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Scaling Adaptive Instructional System (AIS) Architectures in Low-Adaptive Training Ecosystems

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Part of the book series:Lecture Notes in Computer Science ((LNISA,volume 12792))

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Abstract

This paper reviews horizontal and vertical scaling methodologies for adaptive instructional system (AIS) software architectures. The termAIS refers to any instructional approach that accommodates individual differences to facilitate and optimize the acquisition of knowledge and/or skills. The authors propose a variety of scaling methods to enhance the interaction between AISs and low-adaptive training ecosystems with the goal of increasing adaptivity and thereby increasing learning and performance. Typically, low-adaptive training systems only accommodate differences in the learner’s in-situ performance during training and do not consider the impact of other factors (e.g., emotions, prior knowledge, goal-orientation, or motivation) that influence learning. AIS architectures such as the Generalize Intelligent Framework for Tutoring (GIFT) can accommodate individual differences and interact with low-adaptive training ecosystems to model a common operational picture of the training relative. These capabilities enable AISs to track progress toward learning objectives and to intervene and adapt the training ecosystem to needs and capabilities of each learner. Finding new methods to interface AISs with a greater number of low-adaptive training ecosystems will result in more efficient and effective instruction.

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Author information

Authors and Affiliations

  1. Soar Technology, Inc., Orlando, FL, USA

    Robert A. Sottilare

  2. US Army CCDC-STTC, Orlando, FL, USA

    Keith W. Brawner

Authors
  1. Robert A. Sottilare

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  2. Keith W. Brawner

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Correspondence toRobert A. Sottilare.

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Editors and Affiliations

  1. Soar Technology, Inc., Orlando, FL, USA

    Robert A. Sottilare

  2. Fraunhofer FKIE, Wachtberg, Germany

    Jessica Schwarz

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Sottilare, R.A., Brawner, K.W. (2021). Scaling Adaptive Instructional System (AIS) Architectures in Low-Adaptive Training Ecosystems. In: Sottilare, R.A., Schwarz, J. (eds) Adaptive Instructional Systems. Design and Evaluation. HCII 2021. Lecture Notes in Computer Science(), vol 12792. Springer, Cham. https://doi.org/10.1007/978-3-030-77857-6_20

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