Recommender System in eLearning: A Survey

eLearning has completely transformed the way in which learning is imparted to students. Relevance of the topic being taught is often found lacking in learning material. Students can access lot of contents or video for learning different topics but keeping track of its relevance for him is a tedious job. Recommendation system plays an important role in such situations. The system which provides recommendation is a reference system that would recommend an education work to a student based on the works already done. This paper reviews the main paradigms of recommendation systems using explicit and implicit feedback and the various methodologies that have been implemented to design recommender systems to enhance learning. The concepts of eLearning and recommendation systems are summarized. eLearning recommendation systems will be useful to enhance learning.

[1]  Yu Liu,et al.  A novel deep hybrid recommender system based on auto-encoder with neural collaborative filtering , 2018, Big Data Min. Anal..

[2]  Yanbing Liu,et al.  3-HBP: A Three-Level Hidden Bayesian Link Prediction Model in Social Networks , 2018, IEEE Transactions on Computational Social Systems.

[3]  J. Suleri,et al.  Comparing Virtual Learning, Classical Classroom Learning and Blended Learning , 2019, European Journal of Sustainable Development Research.

[4]  Gang Wu,et al.  Digital content recommendation system using implicit feedback data , 2017, 2017 IEEE International Conference on Big Data (Big Data).

[5]  Yong Li,et al.  E-learning Recommendation System , 2008, 2008 International Conference on Computer Science and Software Engineering.

[6]  Martin Szomszor,et al.  Comparison of implicit and explicit feedback from an online music recommendation service , 2010, HetRec '10.

[7]  Dit-Yan Yeung,et al.  Collaborative Deep Learning for Recommender Systems , 2014, KDD.

[8]  S. M. Taheri,et al.  DeepMovRS: A unified framework for deep learning-based movie recommender systems , 2018, 2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS).

[9]  Tranos Zuva,et al.  Assessment of E-Learning Readiness in South African Schools , 2018, 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD).

[10]  Deepshikha Aggarwal Role of e-Learning in A Developing Country Like India , 2009 .

[11]  Lina Yao,et al.  Deep Learning Based Recommender System , 2017, ACM Comput. Surv..

[12]  Shih-Chieh Huang,et al.  A Dynamic E-learning System for the Collaborative Business Environment , 2007, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007).

[13]  Hai Liu,et al.  A content-based recommendation algorithm for learning resources , 2017, Multimedia Systems.

[14]  Caihua Wu,et al.  Deep Learning Based Recommendation: A Survey , 2017, ICISA.

[15]  Ali Shariq Imran,et al.  User behaviour analysis on LMS and MOOC , 2015, 2015 IEEE Conference on e-Learning, e-Management and e-Services (IC3e).

[16]  Ju Ren,et al.  A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms , 2019, ACM Comput. Surv..

[17]  Duen-Ren Liu,et al.  Document recommendation with implicit feedback based on matrix factorization and topic model , 2018, 2018 IEEE International Conference on Applied System Invention (ICASI).

[18]  Indira Koneru Administering MHRD guidelines-compliant eassessments through moodle , 2017, 2017 5th National Conference on E-Learning & E-Learning Technologies (ELELTECH).