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

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

doi:10.1007/978-3-030-60128-7_24

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

Franklin Bernal (First Author)
, Jorge Maldonado-Mahauad
, Klinge Villalba-Condori
, Miguel Zúñiga-Prieto
, Jaime Veintimilla-Reyes
, Magali Mejía (Last Author)

Universidad de Cuenca
Pontificia Universidad Católica de Chile
Universidad Continental

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 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 language	English
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
Pages	307-325
Number of pages	19
ISBN (Print)	9783030601270
DOIs	https://doi.org/10.1007/978-3-030-60128-7_24
State	Published - 2020
Event	22nd International Conference on Human-Computer Interaction,HCII 2020 - Copenhagen, Denmark Duration: 19 Jul 2020 → 24 Jul 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12425 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Human-Computer Interaction,HCII 2020
Country/Territory	Denmark
City	Copenhagen
Period	19/07/20 → 24/07/20

Keywords

Coursera
Learning analytics
Learning strategies
MOOC
Process mining
Study sessions

Access to Document

10.1007/978-3-030-60128-7_24

Cite this

Bernal, F., Maldonado-Mahauad, J., Villalba-Condori, K., Zúñiga-Prieto, M., Veintimilla-Reyes, J., & Mejía, M. (2020). Analyzing Students’ Behavior in a MOOC Course: A Process-Oriented Approach. In C. Stephanidis, D. Harris, W.-C. Li, D. D. Schmorrow, C. M. Fidopiastis, P. Zaphiris, A. Ioannou, A. Ioannou, X. Fang, R. A. Sottilare, & J. Schwarz (Eds.), HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings (pp. 307-325). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12425 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-60128-7_24

Bernal, Franklin ; Maldonado-Mahauad, Jorge ; Villalba-Condori, Klinge et al. / Analyzing Students’ Behavior in a MOOC Course : A Process-Oriented Approach. HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings. editor / 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. Springer Science and Business Media Deutschland GmbH, 2020. pp. 307-325 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Analyzing Students{\textquoteright} Behavior in a MOOC Course: A Process-Oriented Approach",

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{\textquoteright} 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{\textquoteright} 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{\textquoteright} behavior in online environments.",

keywords = "Coursera, Learning analytics, Learning strategies, MOOC, Process mining, Study sessions",

author = "Franklin Bernal and Jorge Maldonado-Mahauad and Klinge Villalba-Condori and Miguel Z{\'u}{\~n}iga-Prieto and Jaime Veintimilla-Reyes and Magali Mej{\'i}a",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 22nd International Conference on Human-Computer Interaction,HCII 2020 ; Conference date: 19-07-2020 Through 24-07-2020",

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editor = "Constantine Stephanidis and Don Harris and Wen-Chin Li and Schmorrow, \{Dylan D.\} and Fidopiastis, \{Cali M.\} and Panayiotis Zaphiris and Andri Ioannou and Andri Ioannou and Xiaowen Fang and Sottilare, \{Robert A.\} and Jessica Schwarz",

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Bernal, F, Maldonado-Mahauad, J, Villalba-Condori, K, Zúñiga-Prieto, M , Veintimilla-Reyes, J & Mejía, M 2020, Analyzing Students’ Behavior in a MOOC Course: A Process-Oriented Approach. in C Stephanidis, D Harris, W-C Li, DD Schmorrow, CM Fidopiastis, P Zaphiris, A Ioannou, A Ioannou, X Fang, RA Sottilare & J Schwarz (eds), HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12425 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 307-325, 22nd International Conference on Human-Computer Interaction,HCII 2020, Copenhagen, Denmark, 19/07/20. https://doi.org/10.1007/978-3-030-60128-7_24

Analyzing Students’ Behavior in a MOOC Course: A Process-Oriented Approach. / Bernal, Franklin (First Author); Maldonado-Mahauad, Jorge; Villalba-Condori, Klinge et al.
HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings. ed. / 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. Springer Science and Business Media Deutschland GmbH, 2020. p. 307-325 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12425 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Analyzing Students’ Behavior in a MOOC Course

T2 - 22nd International Conference on Human-Computer Interaction,HCII 2020

AU - Bernal, Franklin

AU - Maldonado-Mahauad, Jorge

AU - Villalba-Condori, Klinge

AU - Zúñiga-Prieto, Miguel

AU - Veintimilla-Reyes, Jaime

AU - Mejía, Magali

PY - 2020

Y1 - 2020

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AB - 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.

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Bernal F, Maldonado-Mahauad J, Villalba-Condori K, Zúñiga-Prieto M , Veintimilla-Reyes J , Mejía M. Analyzing Students’ Behavior in a MOOC Course: A Process-Oriented Approach. In Stephanidis C, Harris D, Li WC, Schmorrow DD, Fidopiastis CM, Zaphiris P, Ioannou A, Ioannou A, Fang X, Sottilare RA, Schwarz J, editors, HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games - 22nd HCI International Conference, HCII 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 307-325. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-60128-7_24

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

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Learning analytics for the study of self -regulated learning strategies in a context of hybrid learning

Cite this

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

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

Learning analytics for the study of self -regulated learning strategies in a context of hybrid learning

Cite this