Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities

Statewide accountability programs are incorporating academic growth estimates for general assessments. This transition focuses attention on modeling growth for students with significant cognitive disabilities (SWSCD) who take alternate assessments based on alternate achievement standards (AA-AAS), a...

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Main Author: Farley, Daniel
Other Authors: Stevens, Joseph
Language:en_US
Published: University of Oregon 2017
Subjects:
Online Access:http://hdl.handle.net/1794/22787
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spelling ndltd-uoregon.edu-oai-scholarsbank.uoregon.edu-1794-227872018-12-20T05:48:37Z Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities Farley, Daniel Stevens, Joseph AA-AAS Accountability Alternate assessment Growth Students with significant cognitive disabilities Statewide accountability programs are incorporating academic growth estimates for general assessments. This transition focuses attention on modeling growth for students with significant cognitive disabilities (SWSCD) who take alternate assessments based on alternate achievement standards (AA-AAS), as most states attempt to structure their AA-AAS systems as similarly as possible to their general assessments (GA). Test scaling, group heterogeneity, small sample sizes, missing data, and the use of status-based assessments that were not necessarily designed to measure a developmental continuum complicate modeling growth for SWSCD. This study addressed these challenges by: (a) analyzing test results from a common scale, (b) modeling achievement and growth for students in multiple demographic and exceptionality categories, and (c) using multiple cohorts to increase sample sizes. Latent growth curve modeling (LGCM) was used to define growth estimates based on exceptionality, sex, race, and economic disadvantage. Unconditional latent class growth analysis (LCGA) was used to determine the number of homogeneous subgroups that existed within the heterogeneous population of SWSCD for subsequent growth mixture modeling (GMM). Unconditional GMM was used to define the number of homogeneous subgroups of students with similar intercept and growth patterns within the overall population of SWSCD. Discriminant function analysis (DFA) including student exceptionality, sex, race, and economic disadvantage status was also used to analyze class membership post hoc. SWSCD with different exceptionalities generally had significantly different average initial achievement but growth rates that did not differ significantly from each other. SWSCD classified as economically disadvantaged performed significantly lower than their peers in initial achievement, yet exhibited growth rates that were not statistically different than the reference group. This study also found evidence for two separate latent classes of students with exceptionalities on the Oregon AA-AAS. The first class had lower achievement and larger growth rates, while the second class had higher achievement and slower growth rates. Students identified as SLD and CD were generally higher-performing, while students identified as ID, ASD, and OI were lower performing across all analytic models. 2017-09-27T21:44:09Z 2017-09-27T21:44:09Z 2017-09-27 Electronic Thesis or Dissertation http://hdl.handle.net/1794/22787 en_US All Rights Reserved. University of Oregon
collection NDLTD
language en_US
sources NDLTD
topic AA-AAS
Accountability
Alternate assessment
Growth
Students with significant cognitive disabilities
spellingShingle AA-AAS
Accountability
Alternate assessment
Growth
Students with significant cognitive disabilities
Farley, Daniel
Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities
description Statewide accountability programs are incorporating academic growth estimates for general assessments. This transition focuses attention on modeling growth for students with significant cognitive disabilities (SWSCD) who take alternate assessments based on alternate achievement standards (AA-AAS), as most states attempt to structure their AA-AAS systems as similarly as possible to their general assessments (GA). Test scaling, group heterogeneity, small sample sizes, missing data, and the use of status-based assessments that were not necessarily designed to measure a developmental continuum complicate modeling growth for SWSCD. This study addressed these challenges by: (a) analyzing test results from a common scale, (b) modeling achievement and growth for students in multiple demographic and exceptionality categories, and (c) using multiple cohorts to increase sample sizes. Latent growth curve modeling (LGCM) was used to define growth estimates based on exceptionality, sex, race, and economic disadvantage. Unconditional latent class growth analysis (LCGA) was used to determine the number of homogeneous subgroups that existed within the heterogeneous population of SWSCD for subsequent growth mixture modeling (GMM). Unconditional GMM was used to define the number of homogeneous subgroups of students with similar intercept and growth patterns within the overall population of SWSCD. Discriminant function analysis (DFA) including student exceptionality, sex, race, and economic disadvantage status was also used to analyze class membership post hoc. SWSCD with different exceptionalities generally had significantly different average initial achievement but growth rates that did not differ significantly from each other. SWSCD classified as economically disadvantaged performed significantly lower than their peers in initial achievement, yet exhibited growth rates that were not statistically different than the reference group. This study also found evidence for two separate latent classes of students with exceptionalities on the Oregon AA-AAS. The first class had lower achievement and larger growth rates, while the second class had higher achievement and slower growth rates. Students identified as SLD and CD were generally higher-performing, while students identified as ID, ASD, and OI were lower performing across all analytic models.
author2 Stevens, Joseph
author_facet Stevens, Joseph
Farley, Daniel
author Farley, Daniel
author_sort Farley, Daniel
title Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities
title_short Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities
title_full Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities
title_fullStr Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities
title_full_unstemmed Exploring Reading Growth Profiles for Middle School Students with Significant Cognitive Disabilities
title_sort exploring reading growth profiles for middle school students with significant cognitive disabilities
publisher University of Oregon
publishDate 2017
url http://hdl.handle.net/1794/22787
work_keys_str_mv AT farleydaniel exploringreadinggrowthprofilesformiddleschoolstudentswithsignificantcognitivedisabilities
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