Adaptive, Policy-Driven, After Action Review in the Generalized Intelligent Framework for Tutoring

摘要

Tutoring on a one-on-one basis from an expert human tutor who is also a subject matter expert represents the ideal arrangement for learning - improving student outcomes on between one and two standard deviations [8]. However, this is not feasible for the vast majority of instruction. One way to attempt attaining similar performance is through the use of Intelligent Tutoring Systems (ITS) - computer systems which can take expert-created content and tutor it with built-in instructional expertise. Systems such as the Generalized Intelligent Framework for Tutoring (GIFT) allow for the creation and configuration of this type of tutoring systems, marrying content from the expert and instruction from a configured system [7].