Retracted: E-Learning Recommender Systems Based on Goal-Based Hybrid Filtering

Abstract

This research work is based on the thesis contribution by proposing the goal-based hybrid filtering approach in e-learning recommender systems (eLearningRecSys). The proposed work has been used to analyze the personalized similarities between learner's profile preferences collaboratively. The proposed work consists of two hybridizations: the first hybridization has been made with content-based filtering and collaborative features to overcome the new-learners zero-rated profile recommendations issue; the second hybridization has been done with collaborative filtering and k-neighborhood scheme features to improve the averagelearner's low-rated profile recommendations issue. Therefore, the proposed goal-based hybrid filtering approach that hybridized content-based filtering, collaborative filtering and k-neighborhood features simultaneously works on both types of learner's profiles recommendation issues in e-learning environments. The experiments in the proposed work are done using the famous "MovieLens" dataset, while the evaluation of experimental results has been performed with mean of precision 83.44% and mean of recall 85.22%, respectively. t-test result shows the probability difference value of 0.29 between the proposed hybrid approach and the evaluated literature work. The results demonstrate the effectiveness of the proposed hybrid recommender systems in e-learning scenarios.

Towards an Evolution of E-Learning Recommendation Systems: From 2000 to Nowadays

“…• An e-learning recommender systems based on hybrid filtering [30] The approach comprises a two-sided hybrid recommendation system, the first side is a hybridisation between content filtering and collaborative filtering, while the second side is a hybridisation between collaborative filtering and the k-neighbour algorithm. The framework consists of several aspects: a) Learner profile b) Relevant contents c) Recommendations addressed to the target learner • A hybrid system [31] This hybrid system consists on the one hand of collaborative resource filtering and then applying the sequential algorithm to detect common resources.…”

Analysis of College Classes Based on U-CLASS System Using Personal Mobile Nodes

“…Park [12] showed a representative pedagogical framework for mobile learning and categorized educational applications of mobile technologies into four types. In addition, there are a number of studies [13][14][15] that show the integration of mobile technologies with a learning management system.…”

Improve Learner-based Recommender System with Learner’s Mood in Online Learning Platform

“…We want to help those learners who use SoIS-based collaborative learning platform for learning to efficiently obtain the most suitable educational resources for their current learning process. Recommender systems in online learning is a branch of information retrieval where learning resources are filtered and presented to the learners [3]. However, how to improve the accuracy of the recommender system is still a direction worth researching.…”