A Student-Centered Framework for Responsible Use of Generative AI in Higher Education

Synthesis: Alsammani (2026) proposes a student-facing framework for responsible Generative AI use in Higher Ed: ten actionable guidelines organized around three pillars — Learning and Growth, Ethics and Integrity, and Awareness and Safety. Drawing on a structured interpretive synthesis of 2023–2026 research and major policy frameworks, the paper argues the three pillars are jointly necessary because each addresses a distinct, empirically documented failure mode, and that portable student-facing guidelines can support responsible use by externalizing metacognitive prompts that unguided AI use tends to weaken. The framework is distinctive in being student-facing, course-agnostic, and actionable at the point of decision, and it specifies five empirically testable propositions.

The Gap Between Policy and the Moment of Decision

Institutional guidance on generative AI has expanded rapidly, yet it overwhelmingly addresses administrators, instructors, and assessment designers rather than the students who make most decisions about AI use. Adoption has raced ahead of design: UK national surveys record undergraduate generative AI use rising from 66% in 2024 to 95% in 2026, with 94% reporting using it for assessed work. Students report that the boundary of acceptable use remains unclear precisely at the moment they must act — interviews describe an indistinct "line" between acceptable and unacceptable use, a difficulty rooted not in ignorance of policy but in the absence of anything that translates policy into a judgment about the task at hand.

Three Pillars, Ten Guidelines

The framework organizes student-facing guidance around three jointly necessary pillars:

1. Learning and Growth — guidelines that help students use AI to deepen learning rather than bypass it, supporting Self Regulated Learning and Metacognition.
2. Ethics and Integrity — guidelines addressing Academic Integrity, attribution, and the honest disclosure of AI use.
3. Awareness and Safety — guidelines covering critical evaluation of AI output, privacy, and awareness of the limits and risks of generative tools.

The argument is that the three pillars are jointly necessary because each addresses a distinct, empirically documented failure mode of unguided AI use. Because unguided use can weaken the metacognitive prompts that support responsible decisions, the portable set of guidelines works by externalizing those prompts into explicit, actionable checks at the point of decision.

Distinctive Positioning

Compared with policy guidance, institutional frameworks, assessment scales, and AI literacy curricula, the framework is distinctive in being student-facing (written for the person making the decision), course-agnostic (portable across disciplines and assignments), and actionable at the point of decision (translatable into a judgment about a specific task). This directly addresses the documented gap between institutional policy and the student's moment of choice. The paper specifies five empirically testable propositions to guide evaluation of the framework's effectiveness.

Connected Concepts

• Generative AI
• Higher Ed
• AI Literacy
• Academic Integrity
• Self Regulated Learning
• Metacognition
• Ethics
• Agency
• Governance
• Trust Calibration

Connected Articles

• Guided Inquiry GenAI Course Policy 2026 — A Guided Inquiry Approach to Students Co-Designing Generative AI Course Policies
• Chang Should I Tell My Teacher AI Disclosure 2026 — "Should I Tell My Teacher?" Student AI Disclosure Practices
• Taylor Lacroix Purpose Before Policy Academic Integrity 2026 — Purpose Before Policy
• Learn Framework Responsible GenAI Pbl 2026 — The LEARN Framework for Responsible Use of Generative AI
• Kirsanov Beyond Detection AI Online Assessments 2026 — Beyond Detection: How Students Use—and Hide—AI

Citation

Alsammani, A. (2026). A Student-Centered Framework for Responsible Use of Generative AI in Higher Education. EdArXiv preprint.