@article{MAKHILLJEAS201712814360,
    title = {A Personalized e-Learning Portal D2L Recommender System},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {8},
    pages = {2084-2087},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.2084.2087},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.2084.2087},
    author = {Walid},
    keywords = {D2L,e-Learning,recommender systems,personalized e-Larning,PEPRS},
    abstract = {The e-Learning environments depend mainly on a series of by interactive contact details services.
Recommender system in the course of e-Learning programs that is trying to recommend actions to the learner
on behavior of the former educated workers. In this study proposed a framework a rule-based e-Learning Portal
D2L Recommender System (PEPRS) and EPERS can assist and support learners in the search for educational
materials and courses that suit their requirements. In suggested framework was developed D2L rules-based
research on appropriate educational materials that meet the needs of all students.}
    }