A Rudimentary Progression Model for Artificial Intelligence in Education Competencies and Skills

Petros Lameras, Iraklis Paraskakis, Stathis Konstantinidis

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

    1 Citation (Scopus)
    102 Downloads (Pure)


    Artificial Intelligence in Education is progressing with accelerated pace, and this impacts the role of the teacher in becoming catalyst in designing and orchestrating teaching and learning with the use of AI-based systems. This study proposes a rudimentary competency framework with an associated progression model that aims to help teachers to plan, develop, self-assess, and reflect on existing and new competencies for teaching and learning through AI-based systems. The framework encompasses six competency themes along with six relational and inclusive descriptors of competency progression levels that may be used either as standalone or as a concerted set of competencies for enabling complete and holistic conceptualisations, and utilizations of competencies and capabilities that teachers may envisage to develop for making the leap into adaptive and automated AI-based teaching and learning. The AIED Comp framework may inform computational representation models and algorithms that focus on teacher-facing AIED applications and tools for gaining insights on skills and capabilities teachers may employ for innovating in their classroom.
    Original languageEnglish
    Title of host publicationNew Realities, Mobile Systems and Applications - Proceedings of the 14th IMCL Conference
    Subtitle of host publicationProceedings of the 14th IMCL Conference
    EditorsMichael E Auer, Thrasyvoulos Tsiatsos
    Number of pages10
    ISBN (Electronic)978-3-030-96296-8
    ISBN (Print)978-3-030-96295-1
    Publication statusPublished - 2022
    Event14th International Conference on Interactive Mobile Communication, Technologies and Learning - Virtual, Thessaloniki, Greece
    Duration: 4 Nov 20215 Nov 2021
    Conference number: 14

    Publication series

    NameLecture Notes in Networks and Systems
    ISSN (Print)2367-3370


    Conference14th International Conference on Interactive Mobile Communication, Technologies and Learning
    Abbreviated titleIMCL 2021

    Bibliographical note

    The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-030-96296-8_84

    Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

    This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.


    • Artificial Intelligence in Education (AIED)
    • AIED competencies
    • Teaching and learning
    • Progression model
    • Teachers


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    • Reframing Digital Capabilities in Higher Education

      Papageorgiou, V., Beer, N., Bryant, P., Lameras, P. & Varga-Atkins, T., Jun 2024, Inspire: Learning for Teaching in Higher Education. McNamara, A., Mahon, D., Papageorgiou, V. & Ramdeo, J. (eds.). Nova Science Publshers, 17 p. (Education in a Competitive and Globalizing World).

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

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