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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

© 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.
Original languageAmerican English
Title of host publicationLanguage proficiency classification during computer-based test with EEG pattern recognition methods
Pages288-296
Number of pages9
ISBN (Electronic)9783319592251
DOIs
StatePublished - 1 Jan 2017
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 1 Jan 2017 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10267 LNCS
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period1/01/17 → …

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