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The Characteristics of Non-Proficient Special Education and Non-Special Education Students on Large-Scale Assessments
Yi-Chen Wu, Kristi Liu, Martha Thurlow, & Sheryl Lazarus
National Center on Educational OutcomesUniversity of Minnesota
This paper was developed, in part, with support from the U.S. Department of Education, Office of Special Education Programs grants (#H373X070021). Opinions expressed herein do not necessarily reflect those of the U.S. Department of Education or Offices within it.
NCEO Web site(http://www.cehd.umn.edu/nceo/)
Outline
BackgroundAlternate Assessment based on Modified Academic
Achievement Standards (AA-MAS) QuestionsMethod
Data sourceAnalytical Techniques
ResultsConclusions
AA-MAS
4
States may count up to 2% of students participating in an AA-MAS for annual yearly progress (AYP).
Students with IEPAA-MAS is phasing out
on August 23, 2013, the U.S. Department of Education published a proposed rollback of regulation that allowed the AA-MAS (NCEO, 2014).
The assessment may be going away, but struggling learners with disabilities still exist.
Candidates for AA-MAS
Students with low performing belief that low performance on the assessment
indicates a need for students to have a different type of assessment in order to demonstrate their knowledge and skills in a content area.
Students below proficiency levelFederal regulations state that eligible AA-MAS
participants should be “not proficient” on grade-level content within the year of their IEP
Previous study on low performing students
6
Wu, Lazarus, & Thurlow, 2010males, students of color and students from low-income
backgrounds, regardless of whether they have a disability=>LP
If low performing students with these demographic characteristics also have a disability, they are much more likely to remain in the bottom 10th percentile across multiple years of the assessment
AA-MAS participants were significantly more likely to be from minority racial or ethnic backgrounds (Shaftel & Rutt, 2012)
Is proficiency more reasonable?
Individual states set score cut-points for proficiency in different places, depending on the rigor of the state assessment and related standards.
It may be that the group of non-proficient students with disabilities, as stated in federal regulations, is more representative of the characteristics of the total population in a state.
Questions
How does the percent of NP students who receive SPED services compare to the percent of NP Non-SPED students?
How do the demographic characteristics of PNP SPED students compare to the demographic characteristics of PNP Non-SPED students?
Method
Data source
Method-Definition
Non-Proficient Studentsat or below the cut-off score for proficiency
Persistent Non-Proficient Students (PNP)students who were in the non-proficient group all three
years of our analyses.Demographic variables
GenderWhite vs. non-whiteLow income (free/reduced lunch)
Results—RQ1
How does the percent of NP students who receive SPED services compare to the percent of NP Non-SPED students?
Number of students—Reading
10% SPED 90% Non-SPED
Number of students—Math
10% SPED 90% Non-SPED
Proportion—NP Reading
Non-SPED>SPEDStudents in SPED are more likely to be NP
Proportion—NP Math
Non-SPED>SPEDStudents in SPED are more likely to be NP
Proportion—PNP Reading
No pattern across all 4 states
# of NPs
Proportion—PNP Math
# of NPs
Students in SPED are more likely to be PNP (70 vs. 20; 15 vs.14)More than 60% of NP became PNP in state 2
Proportion—PNP
Reading: no pattern foundNP students in SPED were more likely to remain NP in
each of the three years compared to their SPED peers for State 4.
MathNP students in SPED were more likely to remain NP in
each of the three years compared to their Non-SPED peers.
Results—RQ2
How do the demographic characteristics of PNP SPED students compare to the demographic characteristics of PNP Non-SPED students?
Figure 1. Percentage of State 1’s male and female students in the persistently non-proficient, and total, populations on the state reading assessment by special education status
Gender—Reading (State 1)1a. G5R 1b. G8R
Figure 2. Percentage of State 1’s male and female students in the persistently non-proficient, and total, populations on the state math assessment by special education status
Gender—Math (State 1)
2a. G5M 2b. G8M
Figure 1-1. Percentage of State 4’s male and female students in the persistently non-proficient, and total, populations on the state reading assessment by special education status
Gender—Reading (State 4)
1a. G5R 1b. G8R
Figure 2-1. Percentage of State 4’s male and female students in the persistently non-proficient, and total, populations on the state math assessment by special education status
Gender—Math (State 4)
2a. G5M 2b. G8M
Gender—Across states
Similarity PNP are more likely to be malesMore than 50% of SPED population are males
DifferencesThe difference between SPED and non-SPED is quite
different between statesDifference between males and females are not the
same (the gap is bigger on state 1, not on state4)
Gender—Within a state
Within a state, the pattern is consistent across gradesMost of PNP students who received SPED are more
likely to be malesWithin a state, the pattern is not consistent across content areasThe gap is smaller on PNP male between SPED and
non-SPED on Reading, but the gap is bigger on mathMost of PNP students who did not receive SPED are
more likely to be females (True for state 4 math, not for reading).
Figure 3. Percentage of State 1’s white and non-white students in the persistently non-proficient, and total, populations on the state reading assessment by special education status
Ethnicity—Reading (State 1)
3a. G5R 3b. G8R
Figure 4. Percentage of State 1’s white and non-white students in the persistently non-proficient, and total, populations on the state Math assessment by special education status
Ethnicity—Math (State 1)
4a. G5M 4b. G8M
Figure 3-1. Percentage of State 4’s white and non-white students in the persistently non-proficient, and total, populations on the state reading assessment by special education status
Ethnicity—Reading (State 4)
3a. G5R 3b. G8R
Figure 4-1. Percentage of State 4’s white and non-white students in the persistently non-proficient, and total, populations on the state Math assessment by special education status
Ethnicity—Math (State 4)
4a. G5M 4b. G8M
Ethnicity—Across states
Similarity The proportion of the PNP is NOT similar to the whole population
Differences The proportion on SPED PNP population is about 50-50 for state
1 across grades and content areas, but not for state 4. Most PNP students with SPED are more likely to be White (for
state 4; state 1 is 50-50) The difference between SPED and non-SPED is quite different
across states (gap is smaller on state 1) Most of PNP students who receive SPED are more likely to be
non-white (True for state 4, not for state 1).
Ethnicity—Within a state
The pattern is consistent across grades and content areas for state 1, but not for state 4.
The pattern is not consistent across content areasThe gap between SPED and non-SPED is bigger on
Reading than on math across grades for state 4.The gap between SPED and non-SPED is bigger on
Grade 8 than on grade 5 for both content areas.
Figure 5. Percentage of State 3’s low income and non-low income fifth and eighth grades students in the persistently non-proficient and total population on the state reading assessment by special education status
Income Level—Reading (State 3)
5a. G5R 5b. G8R
Figure 6. Percentage of State 3’s low income and non-low income fifth and eighth grades students in the persistently non-proficient and total population on the state math assessment by special education status
Income Level—Math (State 3)
6a. G5M 6b. G8M
Figure 5-1. Percentage of State 4’s low income and non-low income fifth and eighth grades students in the persistently non-proficient and total population on the state reading assessment by special education status
Income Level—Reading (State 4)
5a. G5R 5b. G8R
Figure 6. Percentage of State 4’s low income and non-low income fifth and eighth grades students in the persistently non-proficient and total population on the state math assessment by special education status
Income Level—Math (State 4)
6a. G5M 6b. G8M
Low Income—Across states
Similarities The proportion of the PNP is different from the whole population Most PNP students are more likely to be from low income
regardless the disability statusDifferences
The difference between SPED and non-SPED is quite different across states (the gap in grade 5 is bigger than grade 8 for state 1; However, the gap is bigger in grade 8 than grade 5 for state 4.)
Low Income—Within a state
Within a state, the pattern is consistent across grades and content areas for state 1, but not for state 4.
Within a state, the pattern is not consistent across content areasThe gap between SPED and non-SPED is bigger on
Reading than on Math across grades for state 4.The gap between SPED and non-SPED is bigger on
Grade 8 than on grade 5 for both content areas.
Conclusion
Not exactly same as the findings in Wu et al.’s low performing study (Wu et al, 2012). The possible reason might be due to the cut score for
the proficiency level is quite different among states. Even though some of the characteristics were similar across states (e.g., low-income level), the differences between the SPED and Non-SPED population were not the same across states.
Not the same pattern across the two content areas of reading and math.
Conclusions
There were some similarities in the characteristics of PNP students, such as male, non-white and low-income.
The percentages of PNP students for one state’s content assessments were stable for SPED and non-SPED populations in one of the characteristics, but the same was not the case for other states.For example, in state 1, on the math assessment there were
different patterns for gender and for race/ethnicity. There were relatively stable percentages of male versus
female students in the PNP SPED and Non-SPED groups compared to the total population tested.
Final Comments
AA-MAS is going away, but these students are not going away
The results provide important information about a group of kids who will be in the next generation
assessments it is important to continue to analyze data to see how
this population is doing over time.
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