Quality Approach to Analyze the Causes of Failures in MOOC

Sraidi Soukaina, Smaili El Miloud, Salma Azzouzi, M. E. H. Charaf
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引用次数: 3

Abstract

Massive Open Online Courses (MOOC) have become popular around the world as a free way of online learning. However, one of the crucial problems associated with MOOC is their low completion rate. The analysis of data obtained from the forums and the social media groups associated with MOOCS provides a helpful mean to understand the behavior of the learners. The idea is to examine the correlation between the sentiment level reported on the basis of the forum messages and the rate of students dropping out of the courses. Moreover, a good number of quality tools are used on the domain of Education. Therefore, we propose in this paper to combine the Sentiment Analysis (Machine learning approach) of the forum posts and the ISHIKAWA method (Quality approach) to handle these issues. The aim is to predict the main causes of MOOCs’ failures
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质量方法分析MOOC教学失败原因
大规模在线开放课程(MOOC)作为一种免费的在线学习方式在全球流行起来。然而,与MOOC相关的一个关键问题是其完成率低。从与mooc相关的论坛和社交媒体群中获得的数据分析为理解学习者的行为提供了有益的手段。这个想法是为了检验根据论坛信息报告的情绪水平与学生退学率之间的相关性。此外,在教育领域使用了许多高质量的工具。因此,我们在本文中提出结合论坛帖子的情感分析(机器学习方法)和ISHIKAWA方法(质量方法)来处理这些问题。其目的是预测mooc失败的主要原因
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