Using Multilevel Analyses to Study the Effectiveness of Science Curriculum Materials

Abstract

This paper explores the use of HLM analysis in determining the implementation effects of two science curriculum units on student learning. It also compares HLM results with prior results from ANCOVA analyses. HLM analyses were considered as an alternative to ANCOVA because student data were nested within classrooms. The data for this study are from the Scaling-up Curriculum for Achievement, Learning and Equity Project (SCALE-uP). The sample consists of Grade 6 and Grade 7 students from five matched pairs of middle schools in a large, diverse, metropolitan school district in the US. The HLM null model indicates that approximately 15% of the total variance in student gain scores was found between classrooms. Curriculum treated as a classroom factor was significant for both units tested, as was also the case when treated at the individual level in ANCOVA. However, there were large differences in the effect sizes reported by the two analysis techniques. A major implication is that when the students are nested in classrooms and schools, researchers should consider multi-level analysis and account for classroom/school contexts.

Curriculum‐based teacher professional development in middle school science: A comparison of training focused on cognitive science principles versus content knowledge

“…Because teachers took the teacher knowledge test only once for each unit no matter how many cohorts they taught, we combined Cohort 1 and Cohort 2 teachers. Because teachers filled out a survey every time they finished teaching a unit, we fit HLMs for each unit and cohort combination to compare teacher practice measures (Rethinam, Pyke, & Lynch, ).…”

Large‐scale science education intervention research we can use

“…In science education, a number of studies in the past decade have analyzed the effectiveness of programs when implemented across a large number and wide variety of settings (Borman, Gamoran, & Bowdon, 2008;Buckley et al, 2004;Lee, Maerten-Rivera, Penfield, LeRoy, & Secada, 2008;Penuel, Gallagher, & Moorthy, 2011;Rethinam, Pyke, & Lynch, 2008;Songer, Kelcey, & Gotwals, 2009;Vanosdall, Klentschy, Hedges, & Weisbaum, 2007). Many of these interventions are grounded in decades of basic research on learning and are intended to instantiate principles derived from that research for organizing coherent sequences of instruction for students (Pea & Collins, 2008).…”

Technical pearl: Streamlining the Swan

“…A key aim of effectiveness research is to identify interventions that can work in a wide variety of settings (Flay et al, 2005). In science education, a number of studies in the past decade have analyzed the effectiveness of programs when implemented across a large number and wide variety of settings (Borman, Gamoran, & Bowdon, 2008; Buckley et al, 2004; Lee, Maerten‐Rivera, Penfield, LeRoy, & Secada, 2008; Penuel, Gallagher, & Moorthy, 2011; Rethinam, Pyke, & Lynch, 2008; Songer, Kelcey, & Gotwals, 2009; Vanosdall, Klentschy, Hedges, & Weisbaum, 2007). Many of these interventions are grounded in decades of basic research on learning and are intended to instantiate principles derived from that research for organizing coherent sequences of instruction for students (Pea & Collins, 2008).…”