Discipline-Sensitive Generative AI in Higher Education

Generative artificial intelligence in higher education refers here to the use of computational systems that produce text, code, explanations, feedback-like responses, images, and other outputs from user prompts in university learning, coursework, assessment, and student study practices. This entry focuses on how students use generative AI while studying, preparing assignments, seeking explanations, revising work, programming, brainstorming, or responding to assessment tasks. It defines such use as a situated educational practice shaped by disciplinary expectations, assessment design, AI literacy, study habits, and academic integrity norms. From this perspective, the same AI-supported action may be acceptable as learning support in one course, ambiguous in another, and inappropriate when it conceals authorship, fabricates evidence, or substitutes for independent academic performance.