Creating Error Corpora for Learning Tamil Language for Plus Two Students of Madurai District

Abstract

               Language acquisition is a complex cognitive process wherein learner errors, rather than being mere obstacles, provide critical diagnostic insights into the linguistic challenges faced by students. This paper explores the crucial role of Error Analysis (EA) and the development of a specialized error corpus to systematically study these phenomena in students learning Tamil at the higher secondary level. By employing a data-driven approach known as Computer-aided Error Analysis (CEA), this research aims to transcend anecdotal observations, moving toward a quantitative and qualitative understanding of learner difficulties. The core of this study involves creating a comprehensive learner corpus from authentic data collected from Plus Two students in the Madurai district. This data, encompassing written essays, formal assessments, and observational notes, is electronically stored and meticulously annotated using a custom, three-dimensional error tagging system. This system allows for the precise classification of errors based on their linguistic domain, nature, and affected word category. Processed using Java, the corpus facilitates the efficient retrieval of error patterns, serving as a foundational resource for language teachers, curriculum developers, and applied linguists to design targeted pedagogical tools for Tamil language education.