Genes, Schools, and Interventions That Address Educational Inequality: Can the Science of Treatment-Effect Heterogeneity Unite Diverse Perspectives?

December 13-14, 2018, Austin, TX

This conference will bring together experts in genetics, economics, sociology, psychology, and education, in order to advance an integration of research on the genetics of cognitive and non-cognitive skills, structural determinants of educational inequality, and the effects of large-scale educational interventions. Critical questions at the interface of these rapidly-developing fields include:

  • What, if anything, do results from genetic research and sociological research imply about the effectiveness of educational interventions?
  • How can intervention designs be used to test hypotheses about the mechanisms linking genotypes with complex human phenotypes, including gene-by-environment interaction hypotheses?
  • How can intervention designs be used to test hypotheses about who is advantaged or disadvantaged by school structures?
  • How can discoveries about mechanisms of genetic effects be used to identify intervention targets in diverse school settings?
  • How can integrating genetic data (e.g., measured genotypes, genetically-related samples) into intervention studies improve estimates of overall effects and advance understanding of heterogeneity of treatment effects?

The goal of the conference will be to develop a White Paper with methodological recommendations for how intervention research could integrate genetic and sociological data, and how genetic or population-based studies could integrate light-touch experimental interventions.

 

Organizers

  • David Yeager, University of Texas, Austin
  • Paige Harden, University of Texas, Austin

Program

 
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Videos

Introductions and Orientation
Paige Harden, University of Texas at Austin
David Yeager, University of Texas at Austin
Group #1 : Interventions that Work
Drew Bailey, University of California at Irvine
Christopher Bryan, The University of Chicago
Greg Duncan, University of California at Irvine
David Yeager, University of Texas at Austin
Group #2: Treatment Effect Heterogeneity
Alexandra Burt, Michigan State University
Elliot Tucker-Drob, University of Texas at Austin
Patrick Turley, Broad Institute / MGH
Teppei Yamamoto, MIT
Group #3: Using Genetics to Identify Mechanisms
Dan Belsky, Columbia University
Pietro Biroli, University of Zurich
Tom DiPrete, Columbia University
Paige Harden, University of Texas at Austin
Group #4: Thinking about Place
Robert Crosnoe, University of Texas at Austin
Colter Mitchell, University of Michigan
Chandra Muller, University of Texas at Austin
Candice Odgers, University of California at Irvine