Performance Trajectories and Performance Gaps as Achievement Effect-Size Benchmarks for Educational Interventions
By Howard S. Bloom, C. Hill, A. Black, Mark Lipsey. 2008
510 citations recorded by the source corpus.
Subfields: Education
View Paper: https://www.semanticscholar.org/paper/ab9866b8754d68acbd25b4a477162bba21aed0ca
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In Education
- M. Kraft
- Alan C. K. Cheung
- R. Slavin
- Emma Kopa
- Marissa J. Filderman
- Hugues Lortie-Forgues
- Natalya Verbitsky-Savitz
- Catherine Richards-Tutor
Citations in the corpus
- Rigorous Large-Scale Educational RCTs Are Often Uninformative: Should We Be Concerned? (2019, background): “These trials produced findings consistent with both the null hypothesis of no effect, and also with an effect comparable to that associated with one year of maturation and instruction (Bloom et al., 2008).”
- Learning loss due to school closures during the COVID-19 pandemic (2021, unknown): “At the same time, some studies indicate a progress of up to 0.80 SD annually at the low extreme of our age range (45, 47), which would indicate that remote learning operated at 50% efficiency.”
- A Meta-Analytic Review of the Relations Between Motivation and Reading Achievement for K–12 Students (2020, background): “Others have indicated that effects above 0.20 should be considered educationally meaningful or even large (Bloom et al., 2008; Lipsey et al., 2012).”
- How Methodological Features Affect Effect Sizes in Education (2016, background): “In an article on practical interpretations of the magnitude of effect sizes, cited earlier, Bloom et al. (2008) noted that students in the elementary grades ordinarily gain much more (in terms of achievement effect sizes) from the beginning of each year to the end, in comparison to secondary student”
- Modern Regression Discontinuity Analysis (2012, background): “Bloom, Hill, Black, and Lipsey ( 2008 ) and Hill, Bloom, Black, and Lipsey ( 2008 ) presented an analytic approach and empirical benchmarks for choosing MDESs in education research.”
- Individual Differences in Reading Development (2014, unknown): “Consequently, as learning rates follow a negative accelerated trend (Bloom et al., 2008; Hill et al., 2008), at a certain age, interindividual differences between the early and the late starters will decrease when the negative acceleration trend becomes higher for the better readers (Scarborough, 20”