Engaging Learning Analytics in MOOCS: the good, the bad, and the ugly

Mohammad Khalil, Behnam Taraghi, Martin Ebner

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Learning Analytics is an emerging field in the vast areas of Educational Technology and Technology Enhanced Learning (TEL). It provides tools and techniques that offer researchers the ability to analyze, study, and benchmark institutions, learners and teachers as well as online learning environments such as MOOCs. Massive Open Online Courses (MOOCs) are considered to be a very active and an innovative form of bringing educational content to a broad community. Due to the reasons of being free and accessible to the public, MOOCs attracted a large number of heterogeneous learners who differ in education level, gender, and age. However, there are pressing demands to adjust the quality of the hosted courses, as well as controlling the high dropout ratio and the lack of interaction. With the help of Learning Analytics, it is possible to contain such issues. In this publication, we discuss the principles of engaging Learning Analytics in MOOCs learning environments and review its potential and capabilities (the good), constraints (the bad), and fallacy analytics (the ugly) based on our experience in last year's
Original languageEnglish
Title of host publicationInternational Conference on Education and New Developments
Place of PublicationLjubljana, Slovenia
Publication statusPublished - 13 Jun 2016

Fields of Expertise

  • Information, Communication & Computing


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