Open AccessCustomer-Oriented Aggregators of Massive Open Online Courses: Opportunities and Prospects
Author(s) -
Elena Grigorievna Galizina,
Anna Borisovna Feoktistova,
Sergey A. Makushkin,
Irina Eduardovna Korotaeva,
Elena Yurievna Kartseva,
Natalia Udaltsova
Publication year - 2021
Publication title -
webology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.259
H-Index - 18
ISSN - 1735-188X
DOI - 10.14704/web/v18si05/web18238
Subject(s) - news aggregator , clarity , massive open online course , computer science , scheme (mathematics) , set (abstract data type) , world wide web , data science , mathematics , mathematical analysis , biochemistry , chemistry , programming language
In recent years, the number of online courses known as massive open online courses (MOOC) has increased significantly. Such courses are available on online providers’ sites, such as edX and Coursera. As a result, there is a notable reduction of clarity in terms of various course offerings, and this causes a need to change the MOOC description schemes to help inform potential applicants. The article is aimed at identifying the capabilities of customer-oriented MOOC aggregators and the prospects for their further improvement. The article presents approaches to the concept of customer focus, based on which the definition of a customer-oriented aggregator is formulated. The article analyses course descriptions used by MOOC providers and aggregators for their potential students. Based on this analysis, the authors develop a set of categories describing MOOC, used for the creation of a new MOOC description according to the customer-oriented criteria. The authors conclude that the optimal descriptive MOOC scheme on the MOOC aggregator should satisfy both the academic environment and the customer-oriented criteria that correspond to students’ interests when choosing a MOOC.