Examining classroom influences on student perceptions of school climate: The role of classroom management and exclusionary discipline strategies

Johns Hopkins Center for the Prevention of Youth Violence, Johns Hopkins Bloomberg School of Public Health, USA.
Journal of school psychology (Impact Factor: 2.31). 10/2013; 51(5):599-610. DOI: 10.1016/j.jsp.2013.05.005
Source: PubMed


There is growing emphasis on the use of positive behavior supports rather than exclusionary discipline strategies to promote a positive classroom environment. Yet, there has been limited research examining the association between these two different approaches to classroom management and students' perceptions of school climate. Data from 1902 students within 93 classrooms that were nested within 37 elementary schools were examined using multilevel structural equation modeling procedures to investigate the association between two different classroom management strategies (i.e., exclusionary discipline strategies and the use of positive behavior supports) and student ratings of school climate (i.e., fairness, order and discipline, student-teacher relationship, and academic motivation). The analyses indicated that greater use of exclusionary discipline strategies was associated with lower order and discipline scores, whereas greater use of classroom-based positive behavior supports was associated with higher scores on order and discipline, fairness, and student-teacher relationship. These findings suggest that pre-service training and professional development activities should promote teachers' use of positive behavior support strategies and encourage reduced reliance on exclusionary discipline strategies in order to enhance the school climate and conditions for learning.

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    • "For instance, multilevel measurement modeling with categorical indicators represents the basis of multilevel item response theory (IRT; Fox, 2010; Fox & Glas, 2001; Muthén & Asparouhov, 2012b). There are a number of applications of multilevel SEM with categorical outcomes in the research literature using both frequentist (e.g., Gottfredson et al., 2009; Little, 2013; Mitchell & Bradshaw, 2013) and Bayesian (e.g., Diya, Li, Heede, Sermeus, & Lesaffre, 2013; Goldstein, Bonnet, & Rocher, 2007) approaches, yet simulation research has not been conducted to determine whether the sample size recommendations that have been put forth for continuous outcomes also hold for categorical outcomes. Moreover, a Bayesian approach is uniquely beneficial in the context of categorical data because it can be used to estimate categorical variable models that cannot be analyzed with currently available frequentist approaches (see, e.g., Ansari & Jedidi, 2000; Dunson, 2000; Muthén & Asparouhov, 2012b; Steele & Goldstein, 2006). "
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    • "); f. understanding how school/class climate and instructional practices impact students (Benner, 2013; Bottiani, Bradshaw, & Mendelson, 2014; Curby, Rimm-Kaufman, & Abry, 2013; Mitchell & Bradshaw, 2013; Reddy, Fabiano, Dudek, & Hsu, 2013); g. advancing the science of assessment (Kilgus, Riley-Tillman, Chafouleas, Christ, & Welsh, 2014; McDermott, Watkins, Rovine "

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