Four Types of LLM Reliance and Their Predictors Among Undergraduate Writers: A Mixed-Methods Study at a Minority-Serving R1 University

Hossain (2026) develops a typology of LLM reliance among undergraduate writers at a minority-serving R1 institution, identifying four distinct profiles: strategic scaffolders who use AI for idea generation and structure, critical editors who revise AI output substantially, passive acceptors who submit AI-generated text with minimal changes, and uncritical delegators who offload entire assignments. The mixed-methods design combines survey data with qualitative interviews, revealing that self-efficacy and prior academic preparation are the strongest predictors of the reliance type. The Over Reliance types (passive acceptors and uncritical delegators) were disproportionately represented among students with lower writing self-efficacy, raising Equity concerns. The findings directly inform AI Literacy curriculum design by identifying which student populations need targeted support. The study contributes to Writing Education research by mapping how Student Experience of AI writing tools varies across a diverse student body, challenging one-size-fits-all AI policies in Higher Ed.

Connected Concepts

Over Reliance

Equity

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Citation

Shahin Hossain (2026). Four Types of LLM Reliance and Their Predictors Among Undergraduate Writers: A Mixed-Methods Study at a Minority-Serving R1 University. arXiv:2606.28749. cs.CY / cs.AI / cs.HC.