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Authors
Affiliations
1 School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Mesa, AZ 85212, US
Source
Journal of Engineering Education Transformations, Vol 0, No SP 1 (2018), Pagination:
Abstract
With so many online courses offered as Massive Open Online Courses (MOOC), it is becoming increasingly difficult for an enduser to gauge which course best fits their needs. It would be very helpful for them to make a choice if there is a single place where they can visually compare the offerings of various MOOC providers for the course they are interested in. Previous work has been done in this area through the MOOCLink project that involved integrating data from Coursera, EdX, and Udacity and generation of semantically linked data. The research objective of this paper is to devise algorithms to include data from new MOOC providers and maintain the quality of data through MOOCLink application, as there are lots of new courses being constantly added and old courses being removed by MOOC providers. We present the integration of data from various MOOC providers and algorithms for incrementally updating linked data to maintain their quality in order to provide an interactive MOOC aggregator environment for students to be engaged with up-to-date data.
Keywords
Linked Data, Semantic Web, Engineering Education, Learning Management Systems.
