Abstract

This study explores student perceptions towards artificial intelligence through qualitative and quantitative analysis of student reflections on AI use, focused on how their views shape learning and career preparation. The research addresses a critical gap in understanding alignment between student AI adoption patterns and evolving industry demands. A cross-sectional survey of 219 undergraduate students across diverse academic majors employed automated text analysis and topic modeling to examine planned AI applications and perceived professional transformations. Findings demonstrate that while students exhibit high AI readiness levels, significant misalignments exist between academic AI use and professional requirements. Students predominantly focus on basic applications—data analysis, content generation, and tutoring—while industries increasingly demand sophisticated AI integration, real-time decision support, and ethical compliance frameworks. Ethical considerations received minimal attention across majors. The research reveals concerning over-reliance tendencies, with students treating AI as capability enhancers rather than tools with limitations. These findings contribute by identifying specific gaps in AI education and providing evidence for curriculum reform needs.

Download

Abstract Only

Share

COinS