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Academic Success Assessment through Version Control Systems

Robotics group, dept. of Mechanical, Computer Science, and Aerospace Engineering, University of León, Campus de Vegazana s/n, 24071 León, Spain
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(4), 1492;
Received: 16 January 2020 / Revised: 14 February 2020 / Accepted: 18 February 2020 / Published: 21 February 2020
(This article belongs to the Special Issue Smart Learning)
Version control systems’ usage is a highly demanded skill in information and communication technology professionals. Thus, their usage should be encouraged by educational institutions. This work demonstrates that it is possible to assess if a student can pass a computer science-related subject by monitoring its interaction with a version control system. This paper proposes a methodology that compares the performance of several machine learning models so as to select the appropriate predicting model for the assessment of the students’ achievements. To fit predicting models, three subjects of the Degree in Computer Science at the University of León are considered to obtain the dataset: computer organization, computer programming, and operating systems extension. The common aspect of these subjects is their assignments, which are based on developing one or several programs with programming languages such as C or Java. To monitor the practical assignments and individual performance, a Git repository is employed allowing students to store source code, documentation, and supporting control versions. According to the presented experience, there is a huge correlation between the level of interaction for each student and the achieved grades. View Full-Text
Keywords: computer programming; version control system; machine learning; learning analytics computer programming; version control system; machine learning; learning analytics
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MDPI and ACS Style

Guerrero-Higueras, Á.M.; Fernández Llamas, C.; Sánchez González, L.; Gutierrez Fernández, A.; Esteban Costales, G.; Conde González, M.Á. Academic Success Assessment through Version Control Systems. Appl. Sci. 2020, 10, 1492.

AMA Style

Guerrero-Higueras ÁM, Fernández Llamas C, Sánchez González L, Gutierrez Fernández A, Esteban Costales G, Conde González MÁ. Academic Success Assessment through Version Control Systems. Applied Sciences. 2020; 10(4):1492.

Chicago/Turabian Style

Guerrero-Higueras, Ángel M., Camino Fernández Llamas, Lidia Sánchez González, Alexis Gutierrez Fernández, Gonzalo Esteban Costales, and Miguel Á. Conde González. 2020. "Academic Success Assessment through Version Control Systems" Applied Sciences 10, no. 4: 1492.

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