Eviden ence for F Fea eature e Reassem embly: Gen ender er a - - PowerPoint PPT Presentation

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Eviden ence for F Fea eature e Reassem embly: Gen ender er a - - PowerPoint PPT Presentation

Dec 20, 2022 169 likes •387 views

Eviden ence for F Fea eature e Reassem embly: Gen ender er a and number f fea eatu tures i in L2 Russian Mila Tasseva-Kurktchieva Angelina Rubina tassevak@mailbox.sc.edu arubina@email.sc.edu AAAL 2019 Goals To assess whether

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Eviden ence for F Fea eature e Reassem embly: Gen ender er a and number f fea eatu tures i in L2 Russian

AAAL 2019

Mila Tasseva-Kurktchieva tassevak@mailbox.sc.edu Angelina Rubina arubina@email.sc.edu

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Goals

  • To assess whether L2 learners of Russian can acquire both
  • A feature that is present in their L1 (English), namely [number], and
  • A feature which is not evident in their L1, namely [gender]
  • To assess whether extra-grammatical properties have influence on the

acquisition of grammatical features

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Goals Feature reassembly Methods Results Conclusion

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Feature Reassembly (Lardiere, 2009)

  • L2 acquisition is more than what we commonly call parameter

resetting

  • Feature interpretability (Chomsky, 1995; White et al, 2004)
  • Interpretable features = head features
  • Uninterpretable features = relational features (i.e., need checking and

interpretation at Spell-Out)

 Uninterpretable features, especially those not present in L1, will be un-acquireable (Hawkins and Chan, 1997)  But what if both languages have the same feature realized in syntax?

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Goals Feature reassembly Methods Results Conclusion

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Feature Reassembly (Lardiere, 2009)

  • The feature(s) could be exactly the same  should not cause L2A problems

1) (in) definiteness in English and Spanish

  • The feature(s) could have different compositionality  should cause (some) L2A problems

2) (in)definiteness in French and English

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Goals Feature reassembly Methods Results Conclusion

French English Sg Pl Sg Pl indefinite un/une des a/an Ø definite le/la les the the English Spanish Sg Pl Sg Pl indefinite a Ø el/la Ø definite the the les les

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Feature Reassembly (extension)

  • Slabakova (2008), Cho & Slabakova (2014): difficulty continuum
  • Features which require mapping of L1 morphology to L2 morphology of

equivalent compositionality are easiest to acquire ([±definiteness] in English and Spanish)

  • Features which map L1 to L2 morphology but require compositional

reassembly are more difficult ([±definiteness] in English and French)

  • Features which map a morphologically covert property in one language that is

set in the discourse onto a morphologically overt material in the other language are the most difficult ([aspect] in English and Bulgarian)

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Goals Feature reassembly Methods Results Conclusion

3) Sue baked cakes for 10 years before she became a doctor. 4) Sue baked 3 cakes yesterday. 5) Sue peče torti v prodəlʒenie na 10 godini. 6) Sue izpeče 3 torti včera.

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Implications and predictions

  • Gender and number agreement will cause different problems for

native speakers of English acquiring L2 Russian

  • Acquisition of Russian [NUMBER] requires mapping of L1 morphology to L2

morphology plus feature reassembly

  • Acquisition of Russian [GENDER] requires L1 context to L2 morphology mapping
  • There will be delays in the RTs on the more difficult [GENDER] feature
  • There will be additional frequency effect within each feature

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Harder to acquire Easier to acquire Gender agreement Number agreement

Goals Feature reassembly Methods Results Conclusion

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The languages and features

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Goals Feature reassembly Methods Results Conclusion

English​ Russian​ Singular​ nice book​ nice phone​ nice mirror​ krasiv-AJAFEM.SG knig-АFEM.SG krasiv-YIMASC.SG telefon-ØMASC.SG krasiv-ОENEUT.SG zerkal-ОNEUT.SG Plural​ nice book-S nice phone-S nice mirror-S krasiv-YEFEM.PL knig-IFEM.PL krasiv-YEMASC.PL telefon-YMASC.PL krasiv-YENEUT.PL zerkal-ANEUT.PL

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The cline of difficulty (Slabakova 2008, 2009)

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Harder to acquire Easier to acquire L1 Fcontext L2 Fmorpheme , +reassembly L1 Fmorpheme L2 Fmorpheme, +reassembly

[number] on Nouns [gender] on Fem and

Neut Nouns and Adj’s

Goals Feature reassembly Methods Results Conclusion

L1 Fcontext L2 Fcontext , +reassembly

[gender] on Masc Nouns

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Methodology

  • Participants: 21 second semester learners of Russian as L2
  • 10 participants in SET 1
  • 11 participants in SET 2
  • Materials:
  • A pool of concrete nouns and adjective from 1st semester Russian curriculum
  • Canonical [gender] and [number] affixes
  • Nominative case
  • Form of the NPs:

Adj[gender, number, NOM]—N[gender, number, NOM]

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Goals Feature reassembly Methods Results Conclusion

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Methodology

  • Tests:
  • SET 1: give the features on A  expect participants to retrieve them on N
  • Forced choice comprehension task
  • Fill in the blanks task
  • SET 2: give the features on the N  expect participants to retrieve them on A
  • Grammaticality judgement task
  • Forced choice production task
  • Background questionnaire

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Goals Feature reassembly Methods Results Conclusion

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SET 1: Forced choice comprehension task

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Goals Feature reassembly Methods Results Conclusion

У меня есть желтый ___ из Италии. ‘I have a yellowMASCSG ____ from Italy.’

Target (MascSg) Number competitor (FemPl) Gender competitor (FemSg)

  • 30 target trials
  • 6 conditions, 5

trials per condition

  • 20 fillers
  • 4 practice trials
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SET 2: GJT

  • 6 feature conditions: MascSg, MascPl, FemSg, FemPl, NeutSg, NeutPl
  • 2 grammaticality conditions
  • Grammatical:

7) U menja v škafu zeljonaja rubaška to me in wardrobe greenFEMSG shirtFEMSG ‘In my wardrobe there is a green shirt.’

  • Ungrammatical:

8) Vot zeljonaja derevo na kartinke here’s greenFEMSG treeNEUTSG in picture ‘Here is a green tree in the picture.’

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Goals Feature reassembly Methods Results Conclusion

У меня в шкафу зеленая рубашка. Вот зеленая дерево на картинке.

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Results: SET 1, Forced choice comprehension

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Goals Feature reassembly Methods Results Conclusion

47% 21% 31% 0% 20% 40% 60% 80% 100%

SET1: Accuracy: correct, gender competitor, number competitor

correct gender competitor number competitor 10000 11000 12000 13000 14000 correct gender competitor number competitor

SET 1: RTs of correct, gender competitor, number competitor selections

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Results: SET 1, Forced choice comprehension

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Goals Feature reassembly Methods Results Conclusion

38% 54% 50% 52% 52% 54% 0% 20% 40% 60% 80% 100% Masc Fem Neut

SET 1: Accuracy by condition

singular plural

Masc Fem Neut singular 13250 12131 10694 plural 12986 11398 11237 13250 12131 10694 12986 11398 11237 10000 11000 12000 13000 14000

SET 1: RTs by condition

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Masc Fem Neut correct 38% 54% 52% gender competitor 14% 26% 24% number competitor 48% 18% 26% 38% 54% 52% 14% 26% 24% 48% 18% 26% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

SET 1: selection of gender vs. number competitor

Results: SET 1, Forced choice comprehension

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Goals Feature reassembly Methods Results Conclusion

13250 12131 10694 14040 11815 13702 12389 11093 11895 10000 11000 12000 13000 14000 15000

SET 1: RTs on correct, gender competitor, number competitor selections

correct gender competitor number competitor

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Results: SET 2, Grammaticality judgement

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Goals Feature reassembly Methods Results Conclusion

59% 65% 65% 58% 55% 52%

0% 20% 40% 60% 80% 100%

Masc Fem Neut

SET 2: correct responses singular vs. plural by gender singular plural 11948 10458 10886

11442 9073 10896

2000 4000 6000 8000 10000 12000 14000

Masc Fem Neut

SET 2: RTs singular vs. plural by gender singular plural

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Results: SET 2, Grammaticality judgement

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Goals Feature reassembly Methods Results Conclusion

0% 20% 40% 60% 80% 100% Masc Fem Neut grammatical 61% 67% 68% ungrammatical 56% 53% 48%

SET 2: grammatical vs. ungrammatical by gender

10603 10761 10731 12534 8483 12142

2000 4000 6000 8000 10000 12000 14000

Masc Fem Neut SET 2: RTs of grammatical vs. ungrammatical by gender

grammatical ungrammatical

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Results: SET 2, Grammaticality judgement

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Goals Feature reassembly Methods Results Conclusion

80% 65% 60% 67% 0% 20% 40% 60% 80% 100% singular plural

SET 2: Accuracy grammatical vs. ungrammatical by number

grammatical ungrammatical 10283 12117 11063 9494 5000 10000 15000 singular plural

SET 2: RTs grammatical vs. ungrammatical by number

grammatical ungrammatical

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Results: SET 2, Grammaticality judgement

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Goals Feature reassembly Methods Results Conclusion 0% 20% 40% 60% 80% 100% MascSg MascPl FemSg FemPl NeutSg NeutPl 64% 58% 82% 52% 70% 67% 55% 58% 48% 58% 61% 36%

SET 2: grammatical vs. ungrammatical by condition

grammatical ungrammatical

10432 10479 10067 10751 10162 11973 13384 10430 9748 7901 12602 10263 5000 10000 15000 MascSg MascPl FemSg FemPl NeutSg NeutPl

SET 2: RTs grammatical vs. ungrammatical by condition

grammatical ungrammatical

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Conclusions

  • What we see in the two comprehension tasks supports the Feature

Reassembly hypothesis:

  • They produce better results and are faster on the [number] than the [gender]

feature across the board

  • The gender feature on the head N is easier to comprehend than on the

agreeing Adj

  • Masc is produces the worst results in both singular and plural

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Goals Feature reassembly Methods Results Conclusion

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Thank you!

Selected References: Clahsen, H., & Felser, C. (2006). Grammatical processing in language learners. Applied Psycholinguistics, 27(1), 3-42. Ferreira, F., & Engelhardt, P. E. 2006. Syntax and production. In M. A. Gernsbacher & M. Traxler (Eds.), Handbook of Psycholinguistics (pp. 61-91). Oxford, UK: Elsevier. Ferreira, F., & Patson, N. D. 2007. The 'good enough' approach to language comprehension. Language and Linguistics Compass, 1(1-2), 71-83. Jackendoff, R. 2002. Foundations of Language. Oxford: Oxford University Press. Hawkins, R., & Chan, C. Y. (1997). The Partial Availability of Universal Grammar in Second Language Acquisition: The “Failed Functional Features Hypothesis.” Second Language Research, 13(3), 187–226. Lardiere, Donna 2009. Some thoughts on the contrastive analysis of features in second language

  • acquisition. Second Language Research 25,173 -227.

Slabakova, Roumyana. 2008. Meaning in The Second Languge. Mouton de Gruyter. Slabakova, R. 2009. Features or parameters: Which one makes second language acquisition easier, and more interesting to study? Second Language Research 25,313 -324. Van Patten, B. (2006). Input processing in adult second language acquisition. In Theories in Second Language Acquisition (pp. 115-136). Lawrence Erlbaum Associates, Mahwah, NJ.

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