The Reliance Negotiation Framework: A Dynamic Process Model of Student LLM Engagement in Academic Writing
For educators and policymakers at minority-serving institutions, the RNF provides a more accurate model of student-LLM interaction, challenging static typologies and informing AI literacy pedagogy and academic integrity policy.
Existing frameworks fail to capture the dynamic, within-student variability of LLM engagement in academic writing. This study introduces the Reliance Negotiation Framework (RNF), developed from a mixed-methods study of 382 undergraduates, which models reliance as an ongoing negotiation among four inputs, with a Two-Model Architecture for 13.0% of participants whose ethical commitments preclude negotiation.
Student engagement with large language models (LLMs) in academic writing is not a stable trait, an adoption decision, or a competency level; it is a continuously negotiated process that existing frameworks cannot adequately theorize. Typological models provide categories without mechanisms; technology acceptance models explain adoption but not post-adoption quality; AI literacy frameworks treat competency as a static predictor rather than a live input. None accounts for within-student variability across tasks, the developmental paradox whereby experience produces habituation rather than sophistication, or principled non-use as a form of ethical reasoning. This article introduces the Reliance Negotiation Framework (RNF), developed from a sequential explanatory mixed-methods study of 382 undergraduates at a public minority-serving institution in the United States (survey, N = 382; 14 semi-structured interviews; three qualitative survey strands; 1,435 coded instances). The RNF reconceptualizes LLM reliance as an ongoing negotiation among four concurrent inputs (perceived benefits, perceived risks, ethical commitments, and situational demands) with outputs that recursively modify subsequent decisions. A Two-Model Architecture accommodates the 13.0% of participants whose categorical ethical commitments foreclose negotiation entirely. The framework generates four falsifiable predictions with implications for AI literacy pedagogy, academic integrity policy, and equity-centered practice at minority-serving institutions.