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Automatically identifying learners' problem solving strategies in-process solving algorithmic problems

机译:在过程中解决算法问题时自动识别学习者的问题解决策略

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摘要

Learners often use learning and programming environments to practice basics of programming and solving algorithmic problems. To adapt the software feedback to each learner's problem solving process, the learning environment will be enhanced with a tool to identify the individual problem solving strategy in-process automatically. Former attribution of problem solving strategies to patterns in recorded learner-system interactions by human researchers should be validated with the help of questionnaires based on the Theory of Reasoned Action. To identify the patterns automatically, speech recognition methods can be used. In this research project each single problem solving strategy is modelled by a hidden markov model.
机译:学习者经常使用学习和编程环境来练习编程的基础知识和解决算法问题。为了使软件反馈适应每个学习者的问题解决过程,将使用一种工具来自动识别过程中的各个问题解决策略,从而增强学习环境。问题解决策略对人类研究人员记录的学习者-系统互动中的模式的先前归因,应借助基于“理性行动理论”的问卷进行验证。为了自动识别模式,可以使用语音识别方法。在本研究项目中,每个单独的问题解决策略均由隐藏的马尔可夫模型建模。

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