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In:Learner Corpora and Language Teaching
Edited by Sandra Götz and Joybrato Mukherjee
[Studies in Corpus Linguistics 92] 2019
► pp. 2948

References (20)
References
Bakota, Tibor, Beszédes, Árpád, Gergely, Tamás, Gyalai, Milán Imre, Gyimóthy, Tibor & Füleki, Dániel. 2009. Semi-automatic test case generation from business process models. In Proceedings of the 11th Symposium on Programming Languages and Software Tools and 7th Nordic Workshop on Model Driven Software Engineering, 5–18. Tampere, Finland: Tampere University of Technology. <[URL]> (15 February 2018).
Bayerl, Petra S. 2007. Identifying sources of disagreement: Generalizability theory in manual annotation studies. Computational Linguistics 33(1): 3–8. Google Scholar logo with link to Google Scholar
Fort, Karën, Adda, Gilles & Cohen, K. Bretonnel. 2011. Amazon mechanical turk: Gold mine or coal mine? Computational Linguistics 37(2): 413–420. Google Scholar logo with link to Google Scholar
Gerasimenko, Ekaterina. 2018. Automated Error Detection in English Examination Essays Written by Russian Students. BA dissertation, School of Linguistics, Research University Higher School of Economics, Moscow.Google Scholar logo with link to Google Scholar
Glaznieks, Aivars, Nicolas, Lionel, Stemle, Egon, Abel, Andrea & Lyding, Verena. 2014. Establishing a standardised procedure for building learner corpora. Journal of Applied Language Studies 8(3): 5–20.Google Scholar logo with link to Google Scholar
Granger, Sylviane. 2003. The International Corpus of Learner English: A new resource for foreign language learning and teaching and second language acquisition research. TESOL Quarterly 37(3): 538–546. Google Scholar logo with link to Google Scholar
. 2004. Computer learner corpus research: Current status and future prospects. In Applied Corpus Linguistics: A Multidimensional Perspective, Ulla Connor & Thomas A. Upton (eds), 123–145. Amsterdam: Rodopi. Google Scholar logo with link to Google Scholar
Gierl, Mark J. & Haladyna, Thomas M.. 2012. Automatic Item Generation: Theory and Practice. New York NY: Routledge. Google Scholar logo with link to Google Scholar
Heilman, Michael. 2011. Automatic Factual Question Generation from Text. PhD dissertation, Carnegie Mellon University. CMU-LTI-11-004. <[URL]> (25 February 2018).
Hoshino, Ayako & Nakagawa, Hiroshi. 2007. Assisting cloze test making with a web application. In Proceedings of SITE 2007--Society for Information Technology & Teacher Education International Conference, Roger Carlsen, Karen McFerrin, Jerry Price, Roberta Weber & Dee Anna Willis (eds), 2807–2814. Chesapeake VA: AACE. <[URL]> (25 February 2018).
Hovy, Eduard & Lavid, Julia. 2010. Towards a ‘Science’ of corpus annotation: A new methodological challenge for corpus linguistics. International Journal of Translation 22(1): 13–36.Google Scholar logo with link to Google Scholar
Huddleston, Rodney & Pullum, Geoffrey K. 2002. The Cambridge Grammar of the English Language. Cambridge: CUP. Google Scholar logo with link to Google Scholar
Leech, Geoffrey. 2015. Adding linguistic annotation. In Developing Linguistic Corpora: A Guide to Good Practice. Oxford: Oxbow Books.Google Scholar logo with link to Google Scholar
Lyashevskaja, Olga & Plungian, Vladimir. 2003. Morphological annotation in Russian National Corpus: A theoretical feedback. In 5th International Conference on Formal Description of Slavic Languages (FDSL-5). Frankfurt: Peter Lang.Google Scholar logo with link to Google Scholar
Plugian, Vladimir. 2005. Zachem nuzhen Natsional’ny korpus russkogo yazyka? Neformal’noye vvedeniye (Why do we need Russian National Corpus? Informal introduction). In Russian National Corpus: 2003–2005, 6–20. Moscow: Indrik. <[URL]> (25 February 2018).
Proshina, Zoya G. & Eddy, Anna A. 2017. Russian English: History, Functions, and Features. Cambridge: CUP.Google Scholar logo with link to Google Scholar
Saraceni, Mario. 2015. World Englishes: A Critical Analysis. London: Bloomsbury.Google Scholar logo with link to Google Scholar
Vinogradova, Olga. 2016. The role and applications of expert error annotation in a corpus of English learner texts. In Computational Linguistics and Intellectual Technologies (Proceedings of International Conference “Dialogue 2016”) issue 15(22), 740–751.Google Scholar logo with link to Google Scholar
Vinogradova, Olga, Lyashevskaya, Olga & Panteleeva, Irina. 2017. Multi-level student essay feedback in a learner corpus. In Computational Linguistics and Intellectual Technologies (Papers from the Annual conference “Dialogue”) Issue 16(23), Vol. 1, 382–396. Moscow: RSUH.Google Scholar logo with link to Google Scholar
Vinogradova, Olga & Login, Nikita. 2017. The design of tests with multiple choice questions automatically generated from essays in a learner corpus. Higher School of Economics Research Paper No. WP BRP 60/LNG/2017, 13 December 2017. <[URL]> (25 February 2018).
Cited by (3)

Cited by three other publications

Granger, Sylviane
2024. From early to future learner corpus research. International Journal of Learner Corpus Research 10:2  pp. 247 ff. DOI logo
Perez-Guerra, Javier & Elizaveta Smirnova
2024. L1 Influence on the Use of the English Present Perfect: A Corpus Analysis of Russian and Spanish Learners’ Essays. Journal of Language and Education 10:1  pp. 101 ff. DOI logo
Login, Nikita
2023. Distractor Generation for Lexical Questions Using Learner Corpus Data. Journal of Linguistics/Jazykovedný casopis 74:1  pp. 345 ff. DOI logo

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