Date of Award
Master of Arts (MA)
Susan D. McMahon, Ph.D.
Nathan Todd, Ph.D.
Student misbehavior has become a problem gaining much warranted national attention. To monitor student behavior problems schools are increasingly relying on student office disciplinary referral (ODR) data to identify and monitor students who may be at-risk for future behavioral problems. While research has examined individual-level predictors of student disciplinary referrals, few studies have examined multilevel models, which take into account the nested nature of these data (e.g., students within schools). The current study draws upon Social Disorganization Theory to guide an investigation of student office disciplinary referrals. This study examines office disciplinary referrals among 1,501 students across 13 schools in a high-poverty urban school district. Multilevel modeling strategies are used to examine the extent to which school-level variables (Student Mobility, Student-teacher Ratio, Student-teacher Relations, and Communication of Behavioral Expectations) predict students with chronic levels of disciplinary referrals (i.e., six or more ODRs). Results reveal that school-level characteristics moderate associations between individual-level predictors and student ODRs and provide support for Social Disorganization Theory as well as Person-Environment Fit Theory as guiding frameworks to examine student disciplinary referrals. Future research should continue to use these modeling strategies and investigate pathways leading to these disciplinary events. Implications for research and practice are discussed.
Martinez, Andrew, "School-Level Predictors of Student Office Disciplinary Referrals" (2013). College of Science and Health Theses and Dissertations. 54.