The Maryland High School Assessments (HSA) are tests that ...

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14 HSA ij = β oj + β 1j *(FARM03) + β 2j *(SPED03) + β 3j *(ELL03) + β 4j *(ZMSAMS) + β 5j *(ZMSARS) + β 6j *(ZGPA0203) +β 7j *(SEX)+ β 8j *(ATTEND) + + r ij where HSA English score is expressed as a function of FARM03, β 1j ; student SPED, β 2j ; students’ ELL03, β 3j ; MSA mathematics score at 2003, β 4j ; MSA reading score at 2003, β 5j ; student’s standardized GPA, β 6j ; students’ sex, β 7j ;students’ attendance percentage, β 8j ;and conditional error that remains after controlling for the schoollevel variables, r ij . The variance on the average score of the standardized English achievement of HSA may be modeled with the six school-level predictors -- high school’s percentage special education (HSSPED), high school’s percentage of ELL students (HSELL), high school’s percentage of students of poverty (HSFARMS), high school’s percentage of students attendance (HSATTEND), high school’s percentage of highly qualified teachers (HSHQT), and number of 9th grade students suspended (Suspended). Incorporating those variables led to the following changes to the schoollevel equations: β oj = γ oo + γ o1 *( HSSPED) + γ o2 *( HSELL) + γ o3 *( HSFARMS) + γ o4 *( HSATTEND) +γ o5 *( HSHQT) + γ o6 *( Suspended) + u oj where γ oo is the grand mean for HSA English reading score (overall intercept); γ o1 is the relationship between high school’s percentage of students taking SPED and HSA English score; γ o2 is the relationship between high school’s percentage of ELL students and HSA English score; γ o3 is the relationship between high school’s percentage of students taking FARMS and HSA English score; γ o4 is the relationship between high school’s percentage of students attendance and HSA English score; γ o5
15 is the relationship between high school’s percentage of highly qualified teachers and HSA English score; γ o6 is the relationship between number of 9th grade students suspended and HSA English score. Results are presented in Table 6 under System Four. Results are similar to the OLS regression analysis results with a few exceptions. First, the percentage of days attending school was not significant at the student –level. Second, only three out of the seven level-2 variables are significant: HSELL, HSFARMS and HSATTEND. That is, schools with higher percent of ELL students tend to get lower HSA average HSA scores. On the contrary, schools with higher percent of FARMS-eligible students tend to get higher HSA average scores. In addition, schools of higher percentage of attendance tend to get higher average HSA score. Summary and Discussion In this section of the paper we return to the original questions that we posed and present our findings organized around each of them. 1) To what extent is performance on the HSA predicted by prior performance on the related Maryland School Assessment (MSA) and/or other preceding examinations or available indicators of academic success? Several important predictors of HSA performance emerged from the study. These include two measures of reading (performance on MSA Reading and the Scholastic Reading Inventory, although that test is available in only one county), poverty (defined as FARMS-eligibility), special education, and ELL status. There was some evidence that a student’s attendance, English scores at midterm, and GPA also seem to be related to his or her performance on the HSA English 1 exam.
Page 1 and 2: 1 The Prediction of Performance on
Page 3 and 4: 3 To accomplish this purpose, the M
Page 5 and 6: 5 students are second language spea
Page 7 and 8: 7 In addition, six school-level pre
Page 9 and 10: 9 In the Equation, γ oo is the ove
Page 11 and 12: 11 associated with special educatio
Page 13: 13 tend to achieve high HSA English
Page 17 and 18: 17 2. Students with higher scale sc
Page 19 and 20: 19 examinations (the midterm test)
Page 21 and 22: 21 Table 1: Correlations for studen
Page 23 and 24: 23 Table 3: Correlations for studen
Page 25 and 26: 25 Table 5: OLS Regression Analysis

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