Skip to main content
SpringerLink
Log in

Effect of chunk strength on the performance of children with developmental dyslexia on artificial grammar learning task may be related to complexity

  • Published:
Annals of Dyslexia Aims and scope Submit manuscript

Abstract

There’s a long held view that chunks play a crucial role in artificial grammar learning performance. We compared chunk strength influences on performance, in high and low topological entropy (a measure of complexity) grammar systems, with dyslexic children, age-matched and reading-level-matched control participants. Findings show that age-matched control participants’ performance reflected equivalent influence of chunk strength in the two topological entropy conditions, as typically found in artificial grammar learning experiments. By contrast, dyslexic children and reading-level-matched controls’ performance reflected knowledge of chunk strength only under the low topological entropy condition. In the low topological entropy grammar system, they appeared completely unable to utilize chunk strength to make appropriate test item selections. In line with previous research, this study suggests that for typically developing children, it is the chunks that are attended during artificial grammar learning and create a foundation on which implicit associative learning mechanisms operate, and these chunks are unitized to different strengths. However, for children with dyslexia, it is complexity that may influence the subsequent memorability of chunks, independently of their strength.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • American Psychiatric Association. (2013). Cautionary statement for forensic use of DSM-5. In Diagnostic and statistical manual of mental disorders (5th ed.). doi:10.1176/appi.books.9780890425596.744053.

    Chapter  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 

  • Bailey, T. M., & Pothos, E. M. (2008). AGL StimSelect: software for automated selection of stimuli for artificial grammar learning. Behavior Research Methods, 40, 164–176. doi:10.3758/BRM.40.1.164.

    Article  Google Scholar 

  • Beesley, T., Wills, A. J., & Le Pelley, M. E. (2010). Syntactic transfer in artificial grammar learning. Psychological Bulletin & Review, 17, 122–128.

    Article  Google Scholar 

  • Bennett, I. J., Romano, J. C., Howard, J. H., & Howard, D. V. (2008). Two forms of implicit learning in young adult dyslexics. Annals of the New York Academy of Science., 1145, 184–198. doi:10.1196/annals.1416.006.

    Article  Google Scholar 

  • Berry, D., & Dienes, Z. P. (1993). Implicit learning: Theoretical and empirical issues. Lawrence Erlbaum Associates.

  • Bollt, E. M., & Jones, M. A. (2000). The complexity of artificial grammars. Nonlinear Dynamics, Psychology & Life Science, 4, 153–168.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Démonet, J. F., Taylor, M. J., & Chaixc, Y. (2004). Developmental dyslexia. The Lancet, 363, 1451–1460. doi:10.1016/S0140-6736(04)16106-0.

    Article  Google Scholar 

  • 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 

  • Facoetti, A., Paganoni, P., Turatto, M., Marzola, V., & Mascetti, G. G. (2000). Visual-spatial attention in developmental dyslexia. Cortex, 36, 109–123. doi:10.1016/S0010-9452(08)70840-2.

    Article  Google Scholar 

  • Farmer, T. A., Fine, A. B., Misyak, J. B., & Christiansen, M. H. (2016). The inter-relationship between reading span task performance, linguistic experience, and the processing of unexpected syntactic events. Quarterly Journal of Experimental Psychology.

  • Fletcher, J. M. (2009). Dyslexia: the evolution of a scientific concept. Journal of International Neuropsychological Society, 15, 501–508.

    Article  Google Scholar 

  • Folia, V., Uddén, J., Forkstam, C., Ingvar, M., Hagoort, P., & Peterssona, K. M. (2008). Implicit learning and dyslexia. Annals of the New York Academy of Science., 1145, 132–150. doi:10.1196/annals.1416.012.

    Article  Google Scholar 

  • Gabay, Y., Schiff, R., & Vakil, E. (2012). Dissociation between the procedural learning of letter names and motor sequences in developmental dyslexia. Neuropsychologia, 50, 2435–2441. doi:10.1016/j.neuropsychologia.2012.06.014.

    Article  Google Scholar 

  • Gerken, L. A., Wilson, R., & Lewis, W. (2005). 17-month-olds can use distributional cues to form syntactic categories. Journal of Child Language, 32, 249–268.

    Article  Google Scholar 

  • Gombert, J. E. (2003). Implicit and explicit learning to read: implication as for subtypes of dyslexia. Current Psychology Letters, 10, 1–8.

    Google Scholar 

  • Habib, M. (2000). The neurological basis of developmental dyslexia: an overview and working hypothesis. Brain, 123, 2373–2399. doi:10.1093/brain/123.12.2373.

    Article  Google Scholar 

  • Howard, J. H., Howard, V. D., Japiksea, K. C., & Eden, G. F. (2006). Dyslexics are impaired on implicit higher-order sequence learning, but not on implicit spatial context learning. Neuropsychologia, 44, 1131–1144. doi:10.1016/j.neuropsychologia.2005.10.015.

    Article  Google Scholar 

  • Ise, E., Arnoldi, C. J., Bartling, J., & Schulte-Korne, G. (2012). Implicit learning in children with spelling disability: evidence from artificial grammar learning. Journal of Neural Transmission, 119(9), 999–1010.

    Article  Google Scholar 

  • Katan, P., Kahta, S., Sasson, A., & Schiff, R. (in press). Performance of children with developmental dyslexia on high and low Topological Entropy artificial grammar learning task. Annals of Dyslexia.

  • Knowlton, B. J., & Squire, L. R. (1994). The information acquired during artificial grammar learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 79–91.

    Google Scholar 

  • Knowlton, B. J., & Squire, L. R. (1996). Artificial grammar learning depends on implicit acquisition of both abstract and exemplar-specific information. Journal of Experimental Psychology Learning, Memory and Cognition, 22, 169–181. doi:10.1037//0278-7393.22.1.169.

    Article  Google Scholar 

  • Lieberman, M. D., Chang, G. Y., Chiao, J., Bookheimer, S. Y., & Knowlton, B. J. (2004). An eventrelated fMRI study of artificial grammar learning in a balanced chunk strength design. Journal of Cognitive Neuroscience, 16(3), 427-438.

  • 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 

  • Mathews, R. C., Buss, R. R., Stanley, W. B., Blanchard-Fields, F., Cho, J. R., & Druhan, B. (1989). Role of implicit and explicit processes in learning from examples: a synergistic effect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 1083–1110. doi:10.1037/0278-7393.15.6.1083.

    Google Scholar 

  • Maye, J., Werker, J. F., & Gerken, L. (2002). Infant sensitivity to distributional information can affect phonetic discrimination. Cognition, 82, B101–B111. doi:10.1016/S0010-0277(01)00157-3.

    Article  Google Scholar 

  • Meulemans, T., & Van der Linden, M. (1997). Associative chunk strength in artificial grammar learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, 1007–1028. doi:10.1037/0278-7393.23.4.1007.

    Google Scholar 

  • Meulemans, T., Van der Linden, M., & Perruchet, P. (1998). Implicit sequence learning in children. Journal of Experimental Child Psychology, 69, 199–221. doi:10.1006/jecp.1998.2442.

    Article  Google Scholar 

  • Nicolson, R. I., & Fawcett, A. J. (1990). Automaticity: a new framework for dyslexia research? Cognition, 35, 159–182. doi:10.1016/0010-0277(90)90013-A.

    Article  Google Scholar 

  • Nieuwenhuis, I. L. C., Folia, V., Forkstam, C., Jensen, O., & Petersson, K. M. (2013). Sleep promotes the extraction of grammatical rules. PloS One, 8, e65046. doi:10.1371/journal.pone.0065046.

    Article  Google Scholar 

  • Onnis, L., Destrebecqz, A., Christiansen, M. H., Chater, N., & Cleeremans, A. (2015). Implicit learning of non-adjacent dependencies: a graded, associative account. In P. Rebuschat (Ed.), Implicit and explicit learning of languages. Amsterdam: John Benjamins.

    Google Scholar 

  • Pavlidou, E. V., & Williams, J. M. (2014). Implicit learning and reading: insights from typical children and children with developmental dyslexia using the artificial grammar learning (AGL) paradigm. Research in Developmental Disabilities, 35, 1457–1472. doi:10.1016/j.ridd.2014.03.040.

    Article  Google Scholar 

  • Pavlidou, E. V., Kelly, L. M., & Williams, J. M. (2010). Do children with developmental dyslexia have impairments in implicit learning? Dyslexia, 16, 143–161. doi:10.1002/dys.400.

    Article  Google Scholar 

  • Pavlidou, E. V., Williams, J. M., & Kelly, L. M. (2009). Artificial grammar learning in primary school children with and without developmental dyslexia. Annals of Dyslexia, 59, 55–77. doi:10.1007/s11881-009-0023-z.

    Article  Google Scholar 

  • Pennington, B. F. (2009). Diagnosing learning disorders: a neuropsychological framework (2nd ed.). New York: Guilford Press.

    Google Scholar 

  • Perruchet, P., & Gallego, J. (1997). A subjective unit formation account of implicit learning. In How implicit is implicit learning? (pp. 124–161). New York: Oxford University Press.

    Chapter  Google Scholar 

  • Perruchet, P., Vinter, A. S., & Michael, A. (1998). Learning and development: the implicit knowledge assumption reconsidered. In P. A. Frensch (Ed.), Handbook of implicit learning (pp. 495–531). Thousand Oaks: Sage, Inc, xi, 636 pp.

  • Pothos, E. M., & Kirk, J. (2004). Investigating learning deficits associated with dyslexia. Dyslexia, 10, 61–76.

    Article  Google Scholar 

  • Pothos, E. M., & Wood, R. L. (2009). Separate influences in learning: evidence from artificial grammar learning with traumatic brain injury patients. Brain Research, 1275, 67–72.

    Article  Google Scholar 

  • Pothos, E. M. (2007). Theories of artificial grammar learning. Psychological Bulletin, 133, 227–244. doi:10.1037/0033-2909.133.2.227.

    Article  Google Scholar 

  • Ramus, F., & Ahissar, M. (2012). Developmental dyslexia: the difficulties of interpreting poor performance, and the importance of normal performance. Cognitive Neuropsychology, 29(1–2), 104–122. doi:10.1080/02643294.2012.677420.

    Article  Google Scholar 

  • Reber, A. S. (1969). Transfer of syntactic structure in synthetic languages. Journal of Experimental Psychology, 81, 115–119.

    Article  Google Scholar 

  • Reber, A. S. (1989). Implicit learning and tacit knowledge. Journal of Experimental Psychology: General, 118(3), 219.

    Article  Google Scholar 

  • Reber, A. S. (1993). Implicit learning and tacit knowledge: an essay on the cognitive unconscious, Oxford Psychology Series No. 19. New York: Oxford University Press.

    Google Scholar 

  • Reber, A. S. (1967). Implicit learning of artificial grammars. Journal of Verbal Learning and Verbal Behavior, 6, 855–863. doi:10.1016/S0022-5371(67)80149-X.

    Article  Google Scholar 

  • Redington, M., & Chater, N. (1996). Transfer in artificial grammar learning: a reevaluation. Journal of Experimental Psychology: General, 125, 123–138.

    Article  Google Scholar 

  • Sallas, B., Mathews, R. C., Lane, S. M., & Sun, R. (2007). Developing rich and quickly accessed knowledge of an artificial grammar. Memory and Cognition, 35, 2118–2133. doi:10.3758/BF03192943.

    Article  Google Scholar 

  • Schiff, R. & Kahta, S. (2006). Single-word reading test: vowelized and unvowelized word reading. Haddad Center, Bar-Ilan University, Ramat Gan, Israel.

  • Schiff, R., & Katan, P., (2014). Does complexity matter? Meta-analysis of learner performance in artificial grammar tasks. Frontiers in Psychology, 5, article 1084. doi:10.3389/fpsyg.2014.01084

  • Servan-Schreiber, E., & Anderson, J. R. (1990). Learning artificial grammars with competitive chunking. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16, 592–596.

    Google Scholar 

  • Siegelman, N., & Frost, R. (2015). Statistical learning as an individual ability: theoretical perspectives and empirical evidence. Journal of Memory and Language, 81. doi:10.1016/j.jml.2015.02.001.

  • Snowling, M. J. (2000). Dyslexia. Blackwell publishing dyslexia (2nd ed.). doi:10.1016/B978-0-12-375000-6.00139-7.

    Google Scholar 

  • Stein, J. (2001). The magnocellular theory of developmental dyslexia. Dyslexia, 7, 12–36. doi:10.1002/dys.186.

    Article  Google Scholar 

  • Stein, J., & Walsh, V. (1997). To see but not to read; the magnocellular theory of dyslexia. Trends in Neurosciences, 20, 147–152. doi:10.1016/S0166-2236(96)01005-3.

    Article  Google Scholar 

  • Swanson, H. L., & Jerman, O. (2007). The influence of working memory on reading growth in subgroups of children with reading disabilities. Journal of Experimental Child Psychology, 96, 249–283. doi:10.1016/j.jecp.2006.12.004.

    Article  Google Scholar 

  • Szmalec, A., Loncke, M., Page, M. P. A., & Duyck, W. (2011). Order or disorder? Impaired Hebb learning in dyslexia. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 1270–1279. doi:10.1037/a0023820.

    Google Scholar 

  • Van den Bos, E., & Poletiek, F. H. (2008). Effects of grammar complexity on artificial grammar learning. Memory & Cognition, 36, 1122–1131. doi:10.3758/MC.36.6.1122.

    Article  Google Scholar 

  • Van den Bos, E., & Poletiek, F. H. (2015). Learning simple and complex artificial grammars in the presence of a semantic reference field: effects on performance and awareness. Frontiers in Psychology, article, 158. doi:10.3389/fpsyg.2015.00158.

  • Vellutino, F. R., Fletcher, J. M., Snowling, M. J., & Scanlon, D. M. (2004). Specific reading disability (dyslexia): what have we learned in the past four decades? Journal of Child Psychology and Psychiatry, 45(1), 2-40.

  • 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, 1392–1397.

    Article  Google Scholar 

  • Vidyasagar, T., & Pammer, K. (2010). Dyslexia: a deficit in visuospatial attention, not in phonological processing. Trends in Cognitive Sciences, 14, 57–63. doi:10.1016/j.tics.2009.12.003.

    Article  Google Scholar 

  • Vinter, A., & Perruchet, P. (2000). Implicit learning in children is not related to age: evidence from drawing behavior. Child Development, 71(5), 1223–1240.

    Article  Google Scholar 

  • Vokey, J. R., & Brooks, L. R. (1992). Salience of item knowledge in learning artificial grammars. Journal of Experimental Psychology: Learning, Memory, & Cognition, 18, 328–344.

    Google Scholar 

  • Ziegler, J. C., & Goswami, U. (2005). Reading acquisition, developmental dyslexia, and skilled reading across languages: a psycholinguistic grain size theory. Psychological Bulletin, 13, 3–29. doi:10.1037/0033-2909.131.1.3.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Learning Disabilities Studies, School of Education, Bar-Ilan University, 52900, Ramat-Gan, Israel

    Rachel Schiff, Pesia Katan & Shani Kahta

  2. Haddad Center for Dyslexia and Learning Disabilities, Bar Ilan University, 52900, Ramat-Gan, Israel

    Ayelet Sasson

Authors
  1. Rachel Schiff
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pesia Katan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ayelet Sasson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shani Kahta
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rachel Schiff.

Additional information

This study is part of the research conducted at Bar Ilan University, Ramat Gan, Israel, as partial fulfillment of Pesia Katan’s requirement for a Doctor of Philosophy degree

Appendices

Appendix 1.

Fig. 6
figure 6

An example of a finite state language (from Knowlton Squire, 1996)

Full size image
Fig. 7
figure 7

An example of a finite state language (from Mathews et al. 1989)

Full size image

Appendix 2. Training and test stimuli (from Knowlton & Squire, 1996)

Training:

figure a

Test:

figure b

Appendix 3. Training and test stimuli (from Mathews et al., 1989)

Training:

figure c

Test:

figure d

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schiff, R., Katan, P., Sasson, A. et al. Effect of chunk strength on the performance of children with developmental dyslexia on artificial grammar learning task may be related to complexity. Ann. of Dyslexia 67, 180–199 (2017). https://doi.org/10.1007/s11881-017-0141-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11881-017-0141-y

Keywords

Search

Navigation