Quantum of choice. How learners' feedback monitoring decisions, goals and self-regulated learning skills are related.

Autor/inn/en	Jivet, Ioana; Wong, Jacqueline; Scheffel, Maren; Torre, Manuel Valle; Specht, Marcus; Drachsler, Hendrik
Institution	Association for Computing Machinery
Titel	Quantum of choice. How learners' feedback monitoring decisions, goals and self-regulated learning skills are related.
Quelle	Aus: LAK21 conference proceedings: The impact we make: The contributions of learning analytics to learning, the Eleventh International Conference on Learning Analytics & Knowledge, April 12-16, 2021, online, everywhere. New York, NY: Association for Computing Machinery (2021) S. 416-427 PDF als Volltext kostenfreie Datei (1); PDF als Volltext kostenfreie Datei (2) Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Sammelwerksbeitrag
DOI	10.1145/3448139.3448179
Schlagwörter	Chi-Quadrat-Test; Fragebogenerhebung; Learning Analytics; Entscheidung; Datenerfassung; Design; Entscheidung; Interaktion; Lernziel; Regressionsanalyse; Chi-Quadrat-Test; Lernverhalten; E-Learning; Lernender; Interaktion; Feedback; Lernverhalten; Lernziel; Lernplattform; Datenerfassung; Regressionsanalyse; Design; E-Learning; MOOC (Massive Open Online Course); Tool
Abstract	Learning analytics dashboards (LADs) are designed as feedback tools for learners, but until recently, learners rarely have had a say in how LADs are designed and what information they receive through LADs. To overcome this shortcoming, we have developed a customisable LAD for Coursera MOOCs on which learners can set goals and choose indicators to monitor. Following a mixed-methods approach, we analyse 401 learners' indicator selection behaviour in order to understand the decisions they make on the LAD and whether learner goals and self-regulated learning skills influence these decisions. We found that learners overwhelmingly chose indicators about completed activities. Goals are not associated with indicator selection behaviour, while help-seeking skills predict learners' choice of monitoring their engagement in discussions and time management skills predict learners' interest in procrastination indicators. The findings have implications for our understanding of learners' use of LADs and their design. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2023/1