EDUCAUSE Review: “A Framework for AI Literacy”

From an EDUCAUSE Review Article by Melanie Hibbert, Elana Altman, Tristan Shippen, and Melissa Wright:

Academic and technologies teams at Barnard College developed an AI literacy framework to provide a conceptual foundation for AI education and programming efforts in higher education institutional contexts.

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Our framework provides a structure for learning to use AI, including explanations of key AI concepts and questions to consider when using AI. The four-part pyramid structure was adapted from work done by researchers at the University of Hong Kong and the Hong Kong University of Science and Technology. (The Hong Kong researchers’ work builds upon Bloom’s Taxonomy.) The framework is intended to meet people where they are and scaffold upon their current AI literacy level, whether they have little to no knowledge of AI or are prepared to build their own large language model (LLM). It breaks AI literacy into the following four levels:

1. Understand AI
2. Use and Apply AI
3. Analyze and Evaluate AI
4. Create AI

When applying this framework, it is important to keep in mind that AI is a broad field. There are many types of AI, both real and theoretical. While the concepts enumerated in this article focus primarily on generative AI, the overall structure of the framework can be applied to other forms of AI and technology literacies (e.g., cybersecurity). And, while the information in each level builds on the concepts discussed in the previous level, it is not necessary to learn everything at one level before moving on to the next. For instance, when analyzing how generative AI could impact the labor market, understanding how generative AI models are trained is helpful; however, it’s not necessary to master the intricacies of neural networks to conduct such an analysis.

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While this AI literacy framework is not exhaustive, it provides a conceptual foundation for AI education and programming efforts, particularly in higher education institutional contexts. The intention is to maintain neutrality with AI use, recognizing that technology literacy can lead to the decision not to use it. The impact of AI on higher education will likely be significant, impacting admissions, research, and curricula. Education and foundational literacy are the first steps for a community to engage productively with this rapidly changing technology.

Read the Complete Article (1829 words)

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