Designing an Aligned Generative AI Course Policy: An Equitable and Transparent Learner-Centered Approach

Abstract

This design case describes the design of an Aligned Generative AI Course Policy, in which the allowed and unallowed uses of GenAI tools are described in a transparent manner for students. The process begins with an analysis of student tasks by creating an inventory of each step a student would take that leads to a finished product of their learning. Each task in the inventory is reviewed by the instructor, and they ask themselves: “What, specifically, am I assessing?” Tasks in the inventory that are not assessed, but are simply a step towards a finished product, are noted accordingly. The instructor brainstorms an emerging GenAI workforce competency for every task. A determination is then made to prioritize either the need to assess student performance of the task or build the GenAI workforce competency. The instructor may find that the need to assess tasks which had been assessed earlier in the course (or, in the case of an upper-level course, earlier in the program) can be set at a lower priority, permitting the GenAI workforce competency to prevail. This design-based approach has two benefits: 1) providing a transparent and equitable Generative AI policy for students; and 2) instructors begin to think deeply about what, specifically, they are assessing.