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<p>The rapid expansion of digital education has accelerated the use of online instructional videos, yet variability in video design and production quality continues to shape learners’ engagement and satisfaction. This study developed and tested a structural equation model to examine predictors of undergraduates’ satisfaction with educational videos. Using survey data from 964 students, learning satisfaction was positively predicted by image clarity (β = 0.381, <i>p</i> &lt; 0.001), learning motivation (β = 0.18, <i>p</i> = 0.006), and interactive behavior (β = 0.182, <i>p</i> = 0.011). In contrast, video attachment tools showed a small negative direct association with satisfaction (β = −0.116, <i>p</i> = 0.042). Teacher performance and video attachment tools influenced satisfaction indirectly by shaping learners’ motivation and interactive behavior. These relationships were robust across both maximum likelihood and ordinal DWLS estimations. Although learning self-efficacy and learning barriers did not directly predict satisfaction, self-efficacy exerted its influence through motivation, while learning barriers operated through interactive behavior, highlighting distinct affective and behavioral mechanisms. Overall, the model identifies three interrelated dimensions of satisfaction—perceived video quality, intrinsic affective response, and extrinsic behavioral engagement. Practically, the findings suggest prioritizing high visual clarity, carefully designing attachment features (e.g., captions, playback controls) to minimize cognitive and usability burden, and incorporating instructor presence to strengthen motivation and interaction in video-based instruction.</p>

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Approaching learning satisfaction: Factors influencing educational video learning

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月27日

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  • Fei Wang,
  • Douglas Havard,
  • Tara Barnhart

摘要

The rapid expansion of digital education has accelerated the use of online instructional videos, yet variability in video design and production quality continues to shape learners’ engagement and satisfaction. This study developed and tested a structural equation model to examine predictors of undergraduates’ satisfaction with educational videos. Using survey data from 964 students, learning satisfaction was positively predicted by image clarity (β = 0.381, p < 0.001), learning motivation (β = 0.18, p = 0.006), and interactive behavior (β = 0.182, p = 0.011). In contrast, video attachment tools showed a small negative direct association with satisfaction (β = −0.116, p = 0.042). Teacher performance and video attachment tools influenced satisfaction indirectly by shaping learners’ motivation and interactive behavior. These relationships were robust across both maximum likelihood and ordinal DWLS estimations. Although learning self-efficacy and learning barriers did not directly predict satisfaction, self-efficacy exerted its influence through motivation, while learning barriers operated through interactive behavior, highlighting distinct affective and behavioral mechanisms. Overall, the model identifies three interrelated dimensions of satisfaction—perceived video quality, intrinsic affective response, and extrinsic behavioral engagement. Practically, the findings suggest prioritizing high visual clarity, carefully designing attachment features (e.g., captions, playback controls) to minimize cognitive and usability burden, and incorporating instructor presence to strengthen motivation and interaction in video-based instruction.