Exploring register variation in learner lexis

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Exploring register variation in learner lexis

• The high-frequency verb make in
• native and learner speech and writing
• Claire Hugon
• CECL
• Louvain-la-Neuve
• 24. January 2008

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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

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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

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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?

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Methodology
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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)

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Implementing the methodology the example of make

• 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
• 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

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Top HFVs in the BNC
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Make in the BNC

• 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)

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Implementing the methodology the exampe of make

• 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
• 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

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Make in native and learner speech and writing
some findings
Overall frequency (/100,000 words)
Speech vs writing
Writing
Speech
146.8 lt 350.6
350.6
146.8
NS
126.6 lt 245
245
126.6
NNS
350.6 gt 245
146.8 126.6
NS vs NNS

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

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

• slight underuse of make in NNS speech, but not
  significant

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

Make is a polysemous verb ? qualitative analysis
to explain the results
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• 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

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Distribution of the occurrences of make in the
four corpora, by semantic category
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Delexical uses of make
Overall frequency (/100,000 words)
Speech vs writing
Writing
Speech
120.9
28.7 lt 120.9
28.7
NS
42.9
42.9 lt 80.9
80.9
NNS
120.9 gt 80.9
28.7 lt 42.9
NS vs NNS

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

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

• significant () overuse in NNS speech

• highly significant () underuse of make in NNS
  writing

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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

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Causative uses of make
Overall frequency (/100,000 words)
Speech vs writing
Writing
Speech
142.1
64.9 lt 142.1
64.9
NS
24.2
24.2 lt 102.6
102.6
NNS
142.1 gt 102.6
64.9 gt 24.2
NS vs NNS

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

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

• significant () underuse in NNS speech

• significant () underuse in NNS writing

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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)

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The proportion of each category is remarkably
similar for NS and NNS registers
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• Some previous findings about make
• French-speaking and Swedish-speaking learners
  underuse make in delexical structures (Altenberg
  Granger 2001, Altenberg 2001)
• Swedish-speaking learners overuse causative make
  adj and make verb (Altenberg 2002a, 2002b)
• (Partially) L1-related explanations
• delexical structures avoidance strategy due to
  arbitrary and L1-specific choice of the verb
• causative structures transfer of frequency from
  L1 overgeneralisation

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• Plausible register-related explanation?
• delexical combinationsyes.
• 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
• 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 NNSobserved
  overuse of causative structures.

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• 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

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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 hes making a portrait the
  portrait of a of a girl

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Methodological implications

• e.g. for the causative make V structure, in
  LOCNEC 16 instances/42 involve look
• hes 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

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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

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Thank you!