AI Literacy: Definition, Teaching, Evaluation and Ethical Issues
By Davy Tsz Kit Ng, Jac Ka Lok Leung, S. K. Chu, Maggie Shen Qiao. ASIS&T Annual Meeting, 2021
416 citations recorded by the source corpus.
Artificial Intelligence (AI) is at the top of the agenda for education leaders today in educating the next generation across the globe. However, public understanding of AI technologies and how to define AI literacy is under‐explored. This vision poses upcoming challenges for our next generation to learn about AI. On this note, an exploratory review was conducted to conceptualize the newly emerging concept “AI literacy”, in search for a sound theoretical foundation to define, teach and evaluate AI literacy. Grounded in literature on 18 existing peer‐reviewed articles, this review proposed four aspects (i.e, know and understand, use, evaluate, and ethical issues) for fostering AI literacy based on the adaptation of classic literacies. This study sheds light on the consolidated definition, teaching, and ethical concerns on AI literacy, establishing the groundwork for future research such as competency development and assessment criteria on AI literacy.
Subfields: Computer Science Applications, Health Informatics, Safety Research
View Paper: https://www.semanticscholar.org/paper/d1154da1392c97c2f15ff133ed5291002415b101
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Citations in the corpus
- Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world (2023, methodology): “Although recent research effort has been put to address the need of fostering students’ AI competencies (e.g., Kong et al., 2021; Ng et al., 2021a, b; Xia et al., 2022), rarely do studies reveal what digital competencies teachers need to become ready in an AI-driven learning environment.”