Date
Publisher
arXiv
Multiple external representations (MERs) and personalized feedback support physics learning, yet evidence on how personalized feedback can effectively integrate MERs remains limited. This question is particularly timely given the emergence of multimodal large language models. We conducted a 16-24 week observational study in high school physics (N=661) using a computer-based platform that provided verification and optional elaborated feedback in verbal, graphical and mathematical forms. Linear mixed-effects models and strategy-cluster analyses (ANCOVA-adjusted comparisons) tested associations between feedback use and post-test performance and moderation by representational competence. Elaborated multirepresentational feedback showed a small but consistent positive association with post-test scores independent of prior knowledge and confidence. Learners adopted distinct representation-selection strategies; among students with lower representational competence, using a diverse set of representations related to higher learning, whereas this advantage diminished as competence increased. These findings motivate adaptive feedback designs and inform intelligent tutoring systems capable of tailoring feedback elaboration and representational format to learner profiles, advancing personalized instruction in physics education.
Study at a glance
- Question: How do students' choices of multimodal feedback formats relate to their physics learning and initial skills?
- Setting and data: High schools across four German federal states, grades 10 and 11, 2023–2024, 661 students completing pre- and post-tests.
- Method: Prospective observational cohort study using linear mixed-effects regression, k-means clustering, and ANCOVA.
Why it matters
Personalized feedback and multiple representations support physics learning, but evidence on how feedback can effectively combine modalities remains limited. Understanding these strategies is especially timely with the emergence of multimodal large language models.
Key findings
- Using elaborated multirepresentational feedback was positively associated with post-test scores in both student cohorts, regardless of prior knowledge or confidence.
- Students with lower initial representational competence achieved higher post-test scores when alternating across verbal, graphical, and mathematical feedback rather than relying primarily on verbal feedback.
- For students with higher initial competence, using additional feedback representations offered no detectable learning advantage over a verbal-dominant approach.
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