Video game learning dynamics: Actionable measures of multidimensional learning trajectories

Abstract

Abstract Valid, accessible, reusable methods for instructional video game design and embedded assessment can provide actionable information enhancing individual and collective achievement. Cyberlearning through game‐based, metaphor‐enhanced learning objects ( CyGaME s) design and embedded assessment quantify player behavior to study knowledge discovery and application. CyGaME s is grounded by analogical reasoning theory, cognitive task analysis and knowledge representation. A construct representation argument for validity using evidence‐centered design warrants CyGaME s, its web‐based learning environment, Selene: A Lunar Construction GaME , its embedded assessment, and a learning dynamics approach to student, measurement and statistical models. Two studies ( US volunteers, Study 1: n = 267, mean ( M ) age = 15; Study 2: n = 90, M age = 12) cross‐validate learning dynamics (learner progress, rate of progress and changes in that rate) for Selene 's multidimensional goals while players learn and apply standard‐based science about fundamental geology and space science concepts. Gameplay data analyzed using regression, calculus and hierarchical linear modeling exhibit overall relatively high standardized rates of progress toward each goal statistically higher than zero. For example, adjusting for nesting within individual players, average rate of progress toward the goal of accreting lunar mass is a z ‐score of 1.4 (99% confidence interval = 1.40 lower , 1.48 upper ) or 1.4 standard deviations above zero.

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