Approaching learning satisfaction: Factors influencing educational video learning

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.

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Publication Details

Journal
Education and Information Technologies
Published
2026-04-27
DOI
https://doi.org/10.1007/s10639-026-13996-0
Primary Topic
Visual and Cognitive Learning Processes
Type
article
Field-Weighted Citation Impact
0.00

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article

Approaching learning satisfaction: Factors influencing educational video learning

Tara Barnhart, Douglas Havard, Fei Wang
Education and Information Technologies
Visual and Cognitive Learning Processes
article

Approaching learning satisfaction: Factors influencing educational video learning

Tara Barnhart, Douglas Havard, Fei Wang
article en

Abstract

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.

Education and Information Technologies
Chapman University (US), Sanda University (CN)
Chapman University
Quality Education
Openalex Percentile: Top 12%
Visual and Cognitive Learning Processes
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