Recommender System Techniques and Approaches to Improve the Modern Learning Challenges

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Author(s): Aravindha Ramanan S. (Vellore Institute of Technology, Chennai, India)
Copyright: 2021
Pages: 30
Source title: Machine Learning Approaches for Improvising Modern Learning Systems
Source Author(s)/Editor(s): Zameer Gulzar (BSAR Crescent Institute of Science and Technology, India)and A. Anny Leema (Vellore Institute of Technology (VIT), Vellore, India)
DOI: 10.4018/978-1-7998-5009-0.ch005

Keywords: Educational Technologies / Information Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Recommendation systems have been developed from the web. These recommendation systems are useful in collecting information from an available set of sources for a user's preferences. The information can be acquired from user's collection of details to share, to review, to do positive ratings by monitoring the user's behavior to improve the quality of top ‘N' recommendations. Now if we come to modern learning system, it has good framework to influence the training factors from the data, triggers, and learner's preferences. Modern learning can be compared to online learning which carries to the future needs. Modern learning can be instituted in schools, engineering colleges, and working campus. The modern learning system combines interrelated data, processes, and resources to create a system of interdependencies that work together, adapting to changing business needs. These interdependencies include multi-level dynamics driven by the organization, training professionals, technological advances, and the learners themselves.

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