Toward E-Content Adaptation: Units’ Sequence and Adapted Ant Colony Algorithm
AbstractAn adapted ant colony algorithm is proposed to adapt e-content to learner’s profile. The pertinence of proposed units keeps learners motivated. A model of categorization of course’s units is presented. Two learning paths are discussed based on a predefined graph. In addition, the ant algorithm is simulated on the proposed model. The adapted algorithm requires a definition of a new pheromone which is a parameter responsible for defining whether the unit is in the right pedagogical sequence or in the wrong one. Moreover, it influences the calculation of quantity of pheromone deposited on each arc. Accordingly, results show that there are positive differences in learner’s passages to propose the suitable units depending on the sequence and the number of successes. The proposed units do not depend on the change of number of units around 10 to 30 units in the algorithm process. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Benabdellah, N.C.; Gharbi, M.; Bellafkih, M. Toward E-Content Adaptation: Units’ Sequence and Adapted Ant Colony Algorithm. Information 2015, 6, 564-575.
Benabdellah NC, Gharbi M, Bellafkih M. Toward E-Content Adaptation: Units’ Sequence and Adapted Ant Colony Algorithm. Information. 2015; 6(3):564-575.Chicago/Turabian Style
Benabdellah, Naoual C.; Gharbi, Mourad; Bellafkih, Mostafa. 2015. "Toward E-Content Adaptation: Units’ Sequence and Adapted Ant Colony Algorithm." Information 6, no. 3: 564-575.