2023-07-06 · article · Artificial Intelligence in Education · en
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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.
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This paper concerns artificial intelligence in education and is an article, which means it has cleared peer review and should be weighted accordingly.
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With 1535 citations, the work is already an established reference point in its field. It references 34 works in building its argument.
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A comprehensive AI policy education framework for university teaching and learning is an article, focusing on Artificial Intelligence in Education, published in 2023.
A comprehensive AI policy education framework for university teaching and learning has 1,535 citations in our record, placing it among the highly cited works we track.
Our record lists 1 author for A comprehensive AI policy education framework for university teaching and learning and references 34 other works. Author names aren't in our data yet — the source link on the page lists the full byline.
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