Abstract
The available lexicon for a person usually increases according to their needs through their live evolution. It is especially important during the early stages in students formation; in every class one of the objectives is to get students capable of using an extensive vocabulary according to different topics in which they are involved. We use an online platform, Lexmath, which contains data (latent lexicon) of a significant number of students in a specific geographic region in Chile. This work introduces a software application which uses data from Lexmath to determine the missing lexicon in students, by using Bayesian networks. The goal of this development is to make available to teachers the lexical weaknesses of students, to generate recommendations to improve the available lexicon.
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Salcedo L., P., Pinninghoff J., M.A., Contreras A., R. (2019). Computing the Missing Lexicon in Students Using Bayesian Networks. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science(), vol 11487. Springer, Cham. https://doi.org/10.1007/978-3-030-19651-6_11
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DOI: https://doi.org/10.1007/978-3-030-19651-6_11
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