A comprehensive AI policy education framework for university teaching and learning

TLDR

The study aims to develop an AI education policy for higher education by examining perceptions and implications of text‑generative AI technologies. Data from 457 students and 180 teachers across Hong Kong universities were analyzed using mixed methods, leading to an AI Ecological Education Policy Framework organized into Pedagogical, Governance, and Operational dimensions. The framework promotes a nuanced understanding of AI integration implications, enabling stakeholders to recognize responsibilities and take appropriate actions.

Abstract

Abstract 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.