Generative <scp>AI</scp> ‐Supported Student Video Creation in Communication Education: A Mixed‐Methods Study of Learning Motivation, Career Confidence and Creativity

Abstract

ABSTRACT Generative AI is rapidly entering communication education and reshaping how students create video‐based messages, yet evidence remains limited on how AI adoption relates to learning motivation, career confidence and creativity in communication programs. To fill this void, this mixed‐methods study draws on the UTAUT and Self‐Determination Theory to frame regression models. It analyzes survey data from 768 undergraduates at three Chinese universities and further supplements the quantitative findings with thematic analysis of 20 semi‐structured interviews. Findings show that higher generative AI adoption is positively associated with learning motivation ( β = 0.723, p &lt; 0.001) and career confidence ( β = 0.849, p &lt; 0.001); interview data further indicate a creativity tension, whereby AI supports efficiency and experimentation while also prompting concerns about standardisation, diminished originality and reliance on AI outputs. This study advances research on technology adoption in communication education by highlighting students' dual experiences of empowerment and constraint, and it suggests that AI integration in video creation should combine tool training with structured evaluation and reflective practices to sustain creativity while supporting career development.

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