Abstract

Personalization for academic and social-emotional learning (PASL) is a systemic approach to high school reform that works to strengthen and bridge preexisting academic and social-emotional systems within schools and classrooms. Analyzing student administrative records from 12 schools in a large Florida urban district, we found that, on average, PASL was associated with fewer unexcused absences of ninth graders. Its effects were stronger for students with prior disciplinary incidents in increasing credits earned and reducing unexcused absences. PASL effects did not vary by student race/ethnicity or family income status. The findings provide evideance for the school reform model with an improvement-science approach and suggest directions for supporting students with middle to high school transition.

References

Adams C. M., Ware J. K., Miskell R. C., Forsyth P. B. (2016). Self-regulatory climate: A positive attribute of public schools. Journal of Educational Research, 109(2), 169–180. https://doi.org/10.1080/00220671.2014.934419

Google Scholar

Allensworth E. M., Easton J. Q. (2005). The on-track indicator as a predictor of high school graduation [Conference session]. Consortium on Chicago School Research at the University of Chicago. https://consortium.uchicago.edu/sites/default/files/2023-06/The%20On-Track%20Indicator-Jun2005-Consortium.pdf

Google Scholar

Archambault I., Janosz M., Morizot J., Pagani L. (2009). Adolescent behavioral, affective, and cognitive engagement in school: Relationship to dropout. Journal of school Health, 79(9), 408–415. https://doi.org/10.1111/j.1746-1561.2009.00428.x

Google Scholar

Bandura A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52, 1–26. https://doi.org/10.1146/annurev.psych.52.1.1

Google Scholar

Bandura A. (1989). Human agency in social cognitive theory. American Psychologist, 44(9), 1175–1184. https://doi.org/10.1037//0003-066x.44.9.1175

Google Scholar

Bandura A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037//0033-295x.84.2.191

Google Scholar

Biographies

YIHUA HONG is a senior education research analyst in the Education Practice Area of RTI International. Her major areas of research include school-based accountability, teacher professional development, and instructional effectiveness. She also specializes in research design, advanced quantitative methods, and evaluations of educational programs and policy.

Jeffrey A. Rosen is a senior education research analyst in the Education Practice Area of RTI International. His research interests in education include the impact of social-emotional learning and mental, emotional, and behavioral interventions in K–12 classrooms. In addition to his interests in education, Dr. Rosen also has interests in survey methodology, including the reduction of bias due to nonresponse and the quality of self-report data.

Stacey Rutledge is a professor in the Department of Educational Leadership and Policy Studies at Florida State University. Her research focuses broadly on understanding how the work of administrators, teachers, and students is nested within institutional and policy environments. She also studies how holistic approaches to school reform and technology shape school practices as well as student experiences and outcomes.

Marisa Cannata is a professor of the practice of education policy and school reform at Peabody College of Education and Human Development at Vanderbilt University. Dr. Cannata studies the social and organizational conditions of teachers’ work, including teacher involvement in reform implementation. She studies the implementation and scaling of educational initiatives.

Susan Rotermund is a senior education research analyst in the Education Practice Area of RTI International. Her primary research focus is evaluating and understanding the impact of social-emotional learning programs on students in K–12 classrooms. Her other area of focus is K–12 science, technology, engineering, and math education, including analyzing longitudinal patterns of student achievement and understanding how student experiences vary based on demographic variables.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.