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<p>As video lectures have become an important way for online learning, the learning strategy is one of the important factors that affect the quality of learning. This study investigated the effects of three generative learning strategies (learner-generated explanations, learner-generated drawings, and imagining) on learners’ cognitive load, judgment of learning, learning engagement, learning performance and learning efficiency, compared to the control group.A total of 160 undergraduate students were randomly allocated to one of the four groups (three experimental groups and one control group) and watched the same video lectures about chemistry. Students in the three experimental groups were asked to engage in learning activities tailored to the learning strategy prompts provided in the pause segments of the videos and to complete all measurements. Students in the control group just watched the video without any prompts.Compared with control and imagining, learner-generated explanations and drawings improved engagement, performance, and learning efficiency and showed distinct patterns across intrinsic, extraneous, and germane cognitive load. Judgments of learning improved only for learner-generated explanations, whereas imagining showed no reliable benefits.This study provides empirical evidence to the impact of different generative learning strategies on students’ video learning.</p>

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Which generative strategy works best? examining explanations, drawings, and imagining in video lectures

  • 期刊论文

  • 发表日期：

    2026年4月11日

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  • Qian Huangfu,
  • Zixuan Wang,
  • Yuman Li,
  • Liping Zhu,
  • Yujia Guo

摘要

As video lectures have become an important way for online learning, the learning strategy is one of the important factors that affect the quality of learning. This study investigated the effects of three generative learning strategies (learner-generated explanations, learner-generated drawings, and imagining) on learners’ cognitive load, judgment of learning, learning engagement, learning performance and learning efficiency, compared to the control group.A total of 160 undergraduate students were randomly allocated to one of the four groups (three experimental groups and one control group) and watched the same video lectures about chemistry. Students in the three experimental groups were asked to engage in learning activities tailored to the learning strategy prompts provided in the pause segments of the videos and to complete all measurements. Students in the control group just watched the video without any prompts.Compared with control and imagining, learner-generated explanations and drawings improved engagement, performance, and learning efficiency and showed distinct patterns across intrinsic, extraneous, and germane cognitive load. Judgments of learning improved only for learner-generated explanations, whereas imagining showed no reliable benefits.This study provides empirical evidence to the impact of different generative learning strategies on students’ video learning.