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Direct linkCastellano, Katherine E.; McCaffrey, Daniel F.; Lockwood, J. R. – Journal of Educational Measurement, 2023
The simple average of student growth scores is often used in accountability systems, but it can be problematic for decision making. When computed using a small/moderate number of students, it can be sensitive to the sample, resulting in inaccurate representations of growth of the students, low year-to-year stability, and inequities for…
Descriptors: Academic Achievement, Accountability, Decision Making, Computation
Download full textZhu, Pei; Jacob, Robin; Bloom, Howard; Xu, Zeyu – MDRC, 2011
This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…
Descriptors: Intervention, Academic Achievement, Research Methodology, Research Design
Schochet, Peter Z.; Puma, Mike; Deke, John – National Center for Education Evaluation and Regional Assistance, 2014
This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…
Descriptors: Statistical Analysis, Evaluation Methods, Educational Research, Intervention
Kyari, Murat; Buyukozturk, Sener – Educational Sciences: Theory and Practice, 2009
The outcomes which cannot be generalized are specific for a sample but are unable to be reflected to the rest of the population. The parameters that are reached at the end of the statistics that are scarce in sample arise doubts in the aspect of generalization. In these cases, parameter estimation may not be very stable and outlier values can…
Descriptors: Siblings, Intervals, Academic Achievement, Predictor Variables
Zhu, Pei; Jacob, Robin; Bloom, Howard; Xu, Zeyu – Educational Evaluation and Policy Analysis, 2012
This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools--which comprise three levels of clustering (students in classrooms in schools)--to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises…
Descriptors: Educational Research, Educational Researchers, Research Methodology, Multivariate Analysis
Wolfe, Richard G. – 1987
The Second International Mathematics Study (SIMS) of the International Association for the Evaluation of Educational Achievement (IEA) was conducted in 20 countries on two sampled populations: Population A of 13-year-olds and Population B of students studying mathematics in their final year of secondary school. Mathematics achievement was measured…
Descriptors: Academic Achievement, Algebra, Arithmetic, Calculators
