Using HeuristicsMiner to Analyze Problem-Solving Processes: Exemplary Use Case of a ProductiveFailure Study

Christian Hartmann, Nikol Rummel, Maria Bannert

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

This paper presents a fine-grained process analysis of 22 students in a classroom-based learning setting. The students engaged (and failed) in problem-solving attempts prior to instruction (i.e., the Productive-Failure approach). We used the HeuristicsMiner algorithm to analyze the data of a quasi-experimental study. The applied algorithm allowed us to investigate temporally structured think-aloud data, to outline productive and unproductive problemsolving strategies. Our analyses and findings demonstrated that HeuristicsMiner enables researchers to effectively mine problem-solving processes and sequences, even for smaller sample sizes, which cannot be done with traditional coding-and-counting strategies. The limitations of the algorithm, as well as further implications for educational research and practice, are also discussed.

Original languageEnglish
Pages (from-to)66-86
Number of pages21
JournalJournal of Learning Analytics
Volume9
Issue number2
DOIs
StatePublished - 31 Aug 2022

Keywords

  • HeuristicsMiner
  • Productive-Failure approach
  • classroom setting
  • problem-solving strategies
  • process mining

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