Students’ Perceptions of AI in Education

Author

Inam Khan

How Students from Different Majors Perceive AI in Education

How do university students perceive the usefulness of AI in education, and why do those perceptions differ by field of study?
Drawing on a 2023 Kaggle survey of ~1,200 cybernetics undergraduates, this project cleans and analyzes self‑reported data on AI knowledge, utility, and concerns. The headline result shows that STEM‑leaning majors (Economic Informatics and Economic Cybernetics) are nearly twice as likely to rate AI’s educational utility at the top of the scale (scores 8–10) compared with their peers in Statistics & Forecasting. At the same time, roughly 40 % of all students—regardless of major—still fear AI could replace teachers, underscoring a tension between optimism and caution. By visualizing these contrasts and linking them to knowledge levels and demographic factors, the project highlights where universities must address skepticism while leveraging students’ enthusiasm for AI‑enhanced learning.

Key Takeaways

  • STEM students show higher trust in AI: Students in Economic Informatics and Economic Cybernetics are significantly more likely to rate AI’s usefulness in education as high (scores 8–10).

  • Skepticism persists among Statistics students: Respondents from Statistics & Forecasting are less enthusiastic, reflecting a trust gap based on field of study.

  • Utility ≠ full acceptance: While AI is perceived as useful, many students still express concerns about job replacement and fairness—especially those with lower AI knowledge.

  • Clear need for targeted education: Bridging knowledge gaps and addressing ethical concerns could accelerate adoption and trust in AI-assisted learning tools.