Not All Students Engage Alike: Multi-Institution Patterns in GenAI Tutor Use

Authors: Youjie Chen, Xixi Shi, Xinyu Liu, Shuaiguo Wang, Tracy Xiao Liu, Dragan Gašević Year: 2026 Venue: arXiv (cs.CY)

Summary

Large-scale analysis (N=11,406, 200 classes, 10 institutions) of GenAI tutor engagement. Four engagement types; 10.4% shallow with copy-paste. Students at selective institutions more likely to engage deeply.

Key Contributions

Large-scale analysis (N=11,406, 200 classes, 10 institutions) of GenAI tutor engagement. Four engagement types; 10.4% shallow with copy-paste. Students at selective institutions more likely to engage deeply.

Connections

• intelligent-tutoring

• student-experience

• learning-analytics

• ai-tutor-effectiveness-review

• ai-tutor-behavioral-evaluation

Related Pages

• simulating-learner-task-selection — Different task-selection strategies produce distinct engagement outcomes in tutoring systems

• engagement-forecasting-its — Feature-based engagement forecasting reduces MAE 22-33% vs heuristics; effort dr

• affective-text-wearable-student-health — Affective dimensions in student language predict physiological health outcomes

• students-llm-usage-critical-thinking — Student-initiated LLM use vs. tutor-driven interaction

Citation

Youjie Chen et al. (2026). Not All Students Engage Alike: Multi-Institution Patterns in GenAI Tutor Use. arXiv:2602.00447. cs.CY.