Discovering students’ learning strategies in a visual programming MOOC through process mining techniques

Narjes Rohani; Kobi Gal; Michael Gallagher; Areti Manataki

doi:10.1007/978-3-031-27815-0_39

Discovering students’ learning strategies in a visual programming MOOC through process mining techniques

Narjes Rohani^*, Kobi Gal, Michael Gallagher, Areti Manataki

^*Corresponding author for this work

School of Computer Science

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

1 Citation (Scopus)

24 Downloads (Pure)

Abstract

Understanding students’ learning patterns is key for supporting their learning experience and improving course design. However, this is particularly challenging in courses with large cohorts, which might contain diverse students that exhibit a wide range of behaviours. In this study, we employed a previously developed method, which considers process flow, sequence, and frequency of learning actions, for detecting students’ learning tactics and strategies. With the aim of demonstrating its applicability to a new learning context, we applied the method to a large-scale online visual programming course. Four low-level learning tactics were identified, ranging from project- and video-focused to explorative. Our results also indicate that some students employed all four tactics, some used course assessments to strategize about how to study, while others selected only two or three of all learning tactics. This research demonstrates the applicability and usefulness of process mining for discovering meaningful and distinguishable learning strategies in large courses with thousands of learners.

Original language	English
Title of host publication	Process mining workshops
Subtitle of host publication	ICPM 2022 international workshops, Bozen-Bolzano, Italy, October 23–28, 2022, revised selected papers
Editors	Marco Montali, Arik Senderovich, Matthias Weidlich
Place of Publication	Cham
Publisher	Springer Science and Business Media B.V.
Pages	539-551
Number of pages	13
ISBN (Electronic)	9783031278150
ISBN (Print)	9783031278143
DOIs	https://doi.org/10.1007/978-3-031-27815-0_39
Publication status	Published - 26 Mar 2023
Event	1st International Workshop “Education meets Process Mining" (EduPM 2022), part of the International Conference on Process Mining (ICPM 2022) - Bozen-Bolzano, Italy Duration: 24 Oct 2022 → 24 Oct 2022 https://haplab.org/edupm2022/

Publication series

Name	Lecture notes in business information processing
Volume	468
ISSN (Print)	1865-1348
ISSN (Electronic)	1865-1356

Conference

Conference	1st International Workshop “Education meets Process Mining" (EduPM 2022), part of the International Conference on Process Mining (ICPM 2022)
Country/Territory	Italy
City	Bozen-Bolzano
Period	24/10/22 → 24/10/22
Internet address	https://haplab.org/edupm2022/

Keywords

Process mining
Massive open online courses
Educational data mining
Visual programming
Learning tactic
Learning strategy

Access to Document

10.1007/978-3-031-27815-0_39Licence: CC BY

Rohani-2023-Discovering-student-learning-strategies-ICPM2022-539-CCBY
Copyright © 2023 the Author(s). Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Final published version, 1.95 MBLicence: CC BY

Cite this

Rohani, N., Gal, K., Gallagher, M., & Manataki, A. (2023). Discovering students’ learning strategies in a visual programming MOOC through process mining techniques. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process mining workshops: ICPM 2022 international workshops, Bozen-Bolzano, Italy, October 23–28, 2022, revised selected papers (pp. 539-551). (Lecture notes in business information processing; Vol. 468). Springer Science and Business Media B.V.. https://doi.org/10.1007/978-3-031-27815-0_39

Rohani, Narjes ; Gal, Kobi ; Gallagher, Michael et al. / Discovering students’ learning strategies in a visual programming MOOC through process mining techniques. Process mining workshops: ICPM 2022 international workshops, Bozen-Bolzano, Italy, October 23–28, 2022, revised selected papers. editor / Marco Montali ; Arik Senderovich ; Matthias Weidlich. Cham : Springer Science and Business Media B.V., 2023. pp. 539-551 (Lecture notes in business information processing).

@inproceedings{2734b4830efa4b41ad70def932bca2ad,

title = "Discovering students{\textquoteright} learning strategies in a visual programming MOOC through process mining techniques",

abstract = "Understanding students{\textquoteright} learning patterns is key for supporting their learning experience and improving course design. However, this is particularly challenging in courses with large cohorts, which might contain diverse students that exhibit a wide range of behaviours. In this study, we employed a previously developed method, which considers process flow, sequence, and frequency of learning actions, for detecting students{\textquoteright} learning tactics and strategies. With the aim of demonstrating its applicability to a new learning context, we applied the method to a large-scale online visual programming course. Four low-level learning tactics were identified, ranging from project- and video-focused to explorative. Our results also indicate that some students employed all four tactics, some used course assessments to strategize about how to study, while others selected only two or three of all learning tactics. This research demonstrates the applicability and usefulness of process mining for discovering meaningful and distinguishable learning strategies in large courses with thousands of learners.",

keywords = "Process mining, Massive open online courses, Educational data mining, Visual programming, Learning tactic, Learning strategy",

author = "Narjes Rohani and Kobi Gal and Michael Gallagher and Areti Manataki",

note = "Funding: This work was supported by the Medical Research Council [grant number MR/N013166/1].; 1st International Workshop “Education meets Process Mining{"} (EduPM 2022), part of the International Conference on Process Mining (ICPM 2022) ; Conference date: 24-10-2022 Through 24-10-2022",

year = "2023",

month = mar,

day = "26",

doi = "10.1007/978-3-031-27815-0_39",

language = "English",

isbn = "9783031278143",

series = "Lecture notes in business information processing",

publisher = "Springer Science and Business Media B.V.",

pages = "539--551",

editor = "Marco Montali and Arik Senderovich and Matthias Weidlich",

booktitle = "Process mining workshops",

address = "Germany",

url = "https://haplab.org/edupm2022/",

}

Rohani, N, Gal, K, Gallagher, M & Manataki, A 2023, Discovering students’ learning strategies in a visual programming MOOC through process mining techniques. in M Montali, A Senderovich & M Weidlich (eds), Process mining workshops: ICPM 2022 international workshops, Bozen-Bolzano, Italy, October 23–28, 2022, revised selected papers. Lecture notes in business information processing, vol. 468, Springer Science and Business Media B.V., Cham, pp. 539-551, 1st International Workshop “Education meets Process Mining" (EduPM 2022), part of the International Conference on Process Mining (ICPM 2022), Bozen-Bolzano, Italy, 24/10/22. https://doi.org/10.1007/978-3-031-27815-0_39

Discovering students’ learning strategies in a visual programming MOOC through process mining techniques. / Rohani, Narjes; Gal, Kobi; Gallagher, Michael et al.
Process mining workshops: ICPM 2022 international workshops, Bozen-Bolzano, Italy, October 23–28, 2022, revised selected papers. ed. / Marco Montali; Arik Senderovich; Matthias Weidlich. Cham: Springer Science and Business Media B.V., 2023. p. 539-551 (Lecture notes in business information processing; Vol. 468).

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

TY - GEN

T1 - Discovering students’ learning strategies in a visual programming MOOC through process mining techniques

AU - Rohani, Narjes

AU - Gal, Kobi

AU - Gallagher, Michael

AU - Manataki, Areti

N1 - Funding: This work was supported by the Medical Research Council [grant number MR/N013166/1].

PY - 2023/3/26

Y1 - 2023/3/26

N2 - Understanding students’ learning patterns is key for supporting their learning experience and improving course design. However, this is particularly challenging in courses with large cohorts, which might contain diverse students that exhibit a wide range of behaviours. In this study, we employed a previously developed method, which considers process flow, sequence, and frequency of learning actions, for detecting students’ learning tactics and strategies. With the aim of demonstrating its applicability to a new learning context, we applied the method to a large-scale online visual programming course. Four low-level learning tactics were identified, ranging from project- and video-focused to explorative. Our results also indicate that some students employed all four tactics, some used course assessments to strategize about how to study, while others selected only two or three of all learning tactics. This research demonstrates the applicability and usefulness of process mining for discovering meaningful and distinguishable learning strategies in large courses with thousands of learners.

AB - Understanding students’ learning patterns is key for supporting their learning experience and improving course design. However, this is particularly challenging in courses with large cohorts, which might contain diverse students that exhibit a wide range of behaviours. In this study, we employed a previously developed method, which considers process flow, sequence, and frequency of learning actions, for detecting students’ learning tactics and strategies. With the aim of demonstrating its applicability to a new learning context, we applied the method to a large-scale online visual programming course. Four low-level learning tactics were identified, ranging from project- and video-focused to explorative. Our results also indicate that some students employed all four tactics, some used course assessments to strategize about how to study, while others selected only two or three of all learning tactics. This research demonstrates the applicability and usefulness of process mining for discovering meaningful and distinguishable learning strategies in large courses with thousands of learners.

KW - Process mining

KW - Massive open online courses

KW - Educational data mining

KW - Visual programming

KW - Learning tactic

KW - Learning strategy

UR - https://doi.org/10.1007/978-3-031-27815-0

U2 - 10.1007/978-3-031-27815-0_39

DO - 10.1007/978-3-031-27815-0_39

M3 - Conference contribution

SN - 9783031278143

T3 - Lecture notes in business information processing

SP - 539

EP - 551

BT - Process mining workshops

A2 - Montali, Marco

A2 - Senderovich, Arik

A2 - Weidlich, Matthias

PB - Springer Science and Business Media B.V.

CY - Cham

T2 - 1st International Workshop “Education meets Process Mining" (EduPM 2022), part of the International Conference on Process Mining (ICPM 2022)

Y2 - 24 October 2022 through 24 October 2022

ER -

Rohani N, Gal K, Gallagher M, Manataki A. Discovering students’ learning strategies in a visual programming MOOC through process mining techniques. In Montali M, Senderovich A, Weidlich M, editors, Process mining workshops: ICPM 2022 international workshops, Bozen-Bolzano, Italy, October 23–28, 2022, revised selected papers. Cham: Springer Science and Business Media B.V. 2023. p. 539-551. (Lecture notes in business information processing). Epub 2023 Mar 25. doi: 10.1007/978-3-031-27815-0_39

Discovering students’ learning strategies in a visual programming MOOC through process mining techniques

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this