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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
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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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Marvin, Christine; Kuhn, Miriam; Knoche, Lisa – Grantee Submission, 2013
Parents' interactions with their children can have influential effects on children's language outcomes. Special supports may be needed however, when young children live in poverty and show developmental delays early in life. This study analyzed data for a subset of children enrolled in Early Head Start (EHS) programs and participating in a…
Descriptors: Language Acquisition, Infants, Toddlers, Early Childhood Education