Assessing Language Proficiency from Eye Movements in Reading
We 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...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Association for Computational Linguistics
2021
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| Online Access: | https://hdl.handle.net/1721.1/130436 |
| _version_ | 1826202495867682816 |
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| author | Berzak, Yevgeni Katz, Boris Levy, Roger P |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Berzak, Yevgeni Katz, Boris Levy, Roger P |
| author_sort | Berzak, Yevgeni |
| collection | MIT |
| description | We 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. |
| first_indexed | 2024-09-23T12:08:24Z |
| format | Article |
| id | mit-1721.1/130436 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T12:08:24Z |
| publishDate | 2021 |
| publisher | Association for Computational Linguistics |
| record_format | dspace |
| spelling | mit-1721.1/1304362022-10-01T08:27:20Z Assessing Language Proficiency from Eye Movements in Reading Berzak, Yevgeni Katz, Boris Levy, Roger P Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences We 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. 2021-04-09T20:38:38Z 2021-04-09T20:38:38Z 2018-06 2021-04-06T18:05:23Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/130436 Berzak, 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 http://dx.doi.org/10.18653/v1/n18-1180 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Association for Computational Linguistics Association for Computational Linguistics |
| spellingShingle | Berzak, Yevgeni Katz, Boris Levy, Roger P Assessing Language Proficiency from Eye Movements in Reading |
| title | Assessing Language Proficiency from Eye Movements in Reading |
| title_full | Assessing Language Proficiency from Eye Movements in Reading |
| title_fullStr | Assessing Language Proficiency from Eye Movements in Reading |
| title_full_unstemmed | Assessing Language Proficiency from Eye Movements in Reading |
| title_short | Assessing Language Proficiency from Eye Movements in Reading |
| title_sort | assessing language proficiency from eye movements in reading |
| url | https://hdl.handle.net/1721.1/130436 |
| work_keys_str_mv | AT berzakyevgeni assessinglanguageproficiencyfromeyemovementsinreading AT katzboris assessinglanguageproficiencyfromeyemovementsinreading AT levyrogerp assessinglanguageproficiencyfromeyemovementsinreading |