Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/336607 
Year of Publication: 
2025
Series/Report no.: 
Discussion Paper No. 557
Publisher: 
Ludwig-Maximilians-Universität München und Humboldt-Universität zu Berlin, Collaborative Research Center Transregio 190 - Rationality and Competition, München und Berlin
Abstract: 
We study how AI tutoring affects learning in higher education through a randomized experiment with 334 university students preparing for an incentivized exam. Students either received only textbook material, restricted access to an AI tutor requiring initial independent reading, or unrestricted access throughout the study period. AI tutor access raises test performance by 0.23 standard deviations relative to control. Surprisingly, unrestricted access significantly outperforms restricted access by 0.21 standard deviations, contradicting concerns about premature AI reliance. Behavioral analysis reveals that unrestricted access fosters gradual integration of AI support, while restricted access induces intensive bursts of prompting that disrupt learning flow. Benefits are heterogeneous: AI tutors prove most effective for students with lower baseline knowledge and stronger self-regulation skills, suggesting that seamless AI integration enhances learning when students can strategically combine independent study with targeted support.
Subjects: 
AI Tutors
Large Language Models
Self-regulated Learning
Higher Education
JEL: 
C91
I21
D83
Document Type: 
Working Paper

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