Teacher vs. Algorithm. Learners' Fairness Perception of Learning Analytics Algorithms.

Autor/inn/en	Mai, Linda; Köchling, Alina; Schmodde, Lynn; Wehner, Marius
Titel	Teacher vs. Algorithm. Learners' Fairness Perception of Learning Analytics Algorithms.
Quelle	Aus: Lingnau, Andreas (Hrsg.): DELFI 2021. 19. Fachtagung Bildungstechnologien der GI. Mülheim an der Ruhr: Hochschule Ruhr West (2021) S. 130-145 PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Beigaben	Literaturangaben; Abbildungen; Tabellen; Anhang
Sprache	englisch
Dokumenttyp	online; Sammelwerksbeitrag
ISBN	978-3-946757-03-0
Schlagwörter	Learning Analytics; Algorithmus; Bewertung; Datenverarbeitung; Lernen; Schule; Universität; Computerunterstützter Unterricht; Bildungsmanagement; Datenanalyse; Digitalisierung; Datenaufbereitung; Empfehlung; Fairness; Schule; Schulsystem; Lernen; Computerunterstützter Unterricht; Algorithmus; Datenanalyse; Digitalisierung; Fairness; Universität; Bewertung; Empfehlung; Datenaufbereitung; Datenverarbeitung
Abstract	The use of Learning Management Systems(LMS) isincreasing atschools and universities and, hence, a large amount of data is available for the assessment, recommendation, and final grading of learners. Learning analytics (LA) algorithms can either support or even substitute teachers in the grading process. However, knowledge is limited of how learners react to the algorithmic examination of personal learning data. We examine the effects of the grading entity (i.e., teacher, teacher supported by LA, and LA) on learners' reactions. Using a scenario-based between-subject design of a common grading situation at the end of the school year (N=118), we investigate whether a decrease in teachers' involvement in the grading decision diminishes learners' perceived satisfaction regarding the grading process mediated by fairness. Surprisingly, our preliminary results show that with a decrease of the teacher's involvement the perceived satisfaction is lower, but the perceived fairness is higher. Finally, fairness mediated the influence of the grading entity on satisfaction. Overall, this study offers important theoretical and practical implications when designing and applying an LMS. (Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2023/1