Corpora, Cognitive Styles, English Content-Specific Vocabulary and Academic Language at University Level

Corpora, Cognitive Styles, English Content-Specific Vocabulary and Academic Language at University Level

Giovanna Carloni (University of Urbino, Italy)
DOI: 10.4018/978-1-4666-8519-2.ch009
OnDemand PDF Download:
List Price: $37.50


This chapter shows how learner-centered corpus-designed activities can be effectively implemented while catering to learners' cognitive styles. Examples of corpus-designed activities implemented through a foreign language in higher education are provided and the role of cognitive styles in task performance is analyzed. The use of keyword lists and lexical bundles to design corpus-designed activities is investigated. As a result, foreign language acquisition and the personalization process are discussed within an applied corpus linguistics framework.
Chapter Preview


The use of corpora in language learning has been thoroughly investigated over the last few decades (Wichmann, Fligelstone, McEnery, & Knowles, 1997; Leech, 1997; Aston, 2001; Hunston, 2002; Aston, Bernardini, & Stewart, 2004; Sinclair, 2004; McEnery, Xiao, & Tono, 2006). In particular, the interface between corpora and foreign language pedagogy has been analyzed in relation to different learning contexts (Granath, 2009; Römer, 2009; Hunston, 2009; Meunier & Gouverner, 2009; Mukherjee, 2009). A thorough analysis of English in terms of discourse, pragmatics, relational language, back channels, and vocabulary within an applied corpus linguistics framework has been conducted by O’Keeffe, McCarthy, and Carter (2007). Corpus-based approaches focusing on English language teaching in various learning environments have been both operationalized and examined in recent years (Römer, 2012; Ädel, 2012; Cheng, 2012; Crawford Camiciottoli, 2012). A comprehensive analysis of the application of corpora in foreign language education practice and research has been carried out by Flowerdew (2012).

In language education, both indirect and direct applications of corpora can be implemented. Indirect applications of corpora, such as the use of corpus data by materials writers and researchers to devise teaching materials and syllabi (Römer, 2010 as cited in Flowerdew, 2012), have been used more and more extensively in the last decades. To this regard, it is worth mentioning that in corpus-informed materials, corpus data are employed on the grounds of second language acquisition theories (McCarthy, 2004). Corpus-informed materials—such as English as a Foreign Language (EFL), English for Specific Purposes (ESP), and English for Academic Purposes (EAP) textbooks—have increasingly been made available to instructors and students lately. The role of corpus-informed materials in EAP has been especially researched:

… studies by Ellis et al. (2008) and Simpson-Vlach and Ellis (2010), besides frequency information, also take into account pedagogic relevance as seen through teachers’ eyes, and psycholinguistic salience, to arrive at a pedagogic list of formulaic sequences for teaching academic speech and writing. This triangulated study […] echo[es] the sentiments expressed by Cook and Widdowson that pedagogic relevance may not be circumscribed solely by frequency found in a corpus (Flowerdew, 2012, p. 192).

On the other hand, the direct application of corpora, which entails teachers and/or students engaging directly with corpora and/or corpus data (Römer, 2010 as cited in Flowerdew, 2012), has not been extensively implemented thus far.

Key Terms in this Chapter

Indirect Use of Corpora: Data retrieved from corpora are used by researchers or materials writers to devise materials and syllabi.

Direct Use of Corpora: (a) Instructors and/or students use the data retrieved from corpora to devise and/or carry out activities. (b) Instructors and/or students search corpora directly.

Semantic Prosody: The tendency of words to collocate with lexical items featuring either positive or negative connotations.

Keywords: Words which appear more frequently in a corpus when compared with a general reference corpus.

Data-Driven Learning: A kind of activity implemented by means of (preselected) concordance outputs and requiring learners to infer the rules underpinning the language patterns detected.

N-Grams: A series of contiguous language items which repeatedly co-occur. They are likely to be genre-specific.

Cognitive Styles: The way learners perceive, process, and organize input.

Complete Chapter List

Search this Book: