Assessment Strategies
The following assessment strategies focus on incorporating generative AI into the learning experience. The goal with each of these strategies is to find ways to leverage the benefits of generative AI while doing so in a responsible and ethical manner. Each strategy presents the overall concept, the steps to facilitate the assessment, an example of a prompt that could be used with a generative AI model, and some rationale of the benefits the strategy brings to the learning experience.
This assessment incrementally introduces generative AI through a series of scaffolded activities grounded in course concepts. Students interact with AI while analyzing its capabilities, limitations, and creative uses, before collaboratively producing an ethical usage guide. This builds situated AI literacy while fostering critical thinking.
This assessment strategy integrates a virtual AI teammate into the think-pair-share process. First, students think individually about a prompt. Next, they pair up to discuss their thoughts while also consulting an AI for fresh perspectives. Finally, pairs share their ideas with the class, emphasizing the rationales behind their choices.
The instructor provides an AI counterpart with a discussion prompt. The AI provides relevant ideas that students then rank. Students then meet in groups to analyze the responses and suggest improvements. The class then collaboratively crafts a follow-up prompt seeking to build on the AI's initial perspective, triggering an iterative process.
Students have an AI argue both sides of a controversial issue impartially. Learners review the generated transcript, analyzing which ideas seem compelling. They summarize their overall stance after weighing both perspectives. Articulating their analysis builds communication skills and familiarizes them with core arguments on complex topics.
In this strategy, an AI assistant generates two outlines on a student's chosen topic. The student then annotates the outlines, indicating which ideas they favor and why. Students then share their findings in class. Annotating the AI's work promotes critical analysis skills and accountability for choices that are shared with peers.
This assessment strategy engages students in teaching a concept they've recently learned to an AI programmed to act as a novice undergraduate student. Through this exercise, students enhance their understanding and communication skills, while the AI's critiques help them refine their ability to convey complex ideas clearly and effectively.