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

Area of Science:

• Educational Technology
• Higher Education Studies
• Artificial Intelligence in Education

Background:

• Limited empirical evidence exists on student experiences with AI in Latin American higher education.
• Understanding the emotional, cognitive, and ethical dimensions of AI adoption is crucial for effective integration.
• This study addresses the gap in understanding student ambivalence towards AI tools in academic settings.

Purpose of the Study:

• To examine AI adoption patterns among engineering students in Chile.
• To investigate the perceived usefulness and ambivalent experiences associated with AI tools for academic learning.
• To identify emotional, cognitive, and ethical tensions arising from AI engagement.

Main Methods:

• A mixed-methods approach was employed, combining quantitative and qualitative analyses.
• A questionnaire with closed and open-ended questions was administered to 170 engineering students.
• Quantitative analysis identified adoption rates and perceived usefulness; qualitative analysis explored emerging tensions.

Main Results:

• High AI adoption (73.5%) was observed, primarily driven by perceived usefulness in saving time and improving work.
• Students reported positive overall perceptions but exhibited deep ambivalence.
• Concerns included ethical issues (plagiarism), cognitive dependence, and technical reliability.

Conclusions:

• Effective AI integration in higher education requires more than technological access; it necessitates institutional strategies.
• Promoting critical digital literacy, clear policies, and support programs is essential for ethical and equitable AI adoption.
• Institutional strategies must address competency and gender gaps to ensure AI enhances learning without hindering critical thinking development.