Abstract
In Paraguay, despite the fact that Elementary Education is one of the cornerstones of the educational system, it has not always received the recognition it deserves. Recently, the Paraguayan government has started to focus its effort on evaluating the quality of its education system through the analysis of some factors of the teachers. In this work, which falls into the context of such project, we study the ability to understand the different evaluation types structures in mathematics. The data, collected from elementary mathematics teachers from all over the country, is analyzed by applying an education data mining (EDM) approach. Results show that not all questions are equally important and it is necessary to continue through different lines of action to get insight about the action policy to improve the educational system quality.
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Chaves, V.E.J. et al. (2020). Analysis of Teacher Training in Mathematics in Paraguay’s Elementary Education System Using Machine Learning Techniques. In: Martínez Álvarez, F., Troncoso Lora, A., Sáez Muñoz, J., Quintián, H., Corchado, E. (eds) International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019). CISIS ICEUTE 2019 2019. Advances in Intelligent Systems and Computing, vol 951. Springer, Cham. https://doi.org/10.1007/978-3-030-20005-3_29
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