Top

Published in:

2019 | OriginalPaper | Chapter

Academic Behavior Analysis in Virtual Courses Using a Data Mining Approach

Authors : Dario Delgado-Quintero, Olmer Garcia-Bedoya, Diego Aranda-Lozano, Pablo Munevar-Garcia, Cesar O. Diaz

Published in: Applied Informatics

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Virtual education is one of the educational trends of the 21st century; however knowing the perception of students is a new challenge. This article presents a proposal to define the essential components for the construction of a model for the analysis of the records given by the students enrolled in courses in a virtual learning platform (VLE). The article after a review of the use of data analytics in VLE presents a strategy to characterize the data generated by the student according to the frequency and the slice of the day and week that access the material. With these metrics, clustering analysis is performed and visualized through a map of self-organized Neural Networks. The results presented correspond to five courses of a postgraduate career, where was found that students have greater participation in the forums in the daytime than in the nighttime. Also, they participate more during the week than weekends. These results open the possibility to identify possible early behaviors, which let to implement tools to prevent future desertions or possible low academic performance.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Bioinformatics Methods to Discover Antivirals Against Zika Virus

next chapter Analysis of Usability of Various Geosocial Network POI in Tourism

Alias, U.F., Ahmad, N.B., Hasan, S.: Mining of E-learning behavior using SOM clustering. In: 6th ICT International Student Project Conference: Elevating Community Through ICT, ICT-ISPC 2017, pp. 1–4 (2017). https://doi.org/10.1109/ICT-ISPC.2017.8075350

Bara, M.W., Ahmad, N.B., Modu, M.M., Ali, H.A.: Self-organizing map clustering method for the analysis of e-learning activities. In: 2018 Majan International Conference (MIC), pp. 1–5, March 2018. https://doi.org/10.1109/MINTC.2018.8363155

Baruque, C.B., Amaral, M.A., Barcellos, A., da Silva Freitas, J.a.C., Longo, C.J.: Analysing users’ access logs in Moodle to improve e learning. In: Proceedings of the 2007 Euro American Conference on Telematics and Information Systems, EATIS 2007, pp. 72:1–72:4. ACM, New York (2007). https://doi.org/10.1145/1352694.1352767

Charitopoulos, A., Rangoussi, M., Koulouriotis, D.: Educational data mining and data analysis for optimal learning content management: applied in Moodle for undergraduate engineering studies. In: 2017 IEEE Global Engineering Education Conference (EDUCON), pp. 990–998, April 2017. https://doi.org/10.1109/EDUCON.2017.7942969

Conde, M., Garca-Pealvo, F., Fidalgo-Blanco,, Sein-Echaluce, M.: Study of the flexibility of a learning analytics tool to evaluate teamwork competence acquisition in different contexts. In: CEUR workshop Proceedings, vol. 1925, pp. 63–77 (2017). ceur-ws.org/Vol-1925/paper07.pdf. cited By 0

Dhingra, S., Chaudhry, K.: A study of the impact of data warehousing and data mining implementation on marketing effort. Int. J. Adv. Stud. Comput. Sci. Eng. 7(1), 13–20 (2018)

Elaal, S.: E-learning using data mining. Chin. Egypt. Res. J. Helwan Univ. (2013)

Gamie, E.A., El-Seoud, M.S.A., Salama, M.A., Hussein, W.: Pedagogical and elearning logs analyses to enhance students’ performance. In: Proceedings of the 7th International Conference on Software and Information Engineering, ICSIE 2018, pp. 116–120. ACM, New York (2018). https://doi.org/10.1145/3220267.3220289. Cited by 0

Grover, V., Chiang, R.H., Liang, T.P., Zhang, D.: Creating strategic business value from big data analytics: a research framework. J. Manag. Inf. Syst. 35(2), 388–423 (2018)CrossRef

10.

Hernández-García, Á., Acquila-Natale, E., Iglesías-Pradas, S., Chaparro-Peláez, J.: Design of an extraction, transform and load process for calculation of teamwork indicators in Moodle. In: LASI-SPAIN (2018). ceur-ws.org/Vol-2188/Paper7.pdf

11.

Kohonen, T.: The self-organizing map. Proc. IEEE 78(9), 1464–1480 (1990). https://doi.org/10.1109/5.58325CrossRef

12.

Kolekar, S.V., Pai, R.M., Manohara Pai, M.M.: Adaptive user interface for Moodle based E-learning system using learning styles. Procedia Comput. Sci. 135, 606–615 (2018). https://doi.org/10.1016/j.procs.2018.08.226. The 3rd International Conference on Computer Science and Computational Intelligence (ICCSCI 2018): Empowering Smart Technology in Digital Era for a Better LifeCrossRef

13.

Konstantinidis, A., Grafton, C.: Using Excel Macros to Analyse Moodle Logs. UK Research.Moodle.Net, pp. 4–6 (2013). http://research.moodle.net/pluginfile.php/333/mod_data/content/1233/Using Excel Macros to Analyse Moodle Logs.pdf

14.

Moreira Félix, I., Ambrósio, A.P., Silva Neves, P., Siqueira, J., Duilio Brancher, J.: Moodle predicta: a data mining tool for student follow up. In: Proceedings of the 9th International Conference on Computer Supported Education 1 (CSEDU), pp. 339–346 (2017). https://doi.org/10.5220/0006318403390346

15.

Poon, L.K.M., Kong, S.-C., Wong, M.Y.W., Yau, T.S.H.: Mining sequential patterns of students’ access on learning management system. In: Tan, Y., Takagi, H., Shi, Y. (eds.) DMBD 2017. LNCS, vol. 10387, pp. 191–198. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61845-6_20CrossRef

16.

Poon, L.K.M., Kong, S.-C., Yau, T.S.H., Wong, M., Ling, M.H.: Learning analytics for monitoring students participation online: visualizing navigational patterns on learning management system. In: Cheung, S.K.S., Kwok, L., Ma, W.W.K., Lee, L.-K., Yang, H. (eds.) ICBL 2017. LNCS, vol. 10309, pp. 166–176. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59360-9_15CrossRef

17.

Qiao, C., Hu, X.: Discovering student behavior patterns from event logs: Preliminary results on a novel probabilistic latent variable model. In: 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT), pp. 207–211, July 2018. https://doi.org/10.1109/ICALT.2018.00056

18.

Raga, R.C., Raga, J.D.: A comparison of college faculty and student class activity in an online learning environment using course log data. In: 2017 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computed, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), pp. 1–6, August 2017. https://doi.org/10.1109/UIC-ATC.2017.8397475

19.

Ros, S., Lázaro, J.C., Robles-Gómez, A., Caminero, A.C., Tobarra, L., Pastor, R.: Analyzing content structure and Moodle milestone to classify student learning behavior in a basic desktop tools course. In: Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality, TEEM 2017, pp. 42:1–42:6. ACM, New York (2017). https://doi.org/10.1145/3144826.3145392

20.

Porras, J.T., Alcántara-Manzanares, J., García, S.R.: Virtual platforms use: a useful monitoring tool. EDMETIC 7(1), 242–255 (2018). https://doi.org/10.21071/edmetic.v6i2.8696CrossRef

21.

Sheard, J., Ceddia, J., Hurst, J., Tuovinen, J.: Inferring student learning behaviour from website interactions: a usage analysis. Educ. Inf. Technol. 8(3), 245–266 (2003). https://doi.org/10.1023/A:1026360026073CrossRef

22.

Shim, J.P., French, A.M., Guo, C., Jablonski, J.: Big data and analytics: issues, solutions, and ROI. CAIS 37, 39 (2015)CrossRef

23.

Smith, S.M., et al.: How might the development of data mining and log analysis systems for the Moodle virtual learning environment improve computer science students’ course engagement and encourage course designers’ future engagement with data analysis methods for the evaluation of course resources? Ph.D. thesis, University of Lincoln (2017). http://eprints.lincoln.ac.uk/30882/

24.

Vega, A.B.: Mejora en el descubrimiento de modelos de minería de procesos en educación mediante agrupación de datos de interacción con la plataforma Moodle. Ph.D. thesis, Universidad de Córdoba (2018)

25.

Verma, A., Rathore, S., Vishwakarma, S., Goswani, S.: Multilevel analysis of studentś feedback using Moodle logs in virtual cloud environment. Int. J. Comput. Sci. Inf. Technol. 9, 15–28 (2017). https://doi.org/10.5281/zenodo.2558650CrossRef

26.

Wu, X., et al.: Top 10 algorithms in data mining. Knowl. Inf. Syst. 14(1), 1–37 (2008). https://doi.org/10.1007/s10115-007-0114-2CrossRef

Title: Academic Behavior Analysis in Virtual Courses Using a Data Mining Approach
Authors: Dario Delgado-Quintero
Olmer Garcia-Bedoya
Diego Aranda-Lozano
Pablo Munevar-Garcia
Cesar O. Diaz
Publisher: Springer International Publishing
Book: Applied Informatics
Print ISBN: 978-3-030-32474-2

Electronic ISBN: 978-3-030-32475-9

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-32475-9_2

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner