The Application of Natural Language Processing and Automated Scoring in Second Language Assessment

Heidi Han-Ting Liu

Abstract


Natural language processing (NLP) is an area of research that is used to investigate the application of natural language and is the foundation of machine translation, natural language text processing, natural language generation, multilingual and cross language information retrieval, speech recognition, parsing, and expert systems. To understand natural language in order to build or select appropriate algorithms for processing, three major issues are called into attention: humans' thought processes, the meaning of linguistic input in context, and world knowledge. These considerations have led to the development of various types of NLP tools for lexical and morphological analysis, semantic and discourse analysis, as well as knowledge-based approaches (c.f., Chowdhury, 2003). After decades of evolution and advancement, the current stage of NLP, as Xi (2010) pointed out, has allowed language testing researchers to apply its techniques in developing automated scoring systems for the purpose of language learning and assessment.

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