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The Sequential Scale-Up of an Evidence-Based Intervention: A Case Study

Author

Listed:
  • Jaime Thomas
  • Thomas D. Cook
  • Alice Klein
  • Prentice Starkey
  • Lydia DeFlorio

Abstract

Policy makers face dilemmas when choosing a policy, program, or practice to implement. Researchers in education, public health, and other fields have proposed a sequential approach to identifying interventions worthy of broader adoption, involving pilot, efficacy, effectiveness, and scale-up studies. In this article, we examine a scale-up of an early math intervention to the state level, using a cluster randomized controlled trial. The intervention, Pre-K Mathematics , has produced robust positive effects on children’s math ability in prior pilot, efficacy, and effectiveness studies. In the current study, we ask if it remains effective at a larger scale in a heterogeneous collection of pre-K programs that plausibly represent all low-income families with a child of pre-K age who live in California. We find that Pre-K Mathematics remains effective at the state level, with positive and statistically significant effects (effect size on the Early Childhood Longitudinal Study, Birth Cohort Mathematics Assessment = .30, p

Suggested Citation

  • Jaime Thomas & Thomas D. Cook & Alice Klein & Prentice Starkey & Lydia DeFlorio, 2018. "The Sequential Scale-Up of an Evidence-Based Intervention: A Case Study," Evaluation Review, , vol. 42(3), pages 318-357, June.
    • Handle: RePEc:sae:evarev:v:42:y:2018:i:3:p:318-357
    DOI: 10.1177/0193841X18786818
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    References listed on IDEAS

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    1. Thomas D. Cook, 2014. "Generalizing Causal Knowledge In The Policy Sciences: External Validity As A Task Of Both Multiattribute Representation And Multiattribute Extrapolation," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 33(2), pages 527-536, March.
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