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Buzhardt, Jay; Greenwood, Charles R.; Jia, Fan; Walker, Dale; Schneider, Naomi; Larson, Anne L.; Valdovinos, Maria; McConnell, Scott R. – Exceptional Children, 2020
Data-driven decision making (DDDM) helps educators identify children not responding to intervention, individualize instruction, and monitor response to intervention in multitiered systems of support (MTSS). More prevalent in K-12 special education, MTSS practices are emerging in early childhood. In previous reports, we described the Making Online…
Descriptors: Data Analysis, Decision Making, Special Education, Infants
Peer reviewed Peer reviewed
Mercer, Cecil D.; And Others – Exceptional Children, 1979
Horizontal and vertical prediction performance matrix analyses on 15 early identification studies of children at risk for school problems suggested ten conclusions, including the following: that teacher perceptions and behavioral skill analyses seem to be efficient and useful predictors of school problems; and that physical indices, developmental…
Descriptors: Exceptional Child Research, Identification, Infants, Prediction
Peer reviewed Peer reviewed
Bailey, Donald B., Jr.; And Others – Exceptional Children, 1990
Entry-level university programs (N=449) in eight disciplines were surveyed concerning students' preparation to provide services to young children with disabilities and their families. Although considerable variability was found across disciplines, the average student receives little specialized information concerning either the infancy period or…
Descriptors: Course Content, Disabilities, Early Intervention, Higher Education