期刊
COMPUTERS IN HUMAN BEHAVIOR
卷 86, 期 -, 页码 174-180出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chb.2018.04.043
关键词
Massive open online course (MOOC); Log file analysis; Academic success; Self-regulated learning (SRL); Time-on-task
This study investigated the relationship between uninterrupted time-on-task and academic success of students enrolled in a Massive Open Online Course (MOOC). The variables representing uninterrupted time-on-task, such as number and duration of uninterrupted consecutive learning activities, were mined from the log files capturing how 4286 students tried to learn Newtonian mechanics concepts in a MOOC. These variables were used as predictors in the logistic regression model estimating the likelihood of students getting a course certificate at the end of the semester. The analysis results indicate that the predictive power of the logistic regression model, which was assessed by Area Under the Precision-Recall Curve (AUPRC), depends on the value of off-task activity threshold time, and the likelihood of students getting a course certificate increases as students were doing more uninterrupted learning activities over a longer period of time. The findings from this study suggest that a simple count of learning activities, which has been used as a proxy for time-on-task in previous studies, may not accurately describe student learning in the computer-based learning environment because it does not reflect the quality, such as uninterrupted durations, of those learning activities. (C) 2018 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据