Application of Artificial Intelligence to Adaptive Instruction - Combining the Concepts

Abstract

In recent years, instructional systems for individuals and teams, including virtual environments, serious games, simulator-based training and on-the-job/live training, have been supplemented by Adaptive Instructional Systems (AISs). Artificial Intelligence (AI) techniques and Machine Learning (ML) techniques have been proposed, and are increasingly used, for a number of functions of AISs. This paper aims to combine, on the one hand, the concepts of AI and ML, and, on the other hand, adaptive instruction. The emphasis is put on simulator-based training in a professional context, predominantly skill learning by practicing tasks in simulated environments, either as an individual student or as part of a team. The major goals of this paper are: (1) to provide a basic description of available ML techniques, (2) to sketch the potential use of machine learning techniques in adaptive instruction, and (3) to provide examples of applications from the literature. This paper neither introduces a new AI approach to adaptive instruction, nor does it extensively review the literature of such approaches.