An Automated Approach to Selecting Sentences for Test Case Generation

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Resumo

The modern field of education is characterized by the increasing use of multiple choice tests to assess students’ knowledge and skills. One of the common methods of selecting sentences for such tests is the application of textual data clustering procedures. In this study, a module for sentence selection was developed that includes three steps: preprocessing, sentence parameter computation, and clustering. However, an objective evaluation of the quality of the obtained clusters using the silhouette coefficient and Davis-Boldin index showed that the clustering model used did not give satisfactory results.

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Sobre autores

Maria Maslova

Volzhsky Polytechnic Institute (branch) of Volgograd State Technical University

Autor responsável pela correspondência
Email: miss.mari.m@inbox.ru
ORCID ID: 0000-0003-3845-3972
Código SPIN: 2933-6263

senior teacher, Department of Computer Science and Programming Technology

Rússia, Volzhsky

Bibliografia

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2. Fig. 1. Custering of sentences by five parameters

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3. Fig. 2. Clustering of sentences by two parameters

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