Combining supervised and unsupervised machine learning algorithms to predict the learners’ learning styles-Reference-Cited by-同舟云学术

Combining supervised and unsupervised machine learning algorithms to predict the learners’ learning styles

Published:2019 Issue: Volume:148 Page:87-96
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

AISSAOUI Ouafae EL,EL MADANI Yasser EL ALAMI,OUGHDIR Lahcen,ALLIOUI Youssouf EL

Publisher

Elsevier BV

Subject

General Engineering

Reference21 articles.

1. Learning styles of nursing students and career choices.;Laschinger;J. Adv. Nurs.,1984

2. LEARNING AND TEACHING STYLES;Felder;J. Eng. Educ.,1988

3. Study Process Questionnaire Manual. Student Approaches to Learning and Studying.;Biggs;Aust. Educ. Res. Dev.,1987

4. S. Graf and Kinshuk, “Advanced adaptivity in learning management systems by considering learning styles,” in Proceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2009, 2009, vol. 3, pp. 235–238.

5. J. Kuljis and F. Liu, “A Comparison of Learning Style Theories on the Suitability for elearning,” Conference on Web Technologies, Applications, and Services. pp. 191–197, 2005.

Cited by 41 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. AI-based learning style detection in adaptive learning systems: a systematic literature review;Journal of Computers in Education;2024-06-27

2. Enhancing E-Learning Adaptability with Automated Learning Style Identification and Sentiment Analysis: A Hybrid Deep Learning Approach for Smart Education;Information;2024-05-13

3. Using machine learning algorithms for predicting bridge vertical deflection;Proceedings of the Institution of Civil Engineers - Engineering and Computational Mechanics;2024-03-01

4. Implementing the Dynamic Feedback-Driven Learning Optimization Framework: A Machine Learning Approach to Personalize Educational Pathways;Applied Sciences;2024-01-21

5. A Novel Personalized Learning Framework With Interactive e-Mentoring;IEEE Access;2024