This article describes the implementation of an intelligent agent that provides recommendations for educational resources in a virtual learning environment (VLE). It aims to support pending (undeveloped) student learning activities. It begins by analyzing the proposed VLE data model entities in the recommender process. The pending student activities are then identified, which constitutes the in...

e-Learning is a sought-after option for learners during pandemic situations. In platforms, there are many courses available, and the user needs to select best them. Thus, recommender systems play an important role provide better automation services users in making course choices. It makes recommendations selecting desired based on their preferences. This system can use machine intelligence (MI)...

In this paper we propose a course recommendation system based on historical grades of students in college. Our model will be able to recommend available courses in sites such as: Coursera, Udacity, Edx, etc. To do so, probabilistic topic models are used as follows. On one hand, Latent Dirichlet Allocation (LDA) topic model infers topics from content given in a college course syllabus. On the ot...

With the rapid development of massive open online courses, peer assessment has played an important role in promoting social learning. According to social learning theory, peer assessment in online courses provides students a chance to learn from each other when they review other students’ submissions, which motivates their participation in online social learning. However, existing peer assessme...

Studies show that Learning Management Systems at university level often are lacking necessary for teaching staff member features such as support of various didactical approaches, consideraion of different specifics of engineering disciplines, user-friendly interface. In this paper, a new recommender system aimed at teaching staff of engineering disciplines who wish to use E-Learning tools in th...

the evaluation and selection of recommender systems is a difficult decision making process. this difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. as such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find...

Course recommender system aims at predicting the best combination of courses selected by students. Here in this paper we present how the combination of clustering algorithmSimple K-means Algorithm & association rule algorithmApriori Association Rule is useful in Course Recommender system. If we use only the Apriori association rule algorithm then we need to preprocess the data obtained from Moo...