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.