Given the insufficient number of well-qualified future physics teachers in the U.S., physics programs often seek guidance for how to address this national need. Measurement tools can provide such guidance, by both defining excellence in physics teacher education (PTE) and providing a means to measure progress towards excellence. This paper describes the development of such a measurement tool—the Physics Teacher Education Program Analysis rubric. The rubric was developed by identifying common features and practices at 8 “thriving” PTE programs, defined as large U.S. programs consistently graduating 5 or more future physics teachers in a year. The rubric consists of 89 items, each with 3 levels of achievement (developing, benchmark, exemplary), plus a not present level, which are organized into 6 standards. The rubric has demonstrated a variety of forms of validity, including a strong theoretical basis, empirical validation through program visits, and expert review. The rubric and its associated supporting materials are intended to help program leaders in using a process of continuous improvement and assessment to strengthen existing PTE programs or to establish new pathways for student licensure. The rubric also provides substantive opportunities for research, through further validation and development of the rubric, and by using rubric results to learn more about effective practices in physics teacher education.

In recent years, there has been an increased interest in conceptual blending in physics and mathematics education research as a theoretical framework to study student reasoning. In this paper, we adapt the conceptual blending framework to construct a blending diagram that not only captures the product but also the process of student reasoning when they interpret a mathematical description of a physical system. We describe how to construct a dynamic blending diagram (DBD) and illustrate this using two cases from an interview study. In the interview, we asked pairs of undergraduate physics and mathematics students about the physical meaning of boundary conditions for the heat equation. The selected examples show different aspects of the DBD as an analysis method. We show that by using a DBD, we can judge the degree to which students integrate their understandings of mathematics and physics. The DBD also enables the reader to follow the line of reasoning of the students. Moreover, a DBD can be used to diagnose difficulties in student reasoning.

Many instructional physics labs are shifting to teach experimentation skills, rather than to demonstrate or confirm canonical physics phenomena. Our previous work found that many students engage in questionable research practices in attempts to confirm the canonical physics phenomena, even when confirmation is explicitly not the goal of the lab. This exploratory study aimed to answer three research questions: (RQ1) What are students’ expectations about the purpose of labs when they enter introductory physics?, (RQ2) How do their prior experiences shape those expectations?, (RQ3) In what ways do those expectations relate to their engagement in questionable research practices? Through open-response surveys, we found that students overwhelmingly expressed confirmatory beliefs about the purpose of labs. Through interviews, we found that students’ prior lab experiences were also overwhelmingly confirmatory, despite varying degrees of structure. We then used video of individual groups to explore the ways in which questionable research practices manifest through confirmatory expectations. We confirm previous work that students’ confirmatory expectations can lead them to engage in questionable research practices, but find that these behaviors occur despite instructional messaging about an alternative purpose. Our analyses also suggest that engagement in questionable research practices is more frequent than the previous results indicated through analysis of submitted lab notes. These results further illuminate issues with traditional labs, but suggest that the confirmatory goals, perhaps more so than high structure, are problematic.

The concepts of the Coriolis and the centrifugal force are essential in various scientific fields and they are standard components of introductory physics lectures. In this paper, we explore how students understand and apply concepts of rotating frames of reference in the context of an example lecture demonstration experiment. We found in a predict-observe-explain setting that after predicting the outcome prior to the demonstration, only one out of five physics students correctly reported the observation of the trajectory of a sphere rolling over a rotating disc. Despite this low score, a detailed analysis of distractors revealed a significant improvement in the distractor choices during the observation of the experiment. In this context, we identified three main preconceptions and learning difficulties: The centrifugal force seems to be only required to describe the trajectory if the object is coupled to the rotating system, the inertial forces cause a reaction of an object on which they act, and students systematically mix up the trajectories in the stationary and the rotating frame of reference. Furthermore, we captured students’ eye movements during the predict task and found that physics students with low confidence ratings focused longer on relevant task areas than confident students despite having a comparable score. Consequently, this metric is a helpful tool for the identification of preconceptions using eye tracking. Overall, the results help us to understand the complexity of concept learning from demonstration experiments and provide important implications for instructional design of introductions to rotating frames of reference.

In this article, we discuss the development and the administration of a multiple-choice test, which we named Test of Calculus and Vectors in Mathematics and Physics (TCV-MP), aimed at comparing students’ ability to answer questions on derivatives, integrals, and vectors in a purely mathematical context and in the context of physics. The comparison between the two contexts was achieved by using parallel (isomorphic) questions in mathematics and physics. The final version of the test contains 34 items (17 in a purely mathematical context and 17 in the context of physics) involving different representations (graphs, words, numbers, and formal expressions) of the concepts covered by the test. The test was administered in Spring 2018 to 1252 first-year students enrolled in 23 different degree programs of the School of Science and the School of Engineering of the University of Padua. We assessed the validity, reliability, and discriminatory power of the test both as a whole and at the single-item level, obtaining values within the desired ranges. The analysis of students’ answers to individual items and the comparison between parallel mathematics and physics items provides insights into the factors that affect students’ ability to use derivatives, integrals, and vectors in the context of introductory physics. We believe that the instrument we have developed can be useful not only for research purposes, but also for instructors and for students.

The goal of this research is to provide a rich set of connections between two fields: (i) Nanoscale science and technology (NST) and (ii) topics from a common middle school physics curriculum. NST is emerging as one of the most promising new fields of the 21st century, which is one of the many arguments for including NST topics in secondary science education. A specially designed guided discourse with NST scientists was used to produce a map of connections between the two fields. During the discourse, the scientists were presented with two sets of concepts using a visual board and were asked to find connections between them. All suggested connections and the corresponding context offered by the scientists were arranged and presented as a rich set of connections. For example, (i) the NST concept of characterization methods is connected to mechanical forces and can be explained using the example of an atomic force microscope; (ii) the NST concept of size-dependent properties was connected to 7th grade inquiry skills by explaining the size dependence of accuracy, errors, and defects. This set of connections was validated by an experienced middle school science teacher in an open discussion regarding teachers adopting and implementing the resulting insertion points for the curriculum. This resulting set of connections can be used to enrich the curriculum within the NST field. It also provides a perspective on scientists’ views regarding insertion of contemporary NST topics into physics middle school education.

We report the findings of an empirical study that investigated whether the source of data—firsthand or secondhand data gained from lab work experiments—has an influence on students’ learning outcomes. Results indicate that students’ choice of a correct or incorrect hypothesis for a pendulum lab experiment on the influence of the mass of the bob on the time of oscillation does not depend on who the author of the data at hand is: the student themself, a peer, or a teacher. Further, students judge the importance of the data’s author as relatively unimportant no matter what data source they have at hand. Thus, it seems fairly unimportant whether students use firsthand or secondhand data when the teaching focus is set on choosing a correct hypothesis in the light of empirical data, as long as students get enough information on how the data were generated and how they are analyzed and interpreted. This result is especially relevant for practitioners, as it shows that it is possible to use secondhand data for the purpose of evaluation and interpretation without significant distortions of epistemic learning processes.

Scientific expertise is manifested through extensive cycles of making and acting on decisions. To learn the processes and practices of science, therefore, students must have practice with scientific decision making. We argue that this can only happen if students are afforded agency: the opportunity to make decisions to pursue a goal. In this study, we compared two different introductory physics labs through the lens of structuring and supporting student agency. We explore both the role of decision making agency (students are afforded opportunities to make decisions about their lab investigations) and epistemic agency (students are afforded opportunities to generate knowledge). We found that the two labs differed in both the amount and type of structure provided to students: one lab (the intervention condition), with more overall structure, cued student decision making; the other lab (control condition), with less overall structure, made decisions for students. Students in the intervention condition documented, on average, ten times more decisions during their investigations, including more unprompted decisions. In contrast, in labs with less available epistemic agency (i.e., labs where they had to verify or demonstrate canonical models or constants), students in the intervention condition documented fewer decisions than in labs with more available epistemic agency. We associate the improved decision making with students taking up personal agency, based on significant shifts in students’ tone as they described their experimental methods (from passive, third-person narratives to active, first-person narratives). Students in the intervention condition also made higher-quality decisions in line with scientific practice. The study speaks to the important nuances between structure and agency in instructional labs and tests the generalizability of previous research on lab instruction to a two-year college population.

Recently, Nissen et al. argued in this journal for the use of Cohen’s $d$, in place of the more commonly used normalized gain, in the analysis of preinstruction and postinstruction scores on concept inventories used to measure the effectiveness of instruction. Their reason for advocating such a change is that they say normalized gains are “prescore biased.” We provide five examples, including one cited by Nissen, that show no prescore bias when data are carefully analyzed, demonstrating that the problem with their analysis is omitted variable bias. We show that Cohen’s $d$ is less informative than normalized gain when used as a single parameter measure of teaching effectiveness, even though, as Nissen points out, $d$ is more widely used in other fields. We believe that physics education researchers should continue to use normalized gain to assess educational effectiveness of pedagogy. However, because different student populations can have significantly different responses to the same pedagogy, in any interpretation of normalized gain, it is important to consider a measure of the abilities of the students. In analyzing normalized gains for the Force Concept Inventory (FCI), average scores on either Lawson’s Test of Scientific Reasoning Ability or the SAT should be considered, because these scores are strongly correlated with normalized gain, indicating student abilities may have a greater impact on the gains achieved in a class than the specific pedagogy used.

Research-based assessment instruments (RBAIs) are ubiquitous throughout both physics instruction and physics education research. The vast majority of analyses involving student responses to RBAI questions have focused on whether or not a student selects correct answers and using correctness to measure growth. This approach often undervalues the rich information that may be obtained by examining students’ particular choices of incorrect answers. In the present study, we aim to reveal some of this valuable information by quantitatively determining the relative correctness of various incorrect responses. To accomplish this, we propose an assumption that allows us to define relative correctness: students who have a high understanding of Newtonian physics are likely to answer more questions correctly and also more likely to choose better incorrect responses than students who have a low understanding. Analyses using item response theory align with this assumption, and Bock’s nominal response model allows us to uniquely rank each incorrect response. We present results from over 7000 students’ responses to the Force and Motion Conceptual Evaluation.

Nearly every introductory physics or chemistry course includes live lecture demonstrations, which can range from simple illustrations of a pendulum to elaborate productions with specialized apparatus and highly trained demonstrators. Students and instructors often consider “demos” to be among the highlights of these classes. Yet, in some situations demos may be cumbersome, inaccessible, or otherwise unavailable, and online video demos could offer a convenient alternative. We compared the effectiveness of live demonstrations with online videos under controlled conditions in the first semester of an introductory physics (mechanics) course. Students were randomly assigned to view either a live or video version of two demos. The same instructor presented both versions of the demo using an identical script, keeping the same time on task across both conditions, but with small differences in presentation appropriate to the medium. Compared with the students who saw the live demos, the students who watched the online videos learned more, and their self-reported enjoyment was just as high. We discuss reasons why videos helped students to learn more, including that they are more likely to make correct observations from the video. These results suggest that videos could provide students with an equally effective learning experience when live demos are unavailable. Indeed, even when live demonstrations are available, it may be beneficial to supplement them with online presentations.

As targeted, single-conception curriculum research becomes more prevalent in physics education research (PER), the need for a more sophisticated statistical understanding of the conceptual surveys used becomes apparent. Previously, the factor structure of the Force Concept Inventory (FCI) was examined using exploratory factor analysis (EFA) and exploratory multitrait item response theory (EMIRT). The resulting exploratory driven factor model and two expert-proposed models were tested using confirmatory factor analysis (CFA) and were found to be adequate representations of the FCI’s factor structure for postinstruction student responses. This study compliments the literature by using confirmatory multitrait item response theory (CMIRT) on matched preinstruction to postinstruction student responses ($N=19745$). It was found that the proposed models did not fit the data within a CMIRT framework. To determine why these models did not fit the data, an EMIRT was performed to find suggested modifications to the proposed models. This resulted in a bi-factor structure for the FCI. After calculating the student ability scores for each trait in the modified factor models, only two traits in each of the models were found to exhibit student gains independent of the general, “Newtonian-ness” trait. These traits measure students’ understanding of Newton’s third law and their ability to identify forces acting on objects.

The Force Concept Inventory (FCI) can serve as a summative assessment of students’ conceptual knowledge at the end of introductory physics, but previous work has suggested that the knowledge measured by this instrument is not a unitary construct. In this article, we consider the idea that FCI performance may reflect a number of student attributes including relational knowledge structures of physics concepts, expertlike attitudes, and problem-solving skills. Using a large calculus-based introductory physics course, we show that knowledge of conceptual relationships (i.e., knowledge structures), attitudinal measures, and problem-solving ability are all measures that uniquely contribute to a postinstruction FCI score. While these associations do not reveal the nature of their relation to the FCI (it could be that good students perform well on all these measures), they do provide evidence that improving any one of these aspects may improve a student’s overall FCI score.

Students must actively engage in problem solving to effectively learn in introductory physics courses. However, students often get stuck and are not able to make progress when solving problems outside of their current ability, particularly when one-on-one tutoring and instructor office hours are a limited resource. One effective technique consists of providing students with worked examples during the problem-solving process. While the benefits of worked examples are well established, less is known about how the format of the worked example affects student learning, or the effect of solution videos on student metacognition. This study presents three experiments investigating how the format of animated worked examples affects student learning and metacognition. The results indicate that students learn equally well from different styles of solution videos that follow multimedia learning principles. In addition, attempting to solve problems before viewing the solution videos facilitates learning for problems just outside a student’s current ability, but not for more difficult problems. Further, attempting to solve very difficult problems before viewing animated solution videos can potentially lead to overconfidence, where students believe that they learned more from the solutions than they have actually learned.

We elaborate on a new approach of assessing content-based epistemic clarity of college physics students in terms of their ability to discriminate between different epistemic warrants for propositions in a chained argument in physics. A threefold classification (nominal, physical, and mathematical) of warrants is used, with each class split into a number of distinct epistemic categories. The assessment tool consists of a questionnaire, illustrated here for a standard undergraduate physics derivation, in which the student chooses the appropriate epistemic category (from an appended list) for each proposition in the given derivation. The tool includes a brief supplementary orientation note for clarifying the meaning of different categories. It is tested for reliability and internal consistency. Correlation of content knowledge, ascertained independently, with epistemic clarity is investigated. Surveys on large and diverse samples of physics undergraduates carried out with or without the orientation note reveal a variety of epistemic errors, some common among all groups of students, and some that are good discriminators. The epistemic measure obtained from such a tool is, however, limited in scope by its narrow definition. The construct validity of the tool and the pedagogic relevance of the work are discussed.

The topic of atomic spectra is part of university and secondary school curricula around the world. Relatively little research, however, has been done on the learning and teaching of this subject, despite the fact that it forms a foundation for advanced study in quantum mechanics, astronomy, and astrophysics. A systematic investigation into student understanding of the formation and structure of atomic spectra was conducted among more than 1000 science majors in physics courses at the University of Zagreb, Croatia and the University of Washington, USA. The research had two primary goals: (i) to probe the extent to which university students are able to relate the wavelength of spectral lines to the transition of electrons between energy levels in an atom, and (ii) to probe the extent to which students recognize the conditions under which discrete line spectra are (and are not) formed. This paper focuses on the latter aspect, in particular, student understanding of the experimental setup that is commonly used to illustrate the formation of discrete line spectra. Students were asked about how changes to a setup consisting of a light source, a mask with a slit, a prism (or diffraction grating), and a screen affect the spectra observed. The findings suggest that relatively few students recognize that the type of light source is critical for the formation of line spectra. Instead students often attribute the formation of line spectra to the slit, the prism (or diffraction grating), or even to the distance between the prism and screen.

The evaluation of hypotheses, and the ability to learn from critical reflection on experimental and theoretical tests of those hypotheses, is central to an authentic practice of physics. A large part of physics education therefore seeks to help students understand the significance of this kind of reflective practice and to develop the strategies required to accurately update their belief in the utility of various hypotheses and models. Prior work has introduced Bayesian updating activities as one potential means for cultivating such reflective practice within the context of introductory physics courses. These activities are not fixed pieces of curricular matter, but are better thought of as codified practices that are incorporated within lectures, labs, homework, and exams, and which are adaptable to a broad range of course formats. The Bayesian updating activities engage students in the use of hypothetico-deductive reasoning to test a hypothesis or model, followed by Bayesian updating at the conclusion of this test to update their subjective confidence in the hypothesis or model that was tested. Prior work has identified significant gains in pre- and post comparison of student scores on the Epistemological Beliefs Assessment for Physical Science (EBAPS) in introductory algebra-based courses. Here, we conduct a quasi-experimental study of the impact of Bayesian updating activities on student EBAPS scores in introductory calculus-based courses. Our analysis examines the impact to the overall EBAPS score, the subscores for each of the five original axes identified by the authors of the EBAPS, and the subscores for five alternative axes that were recently identified in other work via factor analysis of student responses [Johnson and Willoughby, Phys. Rev. Phys. Educ. Res. 14, 010135 (2018)]. The results of our analysis show meaningful and credible gains on the overall EBAPS scores as well as for a multitude of the subscores. These gains are noteworthy due to their strength and their ability to be achieved with activities that were implemented as relatively minor alterations to a traditional course structure.

Computation is becoming an increasingly important part of physics education. However, there are currently few theories of learning that can be used to help explain and predict the unique challenges and affordances associated with computation in physics. In this study, we adapt the existing theory of computational literacy, which posits that computational learning can be divided into material, cognitive, and social aspects, to the context of undergraduate physics. Based on an exploratory study of undergraduate physics computational literacy, using a newly developed teaching tool known as a computational essay, we have identified a variety of student practices, knowledge, and beliefs across these three aspects of computational literacy. We illustrate these categories with data collected from students who engaged in an initial implementation of computational essays in a 3rd-semester electricity and magnetism class. We conclude by arguing that this framework can be used to theoretically diagnose student difficulties with computation, distinguish educational approaches that focus on material vs cognitive aspects of computational literacy, and highlight the benefits and limitations of open-ended projects like computational essays to student learning.

Traditionally, multiple choice assessments are graded in a dichotomous manner, where selecting the correct option for a question awards 1 point and the selection of an incorrect option awards 0 points. As a result of this grading scheme, all incorrect response options are treated as being equally incorrect regardless of potential differences in their relative correctness, intentional or otherwise. We propose a partial credit grading model for the Force Concept Inventory (FCI) that allots points to the incorrect responses. This was done using slope parameters from the two-parameter logistics nominal response model (2PLNRM), a model from polytomous item response theory (PIRT). The resulting scores from the partial credit model represent student growth towards a proper Newtonian mindset, as measured by the FCI. Observations indicate that this model accounts for student progression through prominent misconceptions (i.e., impetus) as their world views become more Newtonian. As expected, we find that student total scores increase as a result of the model, but the average overall gains on the assessment are essentially unchanged. The data used in this analysis were maintained and organized by PhysPort and included about 20 000 responses from first semester introductory physics courses at multiple universities. Ultimately, this partial credit model allows instructors to more accurately gauge the growth of their students over the course of instruction. Additionally, as a result of these partial credit scores, we are able to identify potentially malfunctioning questions on the FCI that may be sources of error in measuring student abilities.

Theories developed by Tinto and Nora identify academic performance, learning gains, and involvement in learning communities as significant facets of student engagement that, in turn, support student persistence. Collaborative learning environments, such as those employed in the Modeling Instruction introductory physics course, provide structure for student engagement by encouraging peer-to-peer interactions. Because of the inherently social nature of collaborative learning, we examine student interactions in the classroom using network analysis. We use centrality—a family of measures that quantify how connected or “central” a particular student is within the classroom network—to study student engagement longitudinally. Bootstrapped linear regression modeling shows that students’ centrality predicts future academic performance over and above prior GPA for three out of four centrality measures tested. In particular, we find that closeness centrality explains 28 % more of the variance than prior GPA alone. These results confirm that student engagement in the classroom is critical to supporting academic performance. Furthermore, we find that this relationship for social interactions does not emerge until the second half of the semester, suggesting that classroom community develops over time in a meaningful way.