Exploring the Role of Attitudes and Motivation in Shaping Generative AI Self-EfficacyAmong College Students
Author : Ya-Ping Shih, Yu-chu Yeh, Princy Pappachan, Xingzi Yu
Abstract :With the growing integration of generative artificial intelligence (generative AI) tools in education, understanding the psychological factors that influence college students’ self-efficacy in using generative AI has become increasingly important. This study investigates the relationship between college students’ generative AI use motivation (AIM), attitudes toward generative AI use (AIA), and generative AI self-efficacy (AIE). Inventory investigation through SurveyCake was employed in this study and structural equation modeling was employed to examine the hypothesized relationships among the variables. The results indicated that students with more positive AIA and stronger AIM exhibited higher AIE. Specifically, students who approached generative AI with a mindful, deep learning orientation and demonstrated strong intrinsic motivation were more likely to believe in their ability to use generative AI effectively for academic tasks. These findings suggest that promoting positive attitudes and motivation toward generative AI is key to enhancing students’ self-efficacy. Therefore, it is essential for educators to intentionally design course experiences that cultivate these psychological traits
Keywords :Generative AI, self-efficacy, student motivation, attitudes toward AI, deep learning Intrinsic motivation, psychological factors, AI in education, structural equation modeling Ask ChatGPT
Conference Name :International Conference on Computer Science and Artificial Intelligence (ICCSAI-25)
Conference Place Tokyo, Japan
Conference Date 2nd Jul 2025