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LOT 3: 16-20 jan061 Language Acquisition 3. Elena Lieven, MPI-EVA, Leipzig School of Psychological Sciences, University of Manchester.

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Presentation on theme: "LOT 3: 16-20 jan061 Language Acquisition 3. Elena Lieven, MPI-EVA, Leipzig School of Psychological Sciences, University of Manchester."— Presentation transcript:

1 LOT 3: jan061 Language Acquisition 3. Elena Lieven, MPI-EVA, Leipzig School of Psychological Sciences, University of Manchester

2 LOT 3: jan062 Outline for Session 3 MAIN TOPICS Errors and the ATOM Errors in syntactic questions Learning more complex constructions Constituency, embedding and island constraints ENDNOTE Complex syntax and input Metalinguistic awareness

3 LOT 3: jan063 Errors in the use of non-nominative subjects

4 LOT 3: jan064 The Agreement/Tense Omission Model (ATOM) [Schütze & Wexler, 1998] –Predicted to occur: +AGR/+TNS +NOMI’m goingHe goes +AGR/-TNS +NOMI goingHe go -AGR/+TNS -NOMMe goingHim go Her goneHer went –Predicted not to occur (or to occur at levels compatible with noise): +AGR/+TNS -NOMMe am goingHim goes

5 LOT 3: jan065 Errors that shouldn’t happen! Anne: Manchester Him doesn’t And her has Probably her’s a baby A big girl now, her is I think her was crying for me Becky: Manchester Where does him go? Her is gonna make a dinner Him’s eating you, crocodile Abe: Kuczaj Sometimes her barks nice, sometime her don’ts Her has a tummy ache

6 LOT 3: jan066 Testing the ATOM [Pine et al., 2006] Expected and observed rates of agreement with non- nominative subjects Nina: 3psg he/shehim/herRate Agreeing: Actual Expected(160.8)(62.2)(27.9) Non-agreeing Actual Expected(237.2)(91.8)

7 LOT 3: jan067 Nina’s 3psg by gender rates HeHim Agree2073 Rate expected by chance (154.73)(5.25) Non- agree Rate expected by chance (228.27)(7.75) SheHer Agree67 Rate expected by chance (6.06)(56.96) Non- agree 9134 Rate expected by chance (8.94)(84.04) Expected rate of non-nominative subjects with agreeing verbs = (3.3) Actual Rate = 1.4 Expected rate of non-nominative subjects with agreeing verbs = (90.4) Actual Rate = 53.8

8 LOT 3: jan068 Errors in syntactic questions

9 LOT 3: jan069 Omission Where he go Double marking Where does he does go? Non-inversion Where he does go? Agreement errors Where does you go? Case errors Where does her go? Errors in questions

10 LOT 3: jan0610 [Ambridge, Rowland, Theakston, Tomasello (in press)] Adult: Ask her why the dog is sleeping. Child: Why is the dog sleeping? Adult: Ask her where the pig can swim. Child: Where can the pig swim? 4 year olds MAIN RESULT: different number errors for: different wh- words different auxiliaries ‘same’ auxiliary w/ diff number (e.g., do & does)

11 LOT 3: jan0611 Accounting for patterns of error The error rate is low because children are learning constructions with slots High frequency frames should be protected from error Errors will occur when there isn’t a frame

12 LOT 3: jan0612 Data: –Adam : 2;3 – 4;10 (Brown 1973) –All wh-questions requiring inversion –Patterns of wh + auxiliary ( e.g. where does, what has) Results: Almost all wh-word + auxiliary combinations are produced either inverted or non-inverted - only 3 out of 49 showed ‘optional inversion’ The combinations that the child inverts are more frequent in the input than those that he fails to invert [Rowland & Pine, 2000]

13 13 Errors based on frames? Non-inversion M. You don’t throw things C. Why you don’t throw things? Omission Why you like cakes? → Why + X You like cakes Double marking Why don’t you don’t like cakes? → Why don’t + X You don’t like cakes Agreement errors Where does you go? → Where does X go? You

14 LOT 3: jan0614 Error rates in syntactic questions High frequency wordsLow frequency words FramesNon-framesFramesNon-frames [Rowland, in submission]

15 LOT 3: jan0615 Summary Errors should not be summed across forms Errors can be analysed in terms of patterns in the input Errors, correctly analysed, present important challenges to all theoretical positions that have to answered in terms of the theory

16 LOT 3: jan0616 Relating partially incompatible constructions

17 LOT 3: jan0617 Gaps with precedents at 3;0 Brian 3;0 What you doing GAP ? 0 What you doing GAP there?ADD there What I owe GAP you? 0 What say GAP ?0 What say my computer GAP ?ADD NP Where that come from GAP ?Where did that come from? (M) Where’s it gone GAP ?0 Where’s it gone GAP nowADD now Annie 3;0 Where can he park GAP ? Where can N park? What did you hurt GAP ?0 And what did she do GAP ?And what did NP do? (M)

18 LOT 3: jan0618 Gaps without precedents Brian 3;0 What your found GAP ?*You found X What I love GAP then?*I love X Where you been to GAP ?*I been to X What I bought it in GAP ? I bought it in X Annie 3;0 What can we do GAP with that? We can do X with that And what that done GAP ?*That done X

19 LOT 3: jan0619 Wh construction: Object of verb/preposition is utterance initial What o aux V? Verb frame: Object comes after the verb N s V N o Profile determinance (Langacker) Since a question is intended, the Wh construction is schematic for the composite utterance Note that children make mistakes over this: What I found it? What he done it?

20 LOT 3: jan0620 Learning more abstract constructions

21 LOT 3: jan0621 Building up constructions from prior constructions Schematisation and analogy Constituency, embedding and island constraints

22 LOT 3: jan0622 Building new constructions from old parts

23 LOT 3: jan0623 Diessel & Tomasello

24 LOT 3: jan0624 S-COMPLEMENTS Diessel & Tomasello, Cognitive Linguistics (2001) Subjects:Adam, Eve, Sarah, Naomi, Peter, Nina - 1 to 5 years Complex Ss:2807 tokens Examples from Sarah:Examples from Nina: I think he’s goneSee that monkey crying I think it’s in hereSee Becca sleeping I think my daddy took itSee that go I think I saw oneSee my hands are washed it’s a crazy bone, I thinkSee he bites me I think dis is de bowlSee him lie down

25 LOT 3: jan0625 % Subjects in Complex Ss 1-P2-P3-PLexImp Guess Bet Mean Know Think Wish Hope See Look Watch Remember Virtually no complementizers - Virtually no non-present tenses - Virtually no modals or negations

26 LOT 3: jan0626 RELATIVE CLAUSES Diessel & Tomasello, Cognitive Linguistics (2000) - Subjects: 4 CHILDES children from 1;9 to 5;1 - Total of 324 relative clauses Here’s the toy that goes around. That’s the sugar that fell out. There’s the ball I bought This’s the bird that sings. That’s the one that goes moo. Here’s the boy that ran into the water.

27 LOT 3: jan0627 EarliestAll NP ONLY: “The girl that came with us” PRESENTATIONALS “This is the car that turns around” OBLIQUES “I’m going to the zoo that has snakes”0.06 OBJECT “She has a bathtub that goes with it”.20*.26 SUBJECT “The one that not finished is up there”0.01 * 50% of these = “Look at all the chairs Peter’s got”

28 LOT 3: jan0628 Brandt, Diessel, & Tomasello (in progress) on German V2 “Relative Clauses” “Grosser Wal, der hat Zahnschmerzen” „Muscheln, die kann man essen“ MOTHER (20% = V2): „Ich habe einen Bauernhofkaese, der kommt von Frankreicher Bauernhof.“ “Real” Relative Clauses “Wo ist ein Wal, der Zahnschmerzen hat” One German child, dense corpus, over 900 relative clauses, age

29 LOT 3: jan years old matches adult

30 LOT 3: jan0630 Initial Complex Constructions Early S-comps and relative clauses have restricted range of forms => esp. in matrix clause No general rules for Wh-Questions (tough movement, binding) => some items easier than others, even when all the words are well established

31 LOT 3: jan0631 The construction conspiracy hypothesis [Abbot Smith & Behrens, submitted] Using German dense corpus [Leo] Development of sein- and werden- passive constructions

32 LOT 3: jan0632 Related constructions for the SEIN- and WERDEN-passives + HABENSEINWERDEN + Noun Das ist ein BallDas wird ein Fleugzeug + Adjective Der Ball ist blauDer Ball wird blau + Infinitive Der Mann wird lachen + INTRANSITIVE PARTICIPLE Der Mann hat gelacht Der Ball ist gefallen Hier wird gearbeitet + TRANSITIVE PARTICIPLE Der Mann hat den Wagen angemalt Der Wagen ist angemalt Der Wagen wird angemalt

33 LOT 3: jan0633 Leo versus mother (werden- versus sein-passive)

34 LOT 3: jan0634 Leo’s sein-passive and related constructions (3 rd ps. sg. only)

35 LOT 3: jan0635 Leo’s werden-passives and related constructions (3 rd ps. sg. only)

36 LOT 3: jan0636 Schematisation and analogy

37 LOT 3: jan0637 Schematisation: overlap in lexical material, constituents and meaning Analogy: no shared material, overlap in constituents and meaning car pulling boat truck pulling car Gentner et al.

38 LOT 3: jan0638 Analogy Already have a number of schemas Already know a lot about variations in NPs Create a construction with no lexical material that analogises across the schemas

39 LOT 3: jan0639 “The boy’s chopping the tree” He’s chopping it” “The dog’s eating the toy” He’s eating it” NP’s VERBing NP role of type frequency in VERB and NPs role of varied nouns and single pronoun in NPs role of verb semantics (Goldberg & Casenheiser) cline ANALOGY

40 LOT 3: jan0640 Constraining argument overgeneralisations

41 LOT 3: jan0641 Mommy, can you stay this open? I come closer so it won‘t fall. Don‘t giggle me. She came it over there. I want to stay this rubber band on. Eva won‘t stay things where I want them to be. You cried her. Will you climb me up there? „Kannst Du mich hochklettern?“ Transitivity Overgeneralizations

42 LOT 3: jan0642 Laugh – learned early entrenched no errors Chortle – learned late abstraction achieved no errors Giggle - not entrenched errors Mummy, he’s giggling me  He’s making me giggle

43 LOT 3: jan0643 Three constraining factors working over developmental time. Entrenchment Preemption Verb Subclasses Growing abstractness of the transitive construction Giggle Chortle Laugh Many overgeneralizations b/c not entrenched No overgeneralizations b/c Verb Islands Low overgeneralzations b/c preemption and verb subclasses in addition to entrenchment

44 44 Fixed Transitivity Verbs More EntrenchedLess Entrenched HitStrike TakeRemove ComeArrive DisappearVanish Method Children (3-8 yrs.) see transitive event and then are asked “mismatching” question - “What happened with PATIENT?” - “What did AGENT do?” Results More entrenched verbs overgeneralised less often Brooks et al, 1999 What determines overgeneralisations?

45 LOT 3: jan year-olds, 8-year-olds and adults heard sentences modelling argument structure errors with high and low frequency verbs –She disappeared the rabbit –She vanished the rabbit –He came her to school –He arrived her at school Children asked to indicate whether sentences sounded okay or silly Adults asked to rate sentences on a scale Theakston, 2004 Grammaticality judgements relate to entrenchment

46 LOT 3: jan0646 Adults’ judgments of ungrammatical sentences 0 = ungrammatical, 7 = grammatical

47 LOT 3: jan0647 Constituency, embedding and island constraints

48 LOT 3: jan0648 Johnnie should clean his teeth Johnnieshouldcleanhis teeth Whatshould Johnnie clean GAP!!!! ? INVERSION GAPS Children can’t learn grammar from what they hear

49 LOT 3: jan0649 isMaryhappy happy? Mary is RULE?: change the order of the first noun and the first verb The boywhoissmokingis crazy is crazy?who __ smoking The boy who is smokingisis crazy__crazy? RULE?: change the order of the SUBJECT and the MAIN VERB The boyis The boy who is smoking Moving constituents not words

50 LOT 3: jan0650 Constituency Of course constituency cannot be learned from linear strings But this is a ‘straw person’ argument and a very naïve view of input: If learning form X, the relevant input consists of form X Children build up knowledge of constituents over time and use this to parse more complex sentences The input can give indirect evidence

51 LOT 3: jan0651 It belongs to me The bike with wheels belongs to me The cats my dog chases belong to our neighbour

52 LOT 3: jan0652 The boy wearing a green hat who I saw yesterday in the park is very nice The boy’s nice The bus is red They are really really good They’re the ones I want The ones over there are the ones I want The boy wearing a green hat is nice The girl who dances The one I saw in the playground The one that turns round is mine Constructions gain more constituents Constituents become more complex Form-meaning mappings become more abstract Over time

53 LOT 3: jan0653 Modeling inversion with embedding Network trained on well-formed sentences Types and frequencies mimiced the Manchester corpus input Many sentences as follows : Mary is happyTimmy can swim awfully fast Is Mary happy?Can Timmy swim fast? No sentences : The boy who is smoking is crazy Tested on: Is the boy who smoking is crazy?* Is the boy who is smoking crazy? Clear preference for this [Lewis & Elman, 2001]

54 LOT 3: jan0654 Unbounded dependencies and island constraints Unbounded dependencies cannot be created for every part of a sentence *Who did she see the report that was about She saw the report that was about it *Who did that she knew bother him That she knew X bothered him

55 LOT 3: jan0655 Information structure and unbounded dependencies Backgrounded constructions are islands e.g. restrictive relative clauses and noun complements The potential extraction site must be at least a potential focus domain this introduces a cline of acceptability into grammaticality judgements depending on the degree of backgrounding –e.g. some presentational relatives can serve to convey the main assertion of the clause John is the sort of guy that I don’t know a lot of people who think well of [Cullicover] Lambrecht, Van Valin, Goldberg

56 LOT 3: jan0656 Where does complex syntax come from?

57 LOT 3: jan0657 Multi-clausal wh-questions “Who did the lion know that swam in the pond?” Very rare in children’s naturalistic speech: 12 children aged 1;2 – 6;0 [Stromswold, 1995] 13,000 utterances with who, what, which 200 with gap in ‘embedded’ clause (e.g. What would’ya like to have? What he want to play with?) and these are relatively simple infinitival complements Experiments are often with older children and sometimes with very unnatural sentences: Some 3-year-olds and more older children show evidence of observing various hypothesised syntactic constraints This has been taken as evidence of innate knowledge of these ‘unlearnable’ constraints However there is here also a cline in adult judgements of acceptability for these structures (Goldberg)

58 LOT 3: jan0658 Complex syntax and input: parents [Huttenlocher et al., 2002] Measures: – Proportion of complex sentences (adults) – Number of noun phrases per utterance (children) – Comprehension task: multi-clausal sentences (children) Results: –Proportion of complex sentences by parents the only significant predictor (r =.41, p<.01)

59 LOT 3: jan0659 Complex syntax and input: teachers Participants: –40 nursery classrooms: high SES; low SES, mixed SES –1 teacher per class Measures: –Teacher: Proportion of complex sentences Number of noun phrases per utterance Observation of ‘Quality of teaching’ –Children: Comprehension task: multi-clausal sentences and sentences with varying numbers of noun phrases at time 1 and time 2 Maths task

60 LOT 3: jan0660 Results Comprehension was related to SES at the beginning of the year The children’s growth scores over the year were not related to SES They were significantly and strongly related to the teacher’s proportional use of complex constructions

61 LOT 3: jan0661 End!


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