大规模在线开放课程中学习者参与的分类系统

2016 4th IEEE International Colloquium on Information Science and Technology (CiSt) Pub Date : 2016-10-01 DOI:10.1109/CIST.2016.7805105

H. Hayati, Jihane Sophia Tahiri, Mohammed Khalidi, S. Bennani

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引用次数: 6

摘要

参与是学术过程成功的重要关键之一，本文旨在建立基于学习者参与程度的大规模在线开放课程(MOOC)学习者分类系统模型。在这个范围内，我们的任务是定义参与的概念，并建立其不同的层次。这将使我们能够提出一种基于指标测量的方法，并应用k-means聚类分类算法，以便根据学习者的参与程度对学习者进行分组，这将有助于导师和开发人员做出正确的决策，并将辍学率降至最低。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Classification system of learners engagement within Massive Open Online Courses

Engagement is one of the important key of success in academic process, the present article aims to model the classification system of learners in Massive Open Online Course (MOOC) based on their engagement levels. In this scope, our mission is to define the notion of engagement as well as establish its different levels. This will enable us to present an approach based on indicators measurement with the application of the k-means clustering classification algorithm, in order to group the learners depending on their engagement level, which will help tutors and developers to take good decisions and minimize the dropout rate.

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2016 4th IEEE International Colloquium on Information Science and Technology (CiSt)

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