From Passive Consumption to Active Interaction: Exploring Interactive LLM Scaffolding to Support Learning Engagement
This work addresses the problem of passive consumption of LLM-generated learning content for students, aiming to improve active engagement and learning outcomes.
This paper investigates the impact of embedding interactive components into LLM-generated scaffolding to enhance learning engagement. The study found that interactive scaffolding increased perceived engagement and attentional focus, while also supporting short-term learning performance.
Large Language Models (LLMs) are increasingly used as learning companions, providing scaffolded explanations, hints, or step-by-step guidance. However, in current LLM-based learning scenarios, scaffolded content is primarily consumed passively, offering limited support for active learner engagement. Learning science research suggests that effective educational scaffolding depends not only on what support is provided, but also on how learners engage with it. In this work, we explore whether embedding lightweight interactive components into LLM-generated scaffolding responses can promote learning-oriented engagement and improve short-term learning outcomes. We evaluated this approach through a within-subjects laboratory study (N=8). Results provide initial evidence that interactive scaffolding increases learners' perceived engagement and attentional focus, while supporting short-term learning performance. We conclude with design implications for integrating interaction into LLM-generated scaffolding to support active learning engagement.