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A Survey on Recommendation Systems in E-learning

Authors: Tandel Ayushi; Uchhula Vasundhara;

A Survey on Recommendation Systems in E-learning

Abstract

Currently new innovations and with rapid development of Internet, access to data have been made simpler, this gives raise to new difficulties to utilise educational resources. Gone are the days when conventional method of teaching was the only way where students could learn and practice. In current scenario, learning through MOOC’s is on a rising trend. Massive Online Open Courses (MOOCs) sites, for example, EdX, Coursera and Udacity, are picking up force. In regards to this, students are able to learn through various online educational resources provided by different MOOC’s platform. But it has been observed that is difficult to select the suitable learning material from the available massive educational resources online. Different recommendation systems have been developed to fulfill this need. Recommendation Systems try to assist the user by suggesting the objects that the user may be interested in, predicted on the basis of users known preferences or with similar features of the other users. In this paper we surveyed various recommendation systems and we provide comparative analysis of those systems.

Keywords

E-learning, Recommender system, Massive Online Open Courses

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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