Higher ed frameworks & recommendations for policy development

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.

ChatGPT recently turned one and what a wild, first year it has been. Over the last twelve months, institutions have scrambled to not only better understand generative Artificial Intelligence (AI) and its impact on teaching and learning, but also to determine the best ways to provide guardrails and guidance for faculty, staff, and students. Many […]

Particularly for new technologies that disrupt long-standing practices and cultural beliefs, the work of carefully and intentionally developing effect

As artificial intelligence becomes integrated into all corners of higher education, addressing ethical concerns is crucial to responsible implementati