The computer learner corpus: a versatile new source of data for SLA research

Abstract

The computer corpus has infiltrated all fields of language-related research, from lexicography to literary criticism through artificial intelligence and language teaching. The computer plays a central role in corpus linguistics. A first major advantage of computerization is that it liberates language analysts 'from drudgery and empowers them to focus their creative energies on doing what machines cannot do'. The main goal of Second Language Acquisition (SLA) research is to uncover the principles that govern the process of learning a foreign/second language. Current SLA research is mainly based on introspective data and language use data of the elicited type. One issue of importance in current computer learner corpora (CLC) methodology is how to approach learner corpora. Using the traditional hypothesis-based approach, the analyst starts from a hypothesis based on the literature on SLA research and uses the learner corpus to test his hypothesis.