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ML-Based Teaching Systems : A Conceptual Framework

Title data

Spitzer, Philipp ; Kühl, Niklas ; Heinz, Daniel ; Satzger, Gerhard:
ML-Based Teaching Systems : A Conceptual Framework.
2023
Event: CSCW '23 Companion : Companion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing , 14.-18.10.2023 , Minneapolis , MN , USA.
(Conference item: Conference , Paper )

Abstract in another language

As the shortage of skilled workers continues to be a pressing issue, exacerbated by demographic change, it is becoming a critical
challenge for organizations to preserve the knowledge of retiring experts and to pass it on to novices. While this knowledge transfer
has traditionally taken place through personal interaction, it lacks scalability and requires significant resources and time. IT-based
teaching systems have addressed this scalability issue, but their development is still tedious and time-consuming. In this work, we
investigate the potential of machine learning (ML) models to facilitate knowledge transfer in an organizational context, leading to more
cost-effective IT-based teaching systems. Through a systematic literature review, we examine key concepts, themes, and dimensions
to better understand and design ML-based teaching systems. To do so, we capture and consolidate the capabilities of ML models in
IT-based teaching systems, inductively analyze relevant concepts in this context, and determine their interrelationships. We present
our findings in the form of a review of the key concepts, themes, and dimensions to understand and inform on ML-based teaching
systems. Building on these results, our work contributes to research on computer-supported cooperative work by conceptualizing how
ML-based teaching systems can preserve expert knowledge and facilitate its transfer from SMEs to human novices. In this way, we
shed light on this emerging subfield of human-computer interaction and serve to build an interdisciplinary research agenda

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Information Systems Management > Chair Information Systems Management - Univ.-Prof. Dr.-Ing. Niklas Kühl
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 15 May 2023 08:02
Last Modified: 15 May 2023 08:02
URI: https://eref.uni-bayreuth.de/id/eprint/76425