Computing the Missing Lexicon in Students Using Bayesian Networks

Salcedo L P.; Pinninghoff J M.A.; Contreras A R.

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