An attempt at a comprehensive error analysis using learner corpus and natural language processing techniques

2021 Fiscal Year Final Research Report

• Project/Area Number: 20K21977
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 0102:Literature, linguistics, and related fields
• Research Institution: Matsuyama University
• Principal Investigator: NISHIMURA Yoshito 松山大学, 経済学部, 講師 (00882432)
• Project Period (FY): 2020-09-11 – 2022-03-31
• Keywords: 誤用分析 / 誤用検出 / 学習者コーパス / ライティング / Communicative Adequacy

Outline of Final Research Achievements

The objective of the current study was to address a comprehensive error analysis by employing natural language processing techniques (ERRANT) and a learner corpus (ETS Corpus of Non-Native Written English) to detect and classify an L2 learner’s all possible syntactic and lexical errors and by coding communicative adequacy to each sentence, and thereby find out which errors L2 learners are more likely to make, what error categories they make, and whether the higher the proficiency level the higher the communicative adequacy.

Free Research Field

応用言語学

Academic Significance and Societal Importance of the Research Achievements

熟達度が高い英語学習者が犯しやすい誤用項目と熟達度が低い英語学習者が犯しやすい誤用項目を特定したり、熟達度に関わらずどのような項目において英語学習者が誤用を犯しやすいのかを特定したり、また、どのような誤用が意思伝達を阻害したり、しなかったりするのかを特定することで、効果的な学習の指導や教材開発へ貢献することが可能となる。