Decoding Learning Design Decisions: A Cluster Analysis of 12,749 Teaching and Learning Activities

Substantial progress has been made in how educators can be supported to implement effective learning design (LD) with learning analytics (LA). However, how educators make micro-decisions about designing individual teaching and learning activities (TLAs) and how these are related to wider pedagogical approaches has received limited empirical support. This study explored how 165 educators designed and integrated 12,749 TLA in 218 LDs using clustering, pattern-mining, and correlational analysis. The findings suggest most educators use a combination of four common LD TLAs (i.e., Collaboration, Generating independent learning, Assessment, and Traditional classroom activities). The four common TLAs could be used to develop LA and Generative Artificial Intelligence (Gen-AI) approaches to support educators in making more informed and evidence-based design decisions for effective learning and teaching.