Learner Corpus Research in EAP: Past, Present and Future

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Learner Corpus Research in EAP: Past, Present and Future Lynne Flowerdew 1

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Learner Corpus Research in EAP: Past, Present and Future. Lynne Flowerdew. Outline of talk. Research in: English for General Academic Purposes (EGAP) English for Specific Academic Purposes (ESAP) Some core issues Current and future directions Focus on academic writing. - PowerPoint PPT Presentation

Transcript of Learner Corpus Research in EAP: Past, Present and Future

Page 1: Learner Corpus Research in EAP: Past, Present and Future

Learner Corpus Research in EAP: Past, Present and Future

Lynne Flowerdew

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Outline of talk• Research in:

– English for General Academic Purposes (EGAP)– English for Specific Academic Purposes (ESAP)

• Some core issues

• Current and future directions

Focus on academic writing2

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EGAP learner corpus research: key areas

• Epistemic modality/stance markers

• Tense and aspect

• Vocabulary, collocations and phraseology

(also connectors)

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ESAP Learner Corpus Research

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ESAP learner corpus research: key areas

•Lexical bundles

•Keywords to phraseology

•Metadiscoursal expressions

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Some core issues

• Starting point for analysis:–derived from existing framework or inductive corpus-based vs. corpus-driven (Tognini Bonelli)

–bottom-up vs. top-down

•Choice of reference/control corpus

•Explanation for data (taking into account variables) 6

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EGAP Learner Corpus Research

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Epistemic modality/stance markersArgumentative essays, e.g. ICLE sub-corpora

•governed by epistemic modality

•overlaps with Hyland’s (1999) stance markershedges, boosters, self-mentions, attitude markers

•difficult for students to master complex interplay between hedges and boosters 8

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1. Learner Corpus Research (L1 & L2)

Doubt and certainty (Hyland & Milton 1997)

• 2 corpora, 500,000 words each Learner Native-speaker 150 essays by A level scripts HK students for British school leavers A Level UofEng of similar age + education

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1.Learner Corpus Research • Procedure

– Inventory of 75 of most frequently occurring epistemic lexical devices from:

• Holmes’ (1983) analysis of ‘learned’ sections of Brown & LOB

• Research literature on modality (Coates 1983)• Reference grammars (Quirk et al. 1972)

– 50 sentences of each item(cut-off point, cf. Altenberg)

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1. Learner Corpus Research

• Key findings – Chinese learners: limited range of devices,

inappropriate strong convictionse.g. As I know, I am quite sure some parents are willing to pay… vs. native-speaker:e.g. On balance, it would seem that the only real

solution to the problem would be to….

• Explanation– due to lack of awareness of socio-pragmatic norms– Teaching induced effect – tutorial schools

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2. Learner Corpus Research (L1 & L2)Impact of culture on use of stance exponents in GRICLE (Hatzitheodorou & Mattheoudakis 2011)

•2 sub-corpora of around 200,000 words eachLearner Native-speaker Greek component LOCNESS (not all

timed) of ICLE (timed) + PELCRA (timed) (cf. Ädel 2008)

•Procedure–Focus on adverbials (hedges, boosters, attitude markers) –Hyland’s (2005) categories of metadiscourse as

reference point–own list (e.g. happily) 12

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2. Learner Corpus Research (L1 & L2)• Results

– Motivation for research: initial reading (Greek learners preference for wide range of boosters)

– Preliminary observations borne out by results: Greek learners more emphatic + extensive use of boosters

• Explanation (with reference to cultural factors)– Consulted 1.7 million word Hellenic National Corpus– Culturally induced from the Greek, authoritative style

of writing

NB unlike Hyland & Milton’s (1997) study and GRICLE (2011) study, McEnery & Kifle (2002) found overuse of hedging in argumentative writing of Eritrean students 13

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3. Learner Corpus Research (L2 vs. L2)Use of modal and reporting verbs in expression of stance (Neff et al. 2003)

• Corpora– 5 learner sub- corpora from ICLE (French, Spanish,

Italian, Dutch, German)290,000 words in French …. 195,000 in Spanish

– LOCNESS (150,000 words) as native reference corpus

•Focus on: modal verbs (can, could, may, might, must)

9 reporting verbs (suggest, argue etc.; among 12 most frequently used in preliminary analysis)

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3. Learner Corpus Research (L2 vs. L2)• Results & explanations

– can overused by all groups of non-native writers (massive overuse in Italian and Spanish sub-corpora)

• L1 transfer involving meaning, typology and sociolinguistic norms– Typology

Se puede apreciar un contraste entre...It can be appreciated a contrast between…

– Positive politeness strategiesThe problems that we can find…

• Developmental factors may play a role (cf. Aijmer 2002; Gilquin & Paquot 2008)

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4. ESAP Learner Corpus StudyStance options in data-description task in

statistics (Wharton 2012)

• Corpus: 40 student texts (4705 words)

• Procedures– Inductive using Nvivo

(small set of data in under-researched genre)– Examination and reexamination of texts

• Common Content Assertions (5 propositions)• Common Stances in Assertions (bare, hedged,

vague, boosted, reader-inclusive)16

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ESAP Learner Corpus Research

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ESAP learner corpus research: key areas

•Lexical bundles

•Keywords to phraseology

•Metadiscoursal expressions

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1. Learner Corpus Research: keywords …. phraseology

Function keywords in academic writing (Lee & Chen 2009)

•2 apprentice corpora–Chinese undergraduate dissertations (Eng. Lang.)–Comparable L1 student corpus from BAWE–Both compared with expert corpus of journal articles from same field

•Key finding (article usage) e.g. the students in this study… students will be more motivated if….

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2. ESAP Corpus Research: keywords …. phraseology

Content keywords in Problem-Solution text (Flowerdew 2008)

•2 corpora of around 225,000 words each– Learner corpus of recommendation-based reports– Expert corpus of professional reports

(analogue rather than exemplar corpus;Tribble 2002)

•Key finding– Overuse of superordinate terms in topic sentences

e.g. find a solution to the problem…Over-reliance on rubrics from assignment (‘lexical teddy

bears’, Hasselgren 1994) 20

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Cf. Paquot’s (2010) six interlanguage features

• Limited lexical repertoire • Lack of register awareness• Unidiomatic phraseology• Semantic misuse (problem vs. issue or question)• Overuse of connective devices• Strings of connectives in subject-initial position

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ESAP Learner Research: metadiscourse

Hyland’s (2005) model of metadiscourse

•Interactive: guide reader through text using transitions etc.

•Interactional: involves reader in text using hedges, boosters, attitude markers

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1. ESAP Corpus Research: Interactional

Anticipatory “it” in student and published writing (Hewings & Hewings 2002)

•2 corpora of business writing

– Student corpus: 15 MBA dissertations by NNS (123,633 words)

– Comparable corpus: 28 papers from three different business studies journals (203,389 words ) 23

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1. ESAP Corpus Research: Interactional• Procedures

– Excluded “it” when propositional content, or text-organising role

– four categories derived from data• Hedges, attitude markers, emphatics, attribution

– Results normalised per 1,000 words

• Results & explanations– Learners made less use of “it” clauses in hedging– Greater use of “it” in other 3 categories

– Speculate: more overt effort at persuasion on account of readership 24

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2. ESAP Corpus Research: InteractiveUse of we in a learner corpus of reports (Luzon 2009)

•2 corpora– Learner corpus of reports written by Spanish

engineering students– Corpus for comparison (analogue): engineering RAs

•Key finding– Lack of awareness of conventions for we

e.g. With this paper we want to give you some recommendations

We are going to consider the advantages and …25

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Current and future directions

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Very recent initiatives in Learner Corpora

• Aggregate vs. individual data (cf. Hong article on software in Tono et al. 2012, ICCI project)

• Longitudinal studies (Meunier & Littre 2013)

• More individual metadata –MUCH longitudinal corpus (Eriksson et al.)

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Very recent initiatives in Learner Corpora

• Domain- and genre-specific–VESPA (Paquot) , CALE (Callies)

• Linguistic theories (genre, SFL, pragmatics, politeness strategies, cognitive linguistics etc.

• Computer-mediated, synchronous & asynchronous (McDonald et al. 2013) 28

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Thank you

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