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UPSI Digital Repository (UDRep)
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| Abstract : Perpustakaan Tuanku Bainun |
| This study examined the relationship between college students_ perceptions of artificial intelligence-supported personalized learning experiences and their learning motivation in the context of higher education in China. The purpose of the study was to explore how students_ evaluations of perceived usefulness, perceived ease of use, interactivity, and technical support are related to different types of learning motivation. A quantitative survey design was employed, and data were collected from 365 Chinese university students who had experience using artificial intelligence-related learning tools after data screening. Descriptive statistics, correlation analysis, and multiple regression analysis were conducted. Reliability analysis showed satisfactory internal consistency for all measurement scales with Cronbach alpha values ranging from 0.79 to 0.92. The findings indicated that students generally reported positive perceptions of artificial intelligence-supported personalized learning experiences with mean scores above 3.80 on a five-point Likert scale. Regression results revealed that interactivity was the strongest predictor of learning motivation with _ = 0.42 and p < .001, followed by technical support with _ = 0.31 and p < .001. Perceived usefulness showed a moderate but significant effect with _ = 0.18 and p < .01, while perceived ease of use demonstrated a weak and in some models non-significant effect with _ = 0.06 and p > .05. These results suggest that interaction quality and reliable technical support play a more important role in enhancing learning motivation than system usability alone. In conclusion, this study provides empirical evidence that students_ perceptions of artificial intelligence-supported personalized learning experiences are closely associated with their learning motivation and offers practical implications for the design and improvement of technology-enhanced learning environments in higher education. |
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