# The impact of university students' AI attitudes on AI-assisted creativity: the mediating role of AI usage motivation and the moderating role of AI dependency

## TL;DR

This study explores how university students' attitudes toward AI affect their creativity when using AI tools, with motivation and dependency on AI playing key roles.

## Contribution

The study introduces a model showing how AI usage motivation mediates and AI dependency moderates the relationship between AI attitudes and creativity.

## Key findings

- AI attitudes positively affect AI-assisted creativity through usage motivation.
- Identified regulation is the strongest mediator of this relationship.
- AI dependency weakens intrinsic motivation's effect but strengthens external regulation's impact on creativity.

## Abstract

With the growing use of artificial intelligence (AI) in higher education, understanding how students develop creativity in AI-assisted learning environments has become increasingly important. This study examines how students' attitudes toward AI influence their AI-assisted creativity, focusing on the mediating role of AI usage motivation and the moderating role of AI dependency. The research is informed by the Theory of Planned Behavior and Self-Determination Theory.

Data were collected through a questionnaire survey of 347 university students. Structural equation modeling and bootstrap methods were used to test the relationships among AI attitudes, usage motivation (intrinsic motivation, identified regulation, and external regulation), AI dependency, and AI-assisted creativity.

The results show that AI attitudes have a significant positive effect on AI-assisted creativity, and this relationship is fully mediated by the three types of usage motivation. Among them, identified regulation serves as the strongest mediator. The moderating role of AI dependency differs across motivation types. Higher AI dependency weakens the positive effect of intrinsic motivation on creativity but strengthens the effect of external regulation, while the pathway through identified regulation remains largely stable.

These findings highlight the importance of motivation internalization in promoting creativity in AI-assisted learning contexts. The results suggest that encouraging more self-endorsed forms of motivation may help students use AI tools more creatively, offering theoretical insights and practical guidance for integrating AI into higher education to support student creativity.