Artificial Intelligence (AI) enhances educational experiences in engineering but varies in effectiveness based on student personality traits. This study investigates the impact of personality traits on engineering students’ perceptions of Artificial Intelligence (AI) to optimize AI integration in university courses. Data was collected from students enrolled in two engineering courses during the Academic Year 2023–24. The analysis focused on the Big Five personality traits and various AI perception dimensions. Considering different levels of multivariate regression analysis, we identified key personality traits influencing students’ attitudes towards AI. The findings suggest that tailoring AI integration to students’ personality profiles can enhance engagement and learning outcomes. Future research should explore additional factors, such as age and attitudes towards technical roles, to further refine educational strategies.
Optimizing AI Involvement in Engineering University Courses Based on Students' Personality
Filippi, Stefano
Primo
2024-01-01
Abstract
Artificial Intelligence (AI) enhances educational experiences in engineering but varies in effectiveness based on student personality traits. This study investigates the impact of personality traits on engineering students’ perceptions of Artificial Intelligence (AI) to optimize AI integration in university courses. Data was collected from students enrolled in two engineering courses during the Academic Year 2023–24. The analysis focused on the Big Five personality traits and various AI perception dimensions. Considering different levels of multivariate regression analysis, we identified key personality traits influencing students’ attitudes towards AI. The findings suggest that tailoring AI integration to students’ personality profiles can enhance engagement and learning outcomes. Future research should explore additional factors, such as age and attitudes towards technical roles, to further refine educational strategies.File | Dimensione | Formato | |
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