A large-scale category-based evaluation of a visual language for adaptive hypermedia

Khan, J.; Cristea, A.I.; Alamri, A.

Abstract

Adaptive Hypermedia (AH) provides a personalised and customised approach, enhancing the usability of hypermedia, by building a model of various qualities of a user and applying this information to adapt the content and the navigation to their requirements. However, authoring adaptive materials is not a simple task, as an author may be pressed for time, or simply lack the skills needed to create new adaptive materials from scratch. The most challenging part is the authoring of the adaptation specification (adaptive behaviour rules). This paper tackles this challenge by proposing and evaluating (on a large scale) a visual language for authoring of adaptive hypermedia.

Citation

Khan, J., Cristea, A., & Alamri, A. (2018, June). A large-scale category-based evaluation of a visual language for adaptive hypermedia. Presented at 3rd International Conference on Information and Education Innovations (ICIEI'18), London

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 3rd International Conference on Information and Education Innovations (ICIEI'18)
• Acceptance Date: May 22, 2018
• Online Publication Date: Jun 30, 2018
• Publication Date: Jun 30, 2018
• Deposit Date: Aug 2, 2018
• Publicly Available Date: Aug 2, 2018
• Publisher: Association for Computing Machinery (ACM)
• Pages: 94-98
• Series Title: ACM international conference proceeding series
• Book Title: Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018.
• DOI: https://doi.org/10.1145/3234825.3234834
• Public URL: https://durham-repository.worktribe.com/output/1144090