Learning pattern classification using moodle logs and the visualization of browsing processes by time-series cross-section
Learning pattern classification using moodle logs and the visualization of browsing processes by time-series cross-section
复制标题
使用 Moodle 日志进行学习模式分类以及按时间序列横截面可视化浏览过程
DOI：
10.1016/j.caeai.2022.100105
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
C.
中科院分区：
文献类型：
--
作者：
Dobashi;K.;Ho;C. P.;Fulford;C. P.;Lin;M. F. G.;& Higa;C.
近年来，利用学习管理和电子书系统的远程教育在高等院校和其他各种组织中积极开展。即使在有许多学习者的课堂上，也可以收集和分析学习日志，包括每个人的点击流和测验分数。本研究建议使用Moodle的学习日志对学习模式和异常值进行分类，以识别挣扎的学习者。该方法利用学习者的教材点击流与Moodle中积累的最终考试成绩之间的描述性统计，将学生分为四种学习模式。每种学习模式的频率与期末考试成绩和教材点击流中异常值的出现相关。大多数学习者在每周的课程中经历了四种学习模式，然而，一些在每周测验中得分最高和最低的学习者重复了相同的学习模式。由于重复相同的学习模式，有一种与异常值对应的趋势。教材点击流的时间序列学习分析表明，期末考试成绩低、值异常的学习者往往处于较少的教材点击流和较少的课外时间访问的学习模式下。
In recent years, distance learning using learning management and e-book systems has been actively conducted in higher education institutions and various other organizations. It is possible to collect and analyze learning logs even in classes with many learners, including clickstreams and quiz scores in detail for each individual. This research proposes using Moodle's learning logs to classify learning patterns and outliers in order to identify struggling learners. The proposed method uses the descriptive statistics between the learner's teaching material clickstream and the final test score accumulated in Moodle, and students can be classified into four learning patterns. The frequency of each learning pattern was correlated with the appearance of outliers in the final test score and the teaching material clickstream. Most learners moved through four learning patterns during the weekly lessons, however, some learners scoring at the top and bottom of the weekly quiz scores repeated the same learning patterns. There was a tendency to correspond to an outlier due to the repetition of the same learning pattern. The time-series learning analytics of the teaching material clickstream revealed that learners with low final test scores and abnormal values tended to fall under a learning pattern with a smaller teaching material clickstream and a smaller access outside class hours.