基于学习风格的MOOC课程学习者聚类评价

2019 International Conference of Computer Science and Renewable Energies (ICCSRE) Pub Date : 2019-07-01 DOI:10.1109/ICCSRE.2019.8807503

Ali El Mezouary, Brahim Hmedna, Omar Baz

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引用次数: 5

摘要

本文提出了一种从学习者与MOOC环境交互时的痕迹中自动检测学习者学习风格的方法。参考学习技术中最流行的模型之一Felder-Silverman模型(FSLSM)，对所讨论的方法进行了特别评估，以确定与主动/反思维度相关的学习者的学习风格。

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An evaluation of learner clustering based on learning styles in MOOC course

This article presents an approach for the automatic detection of learners' learning styles from their traces when they interact with a MOOC environment. The approach in question has been evaluated in particular to identify learners' learning styles associated with the active/reflective dimension, with reference to the Felder-Silverman model (FSLSM), which is one of the most popular models in the learning technology.

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2019 International Conference of Computer Science and Renewable Energies (ICCSRE)

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