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A comprehensive AI policy education framework for university teaching and learning
by
Chan, Cecilia Ka Yuk
in
Accountability
/ Artificial intelligence
/ College faculty
/ College students
/ Colleges & universities
/ Data
/ Education
/ Education policy
/ Educational Policy
/ Frame analysis
/ Governance
/ Higher education
/ Infrastructure
/ Instructional Improvement
/ Learning
/ Learning outcomes
/ Pedagogy
/ Privacy
/ Qualitative analysis
/ Qualitative research
/ Research methodology
/ Students
/ Teachers
/ Teaching
/ Universities
2023
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A comprehensive AI policy education framework for university teaching and learning
by
Chan, Cecilia Ka Yuk
in
Accountability
/ Artificial intelligence
/ College faculty
/ College students
/ Colleges & universities
/ Data
/ Education
/ Education policy
/ Educational Policy
/ Frame analysis
/ Governance
/ Higher education
/ Infrastructure
/ Instructional Improvement
/ Learning
/ Learning outcomes
/ Pedagogy
/ Privacy
/ Qualitative analysis
/ Qualitative research
/ Research methodology
/ Students
/ Teachers
/ Teaching
/ Universities
2023
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Do you wish to request the book?
A comprehensive AI policy education framework for university teaching and learning
by
Chan, Cecilia Ka Yuk
in
Accountability
/ Artificial intelligence
/ College faculty
/ College students
/ Colleges & universities
/ Data
/ Education
/ Education policy
/ Educational Policy
/ Frame analysis
/ Governance
/ Higher education
/ Infrastructure
/ Instructional Improvement
/ Learning
/ Learning outcomes
/ Pedagogy
/ Privacy
/ Qualitative analysis
/ Qualitative research
/ Research methodology
/ Students
/ Teachers
/ Teaching
/ Universities
2023
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A comprehensive AI policy education framework for university teaching and learning
Journal Article
A comprehensive AI policy education framework for university teaching and learning
2023
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Overview
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.HighlightsProposed AI Ecological Education Policy Framework for university teaching and learning.Three dimensions: Pedagogical, Governance, and Operational AI Policy Framework.Qualitative and quantitative data collected from students, teachers, and staff.Ten key areas identified for planning an AI policy in universities.Students should play an active role in drafting and implementing the policy.
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