Analyzing Students’ Behavior in a MOOC Course: A Process-Oriented Approach

Franklin Bernal, Jorge Maldonado-Mahauad, Klinge Orlando Villalba Condori, Miguel Zúñiga-Prieto, Jaime Veintimilla-Reyes, Magali Mejía

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

1 Scopus citations

Abstract

Massive Open Online Courses (MOOCs), are one of the most disruptive trends along the last 12 years. This is evidenced by the number of students enrolled since their emergence with over 101 million people taking one of the more than 11,400 MOOCs available. However, the approval rate of students in these types of courses is only about 5%. This has led to a great deal of interest among researchers in studying students’ behavior in these types of courses. The aim of this article is to explore the behavior of students in a MOOC. Specifically, to study students learning sequences and extract their behavioral patterns in the different study sessions. To reach the goal, using process mining techniques, process models of N = 1,550 students enrolled in a MOOC in Coursera were obtained. As a result, two groups of students were classified according to their study sessions, where differences were found both in the students’ interactions with the MOOC resources and in the way the lessons were approached on a weekly basis. In addition, students who passed the course repeated the assessments several times until they passed, without returning to review a video-lecture in advance. The results of this work contribute to extend the knowledge about students’ behavior in online environments.

Original languageEnglish
Title of host publicationHCI International 2020 – Late Breaking Papers
Subtitle of host publicationCognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings
EditorsConstantine Stephanidis, Don Harris, Wen-Chin Li, Dylan D. Schmorrow, Cali M. Fidopiastis, Panayiotis Zaphiris, Andri Ioannou, Andri Ioannou, Xiaowen Fang, Robert A. Sottilare, Jessica Schwarz
PublisherSpringer Science and Business Media Deutschland GmbH
Pages307-325
Number of pages19
ISBN (Print)9783030601270
DOIs
StatePublished - 2020
Externally publishedYes
Event22nd International Conference on Human-Computer Interaction,HCII 2020 - Copenhagen, Denmark
Duration: 19 Jul 202024 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12425 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Human-Computer Interaction,HCII 2020
Country/TerritoryDenmark
CityCopenhagen
Period19/07/2024/07/20

Bibliographical note

Funding Information:
This work has been cofunded by Direcci?n de Investigaci?n de la Universidad de Cuenca (DIUC), CuencaEcuador, under the project ?Anal?tica del aprendizaje para el estudio de estrategias de aprendizaje autorregulado en un contexto de aprendizaje h?brido? (DIUC_XVIII_2019_54). We want also to thanks to the Pontificia Universidad Cat?lica de Chile and Direcci?n de Educaci?n en Ingenier?a DEI.

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

  • Coursera
  • Learning analytics
  • Learning strategies
  • MOOC
  • Process mining
  • Study sessions

Fingerprint

Dive into the research topics of 'Analyzing Students’ Behavior in a MOOC Course: A Process-Oriented Approach'. Together they form a unique fingerprint.

Cite this