Personalized Multimodal Feedback Using Multiple External Representations: Strategy Profiles and Learning in High School Physics

Abstract

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.

Questions this source addresses

• How does elaborated feedback across verbal, graphical, and mathematical representations relate to post-test performance in high school physics?
• What do these findings imply for designing adaptive, multimodal feedback in intelligent tutoring systems that use large language models?
• What representation-selection strategies do students adopt when given feedback in multiple external representation formats, and how do these strategies differ by representational competence?
• Why does using a diverse set of representations benefit students with lower representational competence more than those with higher competence?