Navigating Ambivalence: Artificial Intelligence and Its Impact on Student Engagement in Engineering Education

Abstract

Artificial intelligence (AI) is rapidly transforming higher education, yet limited empirical evidence exists on how students experience the emotional, cognitive, and ethical tensions associated with AI, particularly in Latin American contexts. This study addresses this gap by examining patterns of adoption, perceived usefulness, and the ambivalent experiences that arise when engaging with AI tools for academic learning. A questionnaire combining closed and open-ended questions was administered to 170 engineering students from a Chilean public university. A mixed-methods design was used to analyse the data: quantitative analyses identified adoption patterns and perceived usefulness, while qualitative thematic analysis captured emerging emotional, ethical, and motivational tensions. The results showed high adoption (73.5%), driven by the pragmatic usefulness of saving time, understanding concepts, and improving work. Although the overall perception was positive, a deep ambivalence was identified, with enthusiasm and confidence coexisting with ethical (plagiarism), cognitive (dependence), and technical (reliability) concerns. It is concluded that the effective integration of AI transcends technological access and requires an institutional strategy that promotes critical digital literacy, clear policies, and support programmes that address competency and gender gaps, ensuring ethical and equitable adoption that enhances learning without compromising the development of critical thinking.

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