Expertise-Based Training: Getting More Learners Over the Bar in Less Time

摘要

This article introduces expertise-based training (XBT) as an instructional design theory that draws on the theories, findings, and methods of expertise research in order to create instructional strategies that can hasten the development of advanced learners into experts. The central tenants of XBT are: 1) Key cognitive sub-skills that underlie expert performance can be revealed through expert-novice research, 2) Instructional activities can be designed, often by repurposing expertise-novice research tasks, to systematically train key cognitive sub-skills, and 3) Targeted training of key cognitive sub-skills can hasten learners along their individual paths to expertise. XBT targets apparently "intuitive" aspects of expert decision-making, such as pattern recognition and situation awareness, with drills based on the detection, categorization, and prediction tasks used in expert-novice research. XBT contrasts with, and thus compliments, holistic instructional methods such as Problem-Based Learning and simulator-based training that are associated with professional education and training.