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Augmented Intelligence for Instructional Systems in Simulation-Based Training

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Adaptive Instructional Systems (HCII 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14727))

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Abstract

Augmented Intelligence is a design pattern for a human-centered collaboration model of people and artificial intelligence (AI), where machines assist humans in tasks such as data analysis, information retrieval, decision-making, and task execution. In this study, the concept of Augmented Intelligence is applied within the context of an instructional system for simulation-based training. Here, the collaboration between human and machine is focused on the role of the instructor, which is to guide the learning process of one or more trainees toward some learning objective. We identify different levels of machine support to assist an instructor in this role during an adaptive training cycle. Additionally, two design aspects are discussed that contribute to increased levels of intelligence, namely the challenge of domain alignment to empower automation capabilities, and the benefits of simulation-based task environments to deliver AI-enabled approaches. Examples are discussed in the context of military training.

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Notes

  1. 1.

    Note that the instructor role could also be seen as being fulfilled by the trainee itself, hereby suggesting self-guided training, as opposed to instructor-led training.

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Authors and Affiliations

  1. Royal Netherlands Aerospace Centre, Amsterdam, The Netherlands

    Joost van Oijen

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  1. Joost van Oijen
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Correspondence to Joost van Oijen .

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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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van Oijen, J. (2024). Augmented Intelligence for Instructional Systems in Simulation-Based Training. In: Sottilare, R.A., Schwarz, J. (eds) Adaptive Instructional Systems. HCII 2024. Lecture Notes in Computer Science, vol 14727. Springer, Cham. https://doi.org/10.1007/978-3-031-60609-0_7

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  • DOI: https://doi.org/10.1007/978-3-031-60609-0_7

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