The diagnosing behaviour of intelligent tutoring systems

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    Intelligent Tutoring Systems (ITSs) determine the quality of student responses by means of a diagnostic process, and use this information for providing feedback and determining a student’s progress. This paper studies how ITSs diagnose student responses. In a systematic literature review we compare the diagnostic processes of 40 ITSs in various domains. We investigate what kinds of diagnoses are performed and how they are obtained, and how the processes compare across domains. The analysis identifies eight aspects that ITSs diagnose: correctness, difference, redundancy, type of error, common error, order, preference, and time. All ITSs diagnose correctness of a step. Mathematics tutors diagnose common errors more often than programming tutors, and programming tutors diagnose type of error more often than mathematics tutors. We discuss a general model for representing diagnostic processes.
    Original languageEnglish
    Title of host publicationTransforming Learning with Meaningful Technologies
    Subtitle of host publicationProceedings of ECTEL 2019: the Fourteenth European Conference on Technology Enhanced Learning
    PublisherSpringer
    Pages112-126
    DOIs
    Publication statusPublished - 2019

    Publication series

    NameLNCS
    Volume11722

    Keywords

    • Intelligent Tutoring Systems
    • Diagnosis
    • Feedback

    Fingerprint

    Dive into the research topics of 'The diagnosing behaviour of intelligent tutoring systems'. Together they form a unique fingerprint.

    Cite this