J 2021

Using Process Mining for Git Log Analysis of Projects in a Software Development Course

MACÁK, Martin, Daniela KRÚŽELOVÁ, Stanislav CHREN and Barbora BÜHNOVÁ

Basic information

Original name

Using Process Mining for Git Log Analysis of Projects in a Software Development Course

Authors

MACÁK, Martin (703 Slovakia, guarantor, belonging to the institution), Daniela KRÚŽELOVÁ (703 Slovakia, belonging to the institution), Stanislav CHREN (703 Slovakia, belonging to the institution) and Barbora BÜHNOVÁ (203 Czech Republic, belonging to the institution)

Edition

Education and Information Technologies, 2021, 1360-2357

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 3.666

RIV identification code

RIV/00216224:14330/21:00121448

Organization unit

Faculty of Informatics

DOI

UT WoS

000648824900001

Keywords in English

Learning analytics; Mining software repositories; Software development; Process mining; Educational data mining; Git

Tags

International impact, Reviewed
Změněno: 24/1/2022 12:10, RNDr. Martin Macák, Ph.D.

Abstract

V originále

Understanding the processes in education, such as the student learning behavior within a specific course, is a key to continuous course improvement. In online learning systems, students’ learning can be tracked and examined based on data collected by the systems themselves. However, it is non-trivial to decide how to extract the desired students’ behavior from the limited data in traditional classroom courses. Software development courses are a domain where student behavior analysis would be especially useful, as continuous teaching improvement in this fast progressing domain is necessary. In this paper, we propose to use process mining for improvement-motivated process analysis of a software development course (web development in particular). To this end, we analyze Git logs of students’ projects to understand their development processes. Process mining has been chosen as it can help us to find a descriptive model of this process. The main contribution of this paper is the detailed methodology of process mining usage for students’ project development analysis, considering various commit characteristics, which are crucial in understanding student coding-behavior patterns. The process mining analysis proved to be very useful, indicating multiple directions for the course improvement, which we also include in this work as a secondary contribution. The third contribution of this work is the summary and discussion of the process mining advantages and current gaps in process mining research for this task. The data we used are made publicly available to other researchers.

Links

CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU
(CEP code: EF16_019/0000822)
Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Acronym: C4e)
Investor: Ministry of Education, Youth and Sports of the CR, CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence, Priority axis 1: Strengthening capacities for high-quality research
EF16_019/0000822, research and development project
Name: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur
MUNI/A/1549/2020, interní kód MU
Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 21 (Acronym: SKOMU)
Investor: Masaryk University