Quality Assessment of Learners’ Programs by Grouping Source Code Metrics
Francisco Santos, Francisco Santos, Alana Oliveira, Alana Oliveira, Carlos Neto, Mario Teixeira
2021
Abstract
This article reports on the process of clustering source code metrics from beginner students in an Algorithms course in order to identify their learning profiles. Our approach relies on extracting a set of metadata from Lua programming assignments written by 60 Computer Science undergraduate students, comprising 21 practical exercises. A total of 13 metrics have been selected and submited to clustering algorithms and it was found that hierarchical grouping, K-means and DIANA proved to be more suitable to the set under study. Preliminary results on the relationship between student groups and source code quality are reported. Further research is required towards an automated student performance evaluation strategy to assist in student assessment based on source code quality.
DownloadPaper Citation
in Harvard Style
Santos F., Oliveira A., Neto C. and Teixeira M. (2021). Quality Assessment of Learners’ Programs by Grouping Source Code Metrics. In Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-502-9, pages 339-346. DOI: 10.5220/0010457003390346
in Bibtex Style
@conference{csedu21,
author={Francisco Santos and Alana Oliveira and Carlos Neto and Mario Teixeira},
title={Quality Assessment of Learners’ Programs by Grouping Source Code Metrics},
booktitle={Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2021},
pages={339-346},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010457003390346},
isbn={978-989-758-502-9},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 13th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - Quality Assessment of Learners’ Programs by Grouping Source Code Metrics
SN - 978-989-758-502-9
AU - Santos F.
AU - Oliveira A.
AU - Neto C.
AU - Teixeira M.
PY - 2021
SP - 339
EP - 346
DO - 10.5220/0010457003390346