Griffin Pitts, Neha Rani, Weedguet Mildort, Eva-Marie Cook
AI assistants are changing education. But with help comes risk.
In “Students’ Reliance on AI in Higher Education: Identifying Contributing Factors,” researchers from the University of Florida studied how students use AI tools to solve programming problems.
They didn’t just look at whether AI helps; they asked when students trust it too much, when they ignore it, and what makes them use it well.
5 Key Takeaways for Education Leaders
Reliance Is Not One Thing. The study defines three types of reliance: Appropriate reliance: Accept good advice, reject bad; Overreliance: Accept bad advice; Underreliance: Reject good advice.
Skill and Mindset Matter. Students with strong programming knowledge, confidence, and curiosity did better. They evaluated AI help carefully.
Trust Can Backfire. Overreliance wasn’t tied to students’ skills before the task. It grew during the task as trust and satisfaction with the AI increased.
The “False-Confidence Loop”. Students who trusted the AI too much accepted wrong answers without checking. Positive early experiences led to blind trust.
We Need Reflection and Teaching. Many students noticed they were overrelying. That self-awareness can be used. Educators can design prompts and activities to help students think critically about AI outputs.
Conceptual Framework for AI in Education
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