New Automatic Hybrid Approach for Tracking Learner Comprehension Progress in the LMS

International Journal of Interactive Mobile Technologies

article

Khalid Benabbes¹  Brahim Hmedna²  Khalid Housni¹  Ahmed Zellou³  Ali El Mezouary⁴ 

[1] Faculty of Sciences, Ibn Tofail University;IMISLaboratory, Faculty of Sciences, Ibn Zohr University;ENSIAS, Mohammed V University;EST, Ibn Zohr University

关键词: LMS;    Learning styles;    FSLSM;    Dropout;    Decision Tree;    Rules-based;   

DOI  :  10.3991/ijim.v16i19.33733

学科分类：社会科学、人文和艺术（综合）

来源: International Association of Online Engineering

【 摘 要 】

Learning style is a significant learner-difference factor. Each learner has a preferred learning style and a different way of processing and understanding the novelty. In this paper, a new approach that automatically identify learners learning styles based on their interaction with the Learning Management System (LMS) is introduced. To implement this approach, the traces of 920 enrolled learners in three agronomy courses were exploited using an unsupervised clustering method to group learners according to their degree of engagement. The decision tree classification algorithm relies on the decision rules construction, which is widely adopted to identify the accurate learning style. As missing good decision rules would lead to learning style misclassification, the Felder-Silverman Learning Style Model (FSLSM) is used as it is among the most adopted models in the technology of quality improvement process. The results of this research highlight that most learners prefer the global learning style.

【 授权许可】

CC BY