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The State of the State in Reading

The State of the State in Reading. Barbara Foorman, Ph.D. Yaacov Petscher, Ph.D. Florida State University Florida Center for Reading Research. Closing the Achievement Gap. Has been the focus of the federal initiative in education since ESEA passed in 1965.

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The State of the State in Reading

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  1. The State of the State in Reading Barbara Foorman, Ph.D. Yaacov Petscher, Ph.D. Florida State University Florida Center for Reading Research

  2. Closing the Achievement Gap • Has been the focus of the federal initiative in education since ESEA passed in 1965. • Controlling for SES (FRL, minority, ELL status) in analyzing for achievement gains is widespread. Ex: Beat the Odds analyses. • With NCLB passage in 2001 and emphasis on AYP, value-added analyses popular. • Debates regarding growth vs. attainment and definitions of proficiency continue.

  3. Outcome Measures • Percent meeting high standards in reading: % students passing FCAT (FCAT SSS) • Percent making reading gains: % students making one year’s worth of growth (FCAT DSS) • Percent of lowest 25% making reading gains: % students in lowest quartile that made 1 year of growth (FCAT DSS

  4. Demographics

  5. Comparison of Methods • Covariate Adjusted Scores • Demographics • Academic achievement • Latent Class Analysis • Demographics • Academic achievement

  6. Beating the Odds

  7. Proportion of Schools by Group for School Type and Outcomes

  8. Elementary - Students

  9. Middle School - Students

  10. High School - Students

  11. FLDOE Method • Sort your data file • Calculate mismatches • Identify schools that meet some criteria • What schools are consistently in the same group over all three dependent variables?

  12. Number of Identified Schools

  13. Different Approach Policy analyses are fun but….. Do schools tend to cluster? Can we describe profiles in a meaningful way? Are profiles similar to BTO groupings? What are the differences in identification?

  14. Evaluating Fit Traditional LCA AIC BIC Boostrap Likelihood Ratio Test Entropy Posterior Probability Used a conservative estimate of 0.80 Elementary – 14 schools dropped Middle – 8 schools dropped High – 5 schools dropped

  15. Elementary

  16. Middle

  17. High

  18. Comparing the Classification

  19. What Can We Do? Describe the clusters Explain the differences Provide better recommendations to stakeholders Benefits of LCA Reduced measurement error Include all schools Multivariate

  20. The End BFoorman@fcrr.org YPetscher@fcrr.org

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