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


  • Christoph Sonnenberg University of Wuerzburg, Germany
  • Maria Bannert University of Wuerzburg, Germany



self regulated learning, metacognitive prompting, process analysis, process mining, think‐aloud data, HeuristicsMiner algorithm


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.

Author Biographies

Christoph Sonnenberg, University of Wuerzburg, Germany

Research Associate, Chair of Instructional Media


Maria Bannert, University of Wuerzburg, Germany

Head of the Chair of Instructional Media

Full professor




How to Cite

Sonnenberg, C., & Bannert, M. (2015). Discovering the Effects of Metacognitive Prompts on the Sequential Structure of SRL-Processes Using Process Mining Techniques. Journal of Learning Analytics, 2(1), 72–100.



Special section: Self-regulated learning and learning analytics

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