Chapter 3. Corpus-driven methods for assessing accuracy in learner production

Adopting the perspective of Ellis’s (2007) Associative-Cognitive CREED, this chapter proposes a measure of accuracy in learner production that is based on conditional probabilities. More specifically, we develop a definition of accuracy that involves ‘the proficient selection of constructions in their preferred constructional context in a particular target genre’. Comparing this approach to previous work on linguistic units larger than the word, we discuss how this definition (i) does away with a strict separation of lexis and grammar, shifting the focus to interactions between constructions; (ii) embraces various aspects of accuracy (phonology, morphology, lexis, etc.) instead of being restricted to target-like vocabulary choice alone; and (iii) reflects our understanding of native-like proficiency as a gradual, probabilistic phenomenon that transcends a native-nonnative speaker divide. We then exemplify this measure in two small case studies using lexico-grammatical association patterns from L1 and L2 corpora and discuss implications of the theoretical perspective and the empirical measure for task design.