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 Göttingen. For this, a within- and between-subjects design is used comparing a multi-representational intervention group and a control group working on traditional calculation-based tasks. To analyze the impact of multiple representations, students' performance in a vector calculus test as well as their perceived cognitive load during task processing is compared between the groups. Moreover, analyses offer guidance for further design of multi-representational learning tasks in field-related physics topics.
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 self-assessed 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.
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Domain-specific understanding of digitally represented graphs is necessary for successful learning within and across domains in higher education. Two recent studies conducted a cross-sectional ...analysis of graph understanding in different contexts (physics and finance), task concepts, and question types among students of physics, psychology, and economics. However, neither changes in graph processing nor changes in test scores over the course of one semester have been sufficiently researched so far. This eye-tracking replication study with a pretest–posttest design examines and contrasts changes in physics and economics students’ understanding of linear physics and finance graphs. It analyzes the relations between changes in students’ gaze behavior regarding relevant graph areas, scores, and self-reported task-related confidence. The results indicate domain-specific, context- and concept-related differences in the development of graph understanding over the first semester, as well as its successful transferability across the different contexts and concepts. Specifically, we discovered a tendency of physics students to develop a task-independent overconfidence in the graph understanding during the first semester.
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 (
= 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.
The coordination of multiple external representations is important for learning, but yet a difficult task for students, requiring instructional support. The subject in this study covers a typical ...relation in physics between abstract mathematical equations (definitions of divergence and curl) and a visual representation (vector field plot). To support the connection across both representations, two instructions with written explanations, equations, and visual representations (differing only in the presence of visual cues) were designed and their impact on students' performance was tested. We captured students' eye movements while they processed the written instruction and solved subsequent coordination tasks. The results show that students instructed with visual cues (VC students) performed better, responded with higher confidence, experienced less mental effort, and rated the instructional quality better than students instructed without cues. Advanced eye-tracking data analysis methods reveal that cognitive integration processes appear in both groups at the same point in time but they are significantly more pronounced for VC students, reflecting a greater attempt to construct a coherent mental representation during the learning process. Furthermore, visual cues increase the fixation count and total fixation duration on relevant information. During problem solving, the saccadic eye movement pattern of VC students is similar to experts in this domain. The outcomes imply that visual cues can be beneficial in coordination tasks, even for students with high domain knowledge. The study strongly confirms an important multimedia design principle in instruction, that is, that highlighting conceptually relevant information shifts attention to relevant information and thus promotes learning and problem solving. Even more, visual cues can positively influence students' perception of course materials.
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The Hertzsprung-Russell diagram (HRD) is a fundamental representation in stellar physics. It contains information about key properties of stars and allows inferences about stellar evolution. The use ...of the HRD is an important disciplinary activity in astrophysics. For example, it is particularly important to have a graphical understanding of the HRD in order to understand elementary astrophysical relationships (e.g., about the luminosity, temperature, radius, and mass of stars). However, several research papers indicate that students often have difficulty interpreting the HRD, apparently due to its visual complexity, and a number of learning difficulties have been described. Yet, there is still no evidence concerning how learners actually select and extract information from the HRD when completing tasks. In this study, we examined the gaze patterns and think-aloud protocols of 35 physics students as they performed 14 open-response tasks. Benchmarking against traditional x-y diagrams shows that the HRD imposes a significantly higher cognitive load on students, particularly due to the representation of luminosity, magnitude, and spectral class. Students reported a variety of learning difficulties related to information selection and extraction, sometimes mechanistically copying procedures from typical x-y diagrams. Eye-movement analysis confirmed these learning difficulties on a procedural level and show whether the students fixated on task-relevant parts of the HRD. Based on the study results, preliminary recommendations can be made in order to create engaging learning materials relating to the HRD.
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Eye tracking enables the reconstruction of eye movements and thus the analysis of visual information selection and integration processes during problem solving. In this way, learner-specific ...difficulties can be identified and problem-solving process can be adapted accordingly. For such an adaptation, the prediction of response behavior plays a crucial role. To predict whether a problem is solved correctly or incorrectly, the segmentation of the visual stimulus into specific areas of interest (AOIs) is particularly crucial for the quality of a prediction based on eye-tracking data. In the study presented here, the gaze data of N=115 students were analyzed while solving the Test of Understanding Graphs in Kinematics (TUG-K), a validated test instrument whose items include graphs of position, velocity, and acceleration versus time. For selected items, response accuracy was predicted based on visual attention using multiple logistic regression analysis, examining the influence of AOI segmentation. The prediction quality could be significantly improved when the diagram was not considered as contiguous AOI, but when it was divided into solution-relevant and solution-irrelevant areas. To verify that the AOIs selected by the regression algorithm are indeed relevant to the solution process, an expert rating was performed, which showed moderate to good agreement between the AOIs rated by the experts as relevant to the correct solution and the AOIs selected by the algorithm. There are also pairs of items in the TUG-K that require the same mathematical solution procedure but differ in the physical context. This opened the possibility to investigate a new approach. Based on response accuracy and allocation of visual attention to one item, the response accuracy of the other item of the pair was predicted. It could be shown that the prediction quality based on visual attention was significantly higher than the prediction based on response accuracy. This demonstrates the added value of collecting process-based data versus product-based data for prediction and thus for learner-specific adaptation. The results of this study indicate, first, that only certain areas are crucial for a correct solution when extracting information from diagrams and, second, that the application of mathematical procedures plays a crucial role in interpreting graphs of different physics quantities. These findings thus provide insight into the visual strategies involved in interpreting kinematic diagrams and can also serve as a basis for eye tracking-based adaptation of problem-solving processes, in which adaptation can occur even before an incorrect answer is given.
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This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions. 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 and tablets, simulations, and digital tools for communication, collaboration, and 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.
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