three independent variables alone could explain the dependent variables of promotion and MCAS ELA and Mathematics performance. Because our hypothesis was that school-based practices make a difference in ELL performance, we needed to con- firm that the three independent variables explained only a small proportion of the variance, if any.
Elementary Grades
Regression analyses revealed that the model did not significantly (p >.05) predict promotion rates in two out of the three years. However, in SY2008, the three independent variables explain a small portion of the variance: F(3,58) = 3.205, p<.05. R2 for the model was .142 and adjusted R2 was .098, indicating that nearly 10% of the variance in that year can be explained by percentage of low-income students, percentage of LEP students, and percent- age of LEP students in their first year in the U.S. Table 9.3 displays the unstandardized regression coefficients (B) and standardized regression coef- ficients (β) for each variable.
Regression analyses revealed that the model did not significantly (p >.05) predict MCAS proficiency rates for English Language Arts or Mathematics in any of the four years.
Table 9.3. Regression Coefficients for Elementary Promotion, SY2008
Predictor B
Intercept 79.92
Percent Low Income .200 .257
Percent LEP -.004 -.008
Percent LEP in first year in U.S. -.275 -.309
Table 9.4. Regression Coefficients for Secondary Promotion
SY2007 SY2008
Predictor B B
Intercept 53.62 74.05
Percent Low Income .520 .515 .278 .108
Percent LEP -.307 -.367 -.128 .091
Percent LEP in first year in U.S. NA NA -.138 -.178
Table 9.3. Regression Coefficients for Elementary Promotion, SY2008
Predictor B
Intercept 79.92
Percent Low Income .200 .257
Percent LEP -.004 -.008
Percent LEP in first year in U.S. -.275 -.309
Table 9.4. Regression Coefficients for Secondary Promotion
SY2007 SY2008
Predictor B B
Intercept 53.62 74.05
Percent Low Income .520 .515 .278 .108
Percent LEP -.307 -.367 -.128 .091
Percent LEP in first year in U.S. NA NA -.138 -.178
Table 9.5. Number of Schools with Standardized Residuals Greater than 0.75 across Years Number of Years Elementary Grades Secondary Grades
Promotion ELA Math Promotion ELA Math
One Year 21 10 7 9 3 4
Two Years 5 0 2 3 1 2
Three or Four Years 2 2 2 2 3 2
TOTAL 28 12 11 14 7 8
!
Figure 9.1. Standardized Residuals for High Performing Schools
Note: Data not analyzed for categories where n<15. 0 0.5 1 1.5 2 2.5 3
SY2006 SY2007 SY2008 SY2009
Standardized Residual
Quincy School ELA
Quincy School Math
Sarah Greenwood ELA
Sarah Greenwood Math
116 Learning from Consistently High Performing and Improving Schools for English Language Learners in Boston Public Schools Learning from Consistently High Performing and Improving Schools for English Language Learners in Boston Public Schools 117 To identify two of these schools for further study,
a variety of factors were considered, including the contextual knowledge of the Office of English Language Learners. The goal was to maximize information that could be shared across the district. We again took into account the predominant native language of the ELL students in the school. One of the secondary schools was a middle school with a Chinese SEI program, and since Chinese was already represented in one of the high performing schools, this secondary school was eliminated. The school also experienced a dip in MCAS Mathemat- ics in SY2009. The other secondary school, Excel High School with a Vietnamese SEI program, was identified as the third case study school. Of the two elementary schools with steady improvement, Ellis Elementary, which has an SEI-Spanish program, was selected because it had a stronger upward trajectory and higher standardized residuals than the other elementary school.
Thus, we finalized the selection of two steadily im- proving case study schools to Excel High School and Ellis Elementary School. Their standardized residuals during the study years are shown in Figure 9.2. In summary, four BPS schools were identified for further study using qualitative methods, which are shown in Table 9.6.
This selection of schools does not include middle schools, serving Grades 6-8. Although two middle schools were identified in the regression analyses, they were not chosen for case studies because of contextual reasons, as described previously.47 While this selection of schools represents three of the five major languages spoken by BPS students, it does not represent Haitian Creole or Cape Verdean Creole. Finally, three of the ELL programs are SEI Language Specific programs. None of the schools identified in the multiple regression analyses were SEI Multilingual program schools.
for promotion do not exist across schools, whereas they do for MCAS proficiency.
Of the two elementary cases in Table 9.5, the schools identified as having high performance for multiple years in both ELA and Mathematics were Josiah Quincy Elementary School and Sarah Greenwood K-8 School. These two schools repre- sented two different language groups, Chinese and Spanish, respectively. They also represented two different ELL program types, SEI Language Specific and Two-Way Bilingual.
For the secondary grades, three schools were identi- fied for multiple years in both ELA and Mathemat- ics, though ultimately we chose not to study any of these schools for their secondary grades. One of the secondary schools had an SEI Chinese program. Since there are only four BPS schools with SEI Chinese programs, we did not want to choose two of them as case study schools. Since the Quincy Elementary School serves a larger number of LEP students than the secondary school, the Quincy School was chosen. Another secondary school’s SEI Language Specific program had been converted to an SEI Multilingual program in SY2010. Therefore, this middle school’s program with the strong results was no longer present to be studied. Finally, the third secondary school was Sarah Greenwood K-8 School. While emerging from the multiple regres- sion analysis of the secondary school database with high standardized residuals, the school had too few cases for two of the four years and declining middle school proficiency rates during the remaining two
years. Therefore, we chose not to study the sec- ondary grades at the Sarah Greenwood K-8 School. Thus, we finalized the selection of two high performing case study schools to two elementary schools, the Quincy School and Sarah Greenwood (Grades K-5 only). Their standardized residuals dur- ing the study years are shown in Figure 9.1. Both schools’ standardized residuals for ELA and Math MCAS proficiency exceed 1.0 for all years, mean- ing that their LEP students at MEPA Levels 3 and 4 performed consistently higher than predicted. As noted, a standardized residual of 0.75 is interpreted as MCAS proficiency distinctly higher than schools with similar demographics (Crone & Teddlie, 1995).
Steadily Improving Schools
Our analysis revealed only two elementary schools performing at high levels in multiple areas (i.e., pro- motion, ELA, Mathematics) for at least three years. In order to identify schools that were making sub- stantial gains in outcomes over the four-year study period, additional analyses were conducted. Using the standardized residuals from the results of the regression analyses explained above, we examined the trajectories of each school for SY2006-SY2009 to identify schools whose standardized residuals showed meaningful improvements in MCAS pro- ficiency rates of LEP MEPA Level 3 and 4 students for ELA and Mathematics, ending the study period with a standardized residual of greater than 0.75. Two secondary schools and two elementary schools met this definition.
Table 9.5. Number of Schools with Standardized Residuals Greater than 0.75 across Years Number of Years Elementary Grades Secondary Grades
Promotion ELA Math Promotion ELA Math
One Year 21 10 7 9 3 4
Two Years 5 0 2 3 1 2
Three or Four Years 2 2 2 2 3 2
TOTAL 28 12 11 14 7 8
!
Figure 9.1. Standardized Residuals for High Performing Schools
Note: Data not analyzed for categories where n<15. 0 0.5 1 1.5 2 2.5 3
SY2006 SY2007 SY2008 SY2009
Standardized Residual
Quincy School ELA
Quincy School Math
Sarah Greenwood ELA
Sarah Greenwood Math
Figure 9.2. Standardized Residuals for Improving Schools
Note: Data not analyzed for categories where n<15. -1 -0.5 0 0.5 1 1.5 2 2.5 3
SY2007 SY2008 SY2009
Standarized Residual Ellis ES ELA Ellis ES Math Excel HS ELA Excel HS Math
NOTE: Same as Table 1.2 in Chapter 1
Table 9.6. Case Study Schools
Grades Studied Predominant Native Language ELL Program Type Quincy School K-5 Chinese dialects SEI – Chinese
Sarah Greenwood K-5 Spanish Two-Way Bilingual (Spanish)
Ellis ES K-5 Spanish SEI – Spanish
Excel HS 9-12 Vietnamese SEI – Vietnamese !
Table 9.7. Site Visit Data Collection
# of Class Observations # of Staff Interviewed (Individual & Group) # of Parents and Alumni Interviewed (Groups) # of Community Partners Interviewed or Observed (Individual) Quincy School 15 31 5 4 Sarah Greenwood 16 28 5 7 Ellis ES 9 13 1 0 Excel HS 16 17 6a 1 TOTAL 56 89 13 12
a Alumni were adult graduates of the school who attended the school during the study period. Alumni were interviewed only at
Excel HS.