MOOCs One-Stop Shop: A Realization of a Unified MOOCs Search Engine

Abstract

Massive open online courses (MOOCs) have gained great popularity among adult learners, as many professionals use them to advance their careers. However, many MOOCs providers offer a large number of courses across many subjects, making the search and selection of the appropriate course cumbersome for the learner through a regular Web search. Hence, there is a crucial need for a unified search engine that acts as a one-stop-shop for all MOOCs. This paper presents the design and implementation of a unified MOOCs search model for retrieving and recommending courses from multiple MOOCs. The evaluation showed that the proposed model is reliable and convenient. Initial results showed that the system could present courses from multiple MOOCs that suit users' needs. Moreover, the recommendation functionality is applied for a better user-centric orientation.