1. WBU-ICEVI Joint General Assemblies
The Impact of the Expanded Core Curriculum on Select Quality of Life Indicators for Students with Visual Impairment
ICEVI Day, 22 August 2016
WBU-ICEVI Joint General Assemblies
Orlando, FL

2. The NLTS2 – Dataset National Longitudinal Transition Study 2
Funded by the United States Department of Education, authorized by IDEA amendments
Gathered data from school districts, parents of students with disabilities, the educators of students with disabilities, and from students with disabilities themselves.
Began in the school year with students who were in at least grade 7 or between the ages of 13 and 16, continued through the school year.
Results can be generalized to students with disabilities in general, as well as to each of the individual disability categories (Levine, Marder, & Wagner, 2004).
Captured information related to each of the ECC areas, with the exception of sensory efficiency, while students were in school.

3. Project Information Institute for Education Sciences Grant #R32409288
$232,581
Used data from Waves 1 and 4

4. There are three types of lies:
Keep in Mind …
There are three types of lies:
Lies
Damn Lies, and
Statistics
Mark Twain

5. Factor Analysis
188 submitted for Exploratory Factor Analysis with 9-factor solution, using Principal Components method with Varimax Rotation, Factor Loadings > .5
Resulted in different factors in each educational setting

6. So, What?
8 of the 9 ECC components appeared to be addressed in this sample of youth and adults with visual impairments
But little distinct pattern
Not discrete components
Failed to find a relationship between identified factors and composite variable of “adult success”

7. So What, continued
For those adults engaged in competitive employment, best predictor variables were:
Social behaviors and opportunities
Career and transition services and instruction
Alternative access (braille & large print), but in opposite direction
More braille and large print = less chance of employment?
In general education settings, no factors emerged as predictors

8. So What, continued
When general education and special education settings are considered together, more related services received seems to predict less opportunity for competitive employment
But, which came first?

9. Preliminary Analyses Wave 5
MANOVA to investigate SEM results (difference in means with several dependent variables)
Simplified from the full model to 3 outcomes of interest:
Any Paid Employment Outside the Home
Lodging (living independently from parent[s])
Post-Secondary Education
Use a MANOVA analyses to investigate why the SEM results acted in unexpected ways.
Steps:
Simplified the outcome from the full QOL model to the 3 area that have been identified in Gen Sped literature as indicators to support post-secondary transition
Repeated the factor analysis that Dr. Ferrell used for Wave 4,
One change—Co-Varied receiving “Related Services” with the assumption that high school students who are receiving more services are actually students who have additional exceptionality that were not necessarily identified on their IEPs in addition to their vision impairment.

10. One Change Co-varied receiving “Related Services”
Assumption that high school students who are receiving more services are students who have additional disabilities
Not necessarily identified multiple disability on IEPs

11. Sample Wave 5 (2009-2010) Youth with visual impairments only
No additional exceptionality
Sample Size
Unweighted n = 230
Weighted n = 26,975

12. Factors Independent Variables: Covariate:
Factor 1: Categorical: Career
Factor 2: Dichotomous: Career, Transition
Factor 3: Orientation and Mobility Skills
Factor 4: Social Recreation & Leisure
Factor 5: Alternative—Technology
Factor 6: Alternative—Accommodations (i.e., braille)
Factor 7: Parent Expectations
Factor 8: Independence
Covariate:
Factor 9: Related Services

13. Model 1: Any Paid Work Outside of Home
Factor
Factor Description
Tests of Main Effects-Wald F
 F1
Categorical-Career Transition/ Job Experience
4.439 F6
Alternative Accommodations (i.e., Braille)
10.158 F8
Independence
6.126

14. Model 2: Living Independently
Factor
Factor Description
Tests of Main Effects-Wald F F1
Categorical-Career Transition/Job Experience
8.548 F2
Dichotomous-Career Educational Supports
4.558 F3
Orientation & Mobility
8.439 F5
Compensatory Technology
5.114 F6
Alternative Accommodations (i.e., Braille)
5.756 F7
Parental Expectations
4.836 F8
Independence
9.170

15. Model 2: Living Independently
Note: at alpha = .05
F4 Social, Recreation, & Leisure (p = .047; Wald F = 2.705)
is also statistically significant and could be retained.

16. MANOVA 3 Findings Outcome Variable: Model F1+F2+F3+F4+F5+F6+F7+F8
Transition To Post-Secondary Education
n = 230; df = 174
Model F1+F2+F3+F4+F5+F6+F7+F8
Covariate F9 (Related Services)
Accounted for 29.4% of variance in employment outcomes.

17. Model 3: Post-Secondary Education
Factor
Factor Description
Tests of Main Effects-Wald F F1
Categorical-Career: Transition/Job Experience
7.114 F2
Dichotomous-Career: Educational Supports
5.933 F3
Orientation & Mobility
3.964 F4
Social, Recreational, & Leisure
11.666 F6
Compensatory Accommodations (i.e., Braille)
7.477 F7
Parental Expectations
3.165 F8
Independence
7.224

18. Model 3: Post-Secondary Education
Note: at alpha = .05
F5 Compensatory Technology (p = .006; Wald F = 3.756)
is also statistically significant and could be retained.

19. Limitations? Same as before:
> 10,000 variables
Much missing data, especially from teachers
Number of dichotomous variables required recoding of all variables into dichotomous values
Only 11.4% of sample competitively employed at Wave 4, even though out of school > two years
New: Wave 5 (n = 230) 30.4% reported full-time employment in last job

20. Send-Offs
For the sample of youth with visual impairments only, up to 8 of the 9 ECC components appeared to be addressed
Consistently significant in all .001 models:
Independence
Alternative accommodations
Categorical Career (job experience)
Adjust alpha to .05 and Alternative Technology also significant

21. Send-Offs, continued
For the Wave 5 sample of young adults with only visual impairments best predictor variables for employment, independent living, and post-secondary education were:
Career and transition services and instruction
Alternative access (braille & large print)
Independence skills

22. Send-Offs, continued
Outcomes for participation in paid employment, post-secondary education, and living independently differ within the total population of young adults identified as having visual impairment.

23. Questions To Ask Ourselves
Where is the disconnect?
Why is this sample of youth as unemployed as blind adults were 50 years ago?
Are we expending our energy in the right place at the right time?

24. Lessons Challenge your assumptions! Don’t stop looking/investigating
Ask questions

25. Thank you, merci, gracias, grazie, danke, cпасибо, obrigado, 谢谢
Kay Alicyn Ferrell, PhD
Kathryn D Botsford, PhD