A Survey on Recommendation Systems in E-learning

Vol-4 | Issue-03 | March 2019 | Published Online: 13 March 2019    PDF ( 345 KB )
DOI: https://doi.org/10.5281/zenodo.2592528
Tandel Ayushi 1; Uchhula Vasundhara 2

1ME student, Department of Computer Engineering, Gujarat, Surat (India)

2Assistant Professor, Department of Computer Engineering, Gujarat, Surat (India)


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.

E-learning, Recommender system, Massive Online Open Courses
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