D 2019

Using Process Mining Techniques to Discover Student’s Activities, Navigation Paths, and Behavior in LMS Moodle

DOLÁK, Radim

Basic information

Original name

Using Process Mining Techniques to Discover Student’s Activities, Navigation Paths, and Behavior in LMS Moodle

Authors

DOLÁK, Radim (203 Czech Republic, guarantor, belonging to the institution)

Edition

Cham, Innovative Technologies and Learning. ICITL 2019. Lecture Notes in Computer Science, vol 11937. p. 129-138, 10 pp. 2019

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/47813059:19520/19:A0000051

Organization unit

School of Business Administration in Karvina

ISBN

978-30303-5-3

Keywords in English

E-learning; Moodle; Process mining; DISCO

Tags

Reviewed
Změněno: 9/1/2020 11:09, Ing. Radim Dolák, Ph.D.

Abstract

V originále

This study explores using process mining techniques for analysis of Moodle logs. This topic is very interesting because the use and applications of e-learning solutions have been rising for last decade in the Czech Republic in both academic and commercial area. This study explores using process mining techniques to discover student’s activities, navigation paths, and behavior in LMS Moodle. Data from 701 students from Silesian University in Opava, School of Business Administration in Karvina who followed an online course called “Informatics for Economists I” was used. The events log is from the winter semester of the academic year 2016/2017 and consists of 32 984 events, 33 activities which were conducted by 701 students. It was applied process mining techniques that are implemented in a tool called Disco by Fluxicon. The reader should learn from this study about current promising techniques for analyzing data from e-learning systems and especially about using process mining techniques for Moodle events log analysis.