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Knowledge of Statistics or Statistical Learning? Readers Prioritize the Statistics of their Native Language Over the Learning of Local Regularities Cover

Knowledge of Statistics or Statistical Learning? Readers Prioritize the Statistics of their Native Language Over the Learning of Local Regularities

Open Access
|Feb 2022

References

  1. 1Andrews, S. (1992). Frequency and neighborhood effects on lexical access: Lexical similarity or orthographic redundancy? Journal of Experimental Psychology: Learning, Memory and Cognition, 18(2), 234254. DOI: 10.1037/0278-7393.18.2.234
  2. 2Arciuli, J. (2017). The multi-component nature of statistical learning. Philosophical Transactions of the Royal Society B: Biological Sciences, 372, 20160058. DOI: 10.1098/rstb.2016.0058
  3. 3Arciuli, J. (2018). Reading as statistical learning. Language, Speech, and Hearing Services in Schools, 49(3S), 634643. DOI: 10.1044/2018_LSHSS-STLT1-17-0135
  4. 4Arciuli, J., & Simpson, I. C. (2012). Statistical learning is related to reading ability in children and adults. Cognitive Science, 36(2), 286304. DOI: 10.1111/j.1551-6709.2011.01200.x
  5. 5Aslin, R. N. (2017). Statistical learning: A powerful mechanism that operates by mere exposure. Wiley Interdisciplinary Reviews: Cognitive Science, 8(1–2), e1373. DOI: 10.1002/wcs.1373
  6. 6Aslin, R. N., & Newport, E. L. (2012). Statistical learning: from acquiring specific items to forming general rules. Current Directions in Psychological Science, 21(3), 170176. DOI: 10.1177/0963721412436806
  7. 7Baayen, R. H., Milin, P., Durdevic, D. F., Hendrix, P., & Marelli, M. (2011). An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. Psychological Review, 118(3), 438481. DOI: 10.1037/a0023851
  8. 8Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 148. DOI: 10.18637/jss.v067.i01
  9. 9Biederman, G. B. (1966). Supplementary report: the recognition of tachistoscopically presented five-letter words as a function of digram frequency. Journal of Verbal Learning and Verbal Behaviour, 5(2), 208209. DOI: 10.1016/S0022-5371(66)80020-8
  10. 10Brady, T. F., & Oliva, A. (2008). Statistical learning using real-world scenes: Extracting categorical regularities without conscious intent. Psychological Science, 19(7), 678685. DOI: 10.1111/j.1467-9280.2008.02142.x
  11. 11Bulf, H., Johnson, S. P., & Valenza, E. (2011). Visual statistical learning in the newborn infant. Cognition, 121, 127132. DOI: 10.1016/j.cognition.2011.06.010
  12. 12Cassar, M., & Treiman, R. (1997). The beginnings of orthographic knowledge: Children’s knowledge of double letters in words. Journal of Educational Psychology, 89(4), 631644. DOI: 10.1037/0022-0663.89.4.631
  13. 13Chetail, F. (2015). Reconsidering the role of orthographic redundancy in visual word recognition. Frontiers in Psychological Science, 6, 645. DOI: 10.3389/fpsyg.2015.00645
  14. 14Chetail, F. (2017). What do we do with what we learn? Statistical learning of orthographic regularities impacts written word processing. Cognition, 163, 103120. DOI: 10.1016/j.cognition.2017.02.015
  15. 15Christiansen, M., & Chater, N. (2016). The Now-or-Never bottleneck: A fundamental constraint on language. Behavioral and Brain Sciences, 39, E62. DOI: 10.1017/S0140525X1500031X
  16. 16Christiansen, M. H. (2019). Implicit Statistical Learning: A Tale of Two Literatures. Topics in Cognitive Science, 11, 468481. DOI: 10.1111/tops.12332
  17. 17Crepaldi, D., Amenta, S., Pawel, M., Keuleers, E., & Brysbaert, M. (2015, September). SUBTLEX-IT. Subtitle-based word frequency estimates for Italian. In Proceedings of the Annual Meeting of the Italian Association for Experimental Psychology (pp. 1012).
  18. 18Crepaldi, D., Rastle, K., & Davis, C. J. (2010). Morphemes in their place: Evidence for position specific identification of suffixes. Memory and Cognition, 38(3), 312321. DOI: 10.3758/MC.38.3.312
  19. 19Crepaldi, D., Rastle, K., Davis, C. J., & Lupker, S. (2013). Seeing stems everywhere: Position-independent identification of stem morphemes. Journal of Experimental Psychology: Human Perception and Performance, 39(2), 510525. DOI: 10.1037/a0029713
  20. 20Dale, R., & Christiansen, M. H. (2004). Active and passive statistical learning: Exploring the role of feedback in artificial grammar learning and language. In K. Forbus, D. Gentner, & T. Regier (Eds.), Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 262267). Mahwah, NJ: Erlbaum.
  21. 21Dehaene, S., Cohen, L., Sigman, M., & Vinckier, F. (2005). The neural code for written words: A proposal. Trends in Cognitive Sciences, 9, 335341. DOI: 10.1016/j.tics.2005.05.004
  22. 22Dell, G. S., & Chang, F. (2014). The P-chain: Relating sentence production and its disorders to comprehension and acquisition. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1634), 20120394. DOI: 10.1098/rstb.2012.0394
  23. 23Fiser, J., & Aslin, R. N. (2001). Unsupervised statistical learning of higher order spatial structures from visual scenes. Psychological Science, 12(6), 499504. DOI: 10.1111/1467-9280.00392
  24. 24Fiser, J., & Aslin, R. N. (2002). Statistical learning of higher order temporal structure from visual shape sequences. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28(3), 458467. DOI: 10.1037//0278-7393.28.3.458
  25. 25Fiser, J., & Aslin, R. N. (2005). Encoding multielement scenes: statistical learning of visual feature hierarchies. Journal of Experimental Psychology: General, 134(4), 521537. DOI: 10.1037/0096-3445.134.4.521
  26. 26Frost, R. (2012). Towards a universal model of reading. Behavioral and Brain Sciences, 35(5), 263279. DOI: 10.1017/S0140525X11001841
  27. 27Frost, R., Armstrong, B. C., & Christiansen, M. H. (2020). Statistical Learning Research: A Critical Review and Possible New Directions. Psychological Bulletin, 145(12), 11281153. DOI: 10.1037/bul0000210
  28. 28Frost, R., Kugler, T., Deutsch, A. & Forster, K. I. (2005). Orthographic structure versus morphological structure: Principles of lexical organization in a given language. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(6), 12931326. DOI: 10.1037/0278-7393.31.6.1293
  29. 29Frost, R., Siegelman, N., Narkiss, A., & Afek, L. (2013). What predicts successful literacy acquisition in a second language? Psychological Science, 24(7), 12431252. DOI: 10.1177/0956797612472207
  30. 30Gagl, B., Sassenhagen, J., Haan, S., Gregorova, K., Richlan, F., & Fiebach, C. J. (2020). An orthographic prediction error as the basis for efficient visual word recognition. NeuroImage, 116727. DOI: 10.1016/j.neuroimage.2020.116727
  31. 31Gernsbacher, M. A. (1984). Resolving 20 years of inconsistent interactions between lexical familiarity and orthography, concreteness, and polysemy. Journal of Experimental Psychology: General, 113(2), 256281. DOI: 10.1037/0096-3445.113.2.256
  32. 32Grainger, J., Dufau, S., Montant, M., Ziegler, J. C., & Fagot, J. (2012). Orthographic processing in Baboons (Papio papio). Science, 336, 245248. DOI: 10.1126/science.1218152
  33. 33Grainger, J., Dufau, S., & Ziegler, J. C. (2016). A vision of reading. Trends in Cognitive Science, 20(3), 171179. DOI: 10.1016/j.tics.2015.12.008
  34. 34Grainger, J., & Ziegler, J. C. (2011) A dual-route approach to orthographic processing. Frontiers in Language Sciences, 2, 54. DOI: 10.3389/fpsyg.2011.00054
  35. 35Hedenius, M., Ullman, M. T., Alm, P., Jennische, M., & Persson, J. (2013). Enhanced recognition memory after incidental encoding in children with developmental dyslexia. PloS one, 8(5), e63998. DOI: 10.1371/journal.pone.0063998
  36. 36Ise, E., Arnoldi, C. J., Bartling, J., & Schulte-Körne, G. (2012). Implicit learning in children with spelling disability: Evidence from artificial grammar learning. Journal of Neural Transmission, 119(9), 9991010. DOI: 10.1007/s00702-012-0830-y
  37. 37Janacsek, K., Shattuck, K. F., Tagarelli, K. M., Lum, J. A., Turkeltaub, P. E., & Ullman, M. T. (2020). Sequence learning in the human brain: a functional neuroanatomical meta-analysis of serial reaction time studies. NeuroImage, 207, 116387. DOI: 10.1016/j.neuroimage.2019.116387
  38. 38Jared, D. (2002). Spelling–sound consistency and regularity effects in word naming. Journal of Memory and Language, 46(4), 723750. DOI: 10.1006/jmla.2001.2827
  39. 39Jared, D., McRae, K., & Seidenberg, M. S. (1990). The basis of consistency effects in word naming. Journal of Memory and Language, 29(6), 687715. DOI: 10.1016/0749-596X(90)90044-Z
  40. 40Keuleers, E., Lacey, P., Rastle, K., & Brysbaert, M. (2012). The British Lexicon Project: lexical decision data for 28,730 monosyllabic and disyllabic English words. Behavioral Research Methods, 44, 287304. DOI: 10.3758/s13428-011-0118-4
  41. 41Kühnel, A., Gaschler, R., Frensch, P. A., Cohen, A., & Wenke, D. (2019). Lack of automatic vocal response learning while reading aloud – An implicit sequence learning study. Experimental Psychology, 66(4), 266280. DOI: 10.1027/1618-3169/a000451
  42. 42Lelonkiewicz, J. R., Ktori, M., & Crepaldi, D. (2020). Morphemes as letter chunks: Discovering affixes through visual regularities. Journal of Memory and Language, 115, 104152. DOI: 10.1016/j.jml.2020.104152
  43. 43Lukács, Á., Kemény, F., Lum, J. A., & Ullman, M. T. (2017). Learning and overnight retention in declarative memory in specific language impairment. PloS one, 12(1), e0169474. DOI: 10.1371/journal.pone.0169474
  44. 44Manelis, L. (1974). The effect of meaningfulness in tachistoscopic word perception. Perception & Psychophysics, 16, 182192. DOI: 10.3758/BF03203272
  45. 45Marelli, M., Amenta, S., & Crepaldi, D. (2015). Semantic transparency in free stems: The effect of orthography-semantics consistency on word recognition. Quarterly Journal of Experimental Psychology, 68(8), 15711583. DOI: 10.1080/17470218.2014.959709
  46. 46Massaro, D. W., Jastrzembski, J. E., & Lucas, P. A. (1981). Frequency, orthographic regularity, and lexical status in letter and word perception. Psychology of Learning and Motivation, 15, 163200. DOI: 10.1016/S0079-7421(08)60175-9
  47. 47Mathôt, S., Schreij, D., & Theeuwes, J. (2012). OpenSesame: An open-source, graphical experiment builder for the social sciences. Behavior Research Methods, 44(2), 314324. DOI: 10.3758/s13428-011-0168-7
  48. 48Maurer, U., Blau, V. C., Yoncheva, Y. N., & McCandliss, B. D. (2010). Development of visual expertise for reading: rapid emergence of visual familiarity for an artificial script. Developmental Neuropsychology, 35(4), 404422. DOI: 10.1080/87565641.2010.480916
  49. 49McClelland, J. L., & Johnston, J. C. (1977). The role of familiar units in perception of words and nonwords. Perception & Psychophysics, 22, 249261. DOI: 10.3758/BF03199687
  50. 50Newport, E. L. (2016). Statistical language learning: Computational, maturational, and linguistic constraints. Language and Cognition, 8(3), 447461. DOI: 10.1017/langcog.2016.20
  51. 51Nigro, L., Jiménez-Fernández, G., Simpson, I. C., & Defior, S. (2015). Implicit learning of written regularities and its relation to literacy acquisition in a shallow orthography. Journal of Psycholinguistic Research, 44(5), 571585. DOI: 10.1007/s10936-014-9303-9
  52. 52Nigro, L., Jiménez-Fernández, G., Simpson, I. C., & Defior, S. (2016). Implicit learning of non-linguistic and linguistic regularities in children with dyslexia. Annals of Dyslexia, 66(2), 202218. DOI: 10.1007/s11881-015-0116-9
  53. 53Nissen, M. J., & Bullemer, P. (1987). Attentional requirements of learning: Evidence from performance measures. Cognitive Psychology, 19(1), 132. DOI: 10.1016/0010-0285(87)90002-8
  54. 54Orbán, G., Fiser, J., Aslin, R., & Lengyel, M. (2008). Bayesian learning of visual chunks by human observers. Proceedings of the National Academy of Sciences, 105(7), 27452750. DOI: 10.1073/pnas.0708424105
  55. 55Owsowitz, S. E. (1963). The Effects of Word Familiarity and Letter Structure Familiarity on the Perception of Words. Santa Monica, CA: Rand Corporation Publications.
  56. 56Pacton, 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. DOI: 10.1037/0096-3445.130.3.401
  57. 57Pashler, H., Cepeda, N. J., Wixted, J. T., & Rohrer, D. (2005). When does feedback facilitate learning of words? Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(1), 38. DOI: 10.1037/0278-7393.31.1.3
  58. 58Perruchet, P. (2019). What mechanisms underlie implicit statistical learning? Transitional probabilities versus chunks in language learning. Topics in Cognitive Science, 11(3), 520535. DOI: 10.1111/tops.12403
  59. 59Perruchet, P., & Pacton, S. (2006) Implicit learning and statistical learning: One phenomenon, two approaches. Trends in Cognitive Sciences, 10(5), 233238. DOI: 10.1016/j.tics.2006.03.006
  60. 60Perry, C., Ziegler, J. C., & Zorzi, M. (2007). Nested incremental modeling in the development of computational theories: The CDP+ model of reading aloud. Psychological Review, 114(2), 273315. DOI: 10.1037/0033-295X.114.2.273
  61. 61Piantadosi, S. T. (2014). Zipf’s word frequency law in natural language: A critical review and future directions. Psychonomic Bulletin and Review, 21(5), 11121130. DOI: 10.3758/s13423-014-0585-6
  62. 62Pickering, M. J., & Garrod, S. (2013). An integrated theory of language production and comprehension. Behavioral and Brain Sciences, 36(04), 329347. DOI: 10.1017/S0140525X12001495
  63. 63Plaut, D. C., & Gonnerman, L. M. (2000). Are non-semantic morphological effects incompatible with a distributed connectionist approach to lexical processing? Language and Cognitive Processes, 15(4–5), 445485. DOI: 10.1080/01690960050119661
  64. 64Pollo, T. C., Kessler, B., & Treiman, R. (2009). Statistical patterns in children’s early writing. Journal of Experimental Child Psychology, 104(4), 410426. DOI: 10.1016/j.jecp.2009.07.003
  65. 65Potter, C. E., Wang, T., & Saffran, J. R. (2017). Second language experience facilitates statistical learning of novel linguistic materials. Cognitive Science, 41, 913927. DOI: 10.1111/cogs.12473
  66. 66R Core Team. (2017). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/
  67. 67Rastle, K., Lally, C., Davis, M. H., & Taylor, J. S. H. (2021). The dramatic impact of explicit instruction on learning to read in a new writing system. Psychological Science, 32(4), 471484. DOI: 10.1177/0956797620968790
  68. 68Raven, J. C. (1958). Guide to using the Mill Hill Vocabulary Scale with the Progressive Matrices Scales. England, UK: Lewis & Co.
  69. 69Reber, A. S. (1989). Implicit learning and tacit knowledge. Journal of Experimental Psychology: General, 118(3), 219235. DOI: 10.1037/0096-3445.118.3.219
  70. 70Reifegerste, J., Veríssimo, J., Rugg, M. D., Pullman, M. Y., Babcock, L., Glei, D. A., … & Ullman, M. T. (2020). Early-life education may help bolster declarative memory in old age, especially for women. Aging, Neuropsychology, and Cognition, 135. DOI: 10.1080/13825585.2020.1736497
  71. 71Rueckl, J. G., Mikolinski, M., Raveh, M., Miner, C. S., & Mars, F. (1997). Morphological priming, fragment completion, and connectionist networks. Journal of Memory and Language, 36(3), 382405. DOI: 10.1006/jmla.1996.2489
  72. 72Saffran, J. R., & Kirkham, N. Z. (2018). Infant Statistical Learning. Annual Review of Psychology, 69, 123. DOI: 10.1146/annurev-psych-122216-011805
  73. 73Samara, A., & Caravolas, M. (2017). Artificial grammar learning in dyslexic and nondyslexic adults: Implications for orthographic learning. Scientific Studies of Reading, 21(1), 7697. DOI: 10.1080/10888438.2016.1262865
  74. 74Santolin, C., & Saffran, J. R. (2018). Constraints on statistical learning across species. Trends in Cognitive Sciences, 22(1), 5263. DOI: 10.1016/j.tics.2017.10.003
  75. 75Schmalz, X., Altoè, G., & Mulatti, C. (2017). Statistical learning and dyslexia: A systematic review. Annals of Dyslexia, 67(2), 147162. DOI: 10.1007/s11881-016-0136-0
  76. 76Schmalz, X., & Mulatti, C. (2017). Busting a myth with the Bayes Factor: Effects of letter bigram frequency in visual lexical decision do not reflect reading processes. The Mental Lexicon, 12(2), 263282. DOI: 10.1075/ml.17009.sch
  77. 77Seidenberg, M. S. (1987). Sublexical structures in visual word recognition: Access units or orthographic redundancy? In M. Coltheart (Ed.), Attention & performance XII: The psychology of reading (pp. 245263). Hillsdale, NJ: Erlbaum.
  78. 78Seidenberg, M. S., & MacDonald, M. C. (2018). The impact of language experience on language and reading. Topics in Language Disorders, 38(1), 6683. DOI: 10.1097/TLD.0000000000000144
  79. 79Siegelman, N. (2020). Statistical learning abilities and their relation to language. Language and Linguistics Compass, 14(3), e12365. DOI: 10.1111/lnc3.12365
  80. 80Siegelman, N., Bogaerts, L., Elazar, A., Arciuli, J., & Frost, R. (2018). Linguistic entrenchment: Prior knowledge impacts statistical learning performance. Cognition, 177, 198213. DOI: 10.1016/j.cognition.2018.04.011
  81. 81Siegelman, N., & Frost, R. (2015). Statistical learning as an individual ability: Theoretical perspectives and empirical evidence. Journal of Memory and Language, 81, 105120. DOI: 10.1016/j.jml.2015.02.001
  82. 82Slone, L. K., & Johnson, S. P. (2018). When learning goes beyond statistics: Infants represent visual sequences in terms of chunks. Cognition, 178, 92102. DOI: 10.1016/j.cognition.2018.05.016
  83. 83Taylor, J. S. H., Davis, M. H., & Rastle, K. (2017). Comparing and validating methods of reading instruction using behavioural and neural findings in an artificial orthography. Journal of Experimental Psychology: General, 146(6), 826858. DOI: 10.1037/xge0000301
  84. 84Thiessen, E. D., Kronstein, A. T., & Hufnagle, D. G. (2013). The extraction and integration framework: A two-process account of statistical learning. Psychological Bulletin, 139(4), 792814. DOI: 10.1037/a0030801
  85. 85Turk-Browne, N. B., Jungé, J. A., & Scholl, B. J. (2005). The automaticity of visual statistical learning. Journal of Experimental Psychology: General, 134(4), 552564. DOI: 10.1037/0096-3445.134.4.552
  86. 86Turk-Browne, N. B., Scholl, B. J., Johnson, M. K., & Chun, M. M. (2010). Implicit perceptual anticipation triggered by statistical learning. Journal of Neuroscience, 30(33), 1117711187. DOI: 10.1523/JNEUROSCI.0858-10.2010
  87. 87Ulicheva, A., Harvey, H., Aronoff, M., & Rastle, K. (2020). Skilled readers’ sensitivity to meaningful regularities in English writing. Cognition, 195, 103810. DOI: 10.1016/j.cognition.2018.09.013
  88. 88Ullman, M. T., Earle, F. S., Walenski, M., & Janacsek, K. (2020). The neurocognition of developmental disorders of language. Annual Review of Psychology, 71, 389417. DOI: 10.1146/annurev-psych-122216-011555
  89. 89Westbury, C., & Buchanan, L. (2002). The probability of the least likely non-length-controlled bigram affects lexical decision reaction times. Brain and Language, 81(1–3), 6678. DOI: 10.1006/brln.2001.2507
  90. 90Wilson, M., & Knoblich, G. (2005). The Case for Motor Involvement in Perceiving Conspecifics. Psychological Bulletin, 131(3), 460473. DOI: 10.1037/0033-2909.131.3.460
  91. 91Zipf, G. (1949). Human Behaviour and the Principle of Least Effffort. Reading, MA: Addison-Wesley.
DOI: https://doi.org/10.5334/joc.209 | Journal eISSN: 2514-4820
Language: English
Submitted on: Oct 22, 2021
Accepted on: Feb 2, 2022
Published on: Feb 21, 2022
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Jarosław R. Lelonkiewicz, Michael T. Ullman, Davide Crepaldi, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.