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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
2
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 
well 
Learners of English do good 
sometimes, but doesn’t do 
so at other times. 
don’t
Background 
Why is learners’ 
performance 
inconsistent?
Background 
Two Types of 
Knowledge
Background 
Grammatical 
Knowledge 
Explicit 
Knowledge 
Implicit 
Knowledge
Yu TAMURA 
Graduate School, Nagoya Univ. 
tamura.yu@e.mbox.nagoya-u. 
ac.jp 
Kunihiro KUSANAGI 
Graduate School, Nagoya Univ. 
JSPS Research Fellow 
kusanagi@nagoya-u.jp
Background 
Explicit Knowledge 
Implicit Knowledge 
• Intuitive 
• Procedural 
• Automatic 
• Non-integrated 
• Conscious 
• Declarative 
• Analyzed 
• Integrated 
(Ellis,2004,2005; Jiang,2007)
Background 
Explicit 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 
Measurement 
Explicit 
Knowledge 
• oral production task 
• written production 
task 
• fill-in-the blank 
• verbal reports 
• error correction 
Implicit 
Knowledge
Background 
Measurement 
Explicit 
Knowledge 
• oral production task 
• written production 
task 
• timed/speeded GJT 
• fill-in-the blank 
• verbal reports 
• error correction 
• untimed GJT 
Implicit 
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
NAosnsfearctitvivee 
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 
Factive assertive 
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 
• Assumption 
Japanese 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.
Nonfactive 
Assertive 
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 
Factive assertive 
Assertive (semifactive) Nonassertive (true factive) 
find out regret 
know forget 
realize resent 
adapted 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 assertiveness 
regret + - 
be impossible - - 
be likely - - 
forget + - 
deny - - 
not agree - -
The Present Study 
• Examples 
It 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) 
+ 
100ms 
50ms 
Junya always gets drunk.
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 
0.90 
0.68 
0.45 
0.23 
0.00 
Untimed 
Speeded 
Grammatical Ungrammatical ALL
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]
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 
0.90 
0.68 
0.45 
0.23 
0.00 
Untimed 
Speeded 
Grammatical Ungrammatical ALL
Comparison of Accuracy Score between Untimed and Speeded Condition 
0.90 
0.68 
0.45 
0.23 
0.00 
Untimed 
Speeded 
Response bias? 
Grammatical Ungrammatical ALL
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+τ = M 
μ σ τ 
σ2 + τ2 = SD2 
Untimed 180 3,870 2,085 3,191 
Speeded 180 2,510 828 1,250 
Difference 0 1,360 1,257 1,941
2000 4000 6000 8000 
0e+00 1e-04 2e-04 3e-04 4e-04 
Reading time(ms) Density 
Speeded Grammatical 
Speeded 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.
Bibliography 
Bialystok, 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.

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Tamura & Kusanagi (2014) CELES

  • 1. 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
  • 2. 2
  • 3. 3
  • 4. Overview • Introduction • Background • The Present Study • Results • Discussion • Conclusion
  • 5. Overview • Introduction • Background • The Present Study • Results • Discussion • Conclusion
  • 6. Introduction • This study investigated… –What? • Explicit and Implicit Knowledge of sentence-level constraints –How? •Untimed and Speeded Grammatical Judgment Tests
  • 7. Overview • Introduction • Background • The Present Study • Results • Discussion • Conclusion
  • 8. Background Learners of English do good sometimes, but doesn’t do so at other times.
  • 10. Background well Learners of English do good sometimes, but doesn’t do so at other times. don’t
  • 11. Background Why is learners’ performance inconsistent?
  • 12. Background Two Types of Knowledge
  • 13. Background Grammatical Knowledge Explicit Knowledge Implicit Knowledge
  • 14. Yu TAMURA Graduate School, Nagoya Univ. tamura.yu@e.mbox.nagoya-u. ac.jp Kunihiro KUSANAGI Graduate School, Nagoya Univ. JSPS Research Fellow kusanagi@nagoya-u.jp
  • 15. Background Explicit Knowledge Implicit Knowledge • Intuitive • Procedural • Automatic • Non-integrated • Conscious • Declarative • Analyzed • Integrated (Ellis,2004,2005; Jiang,2007)
  • 16. Background Explicit Knowledge • Intuitive • Procedural • Automatic • Non-integrated • Conscious • Declarative • Analyzed • Integrated Implicit Knowledge These are theoretical constructs and should be separated from processing or learning.
  • 17. Background • How explicit and implicit knowledge are measured?
  • 18. Background Measurement Explicit Knowledge • oral production task • written production task • fill-in-the blank • verbal reports • error correction Implicit Knowledge
  • 19. Background Measurement Explicit Knowledge • oral production task • written production task • timed/speeded GJT • fill-in-the blank • verbal reports • error correction • untimed GJT Implicit Knowledge (Bialystok, 1979; Kusanagi & Yamashita, 2013; Loewen, 2009)
  • 20. 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?
  • 21. 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.
  • 22. Then,
  • 23. What kind of structures would it be?
  • 25. Background • What is assertive predicates?
  • 26. Background • Assertive Predicates –Classification of verbs –Verbs can be classified into two types: Factive and nonfactive (Kiparsky & Kiparsky,1971) –Factivity • complements =true presupposition
  • 27. NAosnsfearctitvivee 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 Factive assertive Assertive (semifactive) Nonassertive (true factive) find out regret know forget realize resent adapted from Hooper (1975, p.92)
  • 28. Background • Classification of verbs – factive/nonfactive verbs can be characterized from the point of assertion. (Hooper, 1975).
  • 29. 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)
  • 30. 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)
  • 31. 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)
  • 32. Background • Characteristics of assertive/non-assertive predicates assertive nonasseritve complement preposing ○ × root transformation ○ ×
  • 33. Then,
  • 34. 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
  • 35. Background • Assumption Japanese 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.
  • 36. Nonfactive Assertive 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 Factive assertive Assertive (semifactive) Nonassertive (true factive) find out regret know forget realize resent adapted from Hooper (1975, p.92)
  • 37. Overview • Introduction • Background • The Present Study • Results • Discussion • Conclusion
  • 38. 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?
  • 39. 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
  • 40. The Present Study • Stimuli (K =24) – 6 non-assertive predicates – 2 grammatical and ungrammatical sentences for each item – 24 fillers factivity assertiveness regret + - be impossible - - be likely - - forget + - deny - - not agree - -
  • 41. The Present Study • Examples It 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.
  • 42. The Present Study • Experiment – Untimed / Speeded GJTs on PCs (HSP ver. 3.2) + 100ms 50ms Junya always gets drunk.
  • 43. 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.
  • 44. 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.
  • 45. Overview • Introduction • Background • The Present Study • Results • Discussion • Conclusion
  • 47. 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]
  • 48. Comparison of Accuracy Score between Untimed and Speeded Condition 0.90 0.68 0.45 0.23 0.00 Untimed Speeded Grammatical Ungrammatical ALL
  • 49. 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
  • 50. 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
  • 51. 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]
  • 52. 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]
  • 53. Comparison of Accuracy Score between Untimed and Speeded Condition 0.90 0.68 0.45 0.23 0.00 Untimed Speeded Grammatical Ungrammatical ALL
  • 54. Comparison of Accuracy Score between Untimed and Speeded Condition 0.90 0.68 0.45 0.23 0.00 Untimed Speeded Response bias? Grammatical Ungrammatical ALL
  • 56. 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]
  • 57. 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]
  • 59. Estimated Parameters of the Reaction Times (ms) Using Ex-Gaussian Distributions The number of reactions Ex-Gaussian distribution μ+τ = M μ σ τ σ2 + τ2 = SD2 Untimed 180 3,870 2,085 3,191 Speeded 180 2,510 828 1,250 Difference 0 1,360 1,257 1,941
  • 60. 2000 4000 6000 8000 0e+00 1e-04 2e-04 3e-04 4e-04 Reading time(ms) Density Speeded Grammatical Speeded Ungrammatical Untimed Grammatical Untimed Ungrammatical
  • 61. Overview • Introduction • Background • The Present Study • Results • Discussion • Conclusion
  • 62. 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.
  • 63. 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
  • 64. Discussion • Knowledge of sentence-level constraints is difficult to acquire naturally? • Necessity of explicit instruction for these types of linguistic features?
  • 65. 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.
  • 66. Overview • Introduction • Background • The Present Study • Results • Discussion • Conclusion
  • 67. 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.
  • 68. Bibliography Bialystok, 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.

Editor's Notes

  1. 大きな研究の課題として「学習者のパフォーマンスは不安定」ということを導入
  2. 今提示された文でなんかおかしなところなかった?と聞いてみる
  3. もう一度提示してみて
  4. 話を戻してなんでそういうことが起こるのかということ・
  5. その学習者のパフォーマンスを説明するために2つの知識があるという立場がある。
  6. 学習者のもっている文法知識は明示的知識と暗示的知識という2つの知識の混成物である。
  7. ところで
  8. 句レベルとか形態素レベルでしか見てない。 明示・暗示的知識の研究でもっと広く文レベルの項目(制約),言語現象をターゲットにするべき で,そのような項目として何があるか? からのassertive predicates(ドヤッ ってなに?
  9. まずは動詞の分類としてfactiveとnon-factiveに分けられるというところから。この基準として用いられるのがfactivityというもの。これは,動詞のcomplementsがture presuppositionなのかどうかによる。
  10. factive/nonfactiveという動詞の分類を,さらにassertiveness (assertion)という観点から分類を試みようとしたのがHooper(1975)である。この分類では,統語的な操作が可能であるかどうかという点で,assertiveとnon-assertiveを区別している。
  11. まず一点目としてcomplement preposingという補文の前置が可能であるかどうかという点。assertive predicatesはこの補文前置が可能である。補文前置が起こったことにより,この補文は文の主なる主張(main assertion)になる。APでは,補文がそもそも命題に対する肯定的な主張を表すのに対し,NonAPでは補文の命題の真理値に対して否定意見を表すかあるいはきわめて弱い意見しか表さないため,補文前置が適用できない。
  12. 次にルート変形が適用できるかどうか。ここでは動詞句前置と呼ばれるルート変形を考える。2aの文から2bの文を導くものを動詞句前置と呼ぶ
  13. APではこのルート変形が可能であるが,NonAPでは不可能。このルート変形は,前置する要素を強調するという働きがある。つまりはそれが主張となっていなければならない。NonAPがこのようなルート変形を許さないのも,その補文が主張を表さないからである。
  14. factive/nonfactiveという動詞の分類を,さらにassertiveness (assertion)という観点から分類を試みようとしたのがHooper(1975)である。この分類では,統語的な操作が可能であるかどうかという点で,assertiveとnon-assertiveを区別している。
  15. APではこのルート変形が可能であるが,NonAPでは不可能。このルート変形は,前置する要素を強調するという働きがある。つまりはそれが主張となっていなければならない。NonAPがこのようなルート変形を許さないのも,その補文が主張を表さないからである。日本語で考えてみても,「かもしれないことを後悔した」というのは容認不可能になるはずである。
  16. よって,明示的にはepistimic auxの使用が制限されるこの現象の知識はなくとも,日本語の知識を援用して暗示的知識として習得されている可能性はないか?
  17. 分析方法として何を用いたか
  18. まずは文法分と非文法文それから全部のそれぞれの記述統計
  19. 正答率のt検定をしてみたが,どこで見ても有意差なし→taskの影響を受けていない→明示的な知識もない?
  20. 効果量とt値でみると,非文法文だけやや高い。
  21. まずは文法分と非文法文それから全部のそれぞれの記述統計
  22. まずは文法分と非文法文それから全部のそれぞれの記述統計
  23. untimedのときには,やはり分布を見ても反応時間が後ろに引っ張られていることがわかる。つまり,明示的知識にアクセスしようとしているということ。しかしながら,表象がないので正答率の上昇にはつながっていない。
  24. というわけでRQ1もRQ2についても否定された
  25. 文レベルのこういった現象はインプットのみで自然に習得するのはかなり難しい?というかそもそも目を向けられていないのではないか? 明示的な介入によってこういった言語項目を指導する必要性もあるのかもしれない。明示的な介入といっても規則を与えるというわけではなくとりあえずconsciousness-raising程度のことは必要なのでは。
  26. サンプルサイズが小さい。非文法文にでは効果量が少し大きくなっておりt値も他よりは高くなっていたのでサンプルサイズを増やせばもしかすると明示的知識はある?あるいはもっと高熟達度話者であれば違う? 選んだnon-assertive predicatesの種類が少なかったので種類と項目数増やしたらまたちがった? もっと他の言語現象での結果がどうなるかも調べる必要がある