Looking Beyond Socioeconomic Status: Using Quantitative Measures of Student Misconduct to Identify "At-Risk" Schools

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dc.contributor.advisor Dr. Richard Haley, Committee Co-Chair en_US
dc.contributor.advisor Dr. Carol Pope, Committee Member en_US
dc.contributor.advisor Dr. Kenneth Brinson, Committee Member en_US
dc.contributor.advisor Dr. Robert Serow, Committee Chair en_US
dc.contributor.author Jackl, Andrew Wayne en_US
dc.date.accessioned 2010-04-02T19:12:07Z
dc.date.available 2010-04-02T19:12:07Z
dc.date.issued 2006-04-12 en_US
dc.identifier.other etd-03192006-133546 en_US
dc.identifier.uri http://www.lib.ncsu.edu/resolver/1840.16/5346
dc.description.abstract The research project used regression analysis to study the relationship between students' misconduct and their schools' corresponding level of academic achievement at the middle and high school levels. This was a non-experimental, ex post facto study conducted using data from a large, Southeastern school district collected over three academic years, 2001 to 2004. The operational variables for this analysis were defined as: 1) socioeconomic status (SES) as measured by the schools' free or reduced lunch percentages, 2) student misconduct (DAR) as measured by the number of suspensions per 100 students in a given school year, and 3) academic achievement (ABC-PC) as measured by the schools' overall academic performance composites calculated via North Carolina's accountability formulas. A data transformation was conducted on the DAR variable by calculating its logarithm (logDAR) to improve the normality of the variable's distribution. Regression analyses were run using the SAS 9.1 analytic software package to determine the nature of the relationships between: 1) SES and ABC-PC, 2) logDAR and ABC-PC, and 3) logDAR and ABC-PC while controlling for SES. It was determined that: 1) SES has a significant relationship to ABC-PC at the middle and high school levels, 2) logDAR has a significant relationship to ABC-PC at the middle and high school levels, 3) logDAR does not have a significant relationship to ABC-PC at the middle school level when SES is entered into the regression equation as a control variable, and 4) logDAR does have a significant relationship to ABC-PC at the high school level, even when SES is entered into the regression equation as a control variable. Regression models using both SES and logDAR as independent variables had greater explanatory power than regression models using either SES or logDAR in isolation. It was concluded that quantitative measures of student misconduct, such as the logDAR covariate, can be useful in identifying schools at the greatest risk of academic failure — particularly at the high school level. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.subject discipline en_US
dc.subject misconduct en_US
dc.subject behavior en_US
dc.subject academic performance composite en_US
dc.subject academic achievement en_US
dc.subject socioeconomic status en_US
dc.subject student behavior en_US
dc.subject student conduct en_US
dc.subject student misconduct en_US
dc.subject student discipline en_US
dc.title Looking Beyond Socioeconomic Status: Using Quantitative Measures of Student Misconduct to Identify "At-Risk" Schools en_US
dc.degree.name PhD en_US
dc.degree.level dissertation en_US
dc.degree.discipline Educational Research and Policy Analysis en_US


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