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Direct linkCirino, Paul T.; Fuchs, Lynn S.; Elias, John T.; Powell, Sarah R.; Schumacher, Robin F. – Journal of Learning Disabilities, 2015
The purpose of this study was to compare subgroups of students with various forms of learning difficulties (< 25th percentile) on cognitive and mathematics characteristics. Students with mathematics difficulty (MD, n = 105), reading difficulty (RD, n = 65), both (MDRD, n = 87), or neither (NoLD, n = 403) were evaluated on an array of cognitive…
Descriptors: Learning Disabilities, Student Characteristics, Cognitive Ability, Mathematics Skills
Shippen, Margaret E.; Miller, Alan; Patterson, DaShaunda; Houchins, David E.; Darch, Craig B. – Rural Special Education Quarterly, 2014
Addressing the reading needs of adolescent learners living in rural areas may create challenges for teachers and administrators in the age of accountability. This study addressed this issue by implementing two explicit instructional approaches with struggling adolescent readers (n = 49) in a rural middle school in the southeastern United States.…
Descriptors: Middle School Students, Adolescents, Rural Schools, Reading Improvement
Swanson, H. Lee; Kudo, Milagros; Guzman-Orth, Danielle – Journal of Educational Psychology, 2016
This study investigated the prevalence and stability of latent classes at risk for reading disabilities (RD) in elementary-aged children whose first language is Spanish. To this end, children (N = 489) in Grades 1, 2, and 3 at Wave 1 were administered a battery of reading, vocabulary, and cognitive measures (short-term memory [STM], working memory…
Descriptors: English Language Learners, At Risk Students, Reading Difficulties, Learning Disabilities
King, Wayne M.; Giess, Sally A.; Lombardino, Linda J. – International Journal of Language & Communication Disorders, 2007
Background: The marked degree of heterogeneity in persons with developmental dyslexia has motivated the investigation of possible subtypes. Attempts have proceeded both from theoretical models of reading and the application of unsupervised learning (clustering) methods. Previous cluster analyses of data obtained from persons with reading…
Descriptors: Statistical Analysis, Reading Difficulties, Models, Databases
