tamura & kusanagi (2014) celes
TRANSCRIPT
Measuring Explicit and Implicit Knowledge of Sentence-Level Discourse Constraints: A Case
of Assertive Predicates in English as a Foreign Language
June 22, 2014 44th CELES
Yamanashi University
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3
Overview
• Introduction• Background• The Present Study• Results• Discussion• Conclusion
Overview
• Introduction• Background• The Present Study• Results• Discussion• Conclusion
Introduction
• This study investigated…–What?
• Explicit and Implicit Knowledge of sentence-level constraints
–How?
• Untimed and Speeded Grammatical Judgment Tests
Overview
• Introduction• Background• The Present Study• Results• Discussion• Conclusion
Background
Learners of English do good sometimes, but doesn’t do so at other times.
Anything wrong?
Background
Learners of English do good sometimes, but doesn’t do so at other times.
well
don’t
Background
Why is learners’ performance inconsistent?
Background
Two Types of Knowledge
Background
Grammatical Knowledge
Explicit Knowledge
Implicit Knowledge
Yu TAMURAGraduate School, Nagoya Univ.
Kunihiro KUSANAGIGraduate School, Nagoya Univ.
JSPS Research Fellow [email protected]
BackgroundExplicit Knowledge
• Intuitive• Procedural• Automatic• Non-integrated
• Conscious• Declarative• Analyzed• Integrated
(Ellis,2004,2005; Jiang,2007)
Implicit Knowledge
BackgroundExplicit Knowledge
• Intuitive• Procedural• Automatic• Non-integrated
• Conscious• Declarative• Analyzed• Integrated
Implicit Knowledge
These are theoretical constructs and should be separated from processing or learning.
Background
• How explicit and implicit knowledge are measured?
Background
Explicit Knowledge
• oral production task• written production
task
• fill-in-the blank• verbal reports• error correction
MeasurementImplicit
Knowledge
Background
Explicit Knowledge
• oral production task• written production
task• timed/speeded GJT
• fill-in-the blank• verbal reports• error correction• untimed GJT
MeasurementImplicit
Knowledge
(Bialystok, 1979; Kusanagi & Yamashita, 2013; Loewen, 2009)
Background• What aspect of grammatical knowledge has been
investigated so far?– syntactic (e.g., reflexive pronouns, verb
complements, relative clauses etc.) – morphosyntactic (e.g., verb tenses and subject
verb agreement, etc.) – morphological constraints (e.g., plural nouns,
inflections, etc.) • What about semantic, pragmatic, and peripheral
phenomena?
Background• Explicit and Implicit knowledge studies
– only focus on narrow area of linguistic phenomena such as morphosyntactic features.
– Need to investigate more various features especially in sentence-level.
Then,
What kind of structures would it be?
Assertive Predicates
Background• What is assertive predicates?
Background• Assertive Predicates
– Classification of verbs
– Verbs can be classified into two types: Factive and nonfactive (Kiparsky & Kiparsky,1971)
– Factivity
• complements =true presupposition
NonfactiveAssertive
Weak Assertive Strong assertive Nonassertive
think acknowledge insist agree be likely
believe admit intimate be afraid be possible
suppose affirm maintain be certain be probable
expect allege mention be sure be unlikely
imagine answer point out be clear be impossible
guess argue predict be obvious be improbable
seem assert report be evident neg + strong assertiveFactive
Assertive (semifactive) Nonassertive (true factive)
find out regret
know forget
realize resent
adapted from Hooper (1975, p.92)
Background• Classification of verbs
– factive/nonfactive verbs can be characterized from the point of assertion.(Hooper, 1975).
Background• Classification of verbs
– Complement preposing(1a) Many of the applicants are women, it seems.(1b) *Many of the applicants are women, it’s likely.Assertive predicates allow complement preposing.
(e.g.,Hooper ,1975)
Background• Classification of verbs
– Root Transformations (RT) (2a)Sally plans for Gary to marry her, and he will marry her.→(2b) Sally plans for Gary to marry her, and marry her he will. (VP preposing)
(e.g.,Hooper ,1975)
Background• Classification of verbs
– Root Transformations (RT) (2c) Sally plans for Gary to marry her, and it seems that marry her he will. (2d) *Sally plans for Gary to marry her, and it’s likely that marry her he will. Assertive Predicates allow root transformations.
(e.g.,Hooper & Thompson, 1973)
Background• Characteristics of assertive/non-assertive
predicates
assertive nonasseritve
complement preposing ○ ×
root transformation ○ ×
Then,
Background• Non-assertive predicates do not take assertion
as their complements. The old woman regrets that his son smokes. *The old woman regrets that his son may smoke. • In Japanese, その老婆は息子がタバコを吸っていることを後悔した*その老婆は息子がタバコを吸っているかもしれないことを後悔した
Background• AssumptionJapanese EFL learners would not know the rule of non-assertive predicates explicitly, but they may implicitly be able to judge the grammaticality by the help of their L1 knowledge.
NonfactiveAssertive
Weak Assertive Strong assertive Nonassertive
think acknowledge insist agree be likely
believe admit intimate be afraid be possible
suppose affirm maintain be certain be probable
expect allege mention be sure be unlikely
imagine answer point out be clear be impossible
guess argue predict be obvious be improbable
seem neg + strong assertiveFactive
Assertive (semifactive) Nonassertive (true factive)find out regret
know forget
realize resentadapted from Hooper (1975, p.92)
Overview
• Introduction• Background• The Present Study• Results• Discussion• Conclusion
The Present Study
• RQs– Do Japanese EFL learners have explicit
knowledge of the discourse constraints?
– Do Japanese EFL learners have implicit knowledge of the discourse constraints?
The Present Study• Participants
– 18 Japanese graduate students
Age TOEIC Score
n M SD M SD
Participants 18 24.72 3.75 813.21 102.50
The Present Study• Stimuli (K =24)
– 6 non-assertive predicates
– 2 grammatical and ungrammatical sentences for each item
– 24 fillers factivity assertivenessregret + -be impossible - -be likely - -forget + -deny - -not agree - -
The Present Study• ExamplesIt is impossible [that the woman is the criminal].*It is impossible [that the woman may be the criminal].
Non-assertive predicates restrict the use of epistemic auxiliary or modal in embedded clause.
The Present Study• Experiment
– Untimed / Speeded GJTs on PCs (HSP ver. 3.2)
+
Junya always gets drunk.
100ms
50ms
The Present Study• Experiment
– The participants took untimed and speeded GJTs in turn.
– One of four conditions was attributed to each participant
• untimed/speeded ×grammatical / ungrammatical – Test items were presented randomly.
The Present Study
• Analysis –Accuracy Score
• t-test –Sensitivity Score (d’)
• t-test –Reaction Time
• Ex-Gaussian Distribution
–Outlier(M+2.5SD) was replaced to the mean scores.
Overview
• Introduction• Background• The Present Study• Results• Discussion• Conclusion
Accuracy Score
Descriptive Statistics of the Accuracy Score
K M SD 95%CI
Untimed Overall 20 .60 .12 [.55,.67]
Grammatical items 10 .71 .23 [.62,.84]
Ungrammatical items 10 .43 .33 [.26,.60]
Speeded Overall 20 .55 .15 [.47,.63]
Grammatical items 10 .74 .24 [.61,.85]
Ungrammatical items 10 .31 .30 [.18,.48]
Comparison of Accuracy Score between Untimed and Speeded Condition
0.00
0.23
0.45
0.68
0.90
Grammatical Ungrammatical ALL
UntimedSpeeded
Results of the t-tests between Untimed and Speeded GJT Scores
t (17) p Cohen’s d
Overall 0.64 0.52 0.21
Grammatical items 0.55 0.58 -0.18
Ungrammatical items 1.06 0.30 0.36
Results of the t-tests between Untimed and Speeded GJT Scores
t (17) p Cohen’s d
Overall 0.64 0.52 0.21
Grammatical items 0.55 0.58 -0.18
Ungrammatical items 1.06 0.30 0.36
Descriptive Statistics of the Accuracy Score
K M SD 95%CI
Untimed Overall 20 .60 .12 [.55,.67]
Grammatical items 10 .71 .23 [.62,.84]
Ungrammatical items 10 .43 .33 [.26,.60]
Speeded Overall 20 .55 .15 [.47,.63]
Grammatical items 10 .74 .24 [.61,.85]
Ungrammatical items 10 .31 .30 [.18,.48]
K M SD 95%CI
Untimed Overall 20 .60 .12 [.55,.67]
Grammatical items 10 .71 .23 [.62,.84]
Ungrammatical items 10 .43 .33 [.26,.60]
Speeded Overall 20 .55 .15 [.47,.63]
Grammatical items 10 .74 .24 [.61,.85]
Ungrammatical items 10 .31 .30 [.18,.48]
Descriptive Statistics of the Accuracy Score
Comparison of Accuracy Score between Untimed and Speeded Condition
0.00
0.23
0.45
0.68
0.90
Grammatical Ungrammatical ALL
UntimedSpeeded
Comparison of Accuracy Score between Untimed and Speeded Condition
0.00
0.23
0.45
0.68
0.90
Grammatical Ungrammatical ALL
UntimedSpeeded
Response bias?
Sensitivity Score
Descriptive Statistics of d’M SD 95%CI t (16) p Cohen’s d
Untimed 0.47 0.86 [0.02,0.92]
0.58 0.56 0.19
Speeded 0.29 0.92 [-0.18,0.77]
Descriptive Statistics of d’M SD 95%CI t (16) p Cohen’s d
Untimed 0.47 0.86 [0.02,0.92]
0.58 0.56 0.19
Speeded 0.29 0.92 [-0.18,0.77]
Reaction Time
Estimated Parameters of the Reaction Times (ms) Using Ex-Gaussian Distributions
The number of reactions
Ex-Gaussian distribution
μ σ τ
Untimed 180 3,870 2,085 3,191
Speeded 180 2,510 828 1,250
Difference 0 1,360 1,257 1,941
μ+τ = M
σ2 + τ2 = SD2
2000 4000 6000 8000
0e+0
01e
-04
2e-0
43e
-04
4e-0
4
Reading time(ms)
Den
sity
Speeded GrammaticalSpeeded Ungrammatical Untimed Grammatical Untimed Ungrammatical
Overview
• Introduction• Background• The Present Study• Results• Discussion• Conclusion
Discussion• Accuracy Scores & Sensitivity Scores
– No task effects
• Both explicit and implicit knowledge are not represented.
• Reaction Times– Participants took much longer time in
untimed condition. • They tried to access their explicit
knowledge.
Discussion• RQ1
– Do Japanese EFL learners have explicit knowledge of the discourse constraints?
→ No• RQ2
– Do Japanese EFL learners have implicit knowledge of the discourse constraints?
→ No
Discussion• Knowledge of sentence-level
constraints is difficult to acquire naturally?
• Necessity of explicit instruction for these types of linguistic features?
Limitations• Small sample size
–Accuracy for ungrammatical sentences in untimed conditions may become higher.
• Learner’s Proficiency?• Choice of non-assertive predicates• More data of linguistic features on
sentence-level discourse constraints.
Overview
• Introduction• Background• The Present Study• Results• Discussion• Conclusion
Conclusion
• Learners did not have both explicit and implicit knowledge of sentence-level constraints.
• These features may be difficult to acquire.
• But why? • Feature research needs to
investigate more about sentence-level discourse constraints.
BibliographyBialystok, E. (1979). Explicit and implicit judgements of L2 grammaticality. Language Learning: A Journal of Applied Linguistics, 29, 81-103. Ellis, R. (2004). The definition and measurement of L2 explicit knowledge. Language learning, 54(2), 227-275. Ellis, R. (2005). Measuring implicit and explicit knowledge of a second language. Studies in Second Language Acquisition, 27(2), 141-172. Hooper, J.B. (1975). On assertive predicates. In: Kimball, J.P. (Ed.), Syntax and Semantics, vol. 4. Academic Press, NY, pp. 91–124. Hooper, J. B., & Thompson, S. A. (1973). On the applicability of root transformations. Linguistic inquiry, 465-497. Jiang, N. (2007). Selective integration of Linguistic knowledge in adult second language learning. Language Learning, 57(1), 1-33. Kiparsky, P., Kiparsky, C. (1970). Fact. In: Bierwisch, M., Heidolph, K.E. (Eds.), Progress in Linguistics: A Collection of Papers. Mouton, The Hague, pp. 143–173. Kusanagi, K., & Yamashita, J. (2013). Influences of linguistic factors on the acquisition of explicit and implicit knowledge: Focusing on agreement type and morphosyntactic regularity in English plural morpheme. Annual Review of English Language Education in Japan, 24, 205–220. Loewen , S . (2009). Grammaticality judgment tests and the measurement of implicit and explicit L2 knowledge . In R. Ellis, S. Loewen, C. Elder, R. Erlam, J. Philp, & H. Reinders (Eds.), Implicit and explicit knowledge in second language learning, testing and teaching (pp. 94–112). Bristol, UK: Multilingual Matters Ltd.