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16 - Implicit Statistical Learning and Second Language Outcomes

A Bayesian Meta-Analysis

from Part IV - Aptitude–Treatment Interaction (ATI)

Published online by Cambridge University Press:  27 May 2023

Zhisheng (Edward) Wen
Affiliation:
Hong Kong Shue Yan University
Peter Skehan
Affiliation:
Institute of Education, University of London
Richard L. Sparks
Affiliation:
Mount St Joseph University
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Summary

Recent theoretical advances viewing language aptitude as multifaceted have led to accumulated evidence on certain constructs beyond the specifications of traditional aptitude tests. In this chapter, we consider the potential role of implicit statistical learning (ISL) mechanisms in second language acquisition (SLA). First, terminological and conceptual issues are examined with the goal of clarifying the processes and knowledge that ISL tasks are claimed to involve. Second, we consider justifications for research into the potential link between ISL and SLA by reviewing the argument for a default implicit processing mode in adult L2 learning. Third, we provide a synthesis of studies assessing the link between ISL and L2 outcomes based on the following research questions: (1) Which studies have examined the association between ISL tasks and L2 outcomes and what are their characteristics? (2) Which measures have been used to investigate the construct of ISL? And (3) What are the accumulated findings of the studies? The overall results of a Bayesian meta-analysis confirmed a positive, albeit weak, link between ISL and SLA (r =.13, [.05,.22]). Moderator analyses and a critical review of ISL tasks suggest avenues for future research.

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Publisher: Cambridge University Press
Print publication year: 2023

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References

Aslin, R. N., & Newport, E. L. (2009). What statistical learning can and can’t tell us about language acquisition. In Colombo, J., McCardle, P., & Freund, L. (eds.), Infant Pathways to Language: Methods, Models, and Research Disorders. New York, NY: Lawrence Erlbaum, pp. 1529.Google Scholar
**Brooks, P. J., & Kempe, V. (2013). Individual differences in adult foreign language learning: The mediating effect of metalinguistic awareness. Memory & Cognition, 41(2), 281296. https://doi.org/10.3758/s13421-012-0262-9Google Scholar
**Brooks, P. J., Kwoka, N., & Kempe, V. (2017). Distributional effects and individual differences in L2 morphology learning. Language Learning, 67(1), 171207. https://doi.org/10.1111/lang.12204Google Scholar
Büerkner, P.-C. (2017). brms: An R package for Bayesian Multilevel Models using Stan. Journal of Statistical Software, 80(1), 128. https://doi.org/10.18637/jss.v080.i01Google Scholar
Chan, R. K., & Leung, J. H. (2014). Implicit learning of L2 word stress regularities. Second Language Research, 30(4), 463484. https://doi.org/10.1177%2F0267658313510169Google Scholar
Cheung, M. W.-L. (2014). Modeling dependent effect sizes with three-level meta-analyses: A structural equation modelling approach. Psychological Methods, 19(2), 211229. https://doi.org/10.1037/a0032968CrossRefGoogle Scholar
Christiansen, M. H. (2019). Implicit statistical learning: A tale of two literatures. Topics in Cognitive Science, 11(3), 468481 https://doi.org/10.1111/tops.12332CrossRefGoogle ScholarPubMed
**Chui, Y. L. (2017). The role of language proficiency and statistical learning in on-line comprehension of syntax among bilingual adult readers. Master’s thesis, Australian National University. https://doi.org/10.25911/5D6668CFE6E31Google Scholar
Conway, C. M., Bauernschmidt, A., Huang, S. S., & Pisoni, D. B. (2010). Implicit statistical learning in language processing: Word predictability is the key. Cognition, 114(3), 356371. https://doi.org/10.1016/j.cognition.2009.10.009Google Scholar
Cooper, H. (2017). Research Synthesis and Meta-Analysis: A Step-by-Step Approach, 5th ed. Thousand Oaks, CA: Sage.Google Scholar
*Cox, J. G. (2013). Bilingualism, aging, and instructional conditions in non-primary language development. Doctoral dissertation, Georgetown University. http://hdl.handle.net/10822/707455Google Scholar
**Ćurčić, M. (2018). Explaining Differences in Adult Second Language Learning: The Role of Language Input Characteristics and Learners’ Cognitive Aptitudes. Utrecht, the Netherlands: LOT.Google Scholar
Deeks, J. J., Higgings, J. P. T., & Altman, D. G. (2019). Analysing data and undertaking meta-analyses. In Higgings, J. P. T., Thomas, J., Chandler, J., et al. (eds.), Cochrane Handbook for Systematic Reviews of Interventions, 2nd ed. London, UK: Cochrane, pp. 241284.Google Scholar
**Degani, T., & Goldberg, M. (2019). How individual differences affect learning of translation‐ambiguous vocabulary. Language Learning, 69(3), 600651. http://dx.doi.org/10.1111/lang.12344CrossRefGoogle Scholar
Doughty, C. J., Campbell, S. G., Mislevy, M. A., et al. (2010). Predicting near-native ability: The factor structure and reliability of Hi-LAB. In Prior, M. T., Watanabe, Y., & Lee, S.-K. (eds.), Selected Proceedings of the 2008 Second Language Research Forum. Somerville, MA: Cascadilla Proceedings Project, pp. 1031.Google Scholar
Frost, R., Armstrong, B. C., & Christiansen, M. H. (2019). Statistical learning research: A critical review and possible new directions. Psychological Bulletin, 145(12), 11281153. https://doi.org/10.1037/bul0000210CrossRefGoogle ScholarPubMed
Frost, R., Armstrong, B. C., Siegelman, N., & Christiansen, M. H. (2015). Domain generality versus modality specificity: The paradox of statistical learning. Trends in Cognitive Sciences, 19(3), 117125. https://doi.org/10.1016/j.tics.2014.12.010Google Scholar
**Frost, R., Siegelman, N., Narkiss, A., & Afek, L. (2013). What predicts successful literacy acquisition in a second language? Psychological Science, 24(7), 12431252. https://doi.org/10.1177%2F0956797612472207CrossRefGoogle Scholar
Gelman, A., Carlin, J. B., Stern, H. S., et al. (2013). Bayesian Data Analysis, 3rd ed. Boca Raton, FL: CRC Press.CrossRefGoogle Scholar
Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical Science, 7, 457511. https://doi.org/10.1214/ss/1177011136CrossRefGoogle Scholar
Godfroid, A., & Kim, K. M. (2021). The contribution of implicit-statistical learning aptitude to implicit second-language knowledge. Studies in Second Language Acquisition, 43(s3), 606634. https://doi.org/10.1017/S0272263121000085CrossRefGoogle Scholar
Gómez, R. L. (2002). Variability and detection of invariant structure. Psychological Science, 13(5), 431436. https://doi.org/10.1111%2F1467-9280.00476Google Scholar
**Granena, G. (2013). Individual differences in sequence learning ability and second language acquisition in early childhood and adulthood. Language Learning, 63(4), 665703. https://doi.org/10.1111/lang.12018Google Scholar
**Granena, G. (2019). Cognitive aptitudes and L2 speaking proficiency: Links between LLAMA and Hi-LAB. Studies in Second Language Acquisition, 41(2), 313336. https://doi.org/10.1017/S0272263118000256Google Scholar
Granena, G. (2020). Implicit Language Aptitude. Cambridge, UK: Cambridge University Press.Google Scholar
Granena, G., & Yilmaz, Y. (2019). Corrective feedback and the role of implicit sequence-learning ability in L2 online performance. Language Learning(s1), 69, 127156. https://doi.org/10.1111/lang.12319CrossRefGoogle Scholar
Granena, G., Jackson, D. O., & Yilmaz, Y. (eds.) (2016). Cognitive Individual Differences in L2 Processing and Acquisition. Amsterdam, the Netherlands: John Benjamins.Google Scholar
Hamrick, P. (2015). Declarative and procedural memory abilities as individual differences in incidental language learning. Learning and Individual Differences, 44, 915. https://doi.org/10.1016/j.lindif.2015.10.003Google Scholar
Hamrick, P., & Rebuschat, P. (2012). How implicit is statistical learning? In Williams, J. & Rebuschat, P. (eds.), Statistical Learning and Language Acquisition. Berlin: Mouton De Gruyter, pp. 365382.Google Scholar
Hamrick, P., Lum, J. A., & Ullman, M. T. (2018). Child first language and adult second language are both tied to general-purpose learning systems. Proceedings of the National Academy of Sciences, 115(7), 14871492. https://doi.org/10.1073/pnas.1713975115Google Scholar
Harrer, M., Cuijpers, P., Furukawa, T. A, & Ebert, D. D. (2019). Doing Meta-Analysis in R: A Hands-On Guide. London, UK: Routledge. https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/Google Scholar
Hedges, L. V., & Olkin, I. (1985). Statistical Methods for Meta-Analysis. Orlando, FL: Academic Press.Google Scholar
Hedges, L. V., & Vevea, J. L. (1998). Fixed- and random-effects models in meta-analysis. Psychological Methods, 3(4), 486504. https://doi.org/10.1037/1082-989X.3.4.486Google Scholar
**Kaufman, S. B., DeYoung, C. G., Gray, J. R., et al. (2010). Implicit learning as an ability. Cognition, 116(3), 321340. https://doi.org/10.1016/j.cognition.2010.05.011Google Scholar
Kaushanskaya, M., Blumenfeld, H. K., & Marian, V. (2020). The language experience and proficiency questionnaire (LEAP-Q): Ten years later. Bilingualism: Language and Cognition, 23(5), 16. https://doi.org/10.1017/S1366728919000038Google Scholar
**Kerz, E., & Wiechmann, D. (2019). Effects of statistical learning ability on the second language processing of multiword sequences. In Pastor, G. C. & Mitkov, R. (eds.), Computational and Corpus-Based Phraseology. Berlin, Germany: Springer, pp. 200214.Google Scholar
Kidd, E., & Arciuli, J. (2016). Individual differences in statistical learning predict children’s comprehension of syntax. Child Development, 87(1), 184193.Google Scholar
**Lee, O. S. (2014). Individual differences in first and second language sentence processing: Evidence from statistical learning. Doctoral dissertation, University of Hawaii. http://hdl.handle.net/10125/100442Google Scholar
**Lee, O. S. (2016). Artificial grammar learning ability predicts L2 processing of English number agreement. Language Research, 52(1), 87114. https://doi.org/10.1111/cdev.12461Google Scholar
Lenth, R. V. (2020). Emmeans: Estimated Marginal Means, aka Least-Squares Means. CRAN-R Project. https://CRAN.R-project.org/package=emmeansGoogle Scholar
Li, S. (2015). The associations between language aptitude and second language grammar acquisition: A meta-analytic review of five decades of research. Applied Linguistics, 36(3), 385408. https://doi.org/10.1093/applin/amu054CrossRefGoogle Scholar
Li, S., & DeKeyser, R. (2021). Implicit language aptitude: Conceptualizing the construct, validating the measures, and examining the evidence: Introduction to the special issue. Studies in Second Language Acquisition, 43(3), 473497. https://doi.org/10.1017/S0272263121000024Google Scholar
*Linck, J. A., Hughes, M. M., Campbell, S. G., et al. (2013). Hi‐LAB: A new measure of aptitude for high‐level language proficiency. Language Learning, 63(3), 530–56. https://doi.org/10.1111/lang.12011Google Scholar
Linck, J. A., Osthus, P., Koeth, J. T., & Bunting, M. F. (2014). Working memory and second language comprehension and production: A meta-analysis. Psychonomic Bulletin & Review, 21(4), 861–88. https://doi.org/10.3758/s13423-013-0565-2Google Scholar
Long, M. (2015). Second Language Acquisition and Task-Based Language Teaching. Malden, MA: Wiley-Blackwell.Google Scholar
**McDonough, K., & Trofimovich, P. (2016). The role of statistical learning and working memory in L2 speakers’ pattern learning. The Modern Language Journal, 100(2), 428–44. https://doi.org/10.1111/modl.12331Google Scholar
**McDonough, K., Kielstra, P., Crowther, D., & Smith, G. (2016). Structural priming in L2 speech production: Examining relationships among English L2 speakers’ production, cognitive abilities, and awareness. In Mackey, A. & Marsden, E. (eds.), Advancing Methodology and Practice: The IRIS Repository of Instruments for Research into Second Languages. New York, NY: Routledge, pp. 112131.Google Scholar
Misyak, J. B., Christiansen, M. H., & Tomblin, J. B. (2009). Statistical learning of nonadjacencies predicts on-line processing of long-distance dependencies in natural language. In Taatgen, N. A. & van Rijn, H. (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. Cognitive Science Society, pp. 177182.Google Scholar
**Mor, B., & Prior, A. (2020). Individual differences in L2 frequency effects in different script bilinguals. International Journal of Bilingualism, 24(4), 672–69. https://doi.org/10.1177/136700691987635Google Scholar
Norouzian, R., de Miranda, M. A., & Plonsky, L. (2018). The Bayesian revolution in second language research: An applied approach. Language Learning, 68, 10321075. https://doi.org/10.1111/lang.12310Google Scholar
Onnis, L. (2012). The potential contribution of statistical learning to second language acquisition. In Rebuschat, P. & Williams, J. N. (eds.), Statistical learning and language acquisition. Berlin, Germany: Mouton de Gruyter, pp. 203235.Google Scholar
**Onnis, L., Frank, S. L., Yun, H., & Lou-Magnuson, M. (2016). Statistical learning bias predicts second-language reading efficiency. In Papafragou, A., Grodner, D., & Mirman, D. (eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society. Mahwah, NJ: Cognitive Science Society, pp. 21052110.Google Scholar
Onnis, L., Monaghan, P., Richmond, K., & Chater, N. (2005). Phonology impacts segmentation in online speech processing. Journal of Memory and Language, 53(2), 225–23. https://doi.org/10.1016/j.jml.2005.02.011CrossRefGoogle Scholar
Onnis, L., Waterfall, H. R., & Edelman, S. (2008). Learn locally, act globally: Learning language from variation set cues. Cognition, 109(3), 423–43. https://doi.org/10.1016/j.cognition.2008.10.004CrossRefGoogle ScholarPubMed
Paciorek, A., & Williams, J. (2015). Implicit learning of semantic preferences of verbs. Studies in Second Language Acquisition, 37(2), 359–38. https://doi.org/10.1017/S0272263115000108CrossRefGoogle Scholar
Perruchet, P. (2021). Why is the componential construct of implicit language aptitude so difficult to capture?: A commentary on the special issue. Studies in Second Language Acquisition, 43(3), 677691. https://doi.org/10.1017/S027226312100019XGoogle Scholar
Perruchet, P., & Pacton, S. (2006). Implicit learning and statistical learning: One phenomenon, two approaches. Trends in Cognitive Sciences, 10(5), 233238. https://doi.org/10.1016/j.tics.2006.03.006Google Scholar
Pigott, T. D. (2009). Handling missing data. In Cooper, H., Hedges, L. V., & Valentine, J. C. (eds.), The Handbook of Research Synthesis and Meta-Analysis. New York, NY: Russell Sage Foundation, pp. 399416.Google Scholar
Reber, A. S. (1967). Implicit learning of artificial grammars. Journal of Learning and Verbal Behavior, 6, 855863. https://doi.org/10.1016/S0022-5371(67)80149-XGoogle Scholar
Reber, A. S. (1993). Implicit Learning and Tacit Knowledge: An Essay on the Cognitive Unconscious. Oxford, UK: Oxford University Press.Google Scholar
Rebuschat, P. (ed.) (2015). Implicit and Explicit Learning of Languages. Amsterdam, the Netherlands: John Benjamins.Google Scholar
Rebuschat, P., & Williams, J. N. (2012a). Implicit and explicit knowledge in second language acquisition. Applied Psycholinguistics, 33(4), 829856. https://doi.org/10.1017/S0142716411000580Google Scholar
Rebuschat, P., & Williams, J. N. (eds.) (2012b). Statistical Learning and Language Acquisition. Berlin, Germany: Mouton De Gruyter.Google Scholar
**Robinson, P. (2005). Cognitive abilities, chunk-strength, and frequency effects in implicit artificial grammar and incidental L2 learning: Replications of Reber, Walkenfeld, and Hernstadt (1991) and Knowlton and Squire (1996) and their relevance for SLA. Studies in Second Language Acquisition, 27(2), 235268. https://doi.org/10.1017/S0272263105050126CrossRefGoogle Scholar
Robinson, P. (2010). Implicit artificial grammar and incidental natural second language learning: How comparable are they? Language Learning, 60(s2), 245263. https://doi.org/10.1111/j.1467-9922.2010.00608.xGoogle Scholar
Saffran, J. R., Newport, E. L., & Aslin, R. N. (1996). Word segmentation: The role of distributional cues. Journal of Memory and Language, 35(4), 606621. https://doi.org/10.1006/jmla.1996.0032Google Scholar
Schmidt, R. W. (1990). The role of consciousness in second language learning. Applied Linguistics, 11(2), 129158. https://doi.org/10.1093/applin/11.2.129Google Scholar
Seipel, B. E. (2011). The role of implicit learning in incidental vocabulary acquisition while reading. Doctoral dissertation, University of Minnesota. http://hdl.handle.net/11299/116315.Google Scholar
Shadish, W. R., & Haddock, C. K. (2009). Combining estimates of effect size. In Cooper, H., Hedges, L. V., & Valentine, J. C. (eds.), The Handbook of Research Synthesis and Meta-Analysis. New York, NY: Russell Sage Foundation, pp. 257277.Google Scholar
Siegelman, N., & Frost, R. (2015). Statistical learning as an individual ability: Theoretical perspectives and empirical evidence. Journal of Memory and Language, 81, 105120. https://doi.org/10.1016/j.jml.2015.02.001Google Scholar
Skehan, P. (2016). Foreign language aptitude, acquisitional sequences, and psycholinguistic processes. In Granena, G., Jackson, D. O. & Yilmaz, Y. (eds.), Cognitive Individual Differences in L2 Processing and Acquisition. Amsterdam, the Netherlands: John Benjamins, pp. 1538.Google Scholar
Stan Development Team (2018). Stan: A C++ library for programming and sampling. Retrieved from http://mc-stan.orgGoogle Scholar
**Suzuki, Y., & DeKeyser, R. (2015). Comparing elicited imitation and word monitoring as measures of implicit knowledge. Language Learning, 65(4), 860895. https://doi.org/10.1111/lang.12138Google Scholar
**Suzuki, Y., & DeKeyser, R. (2017). The interface of explicit and implicit knowledge in a second language: Insights from individual differences in cognitive aptitudes. Language Learning, 67(4), 747790. https://doi.org/10.1111/lang.12241Google Scholar
Suzuki, Y, DeKeyser, R., & Huang, Y. (Chapter 15, this volume). Implicit (not explicit) learning aptitude predicts the acquisition of difficult (not easy) structure: A visual-world eye-tracking study. In Wen, Z. E., Skehan, P., & Sparks, R. (eds.), Language Aptitude Theory and Practice (pp. xxx–xxx). Cambridge, UK: Cambridge University Press.Google Scholar
Thomas, M. (2006). Research synthesis and historiography: The case of assessment of second language proficiency. In Norris, J. M. & Ortega, L. (eds.), Synthesizing Research on Language Learning and Teaching. Amsterdam/Philadelphia: John Benjamins, pp. 279298.Google Scholar
Vuong, L. C., Meyer, A. S., & Christiansen, M. H. (2016). Concurrent statistical learning of adjacent and nonadjacent dependencies. Language Learning, 66(1), 830. https://doi.org/10.1111/lang.12137Google Scholar
Weiss, D. J., Schwob, N., & Lebkuecher, A. L. (2020). Bilingualism and statistical learning: Lessons from studies using artificial languages. Bilingualism: Language and Cognition, 23(1), 9297. https://doi.org/10.1017/S1366728919000579Google Scholar
Wen, Z. E., Borges Mota, M., & McNeill, A. (2015). Working Memory in Second Language Acquisition and Processing. Bristol, UK: Multilingual Matters.CrossRefGoogle Scholar
Wen, Z. E., Skehan, P., Biedroń, A., Li, S., & Sparks, R. L. (eds.) (2019). Language Aptitude: Advancing Theory, Testing, Research and Practice. New York, NY: Routledge.Google Scholar
Williams, J. N. (2005). Learning without awareness. Studies in Second Language Acquisition, 27(2), 269304. https://doi.org/10.1017/S0272263105050138Google Scholar
**Yi, W. (2018). Statistical sensitivity, cognitive aptitudes, and processing of collocations. Studies in Second Language Acquisition, 40(4), 831856. https://doi.org/10.1017/S0272263118000141Google Scholar
**Yilmaz, Y., & Granena, G. (2019). Cognitive individual differences as predictors of improvement and awareness under implicit and explicit feedback conditions. The Modern Language Journal, 103(3), 686702. https://doi.org/10.1111/modl.12587Google Scholar

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