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Authors: Francisco Alan de O. Santos 1 ; 2 ; Alana Oliveira 3 ; 2 ; Carlos S. Soares Neto 4 and Mario Meireles Teixeira 4

Affiliations: 1 Advanced Center of Informatics and Educational Research, Federal Institute of Maranhão (NAIPE/IFMA), Brazil ; 2 PhD Program in Computer Science, DCCMAPI/UFMA, Brazil ; 3 Computer Engineering, Federal University of Maranhão (UFMA), Brazil ; 4 Departament of Informatics, Federal University of Maranhão (UFMA), Brazil

Keyword(s): Computer Education, Programming, Cluster Analysis, Error Detection, Software Metrics.

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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
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; ISSN 2184-5026, SciTePress, pages 339-346. DOI: 10.5220/0010457003390346

@conference{csedu21,
author={Francisco Alan de O. Santos. and Alana Oliveira. and Carlos S. Soares Neto. and Mario Meireles 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},
issn={2184-5026},
}

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
IS - 2184-5026
AU - Santos, F.
AU - Oliveira, A.
AU - Neto, C.
AU - Teixeira, M.
PY - 2021
SP - 339
EP - 346
DO - 10.5220/0010457003390346
PB - SciTePress