# A Comprehensive AI Policy Education Framework for University Teaching and Learning

arXiv: https://arxiv.org/abs/2305.00280 · HTML: https://mlsanity.com/paper/2305.00280/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 64 references that are in the map.
- First posted on arXiv 29 Apr 2023.

## Builds on (most cited first, 1 of 1)

- [A Framework for Ethical AI at the United Nations](https://mlsanity.com/paper/2104.12547/) (2021)

## Built on by (most cited first, 30 of 34)

- [The Robots are Here: Navigating the Generative AI Revolution in Computing Education](https://mlsanity.com/paper/2310.00658/) (2023)
- [Assessing AI Detectors in Identifying AI-Generated Code: Implications for Education](https://mlsanity.com/paper/2401.03676/) (2024)
- [GenAI Detection Tools, Adversarial Techniques and Implications for Inclusivity in Higher Education](https://mlsanity.com/paper/2403.19148/) (2024)
- [Evolution of AI in Education: Agentic Workflows](https://mlsanity.com/paper/2504.20082/) (2025)
- [The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers?](https://mlsanity.com/paper/2305.02878/) (2023)
- [Tailoring Education with GenAI: A New Horizon in Lesson Planning](https://mlsanity.com/paper/2403.12071/) (2024)
- [Is AI Changing the Rules of Academic Misconduct? An In-depth Look at Students' Perceptions of 'AI-giarism'](https://mlsanity.com/paper/2306.03358/) (2023)
- [From Guidelines to Governance: A Study of AI Policies in Education](https://mlsanity.com/paper/2403.15601/) (2024)
- [Advancing Household Robotics: Deep Interactive Reinforcement Learning for Efficient Training and Enhanced Performance](https://mlsanity.com/paper/2405.18687/) (2024)
- [Deconstructing Student Perceptions of Generative AI (GenAI) through an Expectancy Value Theory (EVT)-based Instrument](https://mlsanity.com/paper/2305.01186/) (2023)
- [ChatGPT and Beyond: The Generative AI Revolution in Education](https://mlsanity.com/paper/2311.15198/) (2023)
- [Multi-stakeholder Perspective on Responsible Artificial Intelligence and Acceptability in Education](https://mlsanity.com/paper/2402.15027/) (2024)
- [Understanding Student and Academic Staff Perceptions of AI Use in Assessment and Feedback](https://mlsanity.com/paper/2406.15808/) (2024)
- [Multi-Stakeholder Alignment in LLM-Powered Collaborative AI Systems: A Multi-Agent Framework for Intelligent Tutoring](https://mlsanity.com/paper/2510.23245/) (2025)
- [Ethical Implications of ChatGPT in Higher Education: A Scoping Review](https://mlsanity.com/paper/2311.14378/) (2023)
- [Assessing instructor-AI cooperation for grading essay-type questions in an introductory sociology course](https://mlsanity.com/paper/2501.06461/) (2025)
- [Experiences with Content Development and Assessment Design in the Era of GenAI](https://mlsanity.com/paper/2503.00081/) (2025)
- [AI University: An LLM-Powered Learning Assistant for Engineering---A Finite Element Method Case Study](https://mlsanity.com/paper/2504.08846/) (2025)
- [Measuring Human Involvement in AI-Generated Text: A Case Study on Academic Writing](https://mlsanity.com/paper/2506.03501/) (2025)
- [Institutional AI Sovereignty Through Gateway Architecture: Implementation Report from Fontys ICT](https://mlsanity.com/paper/2512.08978/) (2025)
- [Brave new world: Artificial Intelligence in teaching and learning](https://mlsanity.com/paper/2310.06856/) (2023)
- [Integrating Generative AI in Hackathons: Opportunities, Challenges, and Educational Implications](https://mlsanity.com/paper/2401.17434/) (2024)
- [AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities](https://mlsanity.com/paper/2409.02017/) (2024)
- [From Prohibition to Adoption: How Hong Kong Universities Are Navigating ChatGPT in Academic Workflows](https://mlsanity.com/paper/2410.01695/) (2024)
- [LLMs Integration in Software Engineering Team Projects: Roles, Impact, and a Pedagogical Design Space for AI Tools in Computing Education](https://mlsanity.com/paper/2410.23069/) (2024)
- [Defining a Strategic Action Plan for AI in Higher Education](https://mlsanity.com/paper/2510.03343/) (2025)
- [Topic Discovery and Classification for Responsible Generative AI Adaptation in Higher Education](https://mlsanity.com/paper/2512.16036/) (2025)
- [Scalable Classification of Course Information Sheets Using Large Language Models: A Reusable Institutional Method for Academic Quality Assurance](https://mlsanity.com/paper/2603.13562/) (2026)
- [ARIA: Adaptive Retrieval Intelligence Assistant -- A Multimodal RAG Framework for Domain-Specific Engineering Education](https://mlsanity.com/paper/2604.06179/) (2026)
- [Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education](https://mlsanity.com/paper/2605.15850/) (2026)

## Abstract (arXiv)

This study aims to develop an AI education policy for higher education by examining the perceptions and implications of text generative AI technologies. Data was collected from 457 students and 180 teachers and staff across various disciplines in Hong Kong universities, using both quantitative and qualitative research methods. Based on the findings, the study proposes an AI Ecological Education Policy Framework to address the multifaceted implications of AI integration in university teaching and learning. This framework is organized into three dimensions: Pedagogical, Governance, and Operational. The Pedagogical dimension concentrates on using AI to improve teaching and learning outcomes, while the Governance dimension tackles issues related to privacy, security, and accountability. The Operational dimension addresses matters concerning infrastructure and training. The framework fosters a nuanced understanding of the implications of AI integration in academic settings, ensuring that stakeholders are aware of their responsibilities and can take appropriate actions accordingly.