At the Intersection of Human and Algorithmic Decision-Making in Distributed Learning

Autor/inn/en	Prinsloo, Paul; Slade, Sharon; Khalil, Mohammad
Titel	At the Intersection of Human and Algorithmic Decision-Making in Distributed Learning
Quelle	In: Journal of Research on Technology in Education, 55 (2023) 1, S.34-47 (14 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Prinsloo, Paul) ORCID (Khalil, Mohammad)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1539-1523
DOI	10.1080/15391523.2022.2121343
Schlagwörter	Decision Making; Algorithms; Artificial Intelligence; Cost Effectiveness; Ethics; Learning Processes; Barriers; Dropout Rate; Institutional Characteristics; Guidelines; Robotics; Correlation; Educational Quality; Academic Advising; Formative Evaluation; Summative Evaluation; School Registration; Learning Analytics; College Admission; Distance Education + Suchen Sie Ihr Suchwort? Decision-making; Entscheidungsfindung; Algorithm; Algorithmus; Künstliche Intelligenz; Kosten-Nutzen-Analyse; Kosten-Nutzen-Denken; Ethik; Learning process; Lernprozess; Richtlinien; Robotertechnik; Korrelation; Quality of education; Bildungsqualität; Akademischer Rat; Schulanmeldung; Hochschulzugang; Hochschulzulassung; Zulassung; Distance study; Distance learning; Fernunterricht
Abstract	This article seeks to explore different combinations of human and Artificial Intelligence (AI) decision-making in the context of distributed learning. Distributed learning institutions face specific challenges such as high levels of student attrition and ensuring quality, cost-effective student support at scale using a range of technologies, such as AI. While there is an expanding body of research on AI in education (AIEd), this conceptual article proposes that combinations of human-algorithmic decision-making systems need careful and critical consideration, not only for their potential, but also for their appropriateness and ethical considerations. We operationalize a framework designed to consider robot autonomy at four key events in students' learning journeys, namely (1) admission and registration; (2) student advising and support; (3) augmenting pedagogy; and (4) formative and summative assessment. We conclude the article by providing pointers for operationalizing options in human-algorithmic decision-making in distributed learning contexts. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01