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A Learning Engineering Model for Learner-Centered Adaptive Systems

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HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games (HCII 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12425))

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Abstract

Multiple academic and industry-based communities have engaged in defining the theoretical constructs, practical approaches, and technical standards for technology-enabled systems of human learning. However, conceptual and architectural models of Adaptive Instructional Systems (AISs) often focus on the functions of the technology, with the learner as a user external to the system. We offer an AIS model that considers the learner as a key component at the heart of a learning system. The learner, along with other human actors and environmental conditions, interact with technology components in a distributed learning system. Modular components surrounding the learner are interoperable. Data flow between the components using standards-based interfaces for instrumented and adaptive learner experiences. The model builds on functional components identified by Glowa & Goodell (2016) in Student-Centered Learning: Functional Requirements for Integrated Systems to Optimize Learning. The model is further informed by the IEEE workgroup P2247.1 developing a standard for the classification of adaptive instructional systems. It examines the learning system at a conceptual level and then maps those conceptual categories to functional components as modules in a distributed learning system. The model is rooted in the process of learning engineering as defined by the IEEE Industry Connection Industry Consortium on Learning Engineering (ICICLE). We envision future design and development of adaptive instructional systems benefiting from an emerging learning engineering discipline that embraces an iterative problem-solving approach. The proposed AIS model is a self-improving system by design that embodies key learning engineering processes.

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Author information

Authors and Affiliations

  1. Quality Information Partners, Fairfax, VA, 22038, USA

    Jim Goodell

  2. Age of Learning, Inc., Glendale, CA, 91203, USA

    Khanh-Phuong (KP) Thai

Authors
  1. Jim Goodell
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  2. Khanh-Phuong (KP) Thai
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Corresponding authors

Correspondence to Jim Goodell or Khanh-Phuong (KP) Thai .

Editor information

Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology – Hellas (FORTH), Heraklion, Greece

    Constantine Stephanidis

  2. Coventry University, Coventry, UK

    Don Harris

  3. Cranfield University, Cranfield, UK

    Wen-Chin Li

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

    Dylan D. Schmorrow

  5. Design Interactive, Inc., Orlando, FL, USA

    Cali M. Fidopiastis

  6. Cyprus University of Technology, Limassol, Cyprus

    Panayiotis Zaphiris

  7. Cyprus University of Technology, Limassol, Cyprus

    Andri Ioannou

  8. DePaul University, Chicago, IL, USA

    Xiaowen Fang

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

    Robert A. Sottilare

  10. Fraunhofer FKIE, Wachtberg, Germany

    Jessica Schwarz

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Goodell, J., Thai, KP.(. (2020). A Learning Engineering Model for Learner-Centered Adaptive Systems. In: Stephanidis, C., et al. HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games. HCII 2020. Lecture Notes in Computer Science(), vol 12425. Springer, Cham. https://doi.org/10.1007/978-3-030-60128-7_41

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  • DOI: https://doi.org/10.1007/978-3-030-60128-7_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60127-0

  • Online ISBN: 978-3-030-60128-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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