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Chine, Danielle R.; Larwin, Karen H. – International Journal of Research in Education and Science, 2022
Hierarchical linear modeling (HLM) has become an increasingly popular multilevel method of analyzing data among nested datasets, in particular, the effect of specialized academic programming within schools. The purpose of this methodological study is to demonstrate the use of HLM to determine the effectiveness of STEM programming in an Ohio middle…
Descriptors: Middle Schools, STEM Education, Instructional Effectiveness, Program Development
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Kelcey, Ben; Phelps, Geoffrey – Evaluation Review, 2013
Objectives: Group-randomized designs are well suited for studies of professional development because they can accommodate programs that are delivered to intact groups (e.g., schools), the collaborative nature of professional development, and extant teacher/school assignments. Though group designs may be theoretically favorable, prior evidence has…
Descriptors: Statistical Analysis, Research Design, Faculty Development, Sample Size
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Faria, Ann-Marie; Greenberg, Ariela; Meakin, John; Bichay, Krystal; Heppen, Jessica – Society for Research on Educational Effectiveness, 2014
Educators have long used test scores to make educational decisions, but only within the last decade has the availability of data been systematic (Abelman, Elmore, Even, Kenyon, & Marshall, 1999). In recent years, interest has spiked in data-driven decision making in education (Marsh, Pane, & Hamilton, 2006). With technological advances and…
Descriptors: Data Analysis, Academic Achievement, Urban Schools, Correlation