References (38)
References
Biber, D. (1993). Representativeness in corpus design. Literary and Linguistic Computing, 8(4), 243–257. Google Scholar logo with link to Google Scholar
Centre for English Corpus Linguistics. (n.d.). Learner corpora around the world. UCLouvain. [URL]
CLARIN ERIC. (n.d.). L2 learner corpora. [URL]
Crossley, S. A., Tian, Y., Baffour, P., Franklin, A., Kim, Y., Morris, W., Benner, B., Picou, A., & Boser, U. (2023). The English language learner insight, proficiency and skills evaluation (ELLIPSE) corpus. International Journal of Learner Corpus Research, 9(2), 248–269. Google Scholar logo with link to Google Scholar
de Marneffe, M. C., Manning, C. D., Nivre, J., & Zeman, D. (2021). Universal dependencies. Computational Linguistics, 47(2), 255–308. Google Scholar logo with link to Google Scholar
Dickinson, M., Israel, R., & Lee, S. H. (2010). Building a Korean web corpus for analyzing learner language. In Proceedings of the Sixth Web as Corpus Workshop (NAACL HLT 2010) (pp. 8–16). Association for Computational Linguistics.Google Scholar logo with link to Google Scholar
Duolingo. (2025). 2025 Duolingo language report. [URL] (accessed on 11-March-2026).
Eckes, T., & Grotjahn, R. (2006). A closer look at the construct validity of C-tests. Language Testing, 23(3), 290–325. Google Scholar logo with link to Google Scholar
Egbert, J., Biber, D., & Gray, B. (2022). Designing and evaluating language corpora: A practical framework for corpus representativeness. Cambridge University Press. Google Scholar logo with link to Google Scholar
Fouser, R. J. (2001). Sociolinguistic transfer from Japanese into Korean as an L≥ 3. Cross-Linguistic Influence in Third Language Acquisition: Psycholinguistic Perspectives, 311, 149.Google Scholar logo with link to Google Scholar
Gilquin, G., & Granger, S. (2015). Learner language. In D. Biber & R. Reppen (Eds.), The cambridge handbook of English corpus linguistics (pp. 418–435). Cambridge University Press. Google Scholar logo with link to Google Scholar
Granger, S. (2008). The contribution of learner corpora to second language acquisition and foreign language teaching: A critical evaluation. In A. Frank, B. Kettemann, & H. Mehlmauer-Larcher (Eds.), Corpora and language teaching (pp. 13–32). John Benjamins.Google Scholar logo with link to Google Scholar
Hirvela, A. (2017). Argumentation & second language writing: Are we missing the boat?. Journal of Second Language Writing, 361, 69–74. Google Scholar logo with link to Google Scholar
Jarvis, S., & Paquot, M. (2015). Native language identification. In S. Granger, G. Gilquin, & F. Meunier (Eds.), The cambridge handbook of learner corpus research (pp. 605–627). Cambridge University Press. Google Scholar logo with link to Google Scholar
Jarvis, S., & Pavlenko, A. (2008). Crosslinguistic influence in language and cognition. Routledge. Google Scholar logo with link to Google Scholar
Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Choudhury, M. (2020). The state and fate of linguistic diversity and inclusion in the NLP world. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 6282–6293). Association for Computational Linguistics. Google Scholar logo with link to Google Scholar
Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163. Google Scholar logo with link to Google Scholar
Kyle, K., & Eguchi, M. (2024). Evaluating NLP models with written and spoken L2 samples. Research Methods in Applied Linguistics, 3(2), 100120. Google Scholar logo with link to Google Scholar
Lee, S. H., Jang, S. B., & Seo, S. K. (2009). Annotation of Korean learner corpora for particle error detection. Calico Journal, 26(3), 529–544. Google Scholar logo with link to Google Scholar
Lee, S. H., Dickinson, M., & Israel, R. (2012). Developing learner corpus annotation for Korean particle errors. In Proceedings of the Sixth Linguistic Annotation Workshop (pp. 129–133). Association for Computational Linguistics.Google Scholar logo with link to Google Scholar
Lee-Ellis, S. (2009). The development and validation of a Korean C-Test using Rasch Analysis. Language Testing, 26(2), 245–274. Google Scholar logo with link to Google Scholar
Lim, K., Song, J., & Park, J. (2023). Neural automated writing evaluation for Korean L2 writing. Natural Language Engineering, 29(5), 1341–1363. Google Scholar logo with link to Google Scholar
Manning, C. D. (2015). Computational linguistics and deep learning. Computational Linguistics, 41(4), 701–707. Google Scholar logo with link to Google Scholar
Masciolini, A., Berdičevskis, A., Szawerna, M. I., & Volodina, E. (2025a). Annotating second language in Universal Dependencies: A review of current practices and directions for harmonized guidelines. In Proceedings of the Eighth Workshop on Universal Dependencies (UDW, SyntaxFest 2025) (pp. 153–163). Association for Computational Linguistics.Google Scholar logo with link to Google Scholar
Masciolini, A., Caines, A., De Clercq, O., Kruijsbergen, J., Kurfalı, M., Muñoz Sánchez, R., Volodina, E., Östling, R., Allkivi, K., Arhar Holdt, S., Auzina, I., Darģis, R., Drakonaki, E., Frey, J. C., Glišić, I., Kikilintza, P., Nicolas, L., Romanyshyn, M., Rosen, A., ... & Zesch, T. (2025b). Towards better language representation in Natural Language Processing: A multilingual dataset for text-level Grammatical Error Correction. International Journal of Learner Corpus Research, 11(2), 309–335. Google Scholar logo with link to Google Scholar
Meurers, D. (2015). Learner corpora and natural language processing. In S. Granger, G. Gilquin, & F. Meunier (Eds.), The cambridge handbook of learner corpus research (pp. 537–566). Cambridge University Press. Google Scholar logo with link to Google Scholar
National Institute of Korean Language. (n.d.). Korean Learners’ Corpus Search. [URL]
Norris, J. M., & Ortega, L. (2009). Towards an organic approach to investigating CAF in instructed SLA: The case of complexity. Applied Linguistics, 30(4), 555–578. Google Scholar logo with link to Google Scholar
Park, J., & Lee, J. H. (2016). A Korean learner corpus and its features. En-e-hak [Linguistics], (75), 69–85.Google Scholar logo with link to Google Scholar
Song, S., Yuk, J., Choi, C., Yoo, H., Lim, H., Lim, K., & Park, J. (2025). Unified automated essay scoring and grammatical error correction. In Findings of the Association for Computational Linguistics: NAACL 2025 (pp. 4412–4426). Association for Computational Linguistics. Google Scholar logo with link to Google Scholar
Song, J., Lim, K., & Park, J. (2026). Enriching the Korean learner corpus for grammatical error correction and writing assessment. Language Resources and Evaluation, 60(1), 15. Google Scholar logo with link to Google Scholar
Sung, H., & Shin, G-H. (2023). Towards L2-friendly pipelines for learner corpora: A case of written production by L2-Korean learners. In Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023) (pp. 72–82). Association for Computational Linguistics. Google Scholar logo with link to Google Scholar
(2024). Constructing a dependency treebank for second language learners of Korean. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 3747–3758). ELRA and ICCL. Google Scholar logo with link to Google Scholar
(2025a). Second language Korean Universal Dependency treebank v1. 2: Focus on data augmentation and annotation scheme refinement. In Proceedings of the Third Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2025) (pp. 13–19). University of Tartu Library, Estonia.Google Scholar logo with link to Google Scholar
(2025b). Towards robust morphosyntactic analysis of L2 Korean: Evaluating and fine-tuning a Korean language model. ACM Transactions on Asian and Low-Resource Language Information Processing, 24(11), 1–21. Google Scholar logo with link to Google Scholar
(2026). Parser agreement and disagreement in L2 Korean UD: Implications for human-in-the-loop annotation. In Proceedings of the 20th Linguistic Annotation Workshop (LAW XX) (pp. 12–21). Association for Computational Linguistics. Google Scholar logo with link to Google Scholar
Sung, H., Shin, G-H., Lee, C., Sung, Y. K., & Jung, B. K. (2025). UD-KSL treebank v1. 3: A semi-automated framework for aligning XPOS-extracted units with UPOS tags. In Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025) (pp. 115–125). Association for Computational Linguistics. Google Scholar logo with link to Google Scholar
Yoon, H. J., & Polio, C. (2017). The linguistic development of students of English as a second language in two written genres. TESOL Quarterly, 51(2), 275–301. Google Scholar logo with link to Google Scholar
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