A deep understanding of mathematical equations and their physical meaning is an important skill for physicists and therefore a central learning goal in university physics education. However, many students approach mathematical expressions in physics in a purely procedural manner, using them as calculation tools without critically evaluating their physical plausibility. Making sense of equations, that is, being able to interpret and evaluate equations within a physical context, is essential for the development of expertlike reasoning in physics. Frequently employed strategies that assist in the sensemaking process are dimensional, covariational, special, and limiting case analysis. Despite their importance, these strategies are rarely taught or practiced explicitly in university physics courses. The present intervention study systematically implemented sensemaking strategies within a university course for first-year physics students covering topics of electro- and magnetostatics as well as electrodynamics. Traditional exercises were enriched with tasks requiring students to critically evaluate the plausibility of self-derived equations. The tasks were integrated into recitation sessions and homework assignments. A total of N=67 physics students participated in the study. A quasiexperimental pre-post design with two groups was employed to evaluate the effectiveness of the intervention approach. Results show that students highly valued all four strategies equally and reported an increased perceived competence in their application after the intervention. Significant improvements in performance were observed for dimensional (d=0.67) as well as for special case analysis (d=0.50). Students’ performance in analyzing covariations only showed a tendency favoring the intervention group. No intervention-related impact on the performance of limiting case analysis was found, suggesting that this strategy may require more extensive practice. The findings underscore the importance and usefulness of explicitly teaching strategies to support students’ sensemaking of physics equations.

IntroductionThis paper is concerned with investigating the cognitive demands of solving force diagram tasks in different scenarios, specifically in the wind context.MethodsIn this study, students were trained using worked examples and then completed tasks in two different scenarios while their eye movements were monitored with eye-tracking technology. After completing the tasks, cognitive load was assessed to evaluate the impact of task complexity on cognitive processing. Eye-tracking metrics were analyzed in detail to identify gaze strategies, differences and similarities.ResultsIt was found that a three-force scenario (surface wind formation) induced a higher intrinsic cognitive load than a two-force scenario, which is not only theoretically justified by cognitive load theory, but also confirmed by eye-tracking metrics. Although correlation analyses show no significant relationship between the ability to mentally rotate and learning success, the role of mental rotation in problem solving is highlighted by eye-tracking data.DiscussionOur results contribute to a better understanding of the learning and problem-solving mechanisms involved in wind direction determination and offer possible implications for the design of more effective teaching and learning methods in this area.

Multiple external representations (e. g. diagrams, equations) and their interpretations play a central role in science and science learning as research has shown that they can substantially facilitate the learning and understanding of science concepts. Therefore, multiple and particularly visual representations are a core element of university physics. In electrodynamics, which students encounter already at the beginning of their studies, vector fields are a central representation typically used in two forms: the algebraic representation as a formula and the visual representation depicted by a vector field diagram. While the former is valuable for quantitative calculations, vector field diagrams are beneficial for showing many properties of a field at a glance. However, benefiting from the mutual complementarity of both representations requires representational competencies aiming at referring different representations to each other. Yet, previous study results revealed several student problems particularly regarding the conceptual understanding of vector calculus concepts. Against this background, we have developed research-based, multi-representational learning tasks that focus on the visual interpretation of vector field diagrams aiming at enhancing a broad, mathematical as well as conceptual, understanding of vector calculus concepts. Following current trends in education research and considering cognitive psychology, the tasks incorporate sketching activities and interactive (computer-based) simulations to enhance multi-representational learning. In this article, we assess the impact of the learning tasks in a field study by implementing them into lecture-based recitations in a first-year electrodynamics course at the University of Goettingen. For this, a within- and between-subjects design is used comparing a multi-representational intervention group (IG) and a control group (CG) working on traditional calculation-based tasks (N = 81). Group comparisons revealed that students in the intervention group scored significantly higher on a vector field performance test after the intervention (p = 0.04, d = 0.40) while perceiving higher cognitive load during task processing (extraneous p < 0.001, d = 0.75; intrinsic p = 0.02, d = 0.47; germane p = 0.02, d = 0.48). Moreover, students who worked with multi-representational learning tasks achieved higher normalized learning gains in tasks addressing conceptual understanding and representational competencies related to vector field diagrams and vector calculus concepts (g H, IG = 0.35, g H, CG = 0.13). These results provide guidance for the design of multi-representational learning tasks in field-related physics topics and beyond.

This exploratory field study investigates the integration of innovative forms of recitation tasks in a first-year introductory mechanics course, focusing on smartphone-based experimental tasks alongside programming and standard recitation tasks. Smartphones, combined with external sensor modules, serve as a gateway enabling students to conduct various low-cost and authentic physics experiments with first-hand data collection outside traditional lab settings. These tasks aim to enhance students’ agency in independent physics experimentation and enrich homework assignments by dissolving boundaries between lectures, recitation sessions, and traditional labs, and thereby linking theoretical and experimental aspects of undergraduate physics education. To explore this potential, we implemented and evaluated a sample set of nine smartphone-based experimental tasks and, for comparison, three programming tasks as weekly exercises in a first-year physics course at RWTH Aachen University. We investigated students’ perceptions of learning with these new tasks through 12 short surveys involving up to 188 participants, focusing on factors such as goal clarity, difficulty, or feasibility at home. In two additional surveys with 108 and 78 participants, students assessed affective responses to the smartphone-based experimental tasks relative to the programming and standard recitation tasks. Our findings indicate that the smartphone-based experimental tasks were generally well suited to the students and tended to outperform the programming tasks in terms of perceptions of learning with the tasks and affective responses. Overall, students responded positively to the new experimental tasks, with perceptions comparable to, or only partly below, those of long-established standard recitation tasks. These results suggest that smartphone-based experimental tasks can be successfully integrated into teaching and contribute to refining traditional recitation tasks. Students’ differentiated perceptions of the three task types investigated offer valuable insights into how students perceived technology-enhanced recitation tasks in terms of feasibility, engagement, and instructional value. This provides a meaningful basis for instructors and researchers aiming to design more effective and student-centered learning environments in undergraduate physics education.

Gauss’ and Stokes’ theorems are fundamental results in vector calculus and important tools in physics and engineering. When students are asked to describe the meaning of Gauss’ divergence theorem, they often use statements like this: ‘The sum of all sources of a vector field in a region gives the net flux out of the region’. In order to raise this description to a mathematically sound level of understanding, we present an educational approach based on the visual interpretation of the vector differential operators, i.e. divergence and curl. As a starting point, we use simple vector field diagrams for a qualitative approach to connect both sides of the integral theorems, and present an interactive graphical tool to support this connection. The tool allows to visualise two-dimensional vector fields, to specify vector decomposition, to evaluate divergence and curl point wise, and to draw rectangles to determine surface and line integrals. From a meta-perspective, we situate this educational approach into learning with (multiple) representations. Based on prior research, the graphical tool addresses various learning difficulties of vector fields that are connected to divergence and curl. The tool was incorporated into the weekly lecture-based recitations of Physics II (electromagnetism) in 2022 and 2023, and we assessed various educational outcome measures. The students overall reported the tool to be intuitive and user-friendly (level of agreement 76%, N = 125 ), considered it helpful for understanding and recommended its use for introductory physics courses (level of agreement 65%, N = 65 ).

This study presents an approach to integrate innovative forms of recitation tasks into first-year introductory mechanics, with a primary focus on smartphone-based experimental tasks and additional programming tasks for comparison. Smartphones enable inexpensive physics experiments with digitized first-hand data collection outside lab settings. Such student experiments can enhance homework assignments, breaking down barriers between lectures, recitation groups, and labs, and thereby linking theoretical and experimental aspects of undergraduate physics education. To explore this potential, we implemented and evaluated a sample set of nine smartphone-based experimental tasks and three programming tasks as weekly exercises in a first-year physics course at RWTH Aachen University. Through twelve short surveys involving up to 188 participants, we investigated students' perceptions of learning with the new tasks, focusing on factors such as goal clarity, difficulty, or feasibility at home. In two additional surveys with 108 and 78 participants, students compared the new experimental and programming tasks to each other and to standard recitation tasks based on affective variables. Our findings indicate that the smartphone-based experimental tasks were generally well-suited to the students, which tended to outperform the programming tasks in terms of perceptions of learning with the tasks and affective responses. Overall, students responded positively to the new experimental tasks, with perceptions comparable to, or only partly below those of established standard recitation tasks. Given that most of the experimental tasks were newly implemented "on-the-fly" within a running course, while the standard recitation tasks have been refined over years, these results are encouraging. They suggest that smartphone-based experimental tasks can be successfully integrated into teaching.

While lab courses are an integral part of studying physics aiming at a huge variety of learning objectives, research has shown that typical lab courses do not reach all the desired goals. While diverse approaches by lab instructors and researchers try to increase the effectiveness of lab courses, experimental tasks remain the core of any lab course. To keep an overview of these developments and to give instructors (and researchers) a guideline for their own professional efforts at hand, we introduce a research-informed framework for designing experimental tasks in contemporary physics lab courses. In addition, we demonstrate within the scope of the EU-co-funded DigiPhysLab-project how the framework can be used to characterize existing or develop new high-quality experimental tasks for physics lab courses.

EDITORIAL article Front. Educ., 26 March 2024Sec. STEM Education Volume 9 - 2024 | https://doi.org/10.3389/feduc.2024.1389962

Digital signal processing is a valuable practical skill for the contemporary physicist, yet in physics curricula its central concepts are often introduced either in method courses in a highly abstract and mathematics-oriented manner or in lab work with little explicit attention. In this paper, we present an experimental task in which we focus on a practical implementation of the discrete Fourier transform (DFT) in an everyday context of vibration analysis using data collected by a smartphone accelerometer. Students are accompanied in the experiment by a Jupyter notebook companion, which serves as an interactive instruction sheet and a tool for data analysis. The task is suitable for beyond-first-year university physics students with some prior experience in uncertainty analysis, data representation, and data analysis. Based on our observations the experiment is very engaging. Students have consistently reported interest in the experiment and they have found it a good demonstration of the DFT method

Abstract At the University of Göttingen, we implemented undergraduate research projects into a first-year mechanics course for physics majors and teacher-training students. Our primary goal was to foster students’ affective factors and higher-order thinking skills in a self-directed, crosslinking, inquiry-based learning setting. A total of 160 students were organized into 40 small groups which worked on one of six open-ended experimental tasks, utilizing smartphone sensors for flexible first-hand data collection outside laboratories. The tasks originate from the Erasmus+ project DigiPhysLab and were significantly modified and opened to be used for undergraduate research projects. In this manuscript, we present the underlying rationales behind this program, outline the core concepts behind the developed experimental tasks, and explain the actual implementation. Additionally, we offer insights into the assessment process for the project work, including the evaluation of scientific posters and responses to eight reflection questions. To facilitate this, we have employed two rubrics to ensure a comprehensive evaluation process.

For a sound understanding of biological diversity, it is not only important to identify species and recall their names, but to be able to distinguish between organisms based on a range of characteristic traits. However, whether flower or leaf characteristics are more important in identifying plant species and whether colour illustrations in identification books are more helpful than black and white ones is largely unexplored. With the help of a mobile eye-tracking device and pictures from two plant identification books, this study aimed to contribute to filling this knowledge gap. Thirty student teachers, all undergraduates in biology, were shown two freshly picked wildflowers (Medicago sativa and Echium vulgare) and asked to select the corresponding illustration from each of four plants on an identification sheet, which was either in colour or in black and white. For both plants, the number of fixations, and positively correlated fixation duration, were significantly higher for the flower than the leaf part. Although flowers and leaves were fixated longer and more frequently in the black-and-white illustrations, correct identifications were more likely with the coloured identification sheets. The results indicate that colour illustrations and sorting by flower characteristics are particularly helpful in identification aids for undergraduate students.

The current dropout rate in physics studies in Germany is about 60%, with the majority of dropouts occurring in the first year. Consequently, the physics study entry phase poses a significant challenge for many students. Students’ stress perceptions can provide more profound insights into the processes and challenges during that period. In a panel study featuring 67 measuring points involving up to 128 participants at each point, we investigated students’ stress perceptions with the perceived stress questionnaire (PSQ), identified underlying sources of stress, and assessed self-estimated workloads across two different cohorts. This examination occurred almost every week during the first semester, and for one cohort also in the second semester, yielding a total of 3241 PSQ data points and 5823 stressors. The PSQ data indicate a consistent stress trajectory across all three groups studied that is characterized by significant dynamics between measuring points, spanning from M=20.1,SD=15.9 to M=63.6,SD=13.4 on a scale from 0 to 100. Stress levels rise in the first weeks of the lecture, followed by stable, elevated stress levels until the exams and a relaxation phase afterward during the lecture-free time and Christmas vacation. In the first half of the lecture period, students primarily indicated the weekly exercise sheets, the physics lab course, and math courses as stressors; later on, preparation for exams and the exams themselves emerged as the most important stressors. Together with the students’ self-estimated workloads that correlate with the PSQ scores, we can create a coherent picture of stress perceptions among first-year physics students, which builds the basis for supportive measures and interventions.

In mathematics education, students are repeatedly confronted with the tasks of interpreting and relating different representations. In particular, switching between equations and diagrams plays a major role in learning mathematical procedures and solving mathematical problems. In this article, we investigate a rather unexplored topic with precisely such requirements—that is, vector fields. In our study, we first presented a series of multiple-choice tasks to 147 introductory university students at the beginning of their studies and recorded students’ eye movements while they matched vector field diagrams and equations. Thereafter, students had to solve a similar coordination task on paper and justify their reasoning. Two cluster analyses were performed including (i) transition and fixation data on diagrams and options (Model 1), and (ii) additionally the number of horizontal and vertical saccades on the diagram (Model 2). In both models, two clusters emerge—with Model 1 distinguishing behaviors related to representational mapping and Model 2 additionally differentiating students according to representation-specific demands. Model 2 leads to a better distinction between the groups in terms of different performance indicators (test score, response confidence, and spatial ability) which also transfers to another task format. We conclude that vertical and horizontal saccades reflect executive actions of perception when approaching vector field coordination tasks. Thus, we recommend targeted interventions for mathematics lessons; these lessons must focus on a visual handling of the vector field diagram. Further, we infer that students’ difficulties can be attributed to covariational reasoning, thereby indicating the need for further investigations. From a methodological perspective, we reflect on the triangulation of eye-tracking and verbal data in (multiple-choice) assessment scenarios.

ZusammenfassungDie Förderung von Interessen gilt als wesentliches Ziel des naturwissenschaftlichen Unterrichts, sodass der kontextorientierte Unterricht vermehrt an Bedeutung gewonnen hat. Anschließend an den empirischen Befund, dass die Orientierung fachlicher Inhalte an lebensweltliche Kontexte das Interesse von Schülerinnen und Schülern in Lernsituationen erhöhen kann, stellt sich die Frage, welche Kontexte für diesen Zweck besonders geeignet sind. In diesem Zusammenhang greift die vorliegende Untersuchung Argumente der Diskussion um fächerübergreifenden naturwissenschaftlichen Unterricht auf und nutzt zur Einbettung von Lerninhalten Kontexte aus den Themenfeldern Biologie und Technik, die von Mädchen bzw. Jungen als interessant wahrgenommen werden. In einer Online-Studie ($$N=298$$ N = 298 ) wird systematisch geprüft, inwiefern aus diesen Themenfeldern stammende Kontexte in der Lage sind, das situationale Interesse während der Arbeit an Lernstationen zum Energiekonzept zu erhöhen und welchen Einfluss individuelle Faktoren diesbezüglich zeigen. Mehrebenenregressionen mit Random Intercept auf Personenebene zeigen einen positiven Einfluss biologischer Kontexte auf das emotionsbezogene situationale Interesse von Schülerinnen, während durch den Einsatz technischer Kontexte diese Komponente des situationalen Interesses bei Schülern gesteigert werden konnte. Die wertbezogene Komponente des situationalen Interesses kann ebenfalls durch Einsatz von Kontexten eines bevorzugten Themenfeldes erhöht werden. Insgesamt wird deutlich, dass sich vor allem die emotionale Komponente des situationalen Interesses durch die Variation des Kontexts beeinflussen lässt, während die wertbezogene Komponente insbesondere durch das individuelle Interesse an Physik bedingt ist. Selbstkonzept und schulische Leistung zeigen unter Berücksichtigung der individuellen Interessen keinen signifikanten Einfluss. Für die Schulpraxis wird die Bedeutung der Auswahl geeigneter Kontexte deutlich, um mit dem Aufzeigen der Relevanz fachlicher Inhalte potentiell stabile Interessen fördern zu können.

Physics lab courses permanently undergo transformations, in recent times especially to adapt to the emergence of new digital technologies and the Covid-19 pandemic in which digital technologies facilitated distance learning. Since these transformations often occur within individual institutions, it is useful to get an overview of these developments by capturing the status quo of digital technologies and the related acquisition of digital competencies in physics lab courses. Thus, we conducted a survey among physics lab instructors (N=79) at German, Finnish, and Croatian universities. The findings reveal that lab instructors already use a variety of digital technologies and that the pandemic particularly boosted the use of smartphones/tablets, simulations, and digital tools for communication/collaboration/organization. The participants generally showed a positive attitude toward using digital technologies in physics lab courses, especially due to their potential for experiments and students' competence acquisition, motivational effects, and contemporaneity. Acquiring digital competencies is rated as less important than established learning objectives, however, collecting and processing data with digital tools was rated as an important competency that students should acquire. The instructors perceived open forms of labwork and particular digital technologies for specific learning objectives (e.g., microcontrollers for experimental skills) as useful for reaching their learning objectives. Our survey contributes to the reflection of what impact the emergence of digital technologies in our society and the Covid-19 pandemic had on physics lab courses and reveals first indications for the future transformation of hands-on university physics education.

Research has shown that visual representations can substantially enhance the learning and understanding of STEM concepts; despite this, students tend to struggle in using them fluently and consistently. Consequently, educators advocate for explicit instructions that support the coordination of multiple representations, especially when concepts become more abstract and complex. For recent years, the drawing (or sketching) technique has received increasing attention. Theoretical considerations and prior research suggest that drawing has the potential to support knowledge construction and to provide cognitive relief. In this article, we present two studies that investigate the impact of drawing activities in a multi-representational, instruction-based learning scenario from physics, more precisely, in the context of vector fields. Further, mobile and remote eye tracking was used to record students' gaze behavior in addition to monitoring indicators of performance and cognitive load. Here, eye movements provide information about cognitive processes during the completion of the instruction, on the one hand, and during subsequent problem solving, on the other hand. Comparisons of a treatment group instructed with drawing activities and a control group instructed without drawing activities revealed significant differences in students' perceived cognitive load (p = 0.02, d = 0.47 and p = 0.0045, d = 0.37), as well as their response accuracy (p = 0.02, d = 0.51) and their response confidence (p = 0.02, d = 0.55 and p = 0.004, d = 0.64) during assessment after instruction (N = 84). Moreover, students instructed with drawing activities were found to distribute more visual attention to important parts of the instruction (vector field diagram and instructional text, N = 32) compared to the control group and, further, showed effective, expert-like behaviors during subsequent problem solving (N = 53). Finally, as a contribution to current trends in eye-tracking research, the application of mobile and remote eye-tracking in drawing-based learning and assessment scenarios is compared and critically discussed.

This study aimed at evaluating how students perceive the linguistic quality and scientific accuracy of ChatGPT responses to physics comprehension questions. A total of 102 first- and second-year physics students were confronted with three questions of progressing difficulty from introductory mechanics (rolling motion, waves, and fluid dynamics). Each question was presented with four different responses. All responses were attributed to ChatGPT, but in reality, one sample solution was created by the researchers. All ChatGPT responses obtained in this study were wrong, imprecise, incomplete, or misleading. We found little differences in the perceived linguistic quality between ChatGPT responses and the sample solution. However, the students rated the overall scientific accuracy of the responses significantly differently, with the sample solution being rated best for the questions of low and medium difficulty. The discrepancy between the sample solution and the ChatGPT responses increased with the level of selfassessed knowledge of the question content. For the question of highest difficulty (fluid dynamics) that was unknown to most students, a ChatGPT response was rated just as good as the sample solution. Thus, this study provides data on the students' perception of ChatGPT responses and the factors influencing their perception. The results highlight the need for careful evaluation of ChatGPT responses both by instructors and students, particularly regarding scientific accuracy. Therefore, future research could explore the potential of similar "spot the bot" activities in physics education to foster students' critical thinking skills.

Eye tracking is becoming increasingly popular in physics education research (PER). As technology has advanced considerably in recent years and has become more user friendly, it is anticipated that eye tracking will play an increasingly significant role in assessing student learning at the process level in future studies. The main objective of this systematic review is to summarize the current status quo regarding eye tracking in PER and reviewing (a) the dissemination, (b) the methodological implementation, and (c) the insights provided by eye tracking in PER. We identified 33 journal articles, published between March 2005 and April 2021, that used eye tracking for original empirical research in the area of physics education. The results reveal that although eye tracking has been used in many different areas of physics, a clear focus on mechanics is evident, particularly for measuring visual attention in assessment scenarios like problem solving. While a high methodological rigor in the selection and analysis of the visual stimuli was apparent, only a few studies have provided a complete documentation of the technological implementation (e.g., movement restrictions, accuracy, and calibration information) and a theoretical embedding for interpreting eye-tracking data. To synthesize the results of the different studies, we created an inductive category system in accordance with the considered independent variables of the studies. Accordingly, visual attention was most frequently compared between levels of performance (correct vs incorrect or high vs low achievers), thereby leading to performance-discriminating factors of eye movement across studies. Furthermore, learners’ eye movements were compared across different stimuli, different time points, or between student groups to inform multimedia design and shed light on students’ learning progression. In summary, eye tracking is particularly useful for studying processes in different domains that are relevant to PER. Specific gaps in the literature, methodological limitations, and implications of existing findings were also identified to recommend future research and practices.

Multimedia learning theories suggest presenting associated pieces of information in spatial and temporal contiguity. New technologies like Augmented Reality allow for realizing these principles in science laboratory courses by presenting virtual real-time information during hands-on experimentation. Spatial integration can be achieved by pinning virtual representations of measurement data to corresponding real components. In the present study, an Augmented Reality-based presentation format was realized via a head-mounted display and contrasted to a separate display, which provided a well-arranged data matrix in spatial distance to the real components and was therefore expected to result in a spatial split-attention effect. Two groups of engineering students (N = 107; Augmented Reality vs. separate display) performed six experiments exploring fundamental laws of electric circuits. Cognitive load and conceptual knowledge acquisition were assessed as main outcome variables. In contrast to our hypotheses and previous findings, the Augmented Reality group did not report lower extraneous load and the separate display group showed higher learning gains. The pre- and posttest assessing conceptual knowledge were monitored by eye tracking. Results indicate that the condition affected the visual relevancy of circuit diagrams to final problem completion. The unexpected reverse effects could be traced back to emphasizing coherence formation processes regarding multiple measurements.