JOURNAL ARTICLE

An Adaptive E-Learning System based on Student's Learning Styles

Samia DrissiAbdelkrim Amirat

Year: 2016 Journal:   International Journal of Distance Education Technologies Vol: 14 (3)Pages: 34-51   Publisher: IGI Global

Abstract

Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia. The main objective was to develop a new Adaptive Educational Hypermedia System based on Honey and Mumford learning style model (AEHS-H&M) and assess the effect of adapting educational materials individualized to the student's learning style. To achieve the main objectives, a case study was developed. An experiment between two groups of students was conducted to evaluate the impact on learning achievement. Inferential statistics were applied to make inferences from the sample data to more general conditions was designed to evaluate the new approach of matching learning materials with learning styles and their influence on student's learning achievement. The findings support the use of learning styles as guideline for adaptation into the adaptive e-learning hypermedia systems.

Keywords:
Adaptive hypermedia Computer science Learning styles Educational technology Adaptation (eye) Hypermedia Adaptive learning Personalized learning Active learning (machine learning) Mathematics education Cognitive style Blended learning Synchronous learning Multimedia Cooperative learning Teaching method Artificial intelligence Open learning Psychology Cognition

Metrics

31
Cited By
2.41
FWCI (Field Weighted Citation Impact)
30
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Learning Styles and Cognitive Differences
Social Sciences →  Psychology →  Developmental and Educational Psychology
Online Learning and Analytics
Physical Sciences →  Computer Science →  Computer Science Applications

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