1. Working memory, long-term memory, and reading: The case of catastrophe theory versus regression analysis Anna M. T. Bosman Fred Hasselman Ralf Cox Behavioural Science Institute Nijmegen, the Netherlands

2. EWOMS-2006 Who: Scientists & Practitioners What: Reading and reading difficulties Why: ?????? Where: are we now???? W 4 = (Who*What*Why*Where)

3. EWOMS-2006 STRAND S T R A N D / s // t // ɪə // e // n // d / Likely reading errors: /stand/, /sand/, /trend/, /spend/, /rand/ DEARPEARDEADBREAK / ɪə // eə / / e // eɪ / Memory & Reading

4. EWOMS-2006 Beware of heard, a dreadful word That looks like beard and sounds like bird, And dead: it's said like bed, not bead - For goodness sake don't call it deed! Memory & Reading

5. Working memory : Digit Recall Backward Digit Recall Block Recall Long Term Memory: 12-Words Test Reading level decoding : DMT: Score = N correct words / minute EWOMS-2006 Tests

6. Experiment 0 99 Dutch, Grade-1 students (mean age 80 months) 46 without and 53 with reading delays EWOMS-2006 Testwithout RDwith RDSignificance WM: Digit recall22.522.2F < 1 WM: Block recall22.421.6p >.30 WM: Backward recall8.77.2 p <.005 LTM: capacity7.46.3 p <.01

7. EWOMS-2006 Working Memory and remediation Digit recall: Remediation Successful > Remediation Unsuccessful p <.01 Backward recall: Remediation Successful = Remediation Unsuccessful Block recall: Remediation Successful = Remediation Unsuccessful

8. EWOMS-2006 Build-up significant linear and quadratic trends CapacityRemediation Successful > Remediation Unsuccessful p <.05 Long-term memory and remediation

9. EWOMS-2006 Multiple linear regression model Y = b 0 + b 1 X 1 + b 2 X 2

10. EWOMS-2006 Change  Is at the heart of psychology (everything!)  What we want to achieve in RD So why not study it in terms of a dynamics?

11. EWOMS-2006  Describe dynamical systems in terms of mathematics  Enable us to understand discontinuities in behaviour (i.e., change over time)  With the help of so-called control parameters Catastrophe models

12. EWOMS-2006  x is the psychological variable of interest (i.e., reading success)  V is a potential function describing the possible states in which x might eventually occur Un po’ di matematica

13. EWOMS-2006  α en β are control parameters determining the exact shape of the function. x = ‘order parameter’ α = ‘asymmetry parameter’ β = ‘bifurcation parameter’ Potential function of the Cusp-catastrophe model

14. Non-linear or Cusp-catastrophe model EWOMS-2006

15. Dynamic systems tend to seek particular end states, called attractors (the variable x does not change anymore) In terms of mathematics, we need to establish when or Ancora un po’ di matematica

16. Canonical cusp-surface equation EWOMS-2006 Asymmetry parameter: WM Bifurcation parameter: LTM

17. Experiment 1 47 Dutch, Grade-1 students with reading problems –25 boys –22 girls Mean age = 80 months (SD = 5); at memory assessment Assessment –Memory: October/November 2003 –Reading level 1: January/February 2004 –Reading level 2: June/July 2004 EWOMS-2006

18. Results: Linear difference model EWOMS-2006 FactorsR2R2 Model LTM WM: Digit recall.05n.s LTM WM: Backward recall.04n.s LTM WM: Block recall.02n.s dx = b 1 LTM + b 2 WM + b 3

19. Results: Linear interaction model EWOMS-2006 FactorsR2R2 Model LTM WM: Digit recall.05n.s LTM WM: Backward recall.05n.s LTM WM: Block recall.08n.s dx = b 1 LTM + b 2 WM + b 3 LTM*WM + b 4

20. Results: Linear pre-post model EWOMS-2006 FactorsR2R2 Model LTM + Digit recall Reading ***.56p <.0001 ß =.74 LTM + Backward recall Reading ***.57p <.0001 ß =.73 LTM +Block recall Reading ***.57p <.0001 ß =.74 x 2 = b 1 LTM + b 2 WM + b 3 x 1 + b 4

21. Results: Non-linear Cusp-catastrophe model EWOMS-2006 All models p <.0001 R2R2 WMLTMZ2Z2 Z3Z3 Digit recall.61 ß =.23 ns ß =.81 p <.0001 ß = -2.2 p <.04 ß = 2.2 p <.04 Backward recall.62 ß =.17 ns ß =.80 p <.0001 ß = -1.9 p <.01 ß = 1.6 p <.02 Block recall.62 ß =.20 ns ß =.80 p <.0001 ß = -2.1 p <.02 ß = 2.2 p <.03 dx = b 1 x 1 3 + b 2 x 1 2 + b 3 LTMx 1 2 + b 4 WM + b 5

22. What did we learn? Scientifically LTM, WM, and Reading are dynamically related. Thus, the search for independent components as causal mechanisms seem futile Practically impossible to predict reading-remediation success based on LTM and WM levels.Thus: EACH CHILD DESERVES THE EXTRA HELP! EWOMS-2006

23. Tom Braams, MA for keeping us in touch with daily practice Marion IJntema-de Kok, MA for running the Experiment Braams & Partners, Instituut voor Dyslexie Deventer, the Netherlands Many thanks to