A Methodology for Using GitLab for Software Engineering Learning Analytics

Julio Cesar Cortes Rios, Kamilla Kopec-Harding, Sukru Eraslan, Christopher Page, Robert Haines, Caroline Jay, Suzanne Embury

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

To bridge the digital skills gap, we need to train more people in Software Engineering techniques. This paper reports on a project exploring the way students solve tasks using collaborative development platforms and version control systems, such as GitLab, to find patterns and evaluation metrics that can be used to improve the course content and reflect on the most common issues the students are facing. In this paper, we explore Learning Analytics approaches that can be used with GitLab and similar tools, and discuss the challenges raised when applying those approaches in Software Engineering Education, with the objective of building a pipeline that supports the full Learning Analytics cycle, from data extraction to data analysis. We focus in particular on the data anonymisation step of the proposed pipeline to explore the available alternatives to satisfy the data protection requirements when handling personal information in academic environments for research purposes.
Original languageEnglish
Title of host publication12th International Workshop on Cooperative and Human Aspects of Software Engineering
Publication statusPublished - 27 May 2019
Event12th International Workshop on Cooperative and Human Aspects of Software Engineering - Montreal, Canada
Duration: 25 May 2019 → …

Conference

Conference12th International Workshop on Cooperative and Human Aspects of Software Engineering
Abbreviated titleCHASE 2019
Country/TerritoryCanada
CityMontreal
Period25/05/19 → …

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