Automated assessment of learner text complexity
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10441575" target="_blank" >RIV/00216208:11320/21:10441575 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=hyKw8Rj.Wk" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=hyKw8Rj.Wk</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.asw.2021.100529" target="_blank" >10.1016/j.asw.2021.100529</a>
Alternative languages
Result language
angličtina
Original language name
Automated assessment of learner text complexity
Original language description
EFL methodology has always recognized the importance of giving student learners of foreign languages regular and quick feedback on student production, both written and oral. The presented paper describes the decisions taken during the development of an application to measure text complexity, and shows how the results achieved with this application were translated into feedback related to the author's language proficiency. Along with some standard text complexity features, this tool takes into account those that are significant for Russian learners of English. The application provides students with the statistics of the relevant linguistic features of the text in comparison with texts of the learner essays that were considered the top and the bottom levels in the learner corpus. The paper also points out what text features are especially relevant for the assessment of the essays written in English by Russian students. The choice was made possible after the analysis of 3440 texts from Russian Error-Annotated English Learner Corpus, and after applying methods of machine learning and statistical analysis to predict the grade that could be received for the essay.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Assessing Writing
ISSN
1075-2935
e-ISSN
1873-5916
Volume of the periodical
49
Issue of the periodical within the volume
červenec 2021
Country of publishing house
GB - UNITED KINGDOM
Number of pages
16
Pages from-to
100529
UT code for WoS article
000671850600002
EID of the result in the Scopus database
2-s2.0-85105042026