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dc.contributor.authorBerzak, Yevgeni
dc.contributor.authorKatz, Boris
dc.contributor.authorLevy, Roger P
dc.date.accessioned2021-04-09T20:38:38Z
dc.date.available2021-04-09T20:38:38Z
dc.date.issued2018-06
dc.identifier.urihttps://hdl.handle.net/1721.1/130436
dc.description.abstractWe present a novel approach for determining learners' second language proficiency which utilizes behavioral traces of eye movements during reading. Our approach provides standalone eyetracking based English proficiency scores which reflect the extent to which the learner's gaze patterns in reading are similar to those of native English speakers. We show that our scores correlate strongly with standardized English proficiency tests. We also demonstrate that gaze information can be used to accurately predict the outcomes of such tests. Our approach yields the strongest performance when the test taker is presented with a suite of sentences for which we have eyetracking data from other readers. However, it remains effective even using eyetracking with sentences for which eye movement data have not been previously collected. By deriving proficiency as an automatic byproduct of eye movements during ordinary reading, our approach offers a potentially valuable new tool for second language proficiency assessment. More broadly, our results open the door to future methods for inferring reader characteristics from the behavioral traces of reading.en_US
dc.language.isoen
dc.publisherAssociation for Computational Linguisticsen_US
dc.relation.isversionofhttp://dx.doi.org/10.18653/v1/n18-1180en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computational Linguisticsen_US
dc.titleAssessing Language Proficiency from Eye Movements in Readingen_US
dc.typeArticleen_US
dc.identifier.citationBerzak, Yevgeni et al. "Assessing Language Proficiency from Eye Movements in Reading." © 2018 The Association for Computational Linguistics. 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, June 2018, New Orleans, Louisiana, Association for Computational Linguistics, 2018.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.relation.journal2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologiesen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2021-04-06T18:05:23Z
dspace.orderedauthorsBerzak, Y; Katz, B; Levy, Ren_US
dspace.date.submission2021-04-06T18:05:24Z
mit.journal.volume1en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Needed


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