibits content-related variability in responses. We use the recently introduced ChatGPT based on the GPT 4 generative large language model and investigate to what extent ChatGPT could solve the FCI accurately (RQ1) and could be prompted to solve the FCI as if it were a student belonging to a different cohort (RQ2). Furthermore, we study, to what extent ChatGPT could be prompted to solve the FCI as if it were a student having a different force- and mechanics-related preconception (RQ3). In alignment with other research, we found that ChatGPT could accurately solve the FCI. We furthermore found that prompting ChatGPT to respond to the inventory as if it belonged to a different cohort yielded no variance in responses, however, responding as if it had a certain preconception introduced much variance in responses that approximate real human responses on the FCI in some regards.

Much of physics involves the construction and interpretation of equations. Research on physics students’ understanding and application of mathematics has employed Sherin’s symbolic forms or Fauconnier and Turner’s conceptual blending as analytical frameworks. However, previous symbolic forms analyses have commonly treated students’ in-context understanding as their conceptual schema, which was designed to represent the acontextual, mathematical justification of the symbol template (structure of the expression). Furthermore, most conceptual blending analyses in this area have not included a generic space to specify the underlying structure of a math-physics blend. We describe a conceptual blending model for equation construction and interpretation, which we call symbolic blending, that incorporates the components of symbolic forms with the conceptual schema as the generic space that structures the blend of a symbol template space with a contextual input space. This combination complements symbolic forms analysis with contextual meaning and provides an underlying structure for the analysis of student understanding of equations as a conceptual blend. We present this model in the context of student construction of non-Cartesian differential length vectors. We illustrate the affordances of such a model within this context and expand this approach to other contexts within our research. The model further allows us to reinterpret and extend literature that has used either symbolic forms or conceptual blending.

At large institutions of higher education, students frequently have a choice whether to attend the introductory physics sequence asynchronously online, on-site in a traditional lecture setting, or in a reformed studio setting. In this study, we investigate how these different settings are correlated with measures of self-efficacy, interest in physics, and success in subsequent physics and engineering courses, which have the introductory physics sequence as prerequisites. As previous research indicates, some of these measures may depend on gender. We found that the course setting had no significant correlation with the grade in subsequent courses, but that studio settings gave students the feeling of being better prepared, particularly for subsequent courses that included laboratory or recitation components. We also found that gender was correlated with measures of interest in physics, where female students expressed significantly less interest in the subject, regardless of course setting.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] Uncertainty is an important concept in physics laboratory instruction. However, little work has examined how students reason about uncertainty beyond the introductory (intro) level. In this work we aimed to compare intro and beyond-intro students’ ideas about uncertainty. We administered a survey to students at 10 different universities with questions probing procedural reasoning about measurement, student-identified sources of uncertainty, and predictive reasoning about data distributions. We found that intro and beyond-intro students answered similarly on questions where intro students already exhibited expert-level reasoning, such as in comparing two data sets with the same mean but different spreads, identifying limitations in an experimental setup, and predicting how a data distribution would change if more data were collected. For other questions, beyond-intro students generally exhibited more expertlike reasoning than intro students, such as when determining whether two sets of data agree, identifying principles of measurement that contribute to spread, and predicting how a data distribution would change if better data were collected. Neither differences in institutions, student majors, lab courses taken, nor research experience were able to fully explain the variability between intro and beyond-intro student responses. These results call for further research to better understand how students’ ideas about uncertainty develop beyond the intro level.

Understanding measurement uncertainty is crucial in experimental physics, as it enables accurate and reliable measurements, facilitates comparison between measurements, and aids in designing experiments. Consequently, measurement uncertainty has emerged as a critical learning goal for many introductory physics labs. Here, we explore the impact of a recently transformed introductory physics lab at the University of Colorado Boulder on student understanding and interpretation of measurement uncertainty. The transformed course was explicitly designed to prioritize understanding measurement uncertainties as a learning goal and replaced verification labs with measurements where students could not predict the outcomes in advance. We used the physics measurement questionnaire to assess changes in student reasoning about measurement uncertainty at the beginning and end of the semester. Using a subparadigm coding scheme, we assessed different types of prevalent student reasoning and observed for trends in reasoning surrounding measurement uncertainty from the beginning to end of the lab course. Clustering algorithms were utilized to categorize student reasoning and compare these pre- and postsurvey responses. This analysis offers valuable insights into students’ reasoning about measurement uncertainty, including the diversity of initial reasoning clusters and the narrowing of reasoning elements into primarily more expertlike responses after the transformed course. However, challenges were observed in transitioning students from certain clusters, especially those that exhibited brevity in their presurvey responses. Overall, the findings reveal the potential for targeted interventions to deepen these students’ understanding of measurement uncertainty in experimental physics and underscore the significance of evidence-based instructional strategies in physics labs for improving student learning outcomes.

In this study, a conceptual framework of measurement uncertainty was developed and used to guide the development of a multiple-choice concept test for the assessment of students’ knowledge integration in learning measurement uncertainty. Based on assessment data and interview results, students were identified into three levels of knowledge integration including novice, intermediate, and expertlike. The reasoning pathways of students at different levels revealed a progression of reasoning from a rudimentary surface level to a deep understanding that can be mapped in the conceptual framework. This work demonstrates the possibility of identifying a quantitative categorization scheme to model knowledge integration as well as its utility in teaching and learning. Overall, the assessments and interviews revealed common and persistent difficulties in students’ understanding of measurement uncertainty. In addition, students at different levels of knowledge integration demonstrate unique types of knowledge states that can be represented in the conceptual framework, making it a useful tool for analyzing different reasoning pathways and knowledge structures.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] Quantum mechanics is a field often considered very mathematical, abstract, and unintuitive. One way some instructors are hoping to help familiarize their students with these complex topics is to have the students see quantum effects in experiments in undergraduate instructional labs. Here, we present results from an interview study about what it means to both instructors and students to see quantum effects in experiments. We focus on a popular set of quantum optics experiments and find that students believe they are observing quantum effects and achieving related learning goals by working with these experiments. Although it is not possible to see the quantum phenomena directly with their eyes, students point out different aspects of the experiments that contribute to them observing quantum effects. This often includes seeing the experimental results, sometimes in conjunction with interacting with or understanding part of the experiment. There is additional variation across student achievement of the various related learning goals, ranging from many of the students being excited about these experiments and making a connection between the mathematical theory and the experiments to only some of the students seeing a connection between these experiments and quantum technologies. This work can help instructors consider the importance and framing of quantum experiments and raises questions about when and how in the curriculum quantum experiments can be best utilized and how to make related learning goals available to all students.

[This paper is part of the Focused Collection on Qualitative Methods in PER: A Critical Examination.] All people vary in their needs and abilities; however, typical research practices do not consider these variations, which likely impacts who participates in research studies. Additionally, few PER studies have investigated aspects of disability or reported disability identity. Combined, this means that PER researchers typically do not seek out the experiences of disabled people and disabled people might not have access to participate in research studies. In this paper, we demonstrate how a research team can use principles from Universal Design for Learning and the Variation Planning Tool to anticipate expectations of ability and create flexible options in a qualitative research study. We then demonstrate how different interview structures can impact disabled participants through a case study with three participants, all of whom self-identified as students with attention deficit-hyperactivity disorder. Finally, we conclude with implications and suggestions for researchers in planning their study designs. It is critical that, as physics education researchers, we anticipate, welcome, and support disabled participants in our research, particularly as interviews are a prevalent method in the field. Through the example presented in this paper, we hope to encourage researchers to examine their own methods through the lens of accessibility and to offer alternative formats in their research design as a means to combat ableism and to provide access to all research participants.

Linear functions are an essential part of school and university education. Nevertheless, this topic is challenging for many students—especially in STEM topics. In this article, we contribute to the understanding of learning difficulties in the context of mathematical and physical problems. Here, we present the results of an eye-tracking study on visual attention during the interpretation of linear graphs using the gaze-cued retrospective think-aloud (RTA) method. Gaze data of $N=131$ and interview data of $N=60$ grammar school students were recorded while solving items of a validated test instrument: pairs of items in a mathematical and kinematic context that are isomorphic, i.e., have similar surface features and require the same procedure to solve. We will show that the difficulties in interpreting the kinematic diagrams, which have already been identified in 9th-grade students, are still present in students in the entry phase of the upper secondary level. Further, students’ eye-tracking behavior differs significantly between mathematical and kinematic contexts. Triangulation of eye-tracking data with RTA data reveals context-dependent solution strategies—transfer from mathematics to physics is a major problem for students.

Students at all levels of education experience difficulties with the concepts of measurement uncertainties. One task that includes concepts of measurement uncertainties is a data comparison problem where students decide whether two datasets are in agreement or not—an authentic scientific practice. To aid students with these concepts and tasks, sensitive instruments are needed that probe students’ understanding and track their progress. We present a tool in the form of a coding manual that analyzes students’ written justifications for such a data comparison problem. With this coding manual, justifications are coded based on the quantity that is compared and the deciding criterion in this comparison. Our coding manual was used in the evaluation of a digital learning environment (DLE). In this evaluation, 154 participants (aged 14–17 years) wrote a justification for a data comparison problem before and after going through the DLE. These participants were randomly assigned to one of three groups where each group was taught an increased amount of concepts regarding measurement uncertainties. By analyzing the participants’ justifications with our coding manual, we could probe their ability to compare datasets on a fine-grained level. The sensitivity of our tool was illustrated by the increase in higher quality codes with the increased conceptual teaching between the three groups. We argue that our tool for coding justifications can be applied to any data comparison problem giving detailed information about what data analysis methods students use and how they reach their conclusion and thus contributes to the research on students’ understanding of measurement uncertainties.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] Research on nontraditional laboratory (lab) activities in physics shows that students often expect to verify predetermined results, as takes place in traditional lab activities. This understanding of what is taking place, or epistemic framing, may impact students’ behaviors in the lab, either productively or unproductively. In this paper, we present an analysis of student epistemic framing in a nontraditional lab with the aim of understanding how instructional context, specifically instructor behaviors, may shape student framing. We present video data from a lab section taught by an experienced teaching assistant (TA), with 19 students working in seven groups. We argue that student framing in this lab is evidenced by whether or not students articulate experimental predictions and by the extent to which they take up cognitive authority when constructing knowledge (epistemic agency). We show that the TA’s attempts to shift student frames generally succeed with respect to experimental predictions but are less successful with respect to epistemic agency. In part, we suggest, the success of the TA’s attempts reflects whether and how they are responsive to students’ current framing. This work offers evidence that instructors can shift students’ frames in nontraditional labs, while also illuminating the complexities of both student framing and the role of the instructor in shifting that framing in this context.

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] Measurement uncertainty is a critical feature of experimental research in the physical sciences, and the concepts and practices surrounding measurement uncertainty are important components of physics lab courses. However, there has not been a broadly applicable, research-based assessment tool that allows physics instructors to easily measure students’ knowledge of measurement uncertainty concepts and practices. To address this need, we employed evidence-centered design to create the Survey of Physics Reasoning on Uncertainty Concepts in Experiments (SPRUCE). SPRUCE is a pre-post assessment instrument intended for use in introductory (first and second year) physics lab courses to help instructors and researchers identify student strengths and challenges with measurement uncertainty. In this paper, we discuss the development of SPRUCE’s assessment items guided by evidence-centered design, focusing on how instructors’ and researchers’ assessment priorities were incorporated into the assessment items and how students’ reasoning from pilot testing informed decisions around item answer options. We also present an example of some of the feedback an instructor would receive after implementing SPRUCE in a pre-post fashion, along with a brief discussion of how that feedback could be interpreted and acted upon.

[This paper is part of the Focused Collection on Qualitative Methods in PER: A Critical Examination.] Identifying student ideas about particular physics topics is one of the earliest and longest-standing foci of physics education research. This paper presents a method for identifying common conceptual resources for understanding physics, using large numbers of written student responses to conceptual questions. We walk researchers step by step through how we have done this ourselves, from collecting data, to identifying candidate resources, to turning our lists of candidate resources into a coding scheme that can then be applied to datasets of $>200$ responses. The outcome of these methods are lists of common conceptual resources for understanding particular topics in physics, such as forces, energy, circuits, and heat and temperature.

In this study, we investigated female and male students’ sense of belonging and their academic performance measured by the Force Concept Inventory (FCI) and course grades in a calculus-based introductory physics course at a large public university in the United States. We find that compared to male students, female students’ sense of belonging was lower on average, and this gender gap persisted from the beginning to the end of the course. Moreover, both women’s and men’s sense of belonging decreased after the course. We also find that while there was no gender difference in students’ Scholastic Aptitude Test (SAT) math scores and female students had a higher average high school grade point average (GPA) than male students, female students had lower average FCI scores and course grades than male students. Using structural equation modeling, we find that students’ sense of belonging statistically significantly predicts their FCI scores and course grades after controlling for SAT math scores and high school GPA. Our findings suggest that physics instructors should be intentional about creating an inclusive and equitable learning environment in which students from all demographic groups have a high sense of belonging and can excel.