Corpora in language teaching and learning

Abstract

This timeline looks at explicit uses of corpora in foreign or second language (L2) teaching and learning, i.e. what happens when end-users explore corpus data, whether directly via concordancers or integrated into CALL programs, or indirectly with prepared printed materials. The underlying rationale is that such contact provides the massive contextualised exposure needed for language learning, but in a more controlled way than purely haphazard exposure via regular reading or listening, thus promoting or enhancing noticing, language awareness, autonomy, and ultimately producing ‘better learners’. It interweaves with many other notions in language teaching, from authenticity and autonomy to induction and constructivism, taking in much of what we know about language from corpus linguistics itself – its fuzzy, probabilistic nature and the importance of lexical patterns, collocations, chunks, frequencies and distributions. Commonly known as data-driven learning or DDL (Johns 1990), the approach goes back several decades; yet despite its impressive pedigree, a frequent lament is that it remains a marginal practice. Teachers may not be aware of DDL if it is absent from their initial training, or may see it as a research activity confined to higher education. While corpus consultation may appear too demanding for school-age learners, there are connections with the web searches that are already a frequent practice for many. Though lack of uptake is sometimes attributed at least in part to a dearth of empirical research, this claim is increasingly difficult to defend, as witnessed by the number of entries in this timeline and the hundreds of others not included. For a balanced discussion of the limits of DDL as well as what it can reasonably achieve, see Kaltenböck & Mehlmauer-Larcher (2005).

Corpus Use in Language Learning: A Meta‐Analysis

“…Other differences include more rigorous extraction of effect sizes (including values derived from t and F tests and missing data solicited directly from the authors) as well as the formulae used and their interpretation (unbiased d , winsorizing), inclusion of a separate effect size for every unique sample in each study, and a detailed coding manual with calculation of subeffect sizes allowing a post hoc moderator analysis in an attempt to identify what may be responsible for variation between studies (entirely absent in the previous article). Although there have been various other attempts at synthesis of DDL (e.g., Boulton, in press; Chambers, ), to our knowledge the only other meta‐analysis to date is by Mizumoto and Chujo (). Their survey of 14 studies arrived at an overall effect size of d = 0.97 and identified lexicogrammar as the most promising area for DDL work ( d = 2.93).…”

Toward a pattern-based referencing tool: Learner interactions and perceptions

“…Engaging learners in DDL facilitates language learning (Boulton, 2017;Boulton & Cobb, 2017), especially vocabulary learning. Research findings have indicated at least three major benefits of DDL for vocabulary learning: (1) observing concordance outputs raises learners' lexical and contextual awareness (Frankenberg-Garcia, 2012;Tribble, 2002); (2) the process of corpus observation, hypothesis-making, and testing encourages autonomous learning and improves critical thinking skills (Kirk, 2002;O'Sullivan, 2007;Yoon, 2008); and (3) observing concordances helps L2 learners see the relationships and new connections between forms and meanings, which leads to knowledge reconstruction (Sinclair, 2004).…”

Conceptual Model of Politics in American English

“…(11) My reading of the township experiments suggests that while their demise was consistent with the tide of southern politics, it was not as inevitable as it might seem today (58). [13]: politics of the twentieth century (279); range of years [19]: politics of the 1960s (348); present [21]: current politics (251); past [10]: the past 44 years of politics (657); future [8]: politics in years to come (148); history period [18]: Cold War politics (489, 503); post-war politics (361).…”