Many models of AI literacy have emerged in the past few years, which emphasise the need for educators to understand the fundamentals of AI technologies, use AI tools effectively, analyse the output critically and make ethical decisions on use (Kassorla et. al., 2024; Hibbert et. al., 2024; Ng et. al., 2021). However, very few of these frameworks explicitly engage with the emotional impact of Generative AI, and how the discomfort, distrust, and uncertainty that these technologies can present influence the development of new teaching and learning practices. Developing Generative AI literacy requires a level of emotional intelligence, both recognizing our own emotional responses to Generative AI technologies and empathizing with the emotional responses of others, including learners and peers. Although discussion around uniquely human skills and how these need to be considered in educational and assessment design are on the rise (Oregon State University Ecampus), AI literacy also requires engaging with the existential questions that Generative AI raises about what it means to be human and how Generative AI technologies fit into our relationships with each other, society, and the environment.
At Western University, our Generative AI programming explicitly addresses these additional considerations through a holistic framework for AI Literacy. A holistic approach to Generative AI literacy for education requires engaging with multiple intersecting lenses: knowledge, skill, morals, values, affect and interconnectedness. To make an informed decision on if and how to integrate Generative AI tools into teaching and learning practices, educators need to understand how Generative AI technologies work (knowledge), how to use them (skill), the ethics of AI development, training and use (morals), the pedagogical potential of General AI technologies (values), our own emotional response to Generative AI (affect), and our beliefs around how Generative AI technology and use connects with our own humanity and our place in the world (interconnectedness). Our approach to helping instructors foster Generative AI literacy engages with all of these elements, through a reflective self-assessment on “AI-Readiness” built into our asynchronous training modules and through fulsome discussions being facilitated in our Community of Practice. In this session, we will share this holistic framework for Generative AI Literacy, briefly reviewing the domains of knowledge, skill, morals and values, and focusing on the additional complexities of affect and interconnectedness. We will explore some of the ways that we have engaged with these elements of AI Literacy through interactive activities.
Hibbert, M., Altman, E., Shippen , T., & Wright , M. (2024, June 3). A framework for AI literacy. EDUCAUSE Review.
https://er.educause.edu/articles/2024/6/a-framework-for-ai-literacy#:~:text=Academic%20and%20technologies%20teams%20atKassorla, M., Georgieva , M., & Papini, A. (2024, October 17). AI Literacy in Teaching and Learning: A Durable Framework for Higher Education. EDUCAUSE.
https://www.educause.edu/content/2024/ai-literacy-in-teaching-and-learning/executive-summaryNg, D. T. K., Leung, J. K. L., Chu, K. W. S., & Qiao, M. S. (2021). AI Literacy: Definition, Teaching, Evaluation and Ethical Issues. Proceedings of the Association for Information Science and Technology, 58(1), 504–509.
https://doi.org/10.1002/pra2.487Oregon State University Ecampus. (2024) Bloom’s Taxonomy Revisited.
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