Discovering the Effects of Metacognitive Prompts on the Sequential Structure of SRL-Processes Using Process Mining Techniques

Autor/inn/en	Sonnenberg, Christoph; Bannert, Maria
Titel	Discovering the Effects of Metacognitive Prompts on the Sequential Structure of SRL-Processes Using Process Mining Techniques
Quelle	In: Journal of Learning Analytics, 2 (2015) 1, S.72-100 (29 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1929-7750
Schlagwörter	Metacognition; Cues; Control Groups; Outcomes of Education; Learning Processes; Computer Assisted Instruction; Learning Motivation; Experimental Groups; Data Collection; Learning Activities; Data Analysis; Heuristics; Protocol Analysis; Semantics; Undergraduate Students; Foreign Countries; Statistical Analysis; Germany + Suchen Sie Ihr Suchwort? Meta cognitive ability; Meta-cognition; Metakognitive Fähigkeit; Metakognition; Stichwort; Lernleistung; Schulerfolg; Learning process; Lernprozess; Computer based training; Computerunterstützter Unterricht; Motivation for studies; Lernmotivation; Data capture; Datensammlung; Lernaktivität; Auswertung; Heuristik; Semantik; Ausland; Statistische Analyse; Deutschland
Abstract	According to research examining self-regulated learning (SRL), we regard individual regulation as a specific sequence of regulatory activities. Ideally, students perform various learning activities, such as analyzing, monitoring, and evaluating cognitive and motivational aspects during learning. Metacognitive prompts can foster SRL by inducing regulatory activities, which, in turn, improve the learning outcome. However, the specific effects of metacognitive support on the dynamic characteristics of SRL are not understood. Therefore, the aim of our study was to analyze the effects of metacognitive prompts on learning processes and outcomes during a computer-based learning task. Participants of the experimental group (EG, n = 35) were supported by metacognitive prompts, whereas participants of the control group (CG, n = 35) received no support. Data regarding learning processes were obtained by concurrent think-aloud protocols. The EG exhibited significantly more metacognitive learning events than did the CG. Furthermore, these regulatory activities correspond positively with learning outcomes. Process mining techniques were used to analyze sequential patterns. Our findings indicate differences in the process models of the EG and CG and demonstrate the added value of taking the order of learning activities into account by discovering regulatory patterns. (As Provided).
Anmerkungen	Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: http://learning-analytics.info/journals/index.php/JLA/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01