Language proficiency classification during computer-based test with EEG pattern recognition methods

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Resumen

© Springer International Publishing AG 2017. The answering of any test represents a challenge for students; however, foreign students whose first language is not English have to deal with the difficulty of the understanding of a series of questions written on a different language in addition of the effort required to solve the problem. In this study, we recorded the behavior of the brain signals of 16 students, 10 whom first language was English and 6 who were English learners, and used two supervised classification algorithms in order to identify the students’ language proficiency. The results shown that in both approaches, harder problems which required longer time to be responded had a higher accuracy rate; however, more tests are needed in order to understand the physical processing of written math text problem and the difference among both groups.
Idioma originalInglés estadounidense
Título de la publicación alojadaLanguage proficiency classification during computer-based test with EEG pattern recognition methods
Páginas288-296
Número de páginas9
ISBN (versión digital)9783319592251
DOI
EstadoPublicada - 1 ene 2017
EventoLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duración: 1 ene 2017 → …

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen10267 LNCS
ISSN (versión impresa)0302-9743

Conferencia

ConferenciaLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Período1/01/17 → …

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