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Agley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
Chung, C. J. ChanJin; Cartwright, Christopher; Cole, Matthew – Journal of STEM Education: Innovations and Research, 2014
Robotics competitions for K-12 students are popular, but are students really learning and improving their STEM scores through robotics competitions? If not, why not? If they are, how much more effective is learning through competitions than traditional classes? Is there room for improvement? What is the best robotics competition model to maximize…
Descriptors: STEM Education, Robotics, Competition, Teaching Methods
Hedges, Larry V.; Hedberg, E. C. – Evaluation Review, 2013
Background: Cluster-randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…
Descriptors: Correlation, Multivariate Analysis, Educational Experiments, Statistical Analysis