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.
|Title of host publication||HCI International 2020 – Late Breaking Papers|
|Subtitle of host publication||Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings|
|Editors||Constantine 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|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||19|
|State||Published - 2020|
|Event||22nd International Conference on Human-Computer Interaction,HCII 2020 - Copenhagen, Denmark|
Duration: 19 Jul 2020 → 24 Jul 2020
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||22nd International Conference on Human-Computer Interaction,HCII 2020|
|Period||19/07/20 → 24/07/20|
Bibliographical noteFunding 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.
© 2020, Springer Nature Switzerland AG.
- Learning analytics
- Learning strategies
- Process mining
- Study sessions