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Autor/inn/enBannert, Maria; Reimann, Peter; Sonnenberg, Christoph
TitelProcess mining techniques for analysing patterns and strategies in students' self-regulated learning.
Gefälligkeitsübersetzung: Prozess-Mining-Techniken zur Analyse von Mustern und Strategien beim selbstregulierten Lernen.
QuelleIn: Metacognition and learning, 9 (2014) 2, S. 161-185Infoseite zur ZeitschriftVerfügbarkeit 
Spracheenglisch
Dokumenttypgedruckt; Zeitschriftenaufsatz
ISSN1556-1623
SchlagwörterKognitiver Prozess; Metakognition; Selbstgesteuertes Lernen; Strategie; Datenverarbeitung
AbstractIntroduced selected methods of process mining and analyzed students' processes of self-regulated learning (SRL) which include a set of specific sequences of regulatory activities. Successful students perform regulatory activities such as analyzing, planning, monitoring and evaluating cognitive and motivational aspects during learning not only with a higher frequency than less successful learners, but also in a different order or so the authors hypothesize. Whereas most research has concentrated on frequency analysis, so far, little is known about how students' regulatory activities unfold over time. Thus, the aim of the current approach was to also analyze the temporal order of spontaneous individual regulation activities. In this paper, it is demonstrated how the various methods developed in process mining research can be applied to identify process patterns in self-regulated learning events as captured in verbal protocols. The authors also demonstrate how theoretical SRL process models can be tested with process mining methods. Thinking-aloud data from a study with 38 college students (mean age 23 years) learning in a self-regulated manner from a hypermedia was used to illustrate the methodological points. Learning outcomes were measured with the free recall method, a multiple-choice test and a transfer test. (ZPID).
Erfasst vonLeibniz-Institut für Psychologie, Trier
Update2026/3
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