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Direct linkBuzhardt, 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
Buzhardt, Jay; Greenwood, Charles R.; Jia, Fan; Walker, Dale; Schneider, Naomi; Larson, Anne L.; Valdovinos, Maria; McConnell, Scott R. – Grantee Submission, 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
Golas, Julianna C.; Horm, Diane; Caruso, David A. – Journal of Research in Childhood Education, 2006
Early Head Start services are typically offered through home- or center-based delivery models. A formative evaluation of an example of each service delivery model was conducted. The purpose was to examine the issues involved in the implementation of these two service delivery models relative to the content of services, intensity of services,…
Descriptors: Disadvantaged Youth, Program Implementation, Formative Evaluation, Family Involvement
