A comprehensive AI policy education framework for university teaching and learning

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.

Transnational higher education cultures and generative AI: a nominal group study for policy development in English medium instruction

“…This apprehension is in line with the wider debate in other education settings around assessment validity and integrity (e.g. Chan, 2023;Grassini, 2023;Rudolph et al, 2023), while others have addressed GenAI's potential benefits as a learning aid (e.g. Baidoo-Anu and Owusu Ansah, 2023;Escotet, 2023).…”

Values Clarification Exercises to Prepare Nursing Students for Artificial Intelligence Integration

“…During these discussions, students can analyze the ethical implications of AI utilization, assess the potential benefits and risks, and explore the impact on nursing practice and patient outcomes [12]. The aim is to foster critical thinking, reflection, and decision-making skills as students navigate the complexities of AI integration [13]. It is of utmost importance to establish and maintain an inclusive, respectful, and civil environment that encourages the sharing and respectful consideration of diverse perspectives throughout the process.…”

“…It also promotes collaborative learning and enables students to gain insights from their peers' perspectives. By implementing case-based learning exercises, nursing educators can effectively engage students in analyzing real-world scenarios and encourage critical thinking regarding the ethical implications of AI integration in nursing practice [11][12][13].…”

Impact of Digital Contexts in the Training of University Education Students

“…Specificity has been scarce in recent studies that have established this relationship between academic honesty and AI [21]. Recent studies have taken a more holistic and non-specific view, with exploratory and broad studies such as [22] proposing the need for policies with three dimensions: pedagogical (improving teaching and learning outcomes), governance (privacy, security, and accountability issues), and operational (infrastructure and training).…”