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Yuliya Ardasheva Thomas R. Tretter Marti Kinny

Academic achievement among middle school re-designated fluent English proficient students: Closing the gap?. Yuliya Ardasheva Thomas R. Tretter Marti Kinny. Background. English Language Learners (ELLs) are the fastest growing population in the United States

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Yuliya Ardasheva Thomas R. Tretter Marti Kinny

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  1. Academic achievement among middle school re-designated fluent English proficient students: Closing the gap? Yuliya Ardasheva Thomas R. Tretter Marti Kinny

  2. Background English Language Learners (ELLs) are the fastest growing population in the United States The number of school-aged ELLs is expected to increase to 40% by 2050(Goldenberg, 2008). Language minority achievement gap is a reality The 2008 NAEP (Wilde, 2009a, 2009b) Grade 8 mathematics: 31-point gap Grade 12 reading: 46-point gap Typical achievement gap: 25 NCEs (Normal Curve Equivalents; Thomas & Collier, 2002)

  3. Background • ELL population is composed of multiple subgroups • Limited English proficient (LEP) • Students who have “sufficient difficulty speaking, reading, writing, or understanding the English language” (KDE, 2008, par 3) • Re-designated fluent English proficient (RFEP) • Students who had reached an English proficiency benchmark • Little is known about how RFEP students fare academically

  4. Purpose • The primary objective of this study was to examine academic achievement in reading and mathematics of middle school RFEP students in comparison to that of LEP and native-English speaking (NES) students after controlling for individual and school socio-economic status (SES). • Additionally, the study examined whether or not the new state re-classification policies aligned with the NCLB requirements provide a more accurate differentiation between LEP and RFEP students.

  5. Research Questions Do ELL students who had reached an English proficiency benchmark (RFEP) close academic achievement gap? What is the impact of school poverty on academic achievement of re-designated fluent English proficient students? Do the new state re-classification policies aligned with the NCLB requirements more accurately identify English proficiency for academic purposes?

  6. District context • ELL population in the school district • 4,868 ELLs in 2008-09 • 5% of total student population • Fastest growing population in the district • 28% of incoming ELLs are refugees • Continuum of ELL services and support • ESL Newcomer Academy for secondary students • 30% of the comprehensive secondary schools provide English as a second language services • Content-based approach to ELL instruction

  7. Population: Middle school RFEP students schooled in similar to this study’s settings Sampling procedures: School level Selection criteria for schools: A comprehensive school A population of LEP and RFEP students within its body Selection criteria for students: All Grade 6, 7, and 8 NES, LEP and RFEP students enrolled in the selected schools Population and Sampling

  8. Schools: N = 22 ESL services: N = 8 Title I: N = 11 Students: N = 18,523 (17,470 NES; 558 LEP; 500 RFEP) 13.63 years 49% females 57% low SES ELLs: Spanish (47.2%), Bosnian (10.1%), Vietnamese (5.3%), and Mai Mai (4.7%) Length of residence (LOR): LEP: 4.72(SD = 2.37) RFEP: 6.63(SD = 1.84) Sample

  9. Methods • Nonexperimental design • Cross-sectional data collected by a large Midwestern public school district in 2007-2008 school year. • Analytical procedures: • RQ 1&2 • Descriptive statistics • A two-level hierarchical linear model (HLM) (Raudenbush & Bryk, 2002) • RQ 3 • Stepwise multiple regression(MR)

  10. Instruments: KCCT Criterion-referenced (novice, apprentice, proficient, distinguished) Reading test: foundational skills, developing understanding, text interpretation and response skills, and ability to demonstrate a critical stance Mathematics test : knowledge of number properties and operations, measurement, geometry, data analysis and probability, and algebraic thinking Scales scores range from 0 to 80 (differentiated across grade levels) IRT scaling allows for comparison across grade levels Psychometric properties of the test are evaluated and reported yearly

  11. Instruments: English proficiency 1) Prior to 2007, LAS(Duncan & De Aliva, 1988, 1995) • Assessed studentsstructural proficiency (i.e., mastery of discrete language elements such as sounds, morphemes, and grammar rules) • English proficiency levels (3 levels in Reading, Writing; 5 Levels in Speaking, Listening) 2) Since 2007, ACCESS(WIDA, 2008) • Assessesstudents’ functional proficiency(i.e., the ability to use language appropriately given a particular context of use) • Alignedwith • Grade-level content area standards (i.e., test items are tied to academic tasks) • English proficiency levels (6 levels in Reading, Writing, Speaking, Listening) NOTE: The district uses a composite score of “5” for re-classification.

  12. Study Variables: RQ1 & 2

  13. Data Analyses Level 1 equation: Yij = β0j + β1j (GENDERij) + β2j (AGEij) + β3j (LEPij) + β4j (RFEPij) + β5j (SESij) + rij Level 2 equation: β0j = γ00 + γ01(POVERTYR) + u0j βpj = γp0[for p = 1, 2] βpj = γp0 + γp1 (POVERTYR) + upj[for p = 3, 4, 5]

  14. Results: RQ 1 & 2

  15. R eading High SES Low SES Female (NES) Native English speakers 51.14 (P) 42.49 (P) (LEP) Limited English proficient 40.84 (P) 32.19 (A H ) (RFEP) Re - designated English proficient 60.79 (P) 52.14 (P) Male (NES) Native English speakers 45.56 (P) 36.91 (AH) (LEP) Limited English proficient 35.26 (AH) 26.61 (AM) (RFEP) Re - designated English proficient 55.21 (P) 46.56 (P) Note . These estimates are based on an average - age student [ about seventh grade] enr olled in a AM = Apprentice Middle; AH = Apprentice High; P = school that is average on poverty rate. Proficient . Results: Reading

  16. Results: Math 16

  17. Results: RQ 3 (comparing LAS to ACCESS) • Only RFEP students in this analysis • Multiple regression analysis with predictors: SES, Age, years after re-designation, test type-LAS vs. ACCESS • Results: Both tests were equally effective in predicting academic scores (in math, ACCESS-RFEP students did slightly better than those reclassified by LAS)

  18. Results/Conclusions • RQ1: After controlling for gender, age, and student- and school-level socio-economic status, RFEP students significantly outperformed LEP and NES students on state reading and mathematics test. • RQ2: High-poverty schools had a smaller negative impact on RFEP students achievement. • RQ3: ACCESS differentiated between LEP and RFEP students at least as well as LAS, without requiring a qualitative feedback from teachers.

  19. Implications • Research: • Explore academic achievement of RFEP students—when feasible disaggregated by types of language support programs received in the past—in higher grades and other content areas. • Explore potential causes of RFEP students’ high academic achievement.

  20. Implications • Theory: • This study addressed a deficit view of language minority students by highlighting the strong academic achievement attained by former LEP students. • Practice: • Additional support for programs that lead to English proficiency and, thus, enable ELLs to attain high academic achievement is warranted. • Reclassification policies based on an ACCESS composite score of “5” appears to adequately differentiate between LEP and RFEP students without requiring additional input from teachers.

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