Computing the missing lexicon in students using bayesian networks

• Autores: Pedro Salcedo, M.Angélica. Pinninghoff J., Ricardo Contreras Calvache
• Localización: From Bioinspired Systems and Biomedical Applications to Machine Learning: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Almería, Spain, June 3–7, 2019, Proceedings, Part II / coord. por Hojjat Adeli; José Manuel Ferrández Vicente (dir. congr.), José Ramón Álvarez Sánchez (dir. congr.), Félix de la Paz López (dir. congr.), Francisco Javier Toledo Moreo (dir. congr.), 2019, ISBN 978-3-030-19651-6, págs. 109-116
• Idioma: inglés
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• Resumen

  • The available lexicon for a person usually increases accordingto their needs through their live evolution.It is especially important during the early stages in students formation; in every class one ofthe 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.