CORPUS-BASED ERROR ANALYSIS IN ENGLISH
Keywords:
corpus linguistics; error analysis; learner corpus; interlanguage; data-driven learning; applied linguistics; second language acquisition; linguistic competenceAbstract
This explores the use of corpus-based methodologies in analyzing linguistic errors made by English language learners. Error analysis has long been central to applied linguistics, offering valuable insights into the interlanguage processes underlying second language acquisition. The emergence of corpus linguistics has transformed the field by providing empirical, data-driven tools to identify, classify, and interpret learner errors on a scale previously impossible through manual analysis. This study discusses how corpora—systematic digital collections of authentic learner texts—enable researchers to examine patterns of lexical, grammatical, and discourse-level deviations. It also examines the pedagogical implications of corpus-based error analysis (CBEA) for language teaching, assessment, and curriculum design. By integrating theoretical frameworks from interlanguage studies, contrastive analysis, and learner corpus research, this paper argues that corpus-based approaches offer a more objective and replicable foundation for understanding learner difficulties.
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