Machine learning models to predict the dropouts in Massive Open Online Courses

Avinash Kashyap, Ashalatha Nayak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Massive Open Online Courses have emerged as an alternative to the traditional educational system because of the flexibility in timings and also it overcomes the economic and geographical barriers for the users. MOOCs also help learners from diverse background to communicate and exchange knowledge in MOOCs forums. The number of learners enrolling for such courses is very high, despite the unrestricted accessibility the completion rate is very low. Various factors affect the completion of the course by the students such as interest in the subject, purpose of enrolling in the subject, whether the lecturer is able to convey his knowledge to the students or not. EDM (Educational Data Mining) and LA (Learning Analytics) are the fields in which data of students learning activity is analyzed to obtain certain vital information or can be used in prediction using EDM tools and techniques. Data analysis shows that there is a strong relationship between the number of events such as click event, video watched forum post and the successful learner's outcome. Machine Learning algorithms are applied and the result shows that Decision Tree gives an optimum result with the highest performance.

Original languageEnglish
Title of host publication2018 3rd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1083-1087
Number of pages5
ISBN (Electronic)9781538624401
DOIs
Publication statusPublished - 05-2018
Event3rd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018 - Bangalore, India
Duration: 18-05-201819-05-2018

Publication series

Name2018 3rd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018 - Proceedings

Conference

Conference3rd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018
CountryIndia
CityBangalore
Period18-05-1819-05-18

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Health Informatics
  • Instrumentation

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    Kashyap, A., & Nayak, A. (2018). Machine learning models to predict the dropouts in Massive Open Online Courses. In 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018 - Proceedings (pp. 1083-1087). [9012279] (2018 3rd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTEICT42901.2018.9012279