Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-05T03:03:45.023Z Has data issue: false hasContentIssue false

INDIVIDUAL DIFFERENCES IN L2 LITERACY ACQUISITION

PREDICTING READING SKILL FROM SENSITIVITY TO REGULARITIES BETWEEN ORTHOGRAPHY, PHONOLOGY, AND SEMANTICS

Published online by Cambridge University Press:  16 September 2021

Henry Brice
Affiliation:
The Hebrew University of Jerusalem
Noam Siegelman
Affiliation:
Haskins Laboratories
Mark van den Bunt
Affiliation:
Haskins Laboratories
Stephen J. Frost
Affiliation:
Haskins Laboratories
Jay G. Rueckl
Affiliation:
Haskins Laboratories and University of Connecticut
Kenneth R. Pugh
Affiliation:
Haskins Laboratories, University of Connecticut, and Yale University
Ram Frost
Affiliation:
The Hebrew University of Jerusalem, Haskins Laboratories, and University of Connecticut

Abstract

Statistical learning (SL) approaches to reading maintain that proficient reading requires assimilation of rich statistical regularities in the writing system. Reading skills in developing first-language readers are predicted by individual differences in sensitivity to regularities in mappings from orthography to phonology (O-P) and semantics (O-S), where good readers rely more on O-P consistency, and less on O-S associations. However, how these regularities are leveraged by second-language (L2) learners remains an open question. We utilize an individual-differences approach, measuring L2 English learners’ sensitivity to O-P, O-S, and frequency during word-naming, across two years of immersion. We show that reliance on O-P is leveraged by better readers, while reliance on O-S is slower to develop, characterizing less proficient readers. All factors explain substantial individual variance in L2 reading skills. These findings show how SL plays a key role in L2 reading development through its role in assimilating sublexical regularities between print and speech.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This study was supported by the ERC advanced grant awarded to Ram Frost (project 692502-L2STAT), the Israel Science Foundation (grant 217/14 awarded to Ram Frost), and by the National Institute of Child Health and Human Development at the National Institutes of Health (RO1 HD 067364 awarded to Kenneth Pugh and Ram Frost, and PO1 HD 01994 awarded to Jay Rueckl).

The experiment in this article earned Open Materials and Open Data badges for transparent practices. The materials and data are available at https://osf.io/6wgup/ and https://www.iris-database.org/iris/app/home/detail?id=york:939455

References

REFERENCES

Arciuli, J., & Simpson, I. C. (2012). Statistical learning is related to reading ability in children and adults. Cognitive Science, 36, 286304. https://doi.org/10.1111/j.1551-6709.2011.01200.x CrossRefGoogle ScholarPubMed
Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2014). Keep it maximal. Journal of Memory and Language, 68, 143. https://doi.org/10.1016/j.jml.2012.11.001.Random Google Scholar
Bates, D., Mächler, M., Bolker, B. M., & Walker, S. C. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67. 148 https://doi.org/10.18637/jss.v067.i01 CrossRefGoogle Scholar
Bishop, D. V. M. (2006). What causes specific language impairment in children? Current Directions in Psychological Science, 15, 217221. https://doi.org/10.1111/j.1467-8721.2006.00439.x CrossRefGoogle ScholarPubMed
Bogaerts, L., Siegelman, N., & Frost, R. (2020). Statistical learning and language impairments: Toward more precise theoretical accounts. Perspectives on Psychological Science, 16, 319337. https://doi.org/10.1177/1745691620953082 CrossRefGoogle ScholarPubMed
Brice, H., Frost, S. J., Bick, A. S., Molfese, P. J., Rueckl, J. G., Pugh, K. R., & Frost, R. (2021). Tracking second language immersion across time: Evidence from a bi-directional longitudinal cross-linguistic fMRI study. Neuropsychologia, 157, 107796. https://doi.org/10.1016/j.neuropsychologia.2021.107796.CrossRefGoogle Scholar
Brice, H., Mencl, W. E., Frost, S. J., Bick, A. S., Rueckl, J. G., Pugh, K. R., & Frost, R. (2019). Neurobiological signatures of L2 proficiency: Evidence from a bi-directional cross-linguistic study. Journal of Neurolinguistics, 50, 716. https://doi.org/10.1016/j.jneuroling.2018.02.004 CrossRefGoogle ScholarPubMed
Brysbaert, M., & New, B. (2009). Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior Research Methods, 41, 977990. https://doi.org/10.3758/BRM.41.4.977 CrossRefGoogle ScholarPubMed
Chang, Y. N., Monaghan, P., & Welbourne, S. (2019). A computational model of reading across development: Effects of literacy onset on language processing. Journal of Memory and Language, 108, 104025. https://doi.org/10.1016/j.jml.2019.05.003 CrossRefGoogle Scholar
Chateau, D., & Jared, D. (2000). Exposure to print and word recognition processes. Memory and Cognition, 28, 143153. https://doi.org/10.3758/BF03211582 CrossRefGoogle ScholarPubMed
Cortese, M. J., & Fugett, A. (2004). Imageability rating for 3000 monosyllabic words. Behavior Research Methods, 36, 384387.Google Scholar
Cortese, M. J., & Simpson, G. B. (2000). Regularity effects in word naming: What are they? Memory and Cognition, 28, 12691276. https://doi.org/10.3758/BF03211827 CrossRefGoogle Scholar
Duff, F. J., & Hulme, C. (2012). The role of children’s phonological and semantic knowledge in learning to read words. Scientific Studies of Reading, 16, 504525. https://doi.org/10.1080/10888438.2011.598199 CrossRefGoogle Scholar
Ehri, L. C. (2005). Scientific studies of reading learning to read words: Theory, findings, and issues learning to read words. Scientific Studies of Reading, 9, 167188. https://doi.org/10.1207/s1532799xssr0902 CrossRefGoogle Scholar
Elleman, A. M., Steacy, L. M., & Compton, D. L. (2019). The role of statistical learning in word reading and spelling development: More questions than answers. Scientific Studies of Reading, 23, 17. https://doi.org/10.1080/10888438.2018.1549045 CrossRefGoogle ScholarPubMed
Erickson, L. C., & Thiessen, E. D. (2015). Statistical learning of language: Theory, validity, and predictions of a statistical learning account of language acquisition. Developmental Review, 37, 66108. https://doi.org/10.1016/j.dr.2015.05.002 CrossRefGoogle Scholar
Fine, A. B., & Jaeger, T. F. (2013). Evidence for implicit learning in syntactic comprehension. Cognitive Science, 37, 578591. https://doi.org/10.1111/cogs.12022 CrossRefGoogle ScholarPubMed
Frost, R. (2012). Towards a universal model of reading. Behavioral and Brain Sciences, 35, 263279. https://doi.org/10.1017/S0140525X11001841 CrossRefGoogle ScholarPubMed
Frost, R., Armstrong, B. C., & Christiansen, M. H. (2019). Statistical learning research: A critical review and possible new directions. Psychological Bulletin, 145, 11281153. https://doi.org/10.1037/bul0000210 CrossRefGoogle ScholarPubMed
Frost, R., Siegelman, N., Narkiss, A., & Afek, L. (2013). What predicts successful literacy acquisition in a second language? Psychological Science, 24, 12431252. https://doi.org/10.1177/0956797612472207 CrossRefGoogle Scholar
Grainger, J. (1990). Word frequency and neighborhood frequency effects in lexical decision and naming. Journal of Memory and Language, 29, 228244. https://doi.org/10.1016/0749-596X(90)90074-A CrossRefGoogle Scholar
Harm, M. W., & Seidenberg, M. S. (2004). Computing the meanings of words in reading: Cooperative division of labor between visual and phonological processes. Psychological Review, 111, 662720. https://doi.org/10.1037/0033-295X.111.3.662 CrossRefGoogle ScholarPubMed
Havron, N., & Arnon, I. (2017). Minding the gaps: Literacy enhances lexical segmentation in children learning to read. Journal of Child Language, 44, 15161538. https://doi.org/10.1017/S0305000916000623 CrossRefGoogle ScholarPubMed
Havron, N., Raviv, L., & Arnon, I. (2018). Literate and preliterate children show different learning patterns in an artificial language learning task. Journal of Cultural Cognitive Science, 2, 2133. https://doi.org/10.1007/s41809-018-0015-9 CrossRefGoogle Scholar
Hudson, P. T. W., & Bergman, M. W. (1985). Lexical knowledge in word recognition: Word length and word frequency in naming and lexical decision tasks. Journal of Memory and Language, 24, 4658. https://doi.org/10.1016/0749-596X(85)90015-4 CrossRefGoogle Scholar
Jaeger, T. F. (2008). Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models. Journal of Memory and Language, 59, 434446. https://doi.org/10.1016/j.jml.2007.11.007 CrossRefGoogle ScholarPubMed
Jared, D. (2002). Spelling-sound consistency and regularity effects in word naming. Journal of Memory and Language, 46, 723750. https://doi.org/10.1006/jmla.2001.2827 CrossRefGoogle Scholar
Jared, D., McRae, K., & Seidenberg, M. S. (1990). The basis of consistency effects in word naming. Journal of Memory, 29, 687715.Google Scholar
Kuperman, V., & Van Dyke, J. A. (2011). Effects of individual differences in verbal skills on eye-movement patterns during sentence reading. Journal of Memory and Language, 65, 4273. https://doi.org/10.1016/j.jml.2011.03.002 CrossRefGoogle ScholarPubMed
Laing, E., & Hulme, C. (1999). Phonological and semantic processes influence beginning readers’ ability to learn to read words. Journal of Experimental Child Psychology, 73, 183207. https://doi.org/10.1006/jecp.1999.2500 CrossRefGoogle ScholarPubMed
Lammertink, I., Boersma, P., Wijnen, F., & Rispens, J. (2020). Statistical learning in the visuomotor domain and its relation to grammatical proficiency in children with and without developmental language disorder: A conceptual replication and meta-analysis. Language Learning and Development, 16, 426450. https://doi.org/10.1080/15475441.2020.1820340 CrossRefGoogle Scholar
Long, J. A. (2019). Interactions: Comprehensive, user-friendly toolkit for probing interactions (R package version 1.1.0). https://cran.r-project.org/ package=interactionsGoogle Scholar
McClelland, J. L., & Patterson, K. (2002). Rules or connections in past-tense inflections: What does the evidence rule out? Trends in Cognitive Sciences, 6, 465472. https://doi.org/10.1016/S1364-6613(02)01993-9 CrossRefGoogle ScholarPubMed
McRae, K., Jared, D., & Seidenberg, M. S. (1990). On the roles of frequency and lexical access in word naming. Journal of Memory and Language, 29, 4365. https://doi.org/10.1016/0749-596X(90)90009-O CrossRefGoogle Scholar
Monaghan, P., Chang, Y. N., Welbourne, S., & Brysbaert, M. (2017). Exploring the relations between word frequency, language exposure, and bilingualism in a computational model of reading. Journal of Memory and Language, 93, 121. https://doi.org/10.1016/j.jml.2016.08.003 CrossRefGoogle Scholar
Monaghan, P., Shillcock, R. C., Christiansen, M. H., & Kirby, S. (2014). How arbitrary is language? Philosophical Transactions of the Royal Society B: Biological Sciences, 369, 20130299. https://doi.org/10.1098/rstb.2013.0299 CrossRefGoogle ScholarPubMed
Paivio, A., Yuille, J. C., & Madigan, S. A. (1968). Concreteness, imagery, and meaningfulness values for 925 nouns. Journal of Experimental Psychology, 76, 125. https://doi.org/10.1037/h0025327 CrossRefGoogle ScholarPubMed
Ramus, F. (2003). Developmental dyslexia: Specific phonological deficit or general sensorimotor dysfunction? Current Opinion in Neurobiology, 13, 212218. https://doi.org/10.1016/S0959-4388(03)00035-7 CrossRefGoogle ScholarPubMed
Ramus, F., & Ahissar, M. (2012). Developmental dyslexia: The difficulties of interpreting poor performance, and the importance of normal performance. Cognitive Neuropsychology, 29, 104122. https://doi.org/10.1080/02643294.2012.677420 CrossRefGoogle ScholarPubMed
Rueckl, J. G. (2010). Connectionism and the role of morphology in visual word recognition. Mental Lexicon, 5, 371400. https://doi.org/10.1075/ml.5.3.07rue CrossRefGoogle ScholarPubMed
Rumelhart, D. E., & McClelland, J. L. (1986). On learning the past tenses of English verbs. In McClelland, J. L. & Rumelhart, D. E. (Eds.), Parallel Distributed Processing: Explorations in the Microstructure of Cognition : Vol. 2. MIT Press.CrossRefGoogle Scholar
Sawi, O. M., & Rueckl, J. G. (2019). Reading and the neurocognitive bases of statistical learning. Scientific Studies of Reading, 23, 823. https://doi.org/10.1080/10888438.2018.1457681 CrossRefGoogle Scholar
Schmalz, X., Moll, K., Mulatti, C., & Schulte-Körne, G. (2019). Is statistical learning ability related to reading ability, and if so, why? Scientific Studies of Reading, 23, 6476. https://doi.org/10.1080/10888438.2018.1482304 CrossRefGoogle Scholar
Seidenberg, M. S., & Gonnerman, L. M. (2000). Explaining derivational morphology as the convergence of codes. Trends in Cognitive Sciences, 4, 353361. https://doi.org/10.1016/S1364-6613(00)01515-1 CrossRefGoogle ScholarPubMed
Seidenberg, M. S., & McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review, 96, 523568.CrossRefGoogle ScholarPubMed
Share, D. L. (1999). Phonological recoding and orthographic learning: A direct test of the self-teaching hypothesis. Journal of Experimental Child Psychology, 72, 95129. https://doi.org/10.1006/jecp.1998.2481 CrossRefGoogle ScholarPubMed
Siegel, L. S. (1993). Phonological processing deficits as the basis of a reading disability. Developmental Review, 13246257. https://doi.org/10.1006/drev.1993.1011 CrossRefGoogle Scholar
Siegelman, N., Kearns, D. M., & Rueckl, J. G. (2020). Using information-theoretic measures to characterize the structure of the writing system: The case of orthographic-phonological regularities in English. Behavior Research Methods, 52, 12921312. https://doi.org/10.3758/s13428-019-01317-y CrossRefGoogle ScholarPubMed
Siegelman, N., Rueckl, J. G., Steacy, L. M., Frost, S. J., van den Bunt, M., Zevin, J. D., … Morris, R. D. (2020). Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills. Journal of Memory and Language, 114, 104145. https://doi.org/10.1016/j.jml.2020.104145 CrossRefGoogle ScholarPubMed
Steacy, L. M., Compton, D. L., Petscher, Y., Elliott, J. D., Smith, K., Rueckl, J. G., … Pugh, K. R. (2019). Development and prediction of context-dependent vowel pronunciation in elementary readers. Scientific Studies of Reading, 23, 4963. https://doi.org/10.1080/10888438.2018.1466303 CrossRefGoogle ScholarPubMed
Strain, E., & Herdman, C. M. (1999). Imageability effects in word naming: An individual differences analysis. Canadian Journal of Experimental Psychology, 53, 347359. https://doi.org/10.1037/h0087322 CrossRefGoogle ScholarPubMed
Strain, E., Patterson, K., & Seidenberg, M. S. (1995). Semantic effects in single-word naming. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 11401154.Google ScholarPubMed
Torgesen, J. K., Wagner, R. K., & Rashotte, C. (2012). Test of Word Reading Efficiency: (TOWRE-2). Pro-Ed.Google Scholar
Treiman, R., & Kessler, B. (2006). Spelling as statistical learning: Using consonantal context to spell vowels. Journal of Educational Psychology, 98, 642652. https://doi.org/10.1037/0022-0663.98.3.642 CrossRefGoogle Scholar
Treiman, R., Mullennix, J., Bijeljac-Babic, R., & Richmond-Welty, E. D. (1995). The special role of rimes in the description, use, and acquisition of English orthography. Journal of Experimental Psychology: General, 124, 107136. https://doi.org/10.1037/0096-3445.124.2.107 CrossRefGoogle ScholarPubMed
Waters, G. S., & Seidenberg, M. S. (1985). Spelling-sound effects in reading: Time-course and decision criteria. Memory & Cognition, 13, 557572. https://doi.org/10.3758/BF03198326 CrossRefGoogle ScholarPubMed
Wiederholt, J. L., & Bryant, B. R. (2001). Gray Oral Reading Test-Fouth Edition (GORT-4). Pro-Ed.Google Scholar
Woollams, A. M., Lambon Ralph, M. A., Madrid, G., & Patterson, K. E. (2016). Do you read how I read? Systematic individual differences in semantic reliance amongst normal readers. Frontiers in Psychology, 7, 116. https://doi.org/10.3389/fpsyg.2016.01757 CrossRefGoogle Scholar
Yap, M. J., Balota, D. A., Sibley, D. E., & Ratcliff, R. (2012). Individual differences in visual word recognition: Insights from the English Lexicon Project. Journal of Experimental Psychology: Human Perception and Performance, 38, 5379. https://doi.org/10.1037/a0024177 Google ScholarPubMed
Zeno, S., Ivens, S. H., Millard, R. T., & Duvvuri, R. (1995). The Educator’s Word Frequency Guide. Touchstone Applied Science Associates.Google Scholar
Ziegler, J. C., & Goswami, U. (2006). Becoming literate in different languages: Similar problems, different solutions. Developmental Science, 9, 429436. https://doi.org/10.1111/j.1467-7687.2006.00509.x CrossRefGoogle ScholarPubMed