Short Video Platforms for Learning: What Drives Undergraduates' Satisfaction and Continued Use in Chengdu

Abstract

Purpose: This study develops a structural model to examine factors influencing student satisfaction and continuance intention in using short video platforms for educational purposes. Given the rapid growth of the short video industry, the research provides a reference framework for understanding technology adoption in digital learning. Research design, data and methodology: A quantitative approach was adopted using an online questionnaire distributed to 500 liberal arts students at Geely University in Chengdu, China. Non-probability sampling included judgment, quota, and convenience methods. Confirmatory Factor Analysis (CFA) assessed reliability and model fit, while Structural Equation Modeling (SEM) examined relationships among constructs. Results: SEM analysis confirmed all six hypotheses. Perceived usefulness (β = 0.284), perceived enjoyment (β = 0.168), product novelty (β = 0.155), and privacy protection behavior (β = 0.224) significantly affected satisfaction. Satisfaction (β = 0.348) and informational social influence (β = 0.223) positively influenced continuance intention. Conclusions: The findings offer practical guidance for educators, platform designers, and content developers. Enhancing content usefulness, enjoyment, novelty, and privacy measures can significantly improve learner satisfaction. Moreover, fostering a socially supportive learning environment encourages sustained engagement with short video platforms, ultimately improving digital learning outcomes.