Browsing by Author "Dodge, Kenneth A"

Empirical studies of education programs and systems, by nature, rely upon use of student outcomes that are measurable. Often, these come in the form of test scores. However, in light of growing evidence about the long-run importance of other student skills and behaviors, the time has come for a broader approach to evaluating education. This dissertation undertakes experimental, quasi-experimental, and descriptive analyses to examine social, behavioral, and health-related mechanisms of the educational process. My overarching research question is simply, which inside- and outside-the-classroom features of schools and educational interventions are most beneficial to students in the long term? Furthermore, how can we apply this evidence toward informing policy that could effectively reduce stark social, educational, and economic inequalities?

The first study of three assesses mechanisms by which the Fast Track project, a randomized intervention in the early 1990s for high-risk children in four communities (Durham, NC; Nashville, TN; rural PA; and Seattle, WA), reduced delinquency, arrests, and health and mental health service utilization in adolescence through young adulthood (ages 12-20). A decomposition of treatment effects indicates that about a third of Fast Track’s impact on later crime outcomes can be accounted for by improvements in social and self-regulation skills during childhood (ages 6-11), such as prosocial behavior, emotion regulation and problem solving. These skills proved less valuable for the prevention of mental and physical health problems.

The second study contributes new evidence on how non-instructional investments – such as increased spending on school social workers, guidance counselors, and health services – affect multiple aspects of student performance and well-being. Merging several administrative data sources spanning the 1996-2013 school years in North Carolina, I use an instrumental variables approach to estimate the extent to which local expenditure shifts affect students’ academic and behavioral outcomes. My findings indicate that exogenous increases in spending on non-instructional services not only reduce student absenteeism and disciplinary problems (important predictors of long-term outcomes) but also significantly raise student achievement, in similar magnitude to corresponding increases in instructional spending. Furthermore, subgroup analyses suggest that investments in student support personnel such as social workers, health services, and guidance counselors, in schools with concentrated low-income student populations could go a long way toward closing socioeconomic achievement gaps.

The third study examines individual pathways that lead to high school graduation or dropout. It employs a variety of machine learning techniques, including decision trees, random forests with bagging and boosting, and support vector machines, to predict student dropout using longitudinal administrative data from North Carolina. I consider a large set of predictor measures from grades three through eight including academic achievement, behavioral indicators, and background characteristics. My findings indicate that the most important predictors include eighth grade absences, math scores, and age-for-grade as well as early reading scores. Support vector classification (with a high cost parameter and low gamma parameter) predicts high school dropout with the highest overall validity in the testing dataset at 90.1 percent followed by decision trees with boosting and interaction terms at 89.5 percent.

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Many cost-effective, evidence-based developmental programs (EBPs) remain inaccessible to children in need. To improve access to care, this dissertation theoretically and then empirically examines different approaches to advocating for dissemination funding in a polarized political context. Section 1 describes recent advances in the use of morally framed messaging to change attitudes. Section 2 reviews research on political polarization with an emphasis on how polarization affects online message processing. Section 3 describes a theoretically informed EBP advocacy strategy that seeks to tailor and target advocacy messages to promote bipartisan support for EBP dissemination.

Sections 4, 5, and 6 describe three studies designed to test whether motivated social cognition (Jost, Glaser, Kruglanski, & Sulloway, 2003) or moral foundations theory (Graham, Haidt, & Nosek, 2009) may be used to tailor message frames to speak to the distinct needs of Liberals and Conservatives. In Section 7, results and limitations are discussed. Although the three studies provide limited support for the hypothesis that theory can be used to design persuasive, tailored messages, message frames were consistently overwhelmed by competition from partisan cues and ideological arguments. The dissertation concludes by arguing that, in order to generate bipartisan support for EBP dissemination, implementation funding and structures that are already highly prioritized by Liberals need to be designed to appeal to Conservatives’ substantive policy preferences.