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Assessing ELLs for LD within an RTI framework

Assessing ELLs for LD within an RTI framework. Jennifer Venegas, M.A. Alicia Hoerner, Ph.D. ELLs and LD eligibility.

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Assessing ELLs for LD within an RTI framework

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  1. Assessing ELLs for LD within an RTI framework Jennifer Venegas, M.A. Alicia Hoerner, Ph.D.

  2. ELLs and LD eligibility • History of overrepresentation and underrepresentation of ELLs as LD due to linguistic and cultural differences and inappropriate assessment and instruction. (Ochoa, Ortiz, Rhodes, 2005; Donovan & Cross, 2002)s • Considerable demands in parsing out academic difficulties that are due to a learning disability versus difficulties due to factors related to English proficiency. (Wilkinson, Alba, Robertson & Kushner, 2006) • Most referred group of ELLs is that exhibiting reading difficulties. • Over 50% of ELLs score in the bottom 3rd of reading achievement (National Center for Education Statistics, 2005)

  3. Approaches for determining eligibility: Discrepancy model • Measurement of IQ/achievement gap • Utah Estimator: at least 93 percent confident there is a severe discrepancy between the student's expected achievement score and the obtained achievement score. http://estimator.srlonline.org • Criticisms : “wait-to-fail model” • Use of discrepancy models for determining LD contribute to the disproportionate minority representation in special education. (Donovan & Cross, 2002)

  4. Approaches for determining eligibility: Response To Intervention • Response to intervention (RTI) model has been proposed as an alternative approach to determining eligibility for special education. • Not primarily a system for eligibility requirement but an intervention delivery system. • Expectation that RTI approaches to determining SLD eligibility will be more culturally sensitive to issues of disproportionality for minorities with LD. (Linan-Thompson, Cirino, & Vaugh, 2007)

  5. Approaches for determining eligibility: Response To Intervention • Vaughn, Mathes, Linan-Thompson & Francis (2005) say: “At the current time, it is very difficult to actually implement this model with ELLs because efficacy of various interventions has not been tested with this population.” • Esparza (2008) states “The main problem with RTI and ELLs is the same as that with standardized assessment- what is the appropriate standard, expectation for growth or baseline to use?” • Haager (2007) cautions that it is not feasible or desirable to have separate sets of tools and procedures for non-ELLs and ELLs. • Studies shown to be efficacious with non-ELLs should be replicated with ELLs to determine dual utility of instructional tools and practices. • Richardson (2009) found that assessment of ELLs with CBM measures yield different trend lines and slopes. • What is to be expected? What is progress? What is response to intervention?

  6. English learner oral language proficiency and its impact on growth trajectories in reading: A three- year longitudinal study (Richardson, 2009)

  7. English learner oral language proficiency and its impact on growth trajectories in reading: A three- year longitudinal study (Richardson, 2009)

  8. English learner oral language proficiency and its impact on growth trajectories in reading: A three year longitudinal study (Richardson, 2009) • Findings • ELLs were not found to be reading at the same level as non-ELLs; however, ELLs demonstrated variable oral English proficiency, which had a strong influence on reading proficiency level. • ELLs appear to be catching up in the 4th through 6th grades, showing faster growth rates than their non-ELL peers. • ELLs had similar rates of reading to non-ELLs, but different starting and ending points, depending on English proficiency • Best to identify how to help ELLs meet ambitious expectations rather than lowering expectations to meet status quo. • ELLs with SLD in reading will likely present with low level of performance AND low rates of progress.

  9. ELLs and Eligibility • When assessing ELLs it is beneficial to link together multiple sources of information. • Wilkinson, Ortiz, Robertson, & Kushner (2006) suggest paying attention to four domains when determining eligibility. • Early intervention (type, duration, outcomes) • Alternatives explanations to referral question • Assessment (use of culturally and linguistically sensitive tests) • Sensitivity of the multidisciplinary team to CLD factors • Developmental history, home environment, culture, language use, formal and informal testing methods need to be considered with respect to LD eligibility.

  10. Data interpretation for eligibility • Many school psychologists may find themselves unsure of how to go about incorporating data from curriculum based measures along with scores from standardized measures into their evaluation. • SLCSD currently uses standardized measures along with CBM measures to determine eligibility for LD (“combined” approach). • Evidence of appropriate instruction and documentation of repeated assessments to determine student progress in curriculum • Observation in the area of concern • Standardized measure of intellectual ability • Standardized tests in targeted areas of referral • Discrepancy report with at least 93% chance that there is a significant gap between achievement and intelligence

  11. Purpose of presentation • Review two case studies to examine the application of a combined approach when determining LD eligibility for ELLs • Participants: Two ELLs in the third grade • Referral: Possible specific learning disability in reading fluency and comprehension • History and early intervention • Assessment: CBM, rate of progress measurement, and standardized measures • Interpretation

  12. SHAKIRA: Background information • 9 years old, 3rd grade • Born in Mexico • Came to U.S.A. at 2 years with mother • Spanish as first language • Spanish is used as the primary home language • Parent reported head injury due to “low speed” car accident at age 2; reportedly well the next day • Educated in Utah since pre-school in English only • English is dominant language as per Mother • Teacher referral for slow academic progress in reading and math • IPT: Oral language proficiency=limited; Reading= Non-English Reader

  13. SHAKIRA: DIBELS Annual Performance Profile

  14. SHAKIRA: Targeted Intervention • Intervention with reading specialist with instruction in phonics for reading fluency and reading comprehension (Anita Archer Phonics for Reading) • 45 minutes daily for eight weeks in a small group • Baseline: • 13 wpm on 3rd grade level DIBELS • 92 wpm expected for 3rd grade • Target: Increase oral reading fluency and reading comprehension

  15. SHAKIRA: Progress Monitoring Data

  16. SHAKIRA: Standardized Testing Universal Nonverbal Intelligence Test (UNIT)

  17. SHAKIRA: Woodcock-Munoz Language Survey-Revised

  18. SHAKIRA: Selected tests from WJ-III Achievement

  19. SHAKIRA: Estimator Discrepancy Report

  20. 8 years old, 3rd grade Born in Utah Both parents and sister migrated from Mexico Spanish as first language Spanish is used at the primary home language Described as “late talker” by mother English is reported as dominant language as per Mother Educated in U.S.A. in English since Kindergarten Teacher referral for slow academic progress Poor reading fluency and reading comprehension IPT (2nd grade): Oral Language= Limited; Reading= Non-English Reader Family moved back to Mexico after evaluation LUIS MIGUEL: Background information

  21. LUIS MIGUEL: DIBELS Annual Performance Profile

  22. LUIS MIGUEL: Targeted Intervention • Intervention with reading specialist with instruction in phonics for reading fluency and reading comprehension (Anita Archer Phonics for Reading) • 45 minutes daily for eight weeks in a small group • Baseline: • 21 wpm on 3rd grade level DIBELS • 92 wpm expected for 3rd grade • Target: Increase oral reading fluency and reading comprehension

  23. LUIS MIGUEL: DIBELS ORF Data

  24. LUIS MIGUEL: Standardized Testing Universal Nonverbal Intelligence Test (UNIT)

  25. LUIS MIGUEL: Woodcock-Munoz Language Survey-Revised

  26. LUIS MIGUEL: Selected tests from WJ-III Achievement

  27. LUIS MIGUEL: Estimator Discrepancy Report

  28. Repeated assessment of student performance allowed us to obtain a more comprehensive perspective than ‘snapshots’ from standardized assessment. • Inclusion of data showing progress on instructional and grade level contributed to a better understanding to student’s response to intervention. • Level of performance AND growth rate were helpful indicators when attempting to make predictions of learning. • Decisions regarding ELL’s eligibility for SPED need to include data on oral language. • Standardized measures of language proficiency • Parent interviews • Repeated district wide measures of oral language • RTI for oral language? Conclusions

  29. Conclusions (cont.) • When using eligibility approaches that combine CBM and standardized measures, some inconsistency can be expected. • e.g. Luis Miguel’s low ORF scores, yet average Basic Reading (SS=91) • Lack of a significant discrepancy on the Estimator for basic reading for both students. • Training and varied amount exposure to RTI and ELLs among school psychologists and IEP team members may be related to significant differences in interpretation and eligibility outcomes. • Authors felt that eligibility decisions based on combined sources of data remain subjective.

  30. Limitations • Although intervention reportedly targeted reading comprehension, no progress monitoring data were collected on this area. • Difficult to make conclusions regarding response to intervention in this domain. • No information on fidelity of intervention implementation. • Other potential mediating factors intervening on reading measures were not addressed (e.g., ADHD, motivation, compliance).

  31. Future Directions • Need for ongoing support to teachers as they implement academic interventions. • Does intervention need to continue for 8 weeks if initial data is showing inconsistent response? • Schools report a need for additional training on RTI. • Additional guidance at the state and district level on making eligibility determinations based on approaches incorporating RTI data.

  32. Acknowledgements • Salt Lake City School District • Rebecca Robbins • University of Utah • Janiece L. Pompa, Ph.D. • Mary Beth Lindsay Pummel

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