Automatic Recognition of Rubric Representations in Programming Exercises Clusters
DOI:
https://doi.org/10.5753/rbie.2018.26.02.60Keywords:
Clustering, PCA, Rubrics, ProgrammingAbstract
The evaluation of programming exercises is a complex process because, for each exercise that a teacher applies, there are common possibilities for solutions. As the teacher does not always know all the possible solutions of an exercise, it is always a challenge for him to justify all the criteria of his evaluation. In order to support the programming evaluation process, this work proposes a strategy based on clustering techniques and Principal Component Analysis (PCA) to recognize, from solutions developed by students, examples of solutions that represent, in a rubric scheme, the scores assigned by a teacher. The results of the experiments in real programming exercises solutions indicate that our method recognizes representations of rubrics demanding little teacher evaluation effort.
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Copyright (c) 2018 Márcia Gonçalves de Oliveira, Leonardo Leal Reblin, Mateus Batista de Souza, Elias Silva Oliveira
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
