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

Federico Cirett-Galán*, Raquel Torres-Peralta, Carole R. Beal

*Autor correspondiente de este trabajo

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva


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
Título de la publicación alojadaPattern Recognition - 9th Mexican Conference, MCPR 2017, Proceedings
EditoresJesus Ariel Carrasco-Ochoa, Jose Francisco Martinez-Trinidad, Jose Arturo Olvera-Lopez
EditorialSpringer Verlag
Número de páginas9
ISBN (versión impresa)9783319592251
EstadoPublicada - 1 ene 2017
Evento9th Mexican Conference on Pattern Recognition, MCPR 2017 - Huatulco, México
Duración: 21 jun 201724 jun 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
ISSN (versión digital)1611-3349


Conferencia9th Mexican Conference on Pattern Recognition, MCPR 2017

Nota bibliográfica

Publisher Copyright:
© Springer International Publishing AG 2017.


Profundice en los temas de investigación de 'Language proficiency classification during computer-based test with EEG pattern recognition methods'. En conjunto forman una huella única.

Citar esto