Quality assurance in high schools through regression analysis

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dc.contributor.advisorGilmour, James Daviden_ZA
dc.contributor.advisorDunne, Tim Ten_ZA
dc.contributor.authorWatermeyer, John Westertonen_ZA
dc.date.accessioned2016-03-07T06:55:47Z
dc.date.available2016-03-07T06:55:47Z
dc.date.issued1997en_ZA
dc.descriptionIncludes bibliography.en_ZA
dc.description.abstractSchool Effectiveness is a relatively new and poorly defined domain for which a structure is proposed, to facilitate future discussion. Three fields within School Effectiveness are identified, namely School Effectiveness Research (SER), School Improvement (SI) and Quality Assurance (QA). Three divisions are identified within each field on the basis of various criteria. SER has methodological generations, Sl is classified by decade, and three themes of QA are described, including performance indicators (Pis). A definition of effectiveness in terms of regression lines is described and the concept of added value or adjusted achievement developed. This study is concerned with the development of Pis for use within a single school to monitor and promote improvement. The context of the study (a model C senior high school in a predominantly white southern suburb of Cape Town) and the data collected is described before a review is made of some of the analyses which could be used to monitor effectiveness. A technique whereby pupil achievement is adjusted (for prior achievement and other background variables) and the residuals (or adjusted achievement) derived from the regressions investigated with one-way A NOVAs is described and tested using various models and subjects. With respect to groups, it is proposed that statistical significance of differences between mean residuals could be used as a PI. With respect to individual pupils, educators could set their own criterion for investigating cases where adjusted achievement is very large or very small. Statistical significance requires interpretation, however, and the role of professional judgement in modelling and monitoring adjusted achievement is discussed. The view that techniques such as regression analysis can only indicate when professional investigation and intervention might be necessary is stressed. It would seem unwise to rank teachers or subjects on the basis of adjusted achievement.en_ZA
dc.identifier.apacitationWatermeyer, J. W. (1997). <i>Quality assurance in high schools through regression analysis</i>. (Thesis). University of Cape Town ,Faculty of Humanities ,School of Education. Retrieved from http://hdl.handle.net/11427/17553en_ZA
dc.identifier.chicagocitationWatermeyer, John Westerton. <i>"Quality assurance in high schools through regression analysis."</i> Thesis., University of Cape Town ,Faculty of Humanities ,School of Education, 1997. http://hdl.handle.net/11427/17553en_ZA
dc.identifier.citationWatermeyer, J. 1997. Quality assurance in high schools through regression analysis. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Watermeyer, John Westerton AB - School Effectiveness is a relatively new and poorly defined domain for which a structure is proposed, to facilitate future discussion. Three fields within School Effectiveness are identified, namely School Effectiveness Research (SER), School Improvement (SI) and Quality Assurance (QA). Three divisions are identified within each field on the basis of various criteria. SER has methodological generations, Sl is classified by decade, and three themes of QA are described, including performance indicators (Pis). A definition of effectiveness in terms of regression lines is described and the concept of added value or adjusted achievement developed. This study is concerned with the development of Pis for use within a single school to monitor and promote improvement. The context of the study (a model C senior high school in a predominantly white southern suburb of Cape Town) and the data collected is described before a review is made of some of the analyses which could be used to monitor effectiveness. A technique whereby pupil achievement is adjusted (for prior achievement and other background variables) and the residuals (or adjusted achievement) derived from the regressions investigated with one-way A NOVAs is described and tested using various models and subjects. With respect to groups, it is proposed that statistical significance of differences between mean residuals could be used as a PI. With respect to individual pupils, educators could set their own criterion for investigating cases where adjusted achievement is very large or very small. Statistical significance requires interpretation, however, and the role of professional judgement in modelling and monitoring adjusted achievement is discussed. The view that techniques such as regression analysis can only indicate when professional investigation and intervention might be necessary is stressed. It would seem unwise to rank teachers or subjects on the basis of adjusted achievement. DA - 1997 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1997 T1 - Quality assurance in high schools through regression analysis TI - Quality assurance in high schools through regression analysis UR - http://hdl.handle.net/11427/17553 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/17553
dc.identifier.vancouvercitationWatermeyer JW. Quality assurance in high schools through regression analysis. [Thesis]. University of Cape Town ,Faculty of Humanities ,School of Education, 1997 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/17553en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentSchool of Educationen_ZA
dc.publisher.facultyFaculty of Humanitiesen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherEducation, Secondary - South Africa - Cape Townen_ZA
dc.subject.otherAcademic achievement - South Africa - Cape Townen_ZA
dc.subject.otherQuality assurance - South Africa - Cape Townen_ZA
dc.subject.otherRegression analysisen_ZA
dc.subject.otherAnalysis of varianceen_ZA
dc.titleQuality assurance in high schools through regression analysisen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMEden_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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