Self-explanation prompts in video learning: an optimization study

The self-explanation strategy motivates learners to actively select and integrate information, thereby fostering meaningful learning. To generate comprehensive and insightful explanations, learners often require support. However, there is a limited understanding of the optimal form of self-explanation that effectively assists learners in applying this strategy in video learning environments. This study tests various self-explanation prompts, using multiple indicators, including learning outcomes, cognitive load, intrinsic motivation, and engagement, to measure effects. Participants (n = 143) were randomly assigned to five conditions: No Strategy, Focused, Visual Scaffold, Fill-in-blank Scaffold, and Rewrite Scaffold. Results indicate that scaffolded self-explanation prompts enhance learning performance and notably reduce cognitive load, with the Fill-in-blank scaffold demonstrating significant advantages. However, the impact on intrinsic motivation and engagement is not clearly pronounced. To optimize self-explanation strategy’s effectiveness, it is recommended to provide tailored support based on content difficulty and learners’ proficiency levels, facilitating active participation at a balanced cognitive load level.