Computing the Missing Lexicon in Students Using Bayesian Networks
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.
Más información
Título según WOS: | Computing the Missing Lexicon in Students Using Bayesian Networks |
Título según SCOPUS: | Computing the Missing Lexicon in Students Using Bayesian Networks |
Título de la Revista: | BIO-INSPIRED SYSTEMS AND APPLICATIONS: FROM ROBOTICS TO AMBIENT INTELLIGENCE, PT II |
Volumen: | 11487 |
Editorial: | SPRINGER INTERNATIONAL PUBLISHING AG |
Fecha de publicación: | 2019 |
Página de inicio: | 109 |
Página final: | 116 |
Idioma: | English |
DOI: |
10.1007/978-3-030-19651-6_11 |
Notas: | ISI, SCOPUS |