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

Christian Hartmann, N. Rummel, M. Bannert
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引用次数: 4

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 problem-solving 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 code-and-count strategies. The limitations of the algorithm, as well as further implications for educational research and practice, are also discussed.
使用启发式miner分析解决问题的过程:生产性失败研究的示例用例
本文对22名学生在课堂学习环境下的学习过程进行了细致的分析。学生们在接受指导之前尝试解决问题(即,生产性失败方法)。我们使用HeuristicsMiner算法来分析准实验研究的数据。应用的算法使我们能够调查暂时结构化的有声思考数据,勾勒出有效和非有效的解决问题的策略。我们的分析和发现表明,HeuristicsMiner使研究人员能够有效地挖掘解决问题的过程和序列,即使是较小的样本量,这是传统的编码和计数策略无法做到的。本文还讨论了该算法的局限性,以及对教育研究和实践的进一步影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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