Methods to Incorporate Proactivity into Context-Aware Recommender Systems for E-Learning
Daniel Gallego, Enrique Barra, Pedro RodrÃ­guez, Gabriel Huecas
Journal of E-Technology, Vol. 4, No. 3, 2013.
DOI: 
Link: http://www.dline.info/jet/fulltext/v4n3/1.pdf
Abstract:
Recommender systems in e-learning are powerful tools to find suitable educational material during the learning experience. By including contextual information derived from the use of ubiquitous learning environments, the possibility of incorporating proactivity to the recommendation process has arisen to enhance the traditional user requestresponse pattern. In this article we present methods to generate proactive recommendations to e-learning systems users when the situation is appropriate without being needed their explicit request. As a result, interesting learning objects can be recommended attending to the userâ€™s needs in every situation based on location and user context information. The impact of this proactive recommendations generated have been evaluated among teachers and scientists in a real elearning social network called Virtual Science Hub related to the GLOBAL excursion European project. Outcomes indicate that the methods proposed are valid to generate such kind of recommendations in e-learning scenarios. The results also show that the usersâ€™ perceived appropriateness of having proactive recommendations is high in general, although few situations have proved to be inappropriate by users in such educational scenario. In addition to this, details about the proactive user interfaces designed as a consequence of the previous results are provided.