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International Conference on Computational and Corpus-Based Phraseology

EUROPHRAS 2019: Computational and Corpus-Based Phraseology pp 200–214Cite as

Effects of Statistical Learning Ability on the Second Language Processing of Multiword Sequences

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11755))

Abstract

A substantial body of research has demonstrated that both native and non-native speakers are sensitive to the statistics of multiword sequences (MWS). However, this research has predominantly focused on demonstrating that a given sample of participants shows evidence of learning the statistical properties of MWS. Recent theoretical approaches to language learning and processing emphasize the importance of moving away from group-level analyses towards analyses that account for individual differences (IDs). Here, through a within subject design embedded within an IDs framework, we investigate whether and to what extent individual variability in the online processing of MWS are associated with the statistical learning (SL) ability of an individual. Second language learners were administered a battery of SL tasks in the visual and auditory modalities, using verbal and non-verbal stimuli, with adjacent and non-adjacent contingencies along with two online processing tasks of MWS designed to assess sensitivity to the statistics of spoken and written language. We found a number of significant associations between the SL ability and the two processing tasks: Individuals who performed better on an auditory verbal adjacent SL task demonstrated greater sensitivity to the statistics of MWS in the spoken language, whereas individuals with better performance on a visual, non-verbal sequence learning task demonstrated greater sensitivity to the statistics of MWS in the written language. We discuss the implications of these findings for the study of IDs in the processing of MWS.

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Notes

  1. 1.

    Following the literature, we use the term ‘emergentist’ to refer to a family of models and approaches – including usage-based (a.k.a. experience-based) models, constraint-based approaches, exemplar-based models and connectionist models – that is becoming a mainstay of cognitive and psycholinguistic thinking as well as for theories of second language learning (see, [15, 28], for a recent overview).

  2. 2.

    This study was undertaken as part of a larger project designed to investigate the role of a range of cognitive and affective IDs factors on the L2 processing of MWS across several written and spoken input types (registers).

  3. 3.

    The adjacent TPs between adjacent syllables within words were 0.5. To make the adjacent TPs across word boundaries equal to 0.5, each word could be followed by only one of four other words.

  4. 4.

    https://stanfordnlp.github.io/CoreNLP/.

  5. 5.

    https://www.psychopy.org/.

References

  1. Arciuli, J., Simpson, I.C.: Statistical learning is related to reading ability in children and adults. Cogn. Sci. 36(2), 286–304 (2012)

    Article  Google Scholar 

  2. Arnon, I., Snider, N.: More than words: frequency effects for multi-word phrases. J. Mem. Lang. 62(1), 67–82 (2010)

    Article  Google Scholar 

  3. Chang, F., Dell, G.S., Bock, K.: Becoming syntactic. Psychol. Rev. 113(2), 234 (2006)

    Article  Google Scholar 

  4. Christiansen, M.H., Arnon, I.: More than words: the role of multiword sequences in language learning and use. Top. Cogn. Sci. 9(3), 542–551 (2017)

    Article  Google Scholar 

  5. Christiansen, M.H., Chater, N.: Language as shaped by the brain. Behav. Brain Sci. 31(5), 489–509 (2008)

    Article  Google Scholar 

  6. Christiansen, M.H., Chater, N.: Creating Language: Integrating Evolution, Acquisition, and Processing. MIT Press, Cambridge (2016)

    Book  Google Scholar 

  7. Christiansen, M.H., Chater, N.: The now-or-never bottleneck: a fundamental constraint on language. Behav. Brain Sci. 39, e62 (2016)

    Article  Google Scholar 

  8. Conklin, K., Schmitt, N.: The processing of formulaic language. Annu. Rev. Appl. Linguist. 32, 45–61 (2012)

    Article  Google Scholar 

  9. Conway, C.M., Bauernschmidt, A., Huang, S.S., Pisoni, D.B.: Implicit statistical learning in language processing: word predictability is the key. Cognition 114(3), 356–371 (2010)

    Article  Google Scholar 

  10. Davies, M.: The 385+ million word corpus of contemporary american english (1990–2008+): design, architecture, and linguistic insights. Int. J. Corpus Linguist. 14(2), 159–190 (2009)

    Article  Google Scholar 

  11. Dewaele, J.M.: Individual differences in second language acquisition. In: Ritchie, W.C., Bhatia, T.K. (eds.) The New Handbook of Second Language Acquisition, pp. 623–646. Emerald Insight Bingley, England (2009)

    Google Scholar 

  12. Diessel, H.: Frequency effects in language acquisition, language use, and diachronic change. New Ideas Psychol. 25(2), 108–127 (2007)

    Article  Google Scholar 

  13. Dörnyei, Z., Skehan, P.: Individual differences in second language learning. In: The Handbook of Second Language Acquisition, chap. 18, pp. 589–630. Wiley-Blackwell (2008)

    Google Scholar 

  14. Ellis, N.: The associative learning of constructions, learned attention, and the limited L2 endstate. In: Robinson, P., Ellis, N. (eds.) Handbook of Cognitive Linguistics and Second Language Acquisition, chap. 15, pp. 372–405. Routledge (2008)

    Google Scholar 

  15. Ellis, N.C.: Essentials of a theory of language cognition. Mod. Lang. J. 103, 39–60 (2019)

    Article  Google Scholar 

  16. Endress, A.D., Mehler, J.: The surprising power of statistical learning: when fragment knowledge leads to false memories of unheard words. J. Mem. Lang. 60(3), 351–367 (2009)

    Article  Google Scholar 

  17. Ettlinger, M., Morgan-Short, K., Faretta-Stutenberg, M., Wong, P.: The relationship between artificial and second language learning. Cogn. Sci. 40(4), 822–847 (2016)

    Article  Google Scholar 

  18. Frost, R., Armstrong, B.C., Siegelman, N., Christiansen, M.H.: Domain generality versus modality specificity: the paradox of statistical learning. Trends Cogn. Sci. 19(3), 117–125 (2015)

    Article  Google Scholar 

  19. Frost, R., Siegelman, N., Narkiss, A., Afek, L.: What predicts successful literacy acquisition in a second language? Psychol. Sci. 24(7), 1243–1252 (2013)

    Article  Google Scholar 

  20. Gibson, E., et al.: How efficiency shapes human language. Trends Cognit. Sci. 23(5), 389–407 (2019)

    Article  Google Scholar 

  21. Glicksohn, A., Cohen, A.: The role of cross-modal associations in statistical learning. Psychon. Bull. Rev. 20(6), 1161–1169 (2013)

    Article  Google Scholar 

  22. Hernández, M., Costa, A., Arnon, I.: More than words: multiword frequency effects in non-native speakers. Lang. Cogn. Neurosci. 31(6), 785–800 (2016)

    Article  Google Scholar 

  23. Kaufman, S.B., DeYoung, C.G., Gray, J.R., Jiménez, L., Brown, J., Mackintosh, N.: Implicit learning as an ability. Cognition 116(3), 321–340 (2010)

    Article  Google Scholar 

  24. Kerz, E., Wiechmann, D.: Individual differences in L2 processing of multi-word phrases: effects of working memory and personality. In: Mitkov, R. (ed.) EUROPHRAS 2017. LNCS (LNAI), vol. 10596, pp. 306–321. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69805-2_22

    Chapter  Google Scholar 

  25. Kerz, E., Wiechmann, D., Christiansen, M.H.: Tuning to multiple statistics: second language processing of multiword sequences across registers. In: Goel, A., Seifert, C., Freksa, C. (eds.) Proceedings of the 41st Annual Conference of the Cognitive Science Society. Cognitive Science Society, Austin (in press)

    Google Scholar 

  26. Kidd, E.: Implicit statistical learning is directly associated with the acquisition of syntax. Dev. Psychol. 48(1), 171 (2012)

    Article  Google Scholar 

  27. Kidd, E., Arciuli, J.: Individual differences in statistical learning predict children’s comprehension of syntax. Child Dev. 87(1), 184–193 (2016)

    Article  Google Scholar 

  28. Kidd, E., Donnelly, S., Christiansen, M.H.: Individual differences in language acquisition and processing. Trends Cogn. Sci. 22, 154–169 (2017)

    Article  Google Scholar 

  29. Lany, J., Saffran, J.R.: From statistics to meaning: infants’ acquisition of lexical categories. Psychol. Sci. 21(2), 284–291 (2010)

    Article  Google Scholar 

  30. Lemhöfer, K., Broersma, M.: Introducing lextale: a quick and valid lexical test for advanced learners of English. Behav. Res. Methods 44(2), 325–343 (2012)

    Article  Google Scholar 

  31. Manning, C., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S., McClosky, D.: The stanford CoreNLP natural language processing toolkit. In: Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 55–60 (2014)

    Google Scholar 

  32. Matthews, D., Bannard, C.: Children’s production of unfamiliar word sequences is predicted by positional variability and latent classes in a large sample of child-directed speech. Cogn. Sci. 34(3), 465–488 (2010)

    Article  Google Scholar 

  33. Maye, J., Weiss, D.J., Aslin, R.N.: Statistical phonetic learning in infants: facilitation and feature generalization. Dev. Sci. 11(1), 122–134 (2008)

    Article  Google Scholar 

  34. McCauley, S.M., Christiansen, M.H.: Language learning as language use: a cross-linguistic model of child language development. Psychol. Rev. 126(1), 1 (2019)

    Article  Google Scholar 

  35. Misyak, J.B., Christiansen, M.H.: Statistical learning and language: an individual differences study. Lang. Learn. 62(1), 302–331 (2012)

    Article  Google Scholar 

  36. Misyak, J.B., Christiansen, M.H., Tomblin, J.B.: On-line individual differences in statistical learning predict language processing. Front. Psychol. 1, 31 (2010)

    Article  Google Scholar 

  37. Muggeo, V.M.R.: Estimating regression models with unknown break-points. Stat. Med. 22(19), 3055–3071 (2003)

    Article  Google Scholar 

  38. Northbrook, J., Conklin, K.: Is what you put in what you get out?—Textbook-derived lexical bundle processing in beginner English learners. Appl. Linguist. (8) (2018). https://doi.org/10.1093/applin/amy027

  39. Onnis, L., Waterfall, H.R., Edelman, S.: Learn locally, act globally: learning language from variation set cues. Cognition 109(3), 423–430 (2008)

    Article  Google Scholar 

  40. Pacton, S., Fayol, M., Perruchet, P.: Children’s implicit learning of graphotactic and morphological regularities. Child Dev. 76(2), 324–339 (2005)

    Article  Google Scholar 

  41. Saffran, J.R., Aslin, R.N., Newport, E.L.: Statistical learning by 8-month-old infants. Science 274(5294), 1926–1928 (1996)

    Article  Google Scholar 

  42. Saffran, J.R., Wilson, D.P.: From syllables to syntax: multilevel statistical learning by 12-month-old infants. Infancy 4(2), 273–284 (2003)

    Article  Google Scholar 

  43. Seidenberg, M.S., MacDonald, M.C.: The impact of language experience on language and reading. Top. Lang. Disord. 38(1), 66–83 (2018)

    Article  Google Scholar 

  44. Shafto, C.L., Conway, C.M., Field, S.L., Houston, D.M.: Visual sequence learning in infancy: domain-general and domain-specific associations with language. Infancy 17(3), 247–271 (2012)

    Article  Google Scholar 

  45. Shaoul, C., Westbury, C.: Formulaic sequences: do they exist and do they matter? Ment. Lex. 6(1), 171–196 (2011)

    Article  Google Scholar 

  46. Siegelman, N., Bogaerts, L., Christiansen, M.H., Frost, R.: Towards a theory of individual differences in statistical learning. Philos. Trans. R. Soc. B: Biol. Sci. 372(1711), 20160059 (2017)

    Article  Google Scholar 

  47. Siegelman, N., Frost, R.: Statistical learning as an individual ability: theoretical perspectives and empirical evidence. J. Mem. Lang. 81, 105–120 (2015)

    Article  Google Scholar 

  48. Singh, L., Steven Reznick, J., Xuehua, L.: Infant word segmentation and childhood vocabulary development: a longitudinal analysis. Dev. Sci. 15(4), 482–495 (2012)

    Article  Google Scholar 

  49. Siyanova-Chanturia, A., Conklin, K., Van Heuven, W.J.: Seeing a phrase “time and again” matters: the role of phrasal frequency in the processing of multiword sequences. J. Exp. Psychol.: Learn. Mem. Cogn. 37(3), 776 (2011)

    Google Scholar 

  50. Skehan, P.: Individual differences in second language learning. Stud. Second. Lang. Acquis. 13(2), 275–298 (1991)

    Article  Google Scholar 

  51. Spencer, M., Kaschak, M.P., Jones, J.L., Lonigan, C.J.: Statistical learning is related to early literacy-related skills. Read. Writ. 28(4), 467–490 (2015)

    Article  Google Scholar 

  52. Supasiraprapa, S.: Frequency effects on first and second language compositional phrase comprehension and production. Appl. Psycholinguist. 40(4), 987–1017 (2019). https://doi.org/10.1017/S0142716419000109

    Article  Google Scholar 

  53. Thiessen, E.D., Saffran, J.R.: When cues collide: use of stress and statistical cues to word boundaries by 7-to 9-month-old infants. Dev. Psychol. 39(4), 706 (2003)

    Article  Google Scholar 

  54. Thompson, S.P., Newport, E.L.: Statistical learning of syntax: the role of transitional probability. Lang. Learn. Dev. 3(1), 1–42 (2007)

    Article  Google Scholar 

  55. Tremblay, A., Derwing, B., Libben, G., Westbury, C.: Processing advantages of lexical bundles: evidence from self-paced reading and sentence recall tasks. Lang. Learn. 61(2), 569–613 (2011)

    Article  Google Scholar 

  56. Wolter, B., Yamashita, J.: Word frequency, collocational frequency, L1 congruency, and proficiency in L2 collocational processing: what accounts for L2 performance? Stud. Second Lang. Acquis. 40(2), 395–416 (2018)

    Article  Google Scholar 

  57. Wray, A.: Formulaic Language and the Lexicon. Cambridge University Press, Cambridge (2002)

    Book  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of English Linguistics, RWTH Aachen University, Aachen, Germany

    Elma Kerz

  2. Institute for Logic, Language and Computation, University of Amsterdam, Amsterdam, The Netherlands

    Daniel Wiechmann

Authors
  1. Elma Kerz
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  2. Daniel Wiechmann
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Correspondence to Elma Kerz or Daniel Wiechmann .

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Editors and Affiliations

  1. University of Malaga, Malaga, Spain

    Gloria Corpas Pastor

  2. University of Wolverhampton, Wolverhampton, UK

    Ruslan Mitkov

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Kerz, E., Wiechmann, D. (2019). Effects of Statistical Learning Ability on the Second Language Processing of Multiword Sequences. In: Corpas Pastor, G., Mitkov, R. (eds) Computational and Corpus-Based Phraseology. EUROPHRAS 2019. Lecture Notes in Computer Science(), vol 11755. Springer, Cham. https://doi.org/10.1007/978-3-030-30135-4_15

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  • DOI: https://doi.org/10.1007/978-3-030-30135-4_15

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