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Feedback is a promising intervention to foster students’ self-assessment accuracy (SAA), but the effect can vary depending on students‘ initial skill levels or prior performance. In particular, lower-performing students who are less accurate might benefit more from feedback in terms of SAA. To deepen our understanding, the present study investigated the mechanism and dependencies of feedback effects on SAA in the realm of large language models (LLMs). Within a randomized control experiment, we examined the effect of LLM-generated feedback on SAA by considering students’ initial performance and initial SAA as potential moderators. A sample of N = 459 upper secondary students wrote an argumentative essay in English as a foreign language and revised their text. After finishing their first draft (pretest) and revision (posttest) of the draft, students self-assessed their writing performance. Students in the experimental group received GPT-3.5-turbo-generated feedback on their first draft during their revision. In the control group, students could revise their text without feedback. Our results indicated no significant main effect of LLM-generated feedback on students’ SAA. Furthermore, we found a significant interaction effect between feedback and students‘ pretest SAA on SAA changes, indicating that lower-calibrated students improved their SAA with feedback more than students with similar pretest SAA and without feedback. Exploratory analyses revealed that students with higher pretest SAA did not improve their SAA with feedback and decreased their SAA. We discuss this nuanced evidence and draw implications for research and practice using LLM-generated feedback in education.
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Being able to comprehend informal arguments in scientific texts is important for scientific literacy in higher education. Successful intervention studies demonstrating that these skills can be trained in university students have not yet provided evidence that gains of explicit training can be maintained beyond immediate post-training assessment. In this study, we tested whether the gains in argument structure comprehension achieved using a self-directed, web-based training intervention could be maintained over several weeks as an indication of sustained improvement in scientific literacy. We also explored characteristics of students and their engagement with the training intervention that resulted in significant and sustained improvements of their argument structure comprehension skills. One hundred students took part in a voluntary supplement to their university courses, completing an online pretest, a 45-minute training session, a posttest (n = 88), and a followup test (n = 31). Training effects at posttest were compared with an active control group. The results suggest that the training group exhibited significant gains in argument structure comprehension. These gains were maintained across a four-week period. Students with low starting ability profited the most from the training and gains in argument comprehension were greatest for complex arguments. Training results were positively related to student motivation and this effect was fully mediated by their engagement with the training exercises. The results demonstrate that training gains can be maintained after immediate posttraining assessment and suggest that training is particularly effective for low-performing students, for complex arguments, and when students are motivated and engage with the training exercises.
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Background Teacher professional vision describes how teachers perceive classroom events, interpret these events, and form decisions about next strategies. As indicators of visual expertise, noticing, and reasoning, analyses of think-aloud protocols can offer useful insights into novice and expert teachers’ mental models of observed classroom management events. Aims Informed by the cognitive theory of visual expertise, the study compared two methods—a standard frequency-based approach and epistemic network analysis (ENA)—for analysing think-aloud data from novice and expert teachers. The aim was to illustrate the potential of both methods in revealing how teachers integrate noticed visual information and classroom management scripts into elaborate mental representations of classroom management events. Sample Participants were 19 pre-service and 20 in-service teachers. Methods Teachers’ think-aloud data after watching a video with critical classroom management events were coded and analysed using a standard frequency-based approach and epistemic network analysis. Results The frequency-based approach counted the number of codes, indicating that experts verbalized student learning, teacher behavioural management, and alternative management strategies more frequently than novices. In comparison, ENA visualized the temporal co-occurrences of codes within event-related utterances, indicating that novices struggled to make sense of events while experts were able to integrate information and scripts into more elaborate and well-structured mental models. Conclusions When compared to a frequency-based approach, ENA can provide deep insights into teachers‘ mental representations of classroom management events. ENA is thus a useful novel method to examine teachers’ integration of information into mental models as indicators of professional vision and expertise.
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Die beiden Schüler Ole Schenzer und Paul Keßler wurden 2025 mit ihrem Projekt „Wald der Zukunft – Waldbrandresilienz von heimischen Baumarten“ im BundesUmweltWettbewerb mit einem Sonderpreis ausgezeichnet. In einem Video berichten die beiden Jungforscher von ihrem Projekt und ihren Erfahrungen.
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Background The emotion regulation (ER) strategies that teachers use impact their personal well-being. As teachers gain job experience, they may select different, more adaptive strategies. Previous research has often focused on individual ER strategies, neglecting the combined use of multiple strategies. Aims We set out to understand how teachers use a range of different strategies to regulate negative emotions, measured at the daily level across two measurement bursts spaced six months apart, and how their ER strategy patterns are linked with job experience and occupational well-being. Sample Participants were NBurst1 = 268 and NBurst2 = 164 German primary and secondary school teachers. Method Our measurement-burst design involved daily-diary assessments of 12 ER strategies (acceptance, positive reappraisal, social support, situation modification, situation selection, expressive suppression, experience suppression, distraction, acting-out, self-blame, rumination, substance use) at two time points. We applied multilevel latent profile analyses to identify ER profiles at the person level. We explored profiles’ associations with occupational well-being, predicted profile membership by job experience, and looked into profile changes over time. Results Five ER profiles emerged, of which three were common and two unique to the two bursts, differing in the specific combination of strategies. Less experienced teachers were more likely to be in profiles characterized by avoidance strategies. Those profiles were also linked to lower affective well-being and more emotional exhaustion, and displayed lower stability over time. Conclusion Teachers use a wide variety of ER strategies which have implications for their occupational well-being.
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Background The emotion regulation (ER) strategies that teachers use impact their personal well-being. As teachers gain job experience, they may select different, more adaptive strategies. Previous research has often focused on individual ER strategies, neglecting the combined use of multiple strategies. Aims We set out to understand how teachers use a range of different strategies to regulate negative emotions, measured at the daily level across two measurement bursts spaced six months apart, and how their ER strategy patterns are linked with job experience and occupational well-being. Sample Participants were NBurst1 = 268 and NBurst2 = 164 German primary and secondary school teachers. Method Our measurement-burst design involved daily-diary assessments of 12 ER strategies (acceptance, positive reappraisal, social support, situation modification, situation selection, expressive suppression, experience suppression, distraction, acting-out, self-blame, rumination, substance use) at two time points. We applied multilevel latent profile analyses to identify ER profiles at the person level. We explored profiles’ associations with occupational well-being, predicted profile membership by job experience, and looked into profile changes over time. Results Five ER profiles emerged, of which three were common and two unique to the two bursts, differing in the specific combination of strategies. Less experienced teachers were more likely to be in profiles characterized by avoidance strategies. Those profiles were also linked to lower affective well-being and more emotional exhaustion, and displayed lower stability over time. Conclusion Teachers use a wide variety of ER strategies which have implications for their occupational well-being.
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Understanding the global cycling of carbon is critical to participate in the current public discussion on climate change in an informed manner. Fostering system thinking is key to reach this goal. Of the various influences on students’ development of system thinking in relation to the carbon cycle, the present study focuses on the influence of textbooks – both their explanatory texts and the activities they provide for students. Research-based information pertaining to ways students work on acquiring system thinking skills when solving textbook tasks on the carbon cycle is scarce. Therefore, this study investigates two research questions: (1) Which system thinking skills are addressed in German biology textbook tasks on the carbon cycle? and (2) Which entities and activities from different levels of biological organization do students deal with when working on the tasks? The second research question relates to the argument that the multi-level character of the carbon cycle causes particular learning difficulties for students. Following a qualitative content analysis, two coding schemes are developed and applied. The main results: the system thinking skills “identifying system organization” and “analyzing system behavior” are more frequently addressed than “system modeling”. The selection of entities and activities of the carbon cycle in the tasks depicts a variety of individual aspects but often does not allow a continuous tracing of dynamics in the carbon cycle along carbon flows. We suggest a greater emphasis on systems modeling in carbon cycle tasks and that the selection of entities and activities should support knowledge integration.
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Feedback is widely recognized as a key mechanism in educational psychology, shaping learning through cognitive, motivational, and emotional processes. Despite a rich body of research, core questions remain regarding when feedback is effective, why it works, and for whom it fosters meaningful learning. To examine the psychological and contextual mechanisms underlying feedback effectiveness, the studies included in this issue draw on diverse methodologies, including controlled experiments, longitudinal data in school settings, and log data analyses from digital learning platforms. Central themes include the role of learner characteristics in feedback reception, the emotional and motivational dimensions of feedback processing, the impact of design and delivery features, and the reciprocal dynamics between feedback providers and receivers. What emerges across these contributions is a view of feedback as a dialogic and interpretive process, embedded within broader sociocultural and instructional systems. Insights from neuroscience, digital learning environments, and achievement motivation research further advance theorizing on feedback processes and point toward new directions for empirically grounded, interdisciplinary inquiry. Building on these insights and informed by recent theoretical and empirical developments, we offer a model that conceptualizes feedback as a multilayered process—shaped by individual, contextual, and social dynamics, and unfolding across cognitive, emotional, and motivational dimensions. This model captures the complexity of feedback interactions and highlights how feedback can support learners’ ongoing development, both in terms of immediate learning outcomes and longer-term academic development. We outline how such an integrative perspective and interdisciplinary collaborations are necessary for developing feedback practices that are more targeted, responsive, and impactful for lasting educational growth.
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Gehöre ich dazu? Diese Frage beschäftigt viele Menschen in unterschiedlichen Lebenssituationen – ob in der Schule, im Studium oder später im Berufsleben. Besonders im MINT-Bereich spielt die Identität eine entscheidende Rolle: Wer sich mit Mathematik, Informatik, Naturwissenschaften und Technik identifiziert, traut sich oft mehr zu und bleibt langfristig motiviert.
Und wie können Bildungsangebote so gestaltet werden, dass sich alle Schüler*innen
