This applied quantitative dissertation examined how school district discipline policies affect student outcomes within urban high schools across the southern United States. Students faced ongoing behavioral challenges despite multiple policy changes, which the COVID-19 pandemic further exacerbated. The research evaluates zero tolerance disciplinary methods based on the Deterrent Theory of Punishment and restorative justice strategies that emphasize community strengthening and conflict resolution. A predictive correlational design was used to examine the relationship between disciplinary practices and student performance indicators. The analysis focused on variables such as in-school and out-of-school suspensions, standardized test participation, AP course enrollment, and school climate factors, including bullying incidents and referrals to law enforcement. Secondary data from the Civil Rights Data Collection (2021-2022) were analyzed using multiple regression models. Findings revealed that the implementation of restorative practices significantly predicted lower suspension rates and fewer law enforcement referrals, as well as increased AP courses enrollment. However, restorative practices did not have a significant impact on standardized test participation, bullying reports, or restraint and seclusion incidents. Demographic variables such as race and school type also influenced disciplinary outcomes, with higher percentages of Black students associated with increased out-offschool suspensions and referrals. A multicollinearity issue between racial variables limited their simultaneous inclusion in models. While restorative practices showed promise in reducing exclusionary discipline, their broader effects on school climate appeared limited and context-dependent. This study provided educational stakeholders with essential evidence regarding the benefits and limitations of restorative strategies, informing future policy decisions and discipline reform efforts.
| Date of Award | Jan 1 2025 |
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| Original language | English |
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| Supervisor | Shery Bennett (Supervisor), Matthewelaney (Advisor) & Kimberly Durham (Advisor) |
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