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Statistical learning is related to early literacy-related skills

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Abstract

It has been demonstrated that statistical learning, or the ability to use statistical information to learn the structure of one’s environment, plays a role in young children’s acquisition of linguistic knowledge. Although most research on statistical learning has focused on language acquisition processes, such as the segmentation of words from fluent speech and the learning of syntactic structure, some recent studies have explored the extent to which individual differences in statistical learning are related to literacy-relevant knowledge and skills. The present study extends on this literature by investigating the relations between two measures of statistical learning and multiple measures of skills that are critical to the development of literacy—oral language, vocabulary knowledge, and phonological processing—within a single model. Our sample included a total of 553 typically developing children from pre-kindergarten through second grade. Structural equation modeling revealed that statistical learning accounted for a unique portion of the variance in these literacy-related skills. Practical implications for instruction and assessment are discussed.

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Notes

  1. Typical development was indicated by average performance on measures of general intelligence and language. Less than 6 % of the total sample had Peabody Individual Achievement General Information subtest scores that were more than two standard deviations below the mean (M = 92.12; SD = 14.22). Less than 7 % and <2.5 % of the sample attained Expressive and Receptive One Word Picture Vocabulary Test scores that were more than two standard deviations below the mean, respectively (M EOWPVT  = 96.74, SD = 17.50; M ROWPVT  = 100.60; SD = 15.55).

  2. The IQR method is preferred for handling outliers because the median is not affected by outliers in the same way that the mean is if the plus or minus three standard deviations criterion is used.

  3. The Simon task had 21 outliers, CTOPP-E had 17, CTOPP-BW had 10, CTOPP-BNW had 4, CTOPP-MFD had 1, CTOPP-NWR had 13, EOWPVT had 19, ROWPVT had 8, and TOLD-P-SU had 9.

  4. Overall model fit for the unconstrained model remained relatively unchanged even when outliers were removed from the analysis. For this model, χ2 (65) = 108.75; CFI = .96; TLI = .94; RMSEA = .04; SRMR = .04.

  5. CFA modeling for the present sample indicated that a two-factor model (oral language/vocabulary and phonological processing) provided the best fit to the data (Lonigan & Schatschneider, 2013).

References

  • Anderson, R. C., & Freebody, P. (1981). Vocabulary knowledge. In J. Guthrie (Ed.), Comprehension and teaching: Research reviews (pp. 77–117). Newark: International Reading Association.

    Google Scholar 

  • Apfelbaum, K. S., Hazeltine, E., & McMurray, B. (2013). Statistical learning in reading: Variability in irrelevant letters helps children learn phonics skills. Developmental Psychology, 49, 1348–1365.

  • Arciuli, J., & Monaghan, P. (2009). Probabilistic cues to grammatical category in English orthography and their influence during reading. Scientific Studies of Reading, 13, 73–93.

    Article  Google Scholar 

  • Arciuli, J., Monaghan, P., & Seva, N. (2010). Learning to assign lexical stress during reading aloud: Corpus, behavioral, and computational investigations. Journal of Memory and Language, 63(2), 180–196.

    Article  Google Scholar 

  • Arciuli, J., & Simpson, I. (2012). Statistical learning is related to reading ability in children and adults. Cognitive Science, 36, 286–304.

    Article  Google Scholar 

  • Arciuli, J., & von Koss Torkildsen, J. (2012). Advancing our understanding of the link between statistical learning and language acquisition: The need for longitudinal data. Frontiers in Psychology, 3, 1–9.

    Article  Google Scholar 

  • Ashby, J. (2006). Prosody in skilled silent reading: Evidence from eye movements. Journal of Research in Reading, 29, 318–333.

    Article  Google Scholar 

  • Ashby, J., & Clifton, C. (2005). The prosodic property of lexical stress affects eye movements during silent reading. Cognition, 96, B89–B100.

    Article  Google Scholar 

  • Beck, I. L., & McKeown, M. G. (1991). Conditions of vocabulary acquisition. In R. Barr, M. Kamil, P. Mosenthal, & P. D. Pearson (Eds.), Handbook of reading research (Vol. 2, pp. 789–814). New York: Longman.

    Google Scholar 

  • Beck, I. L., McKeown, M. G., & Kucan, L. (2002). Bringing words to life: Robust vocabulary instruction. Solving problems in the teaching of literacy. New York: Guilford Publications.

    Google Scholar 

  • Burgess, S. R., & Lonigan, C. J. (1998). Bidirectional relations of phonological sensitivity and prereading abilities: Evidence from a preschool sample. Jounral of Experimental Child Psychology, 70, 117–141.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Conway, C. M., & Christiansen, M. H. (2005). Modality-constrained statistical learning of tactile, visual, and auditory sequences. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(1), 24.

    Google Scholar 

  • Conway, C. M., & Christiansen, M. H. (2006). Statistical learning within and between modalities pitting abstract against stimulus-specific representations. Psychological Science, 17(10), 905–912.

    Article  Google Scholar 

  • Conway, C. M., Pisoni, D. B., Anaya, E. M., Karpicke, J., & Henning, S. C. (2011). Implicit sequence learning in deaf children with cochlear implants. Developmental Science, 14, 69–82.

    Article  Google Scholar 

  • de Zubicaray, G., Arciuli, J., & McMahon, K. (2013). Putting an “end” to the motor cortex representations of action words. Journal of Cognitive Neuroscience, 25(11), 1957–1974.

    Article  Google Scholar 

  • Deacon, S. H., Conrad, N., & Pacton, S. (2008). A statistical learning perspective on children’s learning about graphotactic and morphological regularities in spelling. Canadian Psychology, 49, 118–124.

    Article  Google Scholar 

  • Ehri, L. C. (1998). Grapheme–phoneme knowledge is essential for learning to read words in English. In J. L. Metsala & L. C. Ehri (Eds.), Word recognition in beginning literacy (pp. 3–40). Mahwah: Lawrence Erlbaum.

    Google Scholar 

  • Erickson, L. C., Kaschak, M. P., Thiessen, E. D., & Berry, C. A. (under review). Individual differences in statistical learning: Conceptual and measurement issues. Manuscript submitted for publication.

  • Evans, J. L., Saffran, J. R., & Robe-Torres, K. (2009). Statistical learning in children with specific language impairment. Journal of Speech, Language, and Hearing Research, 52, 321–335.

    Article  Google Scholar 

  • Fine, A. B., & Jaeger, T. F. (2013). Evidence for implicit learning in syntactic comprehension. Cognitive Science, 37, 578–591.

    Article  Google Scholar 

  • Finn, A., & Hudson Kam, C. I. (2008). The curse of knowledge: First language knowledge impairs adult learners’ use of novel statistics for word segmentation. Cognition, 108, 477–499.

    Article  Google Scholar 

  • Frost, R., Siegelman, N., Narkiss, A., & Afek, L. (2013). What predicts successful literacy acquisition in a second language? Psychological Science, 24, 1243–1252.

    Article  Google Scholar 

  • Gebauer, G. F., & Mackintosh, N. J. (2007). Psychometric intelligence dissociates implicit and explicit learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 34–54.

    Google Scholar 

  • Gombert, J. E. (2003). Implicit and explicit learning to read: Implication as for subtypes of dyslexia. Current Psychology Letters, 10(1), 25–40.

    Google Scholar 

  • Gómez, R., & Gerken, L. (1999). Artificial grammar learning by 1-year-olds leads to specific and abstract knowledge. Cognition, 70, 109–135.

    Article  Google Scholar 

  • Gómez, R. L., & Gerken, L. (2000). Infant artificial language learning and language acquisition. Trends in Cognitive Sciences, 4(5), 178–186.

    Article  Google Scholar 

  • Gough, P. B., & Tunmer, W. E. (1986). Decoding, reading, and reading disability. Remedial and Special Education, 7, 6–10.

    Article  Google Scholar 

  • Hammill, D. D., & Newcomer, P. L. (2008). The test of language development—primary, fourth edition (4th ed.). Austin: PRO-ED.

    Google 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, 662–720.

    Article  Google Scholar 

  • Hoover, W. A., & Gough, P. B. (1990). The simple view of reading. Reading and Writing, 2(2), 127–160.

    Article  Google Scholar 

  • Jones, J. L., & Kaschak, M. P. (2012). Global statistical learning in a visual search task. Journal of Experimental Psychology: Human Perception and Performance, 38, 152–160.

    Google Scholar 

  • Joshi, R. M. (2005). Vocabulary: A critical component of comprehension. Reading and Writing Quarterly, 21(3), 209–219.

    Article  Google Scholar 

  • Just, M. A., & Carpenter, P. C. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 122–149.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Kendeou, P., van den Broek, P., White, M. J., & Lynch, J. S. (2009). Predicting reading comprehension in early elementary school: The independent contributions of oral language and decoding skills. Journal of Educational Psychology, 101, 765–778.

    Article  Google Scholar 

  • Khanna, M. M., & Boland, J. E. (2010). Children’s use of language context in lexical ambiguity resolution. Quarterly Journal of Experimental Psychology, 63, 160–193.

    Article  Google Scholar 

  • Kidd, E. (2012). Implicit statistical learning is directly associated with the acquisition of syntax. Developmental Psychology, 48, 171–184.

    Article  Google Scholar 

  • Kuhl, P. K. (2004). Early language acquisition: Cracking the speech code. Nature Reviews Neuroscience, 5, 831–843.

    Article  Google Scholar 

  • Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato’s problem: The latent semantic analysis theory of the acquisition, induction, and representation of knowledge. Psychological Review, 104, 211–240.

    Article  Google Scholar 

  • Lonigan, C. J., Anthony, J. L., Phillips, B. M., Purpura, D. J., Wilson, S. B., & McQueen, J. D. (2009). The nature of preschool phonological processing abilities and their relations to vocabulary, general cognitive abilities, and print knowledge. Journal of Educational Psychology, 101(2), 345.

    Article  Google Scholar 

  • Lonigan, C. J., & Schatschneider, C. (2013). Explaining reading comprehension of elementary school children: A latent-variable approach to the simple view of reading. In Paper presented at the 20th annual meeting of the society for the scientific study of reading, Hong Kong, China.

  • Lum, J. A., Ullman, M. T., & Conti-Ramsden, G. (2013). Procedural learning is impaired in dyslexia: Evidence from a meta-analysis of serial reaction time studies. Research in Developmental Disabilities, 34(10), 3460–3476.

    Article  Google Scholar 

  • MacDonald, M. C., & Christiansen, M. H. (2002). Reassessing working memory: Comment on Just and Carpenter (1992) and Waters and Caplan (1996). Psychological Review, 109, 35–54.

    Article  Google Scholar 

  • MacDonald, M. C., Pearlmutter, N. J., & Seidenberg, M. S. (1994). The lexical nature of syntactic ambiguity resolution. Psychological Review, 101(4), 676.

    Article  Google Scholar 

  • Martin, N. A., & Browell, R. (2011a). Expressive one-word picture vocabulary task—fourth edition. Austin: PRO-ED.

    Google Scholar 

  • Martin, N. A., & Browell, R. (2011b). Receptive one-word picture vocabulary task—fourth edition. Austin: PRO-ED.

    Google Scholar 

  • Misyak, J. B., & Christiansen, M. H. (2011). Genetic variation and individual differences in language. In I. Arnon & E. V. Clark (Eds.), Experience, variation, and generalization: Learning a first language (trends in language acquisition research) (Vol. 7, pp. 223–238). Amsterdam: John Benjamins.

    Chapter  Google Scholar 

  • Misyak, J. B., & Christiansen, M. H. (2012). Statistical learning and language: An individual differences study. Language Learning, 62, 302–331.

    Article  Google Scholar 

  • Misyak, J. B., Christiansen, M. H., & Tomblin, J. B. (2010a). On-line individual differences in statistical learning predict language processing. Frontiers in psychology, 1, 31.

    Article  Google Scholar 

  • Misyak, J. B., Christiansen, M. H., & Tomblin, J. B. (2010b). Sequential expectations: The role of prediction-based learning in language. Topics in Cognitive Science, 2(1), 138–153.

    Article  Google Scholar 

  • Muthén, L. K., & Muthén, B. O. (1998–2013). Mplus user’s guide (7th ed). Los Angeles, CA: Muthén & Muthén.

  • Nagy, W. E., & Anderson, R. C. (1984). How many words are there in printed school English? Reading Research Quarterly, 19, 304–330.

    Article  Google Scholar 

  • Nash, H., & Snowling, M. (2006). Teaching new words to children with poor existing vocabulary knowledge: A controlled evaluation of the definition and context methods. International Journal of Language and Communication Disorders, 41, 335–354.

    Article  Google Scholar 

  • National Institute of Child Health and Human Development. (2000). Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction (NIH Publication No. 00-4769). Washington, DC: U.S. Government Printing Office.

  • Pacton, S., Perruchet, P., Fayol, M., & Cleeremans, A. (2001). Implicit learning out of the lab: The case of orthographic regularities. Journal of Experimental Psychology: General, 130(3), 401.

    Article  Google Scholar 

  • Perruchet, P., & Pacton, S. (2006). Implicit learning and statistical learning: One phenomenon, two approaches. Trends in Cognitive Sciences, 10, 233–238.

    Article  Google Scholar 

  • Reber, A. (1996). Implicit learning and tacit knowledge: An essay on the cognitive unconscious. Oxford: Oxford University Press.

    Book  Google Scholar 

  • Richgels, D. (2004). Paying attention to language. Reading Research Quarterly, 39, 470–477.

    Article  Google Scholar 

  • Rowland, C. F., & Pine, J. M. (2000). Subject-auxiliary inversion errors and wh-question acquisition: What children do know? Journal of Child Language, 27, 157–181.

    Article  Google Scholar 

  • Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-olds. Science, 274, 1926–1928.

    Article  Google Scholar 

  • Scarborough, H. S. (2001). Connecting early language and literacy to later reading (dis)abilities: Evidence, theory, and practice. In S. B. Neuman & D. K. Dickinson (Eds.), Handbook of early literacy research (pp. 97–110). New York: Guilford Press.

    Google Scholar 

  • Sell, A. J., & Kaschak, M. P. (2009). Does visual speech information affect word segmentation. Memory and Cognition, 37, 889–894.

    Article  Google Scholar 

  • Siegel, L. S. (1993). Phonological processing deficits as the basis of a reading disability. Developmental Review, 13, 246–257.

    Article  Google Scholar 

  • Snowling, M. J. (1980). The development of grapheme–phoneme correspondence in normal and dyslexic readers. Journal of Experimental Child Psychology, 29, 294–305.

    Article  Google Scholar 

  • Stanovich, K. E. (1988). Explaining the differences between the dyslexic and the garden-variety poor reader: The phonological-core variable-difference model. Journal of Learning Disabilities, 21, 590–612.

    Article  Google Scholar 

  • Stokes, S. F. (2010). Neighborhood density and word frequency predict vocabulary size in toddlers. Journal of Speech, Language and Hearing Research, 53(3), 670.

    Article  Google Scholar 

  • Stoodley, C. J., Ray, N. J., Jack, A., & Stein, J. F. (2008). Implicit learning in control, dyslexic, and garden-variety poor readers. Annals of the New York Academy of Sciences, 1145(1), 173–183.

    Article  Google Scholar 

  • Teinonen, T., Fellman, V., Näätänen, R., Alku, P., & Huotilainen, M. (2009). Statistical language learning in neonates revealed by event-related brain potentials. Biomedical Central Neuroscience, 10, 21–28.

    Google Scholar 

  • Thiessen, E. D., Kronstein, A. T., & Hufnagle, D. G. (2013). The extraction and integration framework: A two-process account of statistical learning. Psychological Bulletin, 139, 792–814.

    Article  Google Scholar 

  • Thiessen, E. D., & Saffran, J. R. (2003). When cues collide: Use of stress and statistical cues to word boundaries in 7- to 9-month old infants. Developmental Psychology, 39, 706–716.

    Article  Google Scholar 

  • Trueswell, J. C., Sekerina, I., Hill, N. M., & Logrip, M. L. (1999). The kindergarten-path effect: Studying online sentence processing in young children. Cognition, 73, 89–134.

    Article  Google Scholar 

  • Vicari, S., Finzi, A., Menghini, D., Marotta, L., Baldi, S., & Petrosini, L. (2005). Do children with developmental dyslexia have an implicit learning deficit? Journal of Neurology, Neurosurgery and Psychiatry, 76(10), 1392–1397.

    Article  Google Scholar 

  • Wagner, R. K., & Torgesen, J. K. (1987). The nature of phonological processing and its causal role in the acquisition of reading skills. Psychological Bulletin, 101, 192–212.

    Article  Google Scholar 

  • Wagner, R. K., Torgesen, J. K., & Rashotte, C. A. (1994). Development of reading-related phonological processing abilities: New evidence of bidirectional causality from a latent variable longitudinal study. Developmental Psychology, 30, 73–87.

    Article  Google Scholar 

  • Wagner, R. K., Torgesen, J. K., Rashotte, C. A., & Pearson, N. A. (1999). Comprehensive test of phonological processing. Austin: PRO-ED.

    Google Scholar 

  • Werker, J. F., Yeung, H. H., & Yoshida, K. A. (2012). How do infants become experts at native-speech perception? Current Directions in Psychological Science, 21(4), 221–226.

    Article  Google Scholar 

  • Wilkinson, G. S., & Robertson, G. J. (2006). Wide range achievement test—fourth edition: Professional manual. Lutz: Psychological Assessment Resources.

    Google Scholar 

  • Yu, C. (2008). A statistical associative account of vocabulary growth in early word reading. Language Learning and Development, 4, 32–62.

    Article  Google Scholar 

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Acknowledgments

This research was supported by a Grant from the Institute of Education Sciences (R305F100027), and preparation of this work was supported by a Predoctoral Interdisciplinary Research Training Grant from the Institute of Education Sciences (R305B090021).

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  1. Department of Psychology, Florida Center for Reading Research, Florida State University, 1107 W. Call St., Tallahassee, FL, 32306-4301, USA

    Mercedes Spencer, Michael P. Kaschak, John L. Jones & Christopher J. Lonigan

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  1. Mercedes Spencer
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Correspondence to Mercedes Spencer or Michael P. Kaschak.

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Spencer, M., Kaschak, M.P., Jones, J.L. et al. Statistical learning is related to early literacy-related skills. Read Writ 28, 467–490 (2015). https://doi.org/10.1007/s11145-014-9533-0

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