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The Rise of Multimodal Tutors in Education

  • Daniele Di Mitri*
  • , Jan Schneider
  • , Hendrik Drachsler
  • *Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    Abstract

    This chapter describes the insights derived by the design and development of the Multimodal Tutor, a system that uses artificial intelligence for providing digital feedback and to support psychomotor skills acquisition. In this chapter, we discuss the insights which we gained from eight studies: (1) an exploratory study combining physiological data and learning performance (Learning Pulse); (2) a literature survey on multimodal data for learning and a conceptual model (the Multimodal Learning Analytics Model); (3) an analysis of the technical challenges of Multimodal Learning Analytics (the Big Five Challenges); (4) a technological framework for using multimodal data for learning (the Multimodal Pipeline); (5) a data collection and storing system for multimodal data (the Learning Hub); (6) a data annotation tool for multimodal data (the Visual Inspection Tool); (7) a case study in Cardiopulmonary Resuscitation training (CPR Tutor) consisting of a feasibility study for detecting CPR mistakes; and (8) a real-time feedback study.
    Original languageEnglish
    Title of host publicationHandbook of Open, Distance and Digital Education
    EditorsOlaf Zawicki-Richter, Insung Jung
    Place of PublicationSingapore
    PublisherSpringer Nature Singapore
    Pages1-20
    Number of pages20
    ISBN (Electronic)978-981-19-0351-9
    ISBN (Print)978-981-19-0351-9
    DOIs
    Publication statusPublished - 2 Sept 2022

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