Learning Ethics in AI—Teaching Non-Engineering Undergraduates through Situated Learning

Po-Kang Shih, Chun-Hung Lin, Leon Yufeng Wu and Chih-Chang Yu
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Po-Kang Shih: Center for General Education, Chung Yuan Christian University, Taoyuan City 320314, Taiwan
Chun-Hung Lin: Center for Teacher Education, Chung Yuan Christian University, Taoyuan City 320314, Taiwan
Leon Yufeng Wu: Graduate School of Education, Chung Yuan Christian University, Taoyuan City 320314, Taiwan
Chih-Chang Yu: Department of Information and Computer Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan

Sustainability, 2021, vol. 13, issue 7, 1-16

Abstract: Learning about artificial intelligence (AI) has become one of the most discussed topics in the field of education. However, it has become an equally important learning approach in contemporary education to propose a “general education” agenda that conveys instructional messages about AI basics and ethics, especially for those students without an engineering background. The current study proposes a situated learning design for education on this topic. Through a three-week lesson session and accompanying learning activities, the participants undertook hands-on tasks relating to AI. They were also afforded the opportunity to learn about the current attributes of AI and how these may apply to understanding AI-related ethical issues or problems in daily life. A pre- and post-test design was used to compare the learning effects with respect to different aspects of AI (e.g., AI understanding, cross-domain teamwork, AI attitudes, and AI ethics) among the participants. The study found a positive correlation among all the factors, as well as a strong link between AI understanding and attitudes on the one hand and AI ethics on the other. The implications of these findings are discussed, and suggestions are made for possible future revisions to current instructional design and for future research.

Keywords: artificial intelligence ethics; situated learning; general education; non-engineering students (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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