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and conference attendants at the NBER IO conference, the HBS Platform Strategy Conference, and the NBER workshop on Electric and Autonomous Vehicles. All errors are ours. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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This study aimed to investigate the impact of using ChatGPT as an auxiliary learning tool on university students' learning motivation. Structural equation modeling and regression analysis were employed as the data analysis methods. Questionnaire surveys were conducted to collect data on 196 university students. The results indicated that after using ChatGPT, a negative correlation was found between tension-pressure and interestenjoyment. Perceived competence was significantly positively correlated with interest-enjoyment, while the correlation between perceived value and interest-enjoyment was insignificant. These three variables were found to have varying degrees of influence on interest-enjoyment in the regression analysis. The study concluded that ChatGPT had a certain impact on learning motivation, but university students' frequency of use and proficiency was relatively low, requiring further training. The significance of this study lies in providing a new pedagogical approach that enables students to keep up with contemporary trends. The findings of this study have substantial theoretical and practical implications, offering novel perspectives and avenues for research on university students' learning motivation and contributing to educational reforms by providing valuable insights and directions.