From AI Anxiety to Strategic Regulation: How University Students Transform Generative AI into a Strategic Learning Resource

Eunjeo Kim (2026) examined how university students engage with generative AI as a strategic learning resource in academic writing tasks, focusing on the role of AI anxiety. Using an explanatory sequential mixed-methods design, the study collected survey data and post-task written reflections from 107 university students.

Key Findings

• AI anxiety is productive, not just a barrier: Higher AI anxiety was positively associated with verification and revision behaviors (β=.24, p<.01). Students worried about plagiarism or accuracy were more likely to question every AI sentence, cross-check sources, and revise rather than accept output uncritically.
• Evaluative capacity drives active engagement: Evaluative capacity predicted revision and selective integration (β=.46, p<.001), while ethical awareness strengthened the translation of evaluation into active, responsible AI use (interaction β=.41, p<.01).
• Four regulatory types (N=107): Uncritical Reliance (18.7%), Selective Integration (34.6%), Evaluative Transformation (31.8%), and Strategic Rejection (14.9%). Effective AI use depended not on willingness to use the tool but on the capacity to question outputs, revise selectively, and maintain authorship responsibility. Uncritical reliance risks cognitive offloading, while the other modes reflect active self-regulated engagement.
• AI literacy as regulatory competence: The study frames AI Literacy in higher education less as technology acceptance and more as a form of regulatory competence grounded in evaluative judgment and ethical responsibility.

Implications for AI in Education

This work reframes AI anxiety from a negative construct to a potentially productive signal that encourages closer scrutiny and more deliberate regulation of AI use. It challenges adoption-centered models (like TAM) that treat use as a stable decision, arguing instead that AI use is an ongoing process of judgment, revision, and selective uptake during task performance. For Assessment and Academic Integrity design, it suggests that fostering evaluative capacity and ethical awareness — not merely reducing anxiety — is the key to promoting critical, responsible engagement with GenAI in writing tasks.

Connected Concepts

• Generative AI
• AI Literacy
• Higher Ed
• Student Experience
• Academic Integrity
• Ethics
• Self Regulated Learning
• Metacognition
• Critical Thinking
• Cognitive Offloading
• Feedback
• Assessment
• Plagiarism Detection
• Writing Education
• Technology Acceptance Model

Connected Articles

• Efficiency Gain Illusion AI Overreliance — The efficiency gain illusion: AI overreliance
• GenAI Over Reliance Learning 2026 — GenAI over-reliance and learning
• Students LLM Usage Critical Thinking — Characterizing Students' LLM Usage Behaviors in Critical Thinking Tasks
• Critical Thinking GenAI Scaffolding — Scaffolding Critical Thinking with Generative AI

Citation

Kim, E. (2026). From AI anxiety to strategic regulation: How university students transform generative AI into a strategic learning resource. Computers and Education: Artificial Intelligence, 10, 100622.