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Sequential pattern mining method for analysis of programming learning history based on the learning process

机译：基于学习过程的编程学习历史分析的顺序模式挖掘方法

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摘要

This research aims to realize a novel method for learning history analysis based on the learning processes in programming exercise classes. This paper proposes the sequential pattern mining method specialized for analysis of learning histories of programing learning. This paper initially describes a data processing method which investigates learning transitions as sequences based on the analyses of learners' source codes and compile errors generated in their exercises. Next, this paper describes an analysis support tool. This tool assists collection of learning histories, generation of sequence based on analysis of the histories, extraction of the noteworthy patterns based on SPADE algorithm and acquisition of findings from the extracted patterns. This tool enables to effectively analyze the relationships between learning processes in programming exercises and learning situations. Such analysis can contribute to practical grasping of learning situations in accordance with learning process and acquisition of advanced findings based on it.
机译：本研究旨在基于编程练习课中的学习过程，实现一种新颖的学习历史分析方法。本文提出了一种顺序模式挖掘方法，专门用于分析编程学习的学习历史。本文首先介绍了一种数据处理方法，该方法基于对学习者源代码的分析以及他们在练习中生成的错误，将学习转变按顺序进行调查。接下来，本文介绍了一种分析支持工具。该工具可帮助收集学习历史记录，基于历史记录的分析生成序列，基于SPADE算法提取值得注意的模式以及从提取的模式中获取发现。该工具可以有效地分析编程练习中的学习过程与学习情况之间的关系。这样的分析可以有助于根据学习过程来实际掌握学习情况，并以此为基础获得高级发现。

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