Sequential Pattern Mining System for Analysis of Programming Learning History
Sequential Pattern Mining System for Analysis of Programming Learning History
复制标题
用于分析编程学习历史的序列模式挖掘系统
DOI：
10.1109/dsdis.2015.120
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Youzou Miyadera
中科院分区：
文献类型：
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作者：
Shoichi Nakamura;Kaname Nozaki;Hiroki Nakayama;Yasuhiko Morimoto;Youzou Miyadera
本研究的总体目标是建立依学习过程分析程式设计习题学习历史资料的方法。为了实现这一目标，我们开发了一种顺序模式挖掘的理论方法，专门用于在编程练习中学习历史。在此基础上，设计了一个编程学习历史数据分析系统。该系统由负责收集学习历史、从收集的学习历史中生成序列、从一组序列中提取值得注意的模式以及从提取的模式中获取发现的功能组成。本文主要介绍了该系统的功能及其实现，并对顺序模式挖掘方法进行了概述。
The overall goal of this research is to establish the methodology for analyzing learning history data of programming exercise in accordance with learning processes. To achieve this goal, we developed a theoretical method of sequential pattern mining specialized for learning histories in programming exercise. On the basis of this method, we designed a system for analyzing the programming learning history data. This system consists of functions that are responsible for collection of learning histories, generation of sequence from the collected learning histories, extraction of noteworthy patterns from a set of sequences, and acquisition of findings from the extracted patterns. This paper mainly describes the functions of the system and their implementation along with an overview of the sequential pattern mining method.