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Examining Elements of an Adaptive Instructional System (AIS) Conceptual Model

  • Robert SottilareEmail author
  • Brian Stensrud
  • Andrew J. Hampton
Conference paper
  • 557 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11597)

Abstract

This paper examines the components, functions, and interactions of adaptive instructional systems (AISs) as a method to construct a conceptual model for use in the development of IEEE standards. AISs are artificially-intelligent, computer-based systems that guide learning experiences by tailoring instruction and recommendations based on the goals, needs, and preferences of each individual learner or team in the context of domain learning objectives. IEEE is exploring standards and best practices for AIS modeling, interoperability, and evaluation under its Project 2247 and affiliated working group. This paper was composed to document the interaction of learners with AISs in the context of a domain of instruction. The goal is to identify key interactions within AISs that drive instructional decisions, and to identify the data and methods required to support those machine-based instructions. In other words, we seek to identify methods to assess learner/team progress toward instructional objectives (e.g., knowledge, acquisition, skill development, performance, retention, and transfer of skills from instruction to operational/working environments. As part of the examination of AIS elements, we review a set of popular AIS architectures as a method of identifying what makes AISs unique from other instructional technologies. We conclude with recommendations for future AIS research and standards development.

Keywords

Instructional decisions Learner data Learner interaction Learner states 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Soar Technology, Inc.OrlandoUSA
  2. 2.University of MemphisMemphisUSA

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