Attitude of Engineering Students on AI System
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Abstract
This study explores the attitudes of engineering students toward artificial intelligence (AI) systems, addressing a critical gap in understanding how this demographic engages with and adapts to emerging technologies. Rooted in theories such as the Theory of Planned Behavior and the Multicomponent Model of Attitudes, the study highlights the cognitive, affective, and behavioral dimensions of student engagement with AI. Employing a descriptive quantitative research design, data were collected from 254 engineering students using a stratified random sampling technique. A validated questionnaire on a five-point Likert scale was administered online, and the results were analyzed using statistical methods, including reliability tests and structural equation modelling. The findings reveal generally positive attitudes toward AI, with cognitive engagement and self-efficacy improving as students progress academically. However, gender-based disparities in AI literacy and self-efficacy suggest the need for tailored educational interventions. Despite moderate levels of behavioral engagement, students demonstrated significant readiness to adopt AI systems, with AI literacy being the most influential factor shaping attitudes. The study concludes that integrating AI into engineering curricula can enhance student preparedness for technology-driven professions while addressing disparities to promote equitable learning experiences. These findings provide actionable insights for improving AI education in engineering contexts.
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