A Macrocognitive Design Taxonomy for Simulation-Based Training Systems: Bridging Cognitive Theory and Human–Computer Interaction

Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that underpin adaptive expertise. Macrocognition encompasses higher-order cognitive processes that are essential for performance transfer beyond controlled training conditions. When these processes are insufficiently supported, training systems risk fostering brittle strategies and negative training effects. This paper introduces a macrocognitive design taxonomy for simulation-based training systems derived from a large-scale meta-analysis examining the transfer of macrocognitive skills from immersive simulations to real-world training environments. Drawing on evidence synthesized from 111 studies spanning healthcare, industrial safety, skilled trades, and defense contexts, the taxonomy links macrocognitive theory to human–computer interaction (HCI) design affordances, computational data traces, and feedback and adaptation mechanisms shown to support transfer. Grounded in joint cognitive systems theory and learning engineering practice, the taxonomy treats macrocognition as a designable and computable system concern informed by empirical transfer effects rather than as an abstract explanatory construct.