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This report describes a study that was conducted to determine the perceived degree of usefulness the indicators of progress toward excellence have for the presidents of Florida's 28 community colleges. This study reports this degree of perceived usefulness by using a survey instrument that identified quality indicators developed by the State Board of Community Colleges, Florida Department of Education. Based on a project design and format adapted by the Florida Community/Junior College Inter-Institutional Research Council, this study proposed to identify what information (indicators of progress toward excellence) is considered most valid to the presidents of Florida's community colleges in making quality-evaluation decisions about programs or services offered by their colleges. In addition, this study identified similarities and differences in the usefulness ratings of the indicators for the presidents by the program area in which they most closely associate themselves; by type of institution in which they serve and by other selected personal and institutional classifications. Chapter I includes an introduction to the study, its purposes, rationale, and scope. Chapter II reviews the literature in the area of quality indicators for education and the evaluation of educational quality. Chapter III contains a review of the problem, design of the study, development of the study questionnaire and outlines the design and methodology used in the study. Chapter IV contains the results of a survey of all 28 of Florida's community college presidents and presents these findings in sections dealing with respondents' characteristics, results for all respondents, results by quality indicator groups, and by selected institutional characteristics. Chapter V contains a summary of the study, its results, conclusions, and recommendations. Appendices include the classifications used in the data analysis, the questionnaire, detailed survey results, additional indicators with ratings, and survey follow-up responses.

There are many parametric statistical models that have been designed to measure change in nonequivalent control group studies, but because of assumption violations and potential artifacts, there is no one form of analysis that always appears to be appropriate. While the parametric analysis of covariance and parametric ANCOVAS with a covariate correction are some of the more frequently completed analyses used in nonequivalent control group research, comparative studies with nonparametric counterparts should be completed and results compared with those more commonly used forms of analysis. The current investigation studied and compared the application of four ANCOVA models: the parametric, the covariate-corrected parametric, the rank transform, and the covariate-corrected rank transform. Population parameters were established; sample parameter intervals determined by Monte Carlo simulation were examined; and a best ANCOVA model was systematically and theoretically determined in light of population assumption violations, reliability of the covariate correction, the width of the sample probability level intervals, true parent population parameters, and results of robust regression. Results of data exploration on the parent population revealed that, based on assumptions, the covariate-corrected ANCOVAS are preferred over both the parametric and rank analyses. A reliability coefficient of ṟ=.83 also indicated that a covariate-corrected ANCOVA is effective in error reduction. Robust regression indicated that the outliers in the data set impacted the regression equation for both parametric models, and deemed selection of either model questionable. The tightest probability level interval for the samples serves to delineate the model with the greatest convergence of probability levels, and, theoretically, the most stable model. Results of the study indicated that, because the covariate-corrected rank ANCOVA had by far the tightest interval, it is the preferred model. In addition, the probability level interval of the covariate-corrected rank model is the only model interval that contained the true population parameter. Results of the investigation clearly indicate that the covariate-corrected rank ANCOVA is the model of choice for this nonequivalent control group study. While its use has yet to be reported in the literature, the covariate-corrected rank analysis of covariance provides a viable alternative for researchers who must rely upon intact groups for the answers to their research questions. / Ph. D.

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Numerous school effectiveness studies have utilized least squares regression techniques to produce school effectiveness indices despite the fact that they are subject to serious sampling fluctuations when sample sizes are small. If the sample size is smaller than normally thought adequate for accurate prediction a larger sample can be analyzed by pooling students from similar programs from different schools. Even though the regression weights for similar programs should be similar across schools, direct pooling of students may be less than satisfactory. A technique such as Bayesian m-group regression can be used that will incorporate both the similarity of the regressions across schools as well as the uniqueness of the individual programs. This study empirically examines the predictive efficiency of four regression techniques that utilize individual student data as input. Cross-validation analyses were performed and mean squared errors, mean absolute errors, and correlations between observed and predicted scores were compared for four methods: (1) within-school least squares regression, (2) pooled least squares regression, (3) pooled least squares regression with adjusted alphas, and (4) Bayesian m-group regression with identical regression coefficients. In addition, school effectiveness indices were obtained for the four regression techniques as well as least squares regression using school means and mean difference scores. These effectiveness indices were compared, and the stability of these indices across random samples of students, and across consecutive classes examined. The within-school least squares regression method was found to be somewhat inferior to the other three models in terms of predictive efficiency. The Bayesian m-group equal slope model showed no appreciable advantage over the pooled least squares regression model or the pooled least squares regression model with adjusted alphas. The indices produced by all six methods appear to be capable of representing the relative effectiveness of the schools involved in the study. In addition, those indices that moderate the importance of extreme values remained relatively stable from one subsample to another with correlations ranging from .75 to .85. Stability from class to class were of a much lower magnitude than those values reflecting stability from sample to sample. Correlations between school effectiveness indices of consecutive classes ranged from .28 to .47. / Ph. D.

Thesis (M.Ed.)--University of Hong Kong, 1989. / Includes bibliographical references (leaf 105-111). Also available in print.

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by Frank Wai-ming Tam. / "June 1998." / Thesis (Ph.D.)--Chinese University of Hong Kong, 1998. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Wang, Xueju. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 255-269). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese; some appendixes in Chinese.

The purpose of this research was to provide a descriptive and critical analysis of the function of evaluation teams in regional accreditation of senior colleges and universities--how evaluators perceive their roles, how they spend their time on site, and how they make decisions. The objectives of the study were (1) to determine the extent to which regional accrediting visits do what they are purported to do in regional policy and procedure statements, and (2) to determine the strengths and weaknesses in the onsite evaluation process as perceived by regional evaluation team members. The methodology involved a three-step process: (1) a content analysis of regional policy statements regarding the evaluation visit, (2) a survey of evaluators from five of the six regional associations, and (3) a review and comment on the draft findings by professional staff of the participating regional commissions. An overall response rate of 82 percent was obtained from the sample of 349 evaluators--without the use of follow-up mailings. Regional cross tabulations of evaluator responses, together with Chi-square statistics and standard errors of the percentages, provided the basis for the analysis. Major conclusions of the study were: (1) The lack of clear specification of the purpose of the evaluation team visit rendered it difficult to determine whether the purported purposes of the visit were being met. (2) The major strengths of the evaluation visit lay in the expertise and dedication of the volunteer evaluators, and in the willingness of the commissions to adapt their procedures to changing needs and new technologies. The major weakness in the evaluation visit was the lack of an evaluation framework or model to guide the work of the evaluation team. The researcher's recommendations included (1) the regional commissions should clearly specify the intended purposes of the evaluation visit in light of the overall purposes of regional accreditation, and (2) the regional commissions should utilize a coordinating group such as the Council on Postsecondary Accreditation and the evaluation expertise within academe to develop a framework, or genre, to guide team members in accomplishing the purposes of the visit.