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

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

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Authors

J. Khan



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). A large-scale category-based evaluation of a visual language for adaptive hypermedia. In Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018 (94-98). https://doi.org/10.1145/3234825.3234834

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

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Copyright Statement
© ACM 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2018 The 3rd International Conference on Information and Education Innovations (ICIEI'18), https://doi.org/10.1145/3234825.3234834.






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