A comprehensive AI policy education framework for university teaching and learning

Комплексная рамочная модель политики в области образования, связанного с искусственным интеллектом, для преподавания и обучения в университетах
Cecilia Ka Yuk Chan
2023-07-06

AI Ecological Education Policy FrameworkAI education policyhigher educationtext generative AIuniversity 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.
1
It developed an AI Ecological Education Policy Framework to guide the multifaceted integration of text-generative AI in university teaching and learning.
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The framework aims to clarify stakeholder responsibilities and support appropriate actions for responsible AI integration in academic settings.
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The framework comprises Pedagogical, Governance, and Operational dimensions addressing learning outcomes; privacy, security, and accountability; and infrastructure and training, respectively.
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The study surveyed 457 students and 180 teachers and staff across disciplines in Hong Kong universities using quantitative and qualitative methods.

AI integration in university teaching and learning in Hong Kong higher education

The pedagogical, governance, and operational implications of text-generative AI integration, including teaching and learning outcomes, privacy, security, accountability, infrastructure, and training

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Publication Date
2023-07-06
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Cecilia Ka Yuk Chan
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