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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bergman, J., Sams, A.: How the flipped classroom was born. The Daily Riff Online (2011). http://www.thedailyriff.com/articles/how-the-flipped-classroom-is-radically-transforming-learning-536.php
Pérez-Álvarez, R., Maldonado, J.J., Rendich, R., Pérez-Sanagustín, M., Sapunar, D.: Observatorio MOOC UC: la Adopción de MOOCs en la Educación Superior en América Latina y Europa. In: Actas la Jorn. MOOCs en español en EMOOCs 2017, vol. 2017, pp. 5–14 (2017)
Shah, D.: By the numbers: MOOCs in 2019. Class Central (2020). https://www.classcentral.com/report/mooc-stats-2019/
Kizilcec, R.F., Cohen, G.L.: Eight-minute self-regulation intervention raises educational attainment at scale in individualist but not collectivist cultures. Proc. Natl. Acad. Sci. 114, 4348–4353 (2017)
Kizilcec, R.F., Piech, C., Schneider, E.: Deconstructing disengagement: Analyzing learner subpopulations in massive open online courses. In: ACM International Conference Proceeding Series (2013)
Ferguson, R., Clow, D.: Examining engagement: analysing learner subpopulations in massive open online courses (MOOCs). In: ACM International Conference Proceeding Series (2015)
Normandi Atiaja Atiaja, L., Segundo Guerrero Proenza, R.: MOOCs: origin, characterization, principal problems and challenges in higher education. J. E-Learn. Knowl. Soc. (2016)
Alonso-Mencía, M.E., Alario-Hoyos, C., Maldonado-Mahauad, J., Estévez-Ayres, I., Pérez-Sanagustín, M., Delgado Kloos, C.: Self-regulated learning in MOOCs: lessons learned from a literature review. Educ. Rev. 72, 319–345 (2019)
Maldonado-Mahauad, J., Pérez-Sanagustín, M., Kizilcec, R.F., Morales, N., Munoz-Gama, J.: Mining theory-based patterns from Big data: identifying self-regulated learning strategies in massive open online courses. Comput. Human Behav. 80, 179–196 (2018)
Fincham, O.E., Gasevic, D.V., Jovanovic, J.M., Pardo, A.: From study tactics to learning strategies: an analytical method for extracting interpretable representations. IEEE Trans. Learn. Technol. 12, 59–72 (2018)
Geigle, C., Zhai, C.X.: Modeling MOOC student behavior with two-layer hidden Markov models. In: L@S 2017 - Proceedings of the 4th (2017) ACM Conference on Learning at Scale (2017)
Matcha, W., et al.: Detection of learning strategies: a comparison of process, sequence and network analytic approaches (2019)
Davis, D., Seaton, D., Hauff, C., Houben, G.-J.: Toward large-scale learning design (2018)
Pashler, H., Wagenmakers, E.J.: Editors’ introduction to the special section on replicability in psychological science: a crisis of confidence? Perspect. Psychol. Sci. 7, 528–530 (2012)
Cole, M.: The cultural context of learning and thinking: an exploration in experimental anthropology (1971)
Jovanović, J., Gašević, D., Dawson, S., Pardo, A., Mirriahi, N.: Learning analytics to unveil learning strategies in a flipped classroom. Internet High. Educ. 33, 74–85 (2017)
Mukala, P., Buijs, J., Leemans, M., Van Der Aalst, W.: Learning analytics on coursera event data: a proceb mining approach. In: CEUR Workshop Proceedings (2015)
Van den Beemt, A., Buijs, J., Van der Aalst, W.: Analysing structured learning behaviour in massive open online courses (MOOCs): an approach based on process mining and clustering. Int. Rev. Res. Open Distrib. Learn. 19(5) (2018)
de Barba, P.G., Malekian, D., Oliveira, E.A., Bailey, J., Ryan, T., Kennedy, G.: The importance and meaning of session behaviour in a MOOC. Comput. Educ. 146(2019), 103772 (2020)
Romero, M., Usart, M.: The time factor in MOOCS: time-on-task, interaction temporal patterns, and time perspectives in a MOOC. In: CSEDU 2014 - Proceedings of the 6th International Conference on Computer Supported Education (2014)
Sapunar-Opazo, D., Pérez-Álvarez, R., Maldonado-Mahauad, J., Alario-Hoyos, C., Pérez-Sanagustín, M.: Analyzing learners’ activity beyond the MOOC. In: CEUR Workshop Proceedings (2018)
Kovanović, V., Gašević, D., Dawson, S., Joksimović, S., Baker, R.S., Hatala, M.: Penetrating the black box of time-on-task estimation. In: ACM International Conference Proceeding Series (2015)
Tough, A.: The Adult’s learning projects: a fresh approach to theory (1971)
van Eck, M.L., Lu, X., Leemans, S.J.J., van der Aalst, W.M.P.: PM2: a process mining project methodology. In: Zdravkovic, J., Kirikova, M., Johannesson, P. (eds.) CAiSE 2015. LNCS, vol. 9097, pp. 297–313. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19069-3_19
Maldonado, J.J., Pérez-Sanagustín, M., Bermeo, J.L., Muñoz, L., Pacheco, G., Espinoza, I.: Flipping the classroom with MOOCs. A pilot study exploring differences between self-regulated learners. In: 12th Latin American Conference on Learning Objects and Technologies, LACLO 2017 (2017)
Günther, C.-A., Rozinat, A.: Disco: discover your processes. In: Demonstration Track 10th International Conference Business Process Management (BPM 2012), vol. 940, pp. 40–44 (2012)
Maldonado, J.J., Palta, R., Vázquez, J., Bermeo, J.L., Pérez-sanagustín, M., Munoz-gama, J.: Exploring differences in how learners navigate in MOOCs based on self-regulated learning and learning styles (2016)
Mukala, P., Buijs, J., Leemans, M., van der Aalst, W.: Exploring students’ learning behaviour in MOOCs using process mining techniques. In: Computing Conference (2016)
Guo, P.J., Reinecke, K.: Demographic differences in how students navigate through MOOCs. In: L@S 2014 - Proceedings of the 1st ACM Conference on Learning at Scale (2014)
Sonnenberg, C., Bannert, M.: Discovering the effects of metacognitive prompts on the sequential structure of SRL-processes using process mining techniques. J. Learn. Anal. 2(1), 72–100 (2015)
Alharbi, A., Paul, D., Henskens, F., Hannaford, M.: An investigation into the learning styles and self-regulated learning strategies for computer science students. In: ASCILITE 2011 - The Australasian Society for Computers in Learning in Tertiary Education (2011)
Mukala, M.P., Buijs, J.C.A.M., Leemans, M., van der Aalst, W.M.P.: Learning analytics on coursera event data. In: Simpda (2015)
Acknowledgements
This work has been co-funded by Dirección de Investigación de la Universidad de Cuenca (DIUC), Cuenca-Ecuador, under the project “Analítica del aprendizaje para el estudio de estrategias de aprendizaje autorregulado en un contexto de aprendizaje híbrido” (DIUC_XVIII_2019_54). We want also to thanks to the Pontificia Universidad Católica de Chile and Dirección de Educación en Ingeniería - DEI.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
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: Stephanidis, C., et al. HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games. HCII 2020. Lecture Notes in Computer Science(), vol 12425. Springer, Cham. https://doi.org/10.1007/978-3-030-60128-7_24
Download citation
DOI: https://doi.org/10.1007/978-3-030-60128-7_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-60127-0
Online ISBN: 978-3-030-60128-7
eBook Packages: Computer ScienceComputer Science (R0)