Abstract
Traditional e-learning systems have been, typically, designed for a generic learner, irrespective of individual knowledge, skills and learning styles. In contrast, adaptive e-learning systems can enhance learning by taking into account different learner characteristics and by personalising learning material. Although a large number of systems incorporating learning style have been deployed, there is a lack of comprehensive, comparative evaluations. This paper attempts to bridge this gap by comparing a number of adaptive e-learning systems. It considers three main perspectives: the learner model, the domain model and the adaptation model. A set of criteria is generated for each perspective, and applied to a representative sample of adaptive e-learning systems.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2014 8th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2014 |
| Publisher | IEEE |
| Pages | Article number 6915500, Pages 79-86 |
| Volume | 2014 |
| ISBN (Print) | 978-147994325-8 |
| DOIs | |
| Publication status | Published - Oct 2014 |
Bibliographical note
The paper was given at the 8th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2014; Birmingham City University, Birmingham; United Kingdom; 2 July 2014 through 4 July 2014“© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE
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Keywords
- adaptation model
- adaptive e-learning systems
- domain model
- learner model
- learning style
- learning technologies
