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Perceptions and Predictions with School Climate: Analyzing the Comprehensive School Climate Inventory

Abstract

dc:description.abstract

<p>Through multiple regression and analysis of variance, data from the Comprehensive School Climate Inventory was used to understand the following: 1.) the predictive ability of student perceptions of safety on overall school climate; 2.) the relationship between geographic location and school climate; and 3.) the predictive ability of geographic location and school type on overall school climate. Participants were elementary school students, grades PreK through 8, from 30 elementary schools across the country, with approximately 4,500 student responses. Results showed that students’ perceptions of school safety predicted 80% of the variances in connection to ratings of school climate. There was also a significant relationship between geographic location and ratings of school climate, as students from suburban schools tended to rate their climate as more positive than students from urban or rural schools. Lastly, the results showed that together, school type and geographic location are not able to sufficiently predict ratings of school climate, only explaining 4% of the variance in school climate ratings.</p>

Degree

thesis:*
Name thesis:degree_name
PhD
Level thesis:degree_level
Immediate Access
Discipline thesis:degree_discipline
School Psychology
Year dc:date.available
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Cimorelli, Danielle
Contributors dc:contributor
  • Scott Graves
  • Tammy Hughes
  • Launcelot Brown

Rights

Language dc:language
English

Identifiers

dc:identifier.*
Repository record dc:identifier
https://dsc.duq.edu/etd/164
OAI identifier oai:identifier
oai:dsc.duq.edu:etd-1173

Chain of custody

source
Harvested from
Duquesne
Base URL
dsc.duq.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Cimorelli, Danielle. Perceptions and Predictions with School Climate: Analyzing the Comprehensive School Climate Inventory. Immediate Access thesis, 2017. https://dsc.duq.edu/etd/164