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Session Type: Roundtable Session
This session highlights innovative methodologies used to evaluate educational programs and policies. From causal forests and growth curve modeling to latent profile analysis and item response theory, these studies offer rigorous approaches to understanding impact and heterogeneity. Topics include the effects of performance information on parental investment, long-term outcomes of Pre-K funding, and teacher perceptions of arts-based programs. The group will discuss how advanced analytics can inform decision-making, improve measurement tools, and support equity-focused evaluation in complex educational systems.
Estimating the Treatment Effect Heterogeneity of Providing Performance Information in Education: A Causal Forests Approach - Xinjie Zhang, Vanderbilt University; Yi Wei, Peking University; Yingquan Song, Peking University
Evaluating Arts-based Program Impact Through Teachers’ Perceptions: A Latent Profile Analysis - Xiaobo Wei, University of South Carolina; Ashlee A. Lewis, University of South Carolina; Dalisha Shingler, University of South Carolina
How do Pre-K funding trajectories shape later academic outcomes, and for whom? - Yu Bai, Duke University; Kenneth A. Dodge, Duke University; Jade M. Jenkins, University of California - Irvine; Tyler Watts, Teachers College, Columbia University; Siobhan O'Muircheartaigh, Duke University
Scaling Digitally-Supported Innovations to Accelerate Learning from Within the Instructional Core: A Mixed-Methods Evaluation - Beth R. Holland, FullScale; Megan Benay, FullScale; Rae Lymer, FullScale