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Intelligent Instructional Design via Interactive Knowledge Graph Editing

  • Conference paper
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Learning Technologies and Systems (ICWL 2022, SETE 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13869))

Abstract

The rapid emergence of knowledge graph (KG) research opens the opportunity for revolutionary educational applications. Most studies in this area use KGs as peripheral sources of educational materials rather than a primary tool for Instructional Design. Considerable effort is required to maintain the alignment between KGs and other elements of Instructional Design practice, such as syllabus, course plans, student learning objectives, and teaching outcome evaluation. To bridge such a gap, we present a novel framework named Knowledge Graph Reciprocal Instructional Design (KGRID), which employs KGs as an instructional design tool to organize learning units and instructional data. Viewing the two aspects as a unified ensemble achieves interactive and consistent course plan editing through manipulations of KGs. The included interactive course schedule editing tool distinguishes our framework from other timetabling approaches that only handle the initialization task. Managing instructional data in KG format is indispensable in establishing a foundation of mass instructional data collection for KG research. We envision a collaboration between the two disciplines. With these crucial functionalities and aspirations, KGRID outperforms the practice of replacing Instructional Design tables with concept maps. We present the system architecture, data flow, visualization, and algorithmic aspect of the editing tool.

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Authors and Affiliations

  1. Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong

    Jerry C. K. Chan, Yaowei Wang, Qing Li, George Baciu, Jiannong Cao, Xiao Huang, Richard Chen Li & Peter H. F. Ng

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  1. Jerry C. K. Chan
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  2. Yaowei Wang
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  3. Qing Li
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  4. George Baciu
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  5. Jiannong Cao
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  6. Xiao Huang
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  7. Richard Chen Li
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  8. Peter H. F. Ng
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Corresponding author

Correspondence to Jerry C. K. Chan .

Editor information

Editors and Affiliations

  1. Universidad de La Laguna, Tenerife, Spain

    Carina S. González-González

  2. Universidad Complutense de Madrid, Madrid, Madrid, Spain

    Baltasar Fernández-Manjón

  3. Durham University, Durham, UK

    Frederick Li

  4. Universidad de Salamanca, Salamanca, Spain

    Francisco José García-Peñalvo

  5. Mercatorum University, Rome, Italy

    Filippo Sciarrone

  6. Université de Caen Normandie, Caen, France

    Marc Spaniol

  7. University of Salamanca, Salamanca, Spain

    Alicia García-Holgado

  8. Universidad de La Laguna, Tenerife, Spain

    Manuel Area-Moreira

  9. University of Hagen, Hagen, Germany

    Matthias Hemmje

  10. South China Normal University, Guangzhou, China

    Tianyong Hao

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Chan, J.C.K. et al. (2023). Intelligent Instructional Design via Interactive Knowledge Graph Editing. In: González-González, C.S., et al. Learning Technologies and Systems. ICWL SETE 2022 2022. Lecture Notes in Computer Science, vol 13869. Springer, Cham. https://doi.org/10.1007/978-3-031-33023-0_4

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  • DOI: https://doi.org/10.1007/978-3-031-33023-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-33022-3

  • Online ISBN: 978-3-031-33023-0

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