B3C: Memorable models for learning: Modeling making (a meaningful multitude of) human- and AI-created mnemonics

Abstract

While memorization is at the bottom of Bloom’s Taxonomy pyramid of educational learning objectives, that doesn’t mean it is the least important. As discussed in the presenters’ 2017 and 2024 JSDSE papers (and webinar), it may provide a foundation for “higher-level” conceptual learning called for by the College GAISE Report, especially for learners for whom anxiety or learning disabilities make it hard to hold enough information in their working memory. Learning strategies are critical to students' self-regulated learning (Boekaerts & Corno, 2005; Pintrich, 2000). There are seven common self-regulated learning theories (Panadero, 2017); that each posits students as active constructors of knowledge and can plan, learn, and reflect on their learning. Self-regulation is a cycle that includes cognition, motivation, and emotion at varying levels depending on the particular self-regulated learning theory. Participants can model different learning strategies in small groups using AI-free ideas. Participants will pick a topic related to their context or interest. Learning strategies will include mnemonics of varied forms to help recall and remember. Then, the participants will implement these learning strategies for the same set of topics that they picked earlier in the session.. In the culminating discussion, participants will be asked to reflect on the benefits and challenges of artifacts created by people vs. by AI.