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Educational Psychology Review

, Volume 30, Issue 2, pp 559–583 | Cite as

Student Diversity Representation and Reporting in Universal School-Based Social and Emotional Learning Programs: Implications for Generalizability

  • Hillary L. Rowe
  • Edison J. Trickett
Essay

Abstract

This paper addresses two major and potentially conflicting movements: the importance of diversity as both a conceptual and political issue and the rise of the evidence-based practice movement in education. This tension is particularly important when evaluating and reporting universal interventions because of their intended applicability across diverse groups of children and adolescents. This study contributes to this discussion through an analysis of published school-based universal social and emotional learning (SEL) intervention evaluations in terms of their theoretical and empirical attention to student diversity characteristics. We defined student diversity in terms of five characteristics: gender, race/ethnicity, SES, disability status, and sexual orientation/gender identity. We assessed how and when demographic characteristics were reported, how these characteristics were analyzed as moderators of program outcomes, and how differential effects based on diversity were incorporated into reported intervention generalizability discussions. Results showed that diversity characteristics were inconsistently reported across articles. Most studies did not test for moderating effects, but those that did found inconsistent effects across diversity characteristics. Further, conceptual and/or empirical support for conducting the moderation analyses was often not provided or sufficiently supported by previous literature or a hypothesis. This research highlights the need for a more nuanced understanding of how SEL program effects may be moderated by student demographic characteristics and suggests caution about the generalizability of the reviewed SEL programs across diverse groups of children and adolescents.

Keywords

Diversity Social-emotional learning Program evaluation Meta-analysis 

Notes

Acknowledgements

We thank Dr. David DuBois for his efforts on this manuscript; his insight greatly improved this work and we are grateful for his guidance. We also thank the manuscript reviewers and Dr. Fred Paas for their constructive feedback throughout the revision process.

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© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of Illinois at ChicagoChicagoUSA
  2. 2.Department of Educational and Psychological StudiesUniversity of MiamiCoral GablesUSA

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