A Deep Learning Model for MOOC Dropout Prediction Using Learner's Course-relevant Activities

Mohamad T. Sultan, Hesham El Sayed, Manzoor Ahmed Khan, Mohammed Abduljabar

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

Abstract

Today, Open Massive Online Courses (MOOCs) have become very popular learning platforms with millions of participants. MOOCs provide a flexible distance-learning style courses usually delivered by top international universities. However, despite all benefits and features of MOOCs, these platforms have been heavily criticized due to students' high dropout rate. This have become a phenomenon on MOOCs, where users may enroll in a course but most of these users will dropout the course somewhere before the end. This has triggered the need for a development of a reliable and efficient dropout prediction model that can address this problem and maintain an encouraging learning activity. In this research, we present a deep leaning dropout predictor model to address this classification problem. By observing learner's early course activities and extensive feature engineering, we tried to predict the likelihood of student MOOCs dropout by using deep learning artificial neural networks (ANNs). Through selecting the best parameter values and using validation approach, our model was able to achieve 91% in terms of precision and 90% in terms of accuracy which are better than existing studies. Our obtained results are compared and benchmarked against the existing state of the art literature that addresses the same problem.

Original languageEnglish
Title of host publication2022 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13-18
Number of pages6
ISBN (Electronic)9798350309843
DOIs
Publication statusPublished - 2022
Event2022 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2022 - Virtual, Online, Egypt
Duration: Dec 18 2022Dec 21 2022

Publication series

Name2022 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2022

Conference

Conference2022 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2022
Country/TerritoryEgypt
CityVirtual, Online
Period12/18/2212/21/22

Keywords

  • ANN
  • Dropout prediction
  • MOOCs
  • deep learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management

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