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Direct linkD'Agostino, Jerome V.; Rodgers, Emily – Educational Researcher, 2017
Recent shifts in policy and practice have brought an increasingly more academic focus to the early grades, evidenced in rising standards and the now widely accepted notion that kindergarten is the new first grade. These views however are mostly supported by teacher and parent self-reports and not by an analysis of literacy achievement data. We…
Descriptors: Hierarchical Linear Modeling, Literacy, Achievement Gap, Elementary School Students
Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric – Journal of Experimental Education, 2015
This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…
Descriptors: Effect Size, Measurement Techniques, Statistical Analysis, Research Design
D'Agostino, Jerome V.; Harmey, Sinéad J. – Journal of Education for Students Placed at Risk, 2016
Reading Recovery is one of the most researched literacy programs worldwide. Although there have been at least 4 quantitative reviews of its effectiveness, none have considered all rigorous group-comparison studies from all implementing nations from the late 1970s to 2015. Using a hierarchical linear modeling (HLM) v-known analysis, we examined if…
Descriptors: Meta Analysis, Reading, Reading Programs, Hierarchical Linear Modeling
Download full textRobinson, Ann; Adelson, Jill L.; Kidd, Kristy A.; Cunningham, Christine M. – Gifted Child Quarterly, 2018
Guided by the theoretical framework of curriculum as a platform for talent development, this quasi-experimental field study investigated an intervention focused on engineering curriculum and curriculum based on a biography of a scientist through a comparative design implemented in low-income schools. Student outcome measures included science…
Descriptors: Talent Development, Low Income Groups, Engineering Education, Quasiexperimental Design
