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首页> 外文会议>IIAI International Congress on Advanced Applied Informatics >Learning Process Analysis Based on Sequential Pattern Mining and Lag Sequential Analysis in a Web-Based Inquiry Science Environment
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Learning Process Analysis Based on Sequential Pattern Mining and Lag Sequential Analysis in a Web-Based Inquiry Science Environment

机译：基于Web的查询科学环境中基于顺序模式挖掘和滞后顺序分析的学习过程分析

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摘要

To explore what learning behaviors affect learners science-based inquiry learning performance, this work develops an xAPI (Experience Application Programming Interface)-based learning record store module embedded in a Collaborative Web-based Inquiry Science Environment (CWISE) to record students detailed learning process data, including learning behaviors, learning time, and learning sequence. More importantly, based on the recorded learning behaviors, this work discusses the significant correlation and cause-effect relation among science inquiry ability, learning time, and learning performance, and to explore the remarkable shift and difference in the learning behaviors of learners with different learning performance and inquiry abilities by using sequential pattern mining and lag sequential analysis. The research results show that inquiry ability, total learning time, and inquiry simulation experiment learning time present notably positive correlations with learning performance, with linear regression, showing the predictability of learning performance, on which inquiry simulation experiment learning time appears the most significant effect. Moreover, based on sequential pattern mining, learners with different learning performance do not show significant differences on the learning sequence of the entire inquiry learning course, but follow the inquiry learning process sequence in the curriculum design. Also, based on lag sequential analysis, learners with high learning performance and high inquiry ability would re-adjust the previous hypotheses after proceeding the simulation experiment of buoyancy, while learners with low learning performance and low inquiry ability are lack of such a key inquiry learning behavior.
机译：为了探索哪些学习行为会影响学习者基于科学的探究学习成绩，这项工作开发了一个基于xAPI（体验应用程序编程接口）的学习记录存储模块，该模块嵌入在基于Web的协作式探究科学环境（CWISE）中，以记录学生详细的学习过程数据，包括学习行为，学习时间和学习顺序。更重要的是，基于记录的学习行为，本研究探讨了科学探究能力，学习时间和学习成绩之间的显着相关性和因果关系，并探讨了不同学习者学习行为的显着变化和差异。通过使用顺序模式挖掘和滞后顺序分析来提高绩效和查询能力。研究结果表明，探究能力，总学习时间和探究模拟实验学习时间与学习成绩呈显着正相关，线性回归表明学习表现的可预测性，其中对探究模拟实验学习时间的影响最大。此外，基于顺序模式挖掘，具有不同学习表现的学习者在整个探究学习课程的学习顺序上不会表现出显着差异，而是遵循课程设计中的探究学习过程顺序。同样，基于滞后顺序分析，学习能力高和探究能力强的学习者在进行浮力模拟实验后会重新调整先前的假设，而学习能力低和探究能力低的学习者则缺乏这种关键的探究性学习。行为。

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