Ethical Conditions for University Students' Adoption of Large Language Models in Exam Preparation Contexts

Synthesis: Pérez-Portabella, Arias-Oliva, Padilla-Castillo, and de Andrés-Sánchez (2026) use the Multidimensional Ethics Scale with 151 Spanish undergraduates to test whether ethical perceptions shape intention to use large language models for exam preparation and, in turn, actual use. Necessary Condition Analysis shows all three ethical dimensions (moral equity, consequentialism, deontology) are necessary conditions for intention to use, while PLS-SEM finds only consequentialist and deontological judgments are sufficient predictors; intention is both a necessary and a strong sufficient predictor of actual use. The results position ethical reasoning as central to responsible Large Language Models (LLMs) adoption in assessment contexts.

Key Findings

• All three ethical dimensions are necessary conditions for forming the intention to use LLMs for exam preparation (moral equity d = 0.338, consequentialism d = 0.274, deontology d = 0.207, all p < 0.001).
• Only consequentialism (β = 0.350) and deontology (β = 0.329) had significant sufficient effects on intention; moral equity did not (β = 0.108, p = 0.414).
• Intention to use is both a necessary (d = 0.325) and a very strong sufficient predictor of actual use (β = 0.905, p < 0.001).
• Students apply multiple normative ethical frames rather than a single moral stance when deciding whether to adopt LLMs in assessment contexts.

Implications for AI in Education

The study reframes academic-integrity conversations around the ethical reasoning students actually deploy rather than rule compliance alone. Because consequentialist and deontological judgments drive intention, institutions may support responsible use by making the ethical stakes of LLM use in assessment explicit and by cultivating students' capacity to reason across normative frameworks, complementing code-based approaches to Academic Integrity and AI Use and Disclosure Statements. It also links ethical perception to the technology-acceptance tradition, showing that moral considerations operate alongside perceived usefulness and ease of use in shaping adoption.

Connected Concepts

• Ethics
• Academic Integrity
• AI Use and Disclosure Statements
• Technology Adoption Models
• Generative AI
• Higher Education

Connected Articles

• [genai-chatgpt-adoption-ethics-students-2026] — students' ethical considerations in GenAI adoption
• [socrates-students-instructors-llms-lbt-2025] — student and instructor stances toward LLM use

Citation

Pérez-Portabella, A., Arias-Oliva, M., Padilla-Castillo, G., & de Andrés-Sánchez, J. (2026). Ethical conditions for university students' adoption of large language models in exam preparation contexts. Computers and Education Open, 10, 100323.