IMPACTS OF SERVICE DELIVERY ON SLD IDENTIFICATION, TEACHER EMPLOYMENT, AND OUTCOMES Dr. Paul Sindelar Christopher Leko University of Florida

Historical Trends Historically, there have been consistent annual increases in the numbers of SWDs and SLDs, age 6 to 21, and SETs in the United States. However, since 2005, there have been overall declines in the number of SWDs and SETs. The decline in the number of students with SLD actually began sooner, in 2002.

SETs, 1988 to 2003 (Boe, 2006)

Cumulative Growth in SWDs and SETs, 1988 to 2003 (Boe, 2006)

Number of SWDs

Number of Students with SLD from

Number of SETs from

Number of SETs from

The Numbers Total number of SWDs has fallen by 4.5% Total number of SWDs with SLD has fallen by 12.9% Total number of SETs has fallen by 13.0% There has also been a 9.6% increase in the student/teacher ratio, from 14.3 to The percentage of highly qualified teachers has increased between 2006 and 2010, from 88.8% to 94.2%... …but the total number of highly qualified teachers has declined to levels lower than anytime in the last decade

Possible Reasons for Decline Economic downturn? Policy Implementation? Policies designed to support struggling students before special education intervention is required Inclusion Reading First RTI Boe et al. (2012) conducted a pilot study that analyzed the relationship between measures of reform and the change

Inclusion Identified as the proportion of all SWDs placed in general education classrooms for at least 80% of their school day. Correlated with the changes in SLD prevalence and number of SETs Results Significant negative correlation with the reduction in SLD prevalence (-.27) Significant negative correlation with the reduction in number of SETs (-.31) Interpretation: As percentage of included SWDs increases, SLD prevalence and SET employment decrease

Reading First Defined as the proportion of all elementary schools within a state at which RF was implemented by Correlated with the changes in SLD prevalence and number of SETs Results Significant negative correlation with the reduction in SLD prevalence (-.27) Significant negative correlation with the number of SETs employed (-.61) Interpretation: As the proportion of schools implementing RF increases, SLD prevalence and SET employment decrease.

RTI Used Zirkel and Thomas’ (2010) policy analysis to categorize states into states that did and did not mandate RTI for SLD identification by Compared the change in SLD prevalence in states that did and did not have RTI mandated by Results: In states that required RTI, SLD prevalence declined by 2.53 per 1,000 public K-12 students In states that did not, SLD prevalence declined by This difference is based on limited date (n = 3 states with RTI mandates) but is almost significant (p = 0.126) Interpretation: Reduction in SLD prevalence seems to be greater in states with RTI mandates than in states with no mandate.

Two Possible Explanations There are two possible explanations for these changes: Innovations are having the desired effect: Students are receiving early intervention and thus don’t require special education services later. Struggling schools have less to spend on special education Hiring fewer teachers and identifying fewer students

Purpose of this analysis The purpose of this analysis is to discuss whether the changes in both SLD prevalence and SET employment are associated with successful implementation of innovations. Analysis was performed using outcome data from both NAEP and OSEP

NAEP Outcomes Based of the changes between the NAEP administrations. A nationally representative sample of 4 th and 8 th grade from 94 geographic sampling units. Scores are reported based on the percentage of children below basic, at basic, at proficient, and at advanced for both SWDs and all students We analyzed the changes in the percentage of SWDs and percentage of all students below basic between 2003 and 2009 (a composite of reading and math). Data used in the analysis were collected using publically accessible NAEP data collected through the online NAEP data explorer

OSEP Annual data are collected on the numbers of SWDs who receive a major (10+ days OSS) suspension from school. These are available on a wide range of years and are reported annually on a publically accessible website (ideadata.org) We analyzed the changes in the numbers between 2006 and 2010 Data were collected through ideadata.org

Common Core of Data Data are collected annually regarding both fiscal and non- fiscal data. We collected data on the number of public K-12 students and teachers between 2004 and Data were collected from the CCD’s website (

Expectations about Outcomes If Reform gets better assistance to struggling students faster, we should see the % of all students below basic proficiency falling with increases in Reform. What about the outcomes for SWD, specifically % of SWD Below Minimum Proficiency? Students whose difficulties are ameliorated may never be classified SLD Those still classified SLD are likely have the greatest difficulties As a result, Reform could well be associated with an increase in the % of SWD Below Basic Proficiency even if ALL students still classified SWD are performing at a higher level due to reform.

Methodology Focus on state level changes (mid to late 2000s) to remove influence of confounding variables that differ across states but change little over time We first conduct a factor analysis of: # of elementary schools implementing RF Change in % of students age 6-11 with SLD that spent at least 80% of the school day in a general education setting, 2004 to 2009 Change from in the number of students age 6-11 with a SLD per 100 elementary students, 2004 to We use this factor analysis to derive a latent variable, Reform.

Factor Analysis NOTE from Jim: I’d put either Table 2 (below) here or at least discuss the correlations. RF%ΔInclusionΔSLD/ENR ΔInclusion (0.005) Δ(SLD/ENR) (0.01)(0.029) Reform (NA)

Methodology Five regressions of resource and outcome measures on Reform and control variables. Dependent Variables: Change in Teacher:student ratio in SE (2004 to 2009) Change in Teacher:student ratio in GE Change in % all students below basic Change in % SWDs below basic Change in % SWDs with Major OSS (2006 to 2010) Independent variables other than reform: Change in Teacher:Student ratios included in outcome regressions

Results Reform was significantly associated with: Changes in SET/SWD (-0.52, p =.027) Changes in GET/GES (0.18, p =.032) The change in % of all students below basic (-1.51, p = <.001) The change in the number of students with a major suspension (- 0.42, p = 0.12) There was a non significant relationship between reform and the change in the percentage of SWDs below basic (0.52, p =.607) Increases in SET/SWD and GET/GES associated with a lower percent below basic on NAEP for all students and for SWD, but not significantly related to OSS

Results: Change in Revenue Change in state and local revenue had a significant relationship with changes in GET/GES (0.193, p =.065) Change in state and local revenue had a non significant relationship with change changes in SET/SWD (-0.295, p =.297)

Interpretations The greater the reform, the greater the reduction in teacher:student ratio in SE the greater the increase in teacher:student ration in GE the lower the % of all kids scoring below standard on NAEP the greater the % of SWDs scoring below standard (not statistically significant AND not evidence reform led to poorer performance by individual SWD if it were) the smaller the number of out of school suspensions for SWDs

Discussion Reform implementation seems to be having desired effects on Overall NAEP performance Out of school suspensions for SWDs Reform implementation not significantly associated with changes in % SWD below proficient on NAEP Reform also seems to be associated with shift of resources from special education to general education Reform is associated with a reduction in SET:SWD ratio Reform is associated with an increase in GET:ENR ratio Increases in these ratios are in turn associated with better NAEP performance, so these changes have offsetting indirect effects on NAEP performance

…reversing a historical pattern (Boe, 2006)