LEARNER CORPORA AND SECOND LANGUAGE ACQUISITION RESEARCH

Abstract

This study explores the role of learner corpora in second language acquisition (SLA) research, highlighting their methodological significance, applications, and contributions to understanding language learning processes. Learner corpora, consisting of systematically compiled texts produced by second language learners, provide extensive empirical data that reveal recurring linguistic patterns, developmental trends, and interlanguage phenomena. The analysis of written and spoken corpora enables researchers to identify common errors, track proficiency-related progress, and examine cross-linguistic influences. Furthermore, corpus-based methodologies, including automated annotation, error tagging, and concordance analysis, allow for both quantitative and qualitative investigation of learner language. The findings underscore the pedagogical relevance of learner corpora in designing teaching materials, curriculum planning, and promoting data-driven learning approaches. Despite challenges such as corpus representativeness and the need for careful qualitative interpretation, learner corpora offer a robust foundation for bridging theoretical insights and practical applications in SLA research.