1

Exploring register variation in learner lexis

The high-frequency verb make in native and learner speech and writing

Claire HugonCECL

Louvain-la-Neuve 24. January 2008

2

Outline of the presentation

Background and aims of the study Methodology Setting the scene: make in the BNC Make in native and French-speaking learner speech

and writing Methodological implications and avenues for future

research

3

Background and aims of the study

Broader context: PhD research on the acquisition of high-frequency verbs

3 preliminary remarks: The influence of L1 as the « darling variable » of

learner corpus linguists Learner writing is frequently said to be speech-

like SLA variables are often studied in isolation

4

Background and aims of the study

Research questions: Does register have an influence on the use of

high-frequency verbs (HFVs) such as make in learner English?

Is the use of make in learner writing similar to native speech?

Can register differences be an alternative/ complementary explanation to features of non-nativeness attributed to L1?

5

Methodology

CIA

IL vs IL

registera

vs.

registerb

(CRIA)

L1a

vs

L1b

proficiencya

vs.

proficiencyb

taska

vs.

taskb

...

6

Methodology

Confrontation of native and learner data to detect similarities and differences and try to explain them (to-ing and fro-ing between the two components)

NS (writing)

LOCNESS

NS (speech)

LOCNEC

NNS (writing)

ICLE-FR

NNS (speech)

LINDSEI-FR

7

Implementing the methodology: the example of make

1. native language: make (and other HFVs) in the BNC see how HFVs behave in native language before looking for

differences in learner language BNC: wide-coverage corpus, much larger than LOCNESS better suited for broad, quantitative analysis

2. quantitative and qualitative analysis: make in native and learner speech and writing

native: LOCNESS and LOCNEC learner: ICLE-FR and LINDSEI-FR Comparison of the results

8

Top HFVs in the BNCWhole BNC Spoken BNC Written BNC

1. say 1. get 1. say

2. go 2. go 2. make (rel.freq. 2,190)

3. get 3. say 3. go

4. make (rel.freq.2,160) 4. know 4. take

5. seem 5. think 5. see

6. know 6. see 6. get

7. take 7. come 7. know

8. think 8. mean 8. come

9. come 9. want 9. give

10. give 10. take 10. use

11. look 11. look 11. think

12. use 12. make (rel.freq. 1,905) 12. look

9

Make in the BNC

spoken BNC

(/million words)

written BNC

(/million words)

chi-square value

1,905 2,190 *** 349.7

•Make is less frequent in speech than in writing•the difference is highly significant according to the chi-square test•atypical (most HFVs are more typical of speech)

10

Implementing the methodology: the exampe of make

1. native language: make (and other HFVs) in the BNC see how HFVs behave in native language before looking for

differences in learner language BNC: wide-coverage corpus, much larger than LOCNESS better suited for broad, quantitative analysis

2. quantitative and qualitative analysis: make in native and learner speech and writing

native: LOCNESS and LOCNEC learner: ICLE-FR and LINDSEI-FR Comparison of the results

11

Make in native and learner speech and writing: some findings

350.6 > 245146.8 ≥ 126.6NS vs NNS

126.6 < 245

146.8 < 350.6

Speech vs writing

245126.6NNS

350.6146.8NS

WritingSpeech

Overall frequency (/100,000 words):

highly significant (***) underuse of make in NNS writing brings frequency in NNS writing closer to NS speech

slight underuse of make in NNS speech, but not significant

make is significantly(***) less frequent in NNS speech than in NNS writing

make is significantly (***) less frequent in NS speech than in NS writing

Make is a polysemous verb qualitative analysis to explain the results

12

7 main semantic subdivisions

core meaning (produce, create) delexical uses

‘speech’ collocates other collocates

causative uses causative uses

make + adj make + verb make + noun

‘money’ make phrasal verbs other uses link verbs

13

020406080

100120140160

NS writing NNS writing

NS speech NNS speech

Distribution of the occurrences of make in the four corpora, by semantic category

14

Delexical uses of make

120.9 > 80.928.7 < 42.9NS vs NNS

42.9 < 80.9

28.7 < 120.9

Speech vs writing

80.942.9NNS

120.9 28.7NS

WritingSpeech

Overall frequency (/100,000 words):

highly significant (***) underuse of make in NNS writing

significant (*) overuse in NNS speech

significantly(***) less frequent in NNS speech than in NNS writing

significantly (***) less frequent in NS speech than in NS writing

15

Delexical uses of make

NNS writing: underuse of EAP delexical structures (make a case, make a statement) maybe register-related

NNS speech: overuse of delexical uses probably communication strategy (pressure, online

processing, make as default verb): especially one course we have to make erm . a kind of work when I go . eat em . with my master the: the cooking he

made for us is just er . about er .. an .. experience which I .. made when I was in

first candi

16

Causative uses of make

142.1 > 102.664.9 > 24.2NS vs NNS

24.2 < 102.6

64.9 < 142.1

Speech vs writing

102.624.2NNS

142.164.9NS

WritingSpeech

Overall frequency (/100,000 words):

significant (**) underuse in NNS writing

significant (***) underuse in NNS speech

significantly(***) less frequent in NNS speech than in NNS writing

significantly (***) less frequent in NS speech than in NS writing

17

Causative uses of make

underuse of causative structures as a whole in learner language (both in speech and in writing)

3 causative structures: • make + adjective (make sth easier)• make + verb (make someone feel bad)• make + noun (make someone an outcast)

18

The proportion of each category is remarkably similar for NS and NNS registers

NS writing NNS writing

NS speech NNS speech

Adjective 57% 57.6% 39% 40.9%

Verb 30% 32.7% 54.5% 50%

Noun 13% 9.7% 6.5% 9.1%

Total 100% 100% 100% 100%

19

Some previous findings about make:

1. French-speaking and Swedish-speaking learners underuse make in delexical structures (Altenberg & Granger 2001, Altenberg 2001)

2. Swedish-speaking learners overuse causative make + adj and make + verb (Altenberg 2002a, 2002b)

(Partially) L1-related explanations:1. delexical structures: avoidance strategy due to

arbitrary and L1-specific choice of the verb2. causative structures: transfer of frequency from L1 +

overgeneralisation

20

Plausible register-related explanation?1. delexical combinations:yes.

• Transfer and register have a similar impact. Underuse of delexical structures in NNS writing: much less frequent in NS speech than in NS writing: possible transfer of frequency from target language speech

2. causative structures: no (at least not for Swedish-speaking learners).

• Transfer and register seem to pull in opposite directions: • L1 Swedish causes overuse of L2 English ADJ and VERB

causative structures• English speech uses fewer causatives structures, so poor register

awareness is not a valid explanation for the Swedish-speaking NNS’observed overuse of causative structures.

21

To sum up:

Make is a multi-faceted verb with many meanings, functions, and patterns: a very interesting picture of scale of proficiency of advanced interlanguage emerges

from no knowledge at all (e.g. some phrasal verbs, link verb uses, ‘money’ make are nearly absent)

to near-perfect knowledge (e.g. proportions of 3 causative syntactic structures)

including various levels of partial knowledge (e.g. core uses, delexical uses, overall frequency of causative uses, etc.)

knowing a word is not an all-or-nothing matter

22

Methodological implications

The results can be partially skewed by one part of the interview:

e.g. for the core meaning of make (= produce, create), overuse in LINDSEI-FR due to picture description task NS: do/draw a portrait, do/paint a picture

he paints the picture of a beautiful woman NNS: make a portrait/a drawing/ a picture

there is a painter he’s making a portrait the portrait of a of a girl

23

Methodological implications

e.g. for the causative make + V structure, in LOCNEC 16 instances/42 involve look: he’s now repainting it making her look . much more attractive he makes her look . totally different makes her look very

glamorous clearly topic-induced by picture description which

elicits predictable patterns bears unduly on the overall results for that category not mirrored in LINDSEI-FR (1/11)

probably more appropriate to study the picture description (elicited) separately from the more spontaneous tasks

24

Where to from here? Possible avenues for further research

Complement quantitative analysis of native English HFVs by carrying out a similar analysis on learner data (requires preparation of the data, e.g. tagging of LINDSEI)

Combine corpus data with other types of data (e.g. elicitation) Complement qualitative analysis of make by carrying out similar

analyses of other HFVs reach better understanding of how these complex verbs are gradually

acquired in the interlanguage system Study other variables:

L1: Carry out transfer analysis on the same data + other learner populations Proficiency: longitudinal approach (data from other proficiency levels)

also help to understand the gradual evolution of the interlanguage system in time

25

Thank you!