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

J 2021

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

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

Základní údaje

Originální název

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

Autoři

MACÁK, Martin (703 Slovensko, garant, domácí), Daniela KRÚŽELOVÁ (703 Slovensko, domácí), Stanislav CHREN (703 Slovensko, domácí) a Barbora BÜHNOVÁ (203 Česká republika, domácí)

Vydání

Education and Information Technologies, 2021, 1360-2357

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 3.666

Kód RIV

RIV/00216224:14330/21:00121448

Organizační jednotka

Fakulta informatiky

DOI

http://dx.doi.org/10.1007/s10639-021-10564-6

UT WoS

000648824900001

Klíčová slova anglicky

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

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 24. 1. 2022 12:10, RNDr. Martin Macák, Ph.D.

Anotace

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.

Návaznosti

CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU
(Kód CEP: EF16_019/0000822)

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur (Akronym: C4e)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur, PO 1 Posilování kapacit pro kvalitní výzkum

EF16_019/0000822, projekt VaV

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur

MUNI/A/1549/2020, interní kód MU

Název: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 21 (Akronym: SKOMU)

Investor: Masarykova univerzita, Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 21

Citovat

MACÁK, Martin, Daniela KRÚŽELOVÁ, Stanislav CHREN a Barbora BÜHNOVÁ. Using Process Mining for Git Log Analysis of Projects in a Software Development Course. Education and Information Technologies. 2021, roč. 26, č. 5, s. 5939-5969. ISSN 1360-2357. Dostupné z: https://dx.doi.org/10.1007/s10639-021-10564-6.

@article{1762422,
   author = {Macák, Martin and Krúželová, Daniela and Chren, Stanislav and Bühnová, Barbora},
   article_number = {5},
   doi = {http://dx.doi.org/10.1007/s10639-021-10564-6},
   keywords = {Learning analytics; Mining software repositories; Software development; Process mining; Educational data mining; Git},
   language = {eng},
   issn = {1360-2357},
   journal = {Education and Information Technologies},
   title = {Using Process Mining for Git Log Analysis of Projects in a Software Development Course},
   url = {https://link.springer.com/article/10.1007%2Fs10639-021-10564-6},
   volume = {26},
   year = {2021}
}

TY  - JOUR
ID  - 1762422
AU  - Macák, Martin - Krúželová, Daniela - Chren, Stanislav - Bühnová, Barbora
PY  - 2021
TI  - Using Process Mining for Git Log Analysis of Projects in a Software Development Course
JF  - Education and Information Technologies
VL  - 26
IS  - 5
SP  - 5939-5969
EP  - 5939-5969
SN  - 13602357
KW  - Learning analytics
KW  - Mining software repositories
KW  - Software development
KW  - Process mining
KW  - Educational data mining
KW  - Git
UR  - https://link.springer.com/article/10.1007%2Fs10639-021-10564-6
N2  - 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.
ER  -

MACÁK, Martin, Daniela KRÚŽELOVÁ, Stanislav CHREN a Barbora BÜHNOVÁ. Using Process Mining for Git Log Analysis of Projects in a Software Development Course. \textit{Education and Information Technologies}. 2021, roč.~26, č.~5, s.~5939-5969. ISSN~1360-2357. Dostupné z: https://dx.doi.org/10.1007/s10639-021-10564-6.

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