Enriching the Korean Learner Corpus with Multi-reference Annotations and Rubric-Based Scoring
This addresses a gap in resources for Korean language learners and educators, though it is incremental as it builds on an existing corpus.
The researchers tackled the lack of learner corpora for Korean L2 writing by enhancing the KoLLA corpus with multiple grammatical error correction references and rubric-based scores for grammatical accuracy, coherence, and lexical diversity, resulting in a standardized resource for Korean language education research.
Despite growing global interest in Korean language education, there remains a significant lack of learner corpora tailored to Korean L2 writing. To address this gap, we enhance the KoLLA Korean learner corpus by adding multiple grammatical error correction (GEC) references, thereby enabling more nuanced and flexible evaluation of GEC systems, and reflects the variability of human language. Additionally, we enrich the corpus with rubric-based scores aligned with guidelines from the Korean National Language Institute, capturing grammatical accuracy, coherence, and lexical diversity. These enhancements make KoLLA a robust and standardized resource for research in Korean L2 education, supporting advancements in language learning, assessment, and automated error correction.