A Preliminary Set of Principles to Support Learning in the Context of Generative AI

Abstract

Generative AI chatbots are now widely available, and increasing numbers of students use them. Despite hyperbolic claims, there is little objective evidence of the efficacy of such systems for teaching and learning. Early findings suggest that the use of AI chatbots without guidance or guardrails negatively affects student learning. Using what evidence we do have together with our current understanding of how people learn, I lay out a set of tentative principles for using generative AI to support learning and instruction Given the overarching assumption that learning requires effort and engagement which can easily be bypassed using AI, I propose four practical principles to guide faculty as they maneuver through this new era. (1) Design AI teaching and learning systems to support self-regulated learning. (2) Develop a course structure and culture that rewards the learning journey. (3) Take advantages of the affordances of AI to extend what students know and can do. And (4) develop clear and equitable policies for the use of AI. These principles are predicated on the idea that typical traditional courses (where emphasizing facts and algorithmic problem solving are emphasized) will become obsolete as these tasks are easily (and perhaps better) carried out by AI bots. It will become increasingly important for students to understand how they learn, what they can do with their knowledge, and how to solve complex problems that have societal and economic value.

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