Abstract
The purpose of this study was to investigate the effects of different types of cues and self-explanation prompts in instructional videos on intrinsic motivation, learning engagement, learning outcomes, and cognitive load, which were indicators to measure deep learning performance. Seventy-two college students were randomly assigned to one of the six conditions in a 3 × 2 factorial design with cues (visual vs. textual vs. combined textual-&-visual) and self-explanation prompts (prediction vs. reflection) as the between-subjects factors. To measure participants’ learning engagement, Neurosky mindwave mobile and Tobii pro X3-120 eye-tracker were used to collect their brain wave data and eye movement data, respectively. Learning outcomes were measured with retention and transfer tests, and questionnaires were used to measure participants’ intrinsic motivation and cognitive load, respectively. The results revealed that the textual cues significantly facilitated learning outcomes and learning engagement—attention–while the reflection prompts significantly affected learning engagement—the mean fixation duration—and cognitive load. Notably, the combination of textual cues and reflection prompts and the combination of visual cues and prediction prompts allowed the participants to focus and engage in the video learning process more deeply, resulting in a significantly higher learning outcome than their peers from other conditions. This research could provide some implications for designing short instructional videos to facilitate deep learning.
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This study was supported by the Jiangsu Social Science Foundation Youth Project (20JYC002) and the National Natural Science Foundation of China (62077030).
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Zheng, X., Ma, Y., Yue, T. et al. Effects of different types of cues and self-explanation prompts in instructional videos on deep learning: evidence from multiple data analysis. Education Tech Research Dev 71, 807–831 (2023). https://doi.org/10.1007/s11423-023-10188-2
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DOI: https://doi.org/10.1007/s11423-023-10188-2