Browsing by Author "Duane Akroyd, Committee Co-Chair"

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    Can Factors Related to Self-Regulated Learning and Epistemological Beliefs Predict Learning Achievement in Undergraduate Asynchronous Web-Based Courses?
    (2006-10-04) Bell, Paul David; Paul F. Bitting, Committee Co-Chair; Duane Akroyd, Committee Co-Chair
    The purpose of this study was to examine the effects of subfactors of self-regulated learning (SRL) and epistemological beliefs (EB) on individual learner levels of academic achievement in an asynchronous Web-based learning environment while holding constant the effect of three covariate factors: (a) self-efficacy for using computer technology, (b) reason for taking an online course, and (c) prior college academic achievement. The study population was comprised of 201 undergraduate students enrolled in a variety of asynchronous Web-based courses during the spring 2005 semester at a university in the southeastern region of the United States. Data was collected via a Web-based self-report questionnaire and subjected to the following analyses: (a) separate exploratory factor analyses were performed in order to determine the factor structures for the self-regulated learning and for the epistemological beliefs question items, (b) Pearson correlation coefficients describing the associations among the independent variables and between the independent variables and the dependent variable were compared, and lastly, (c) course grades were regressed on the linear combination of all the variables in the model. Analysis of the data revealed that while 5 of 11 independent variables were associated with the dependent variable (GPA, Expectancy, Effort regulation, Quick learning and GPA_Exp); only three (GPA, Expectancy, and GPA_Exp) were significant predictors in the linear predictive model of learning achievement in asynchronous online courses. Study findings were analyzed and reasons offered for why the predictive model of learning achievement in asynchronous online courses included only one self-regulated learning subfactor, no epistemological belief subfactors, and only one of the three covariate factors. Future research that looks at other factors affecting learner achievement and that employs other research methodologies, such as qualitative analysis, are warranted and would greatly add to the literature related to learning achievement in undergraduate asynchronous online environments.
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    A Comparison of the Academic Performance of Jamaican Community College Transfer Students and Native University Students Enrolled in a Collaborative Baccalaureate Degree Program
    (2010-03-23) Buckle, Earle Melford; Bonnie Fusarelli, Committee Member; Joy Gaston Gayles, Committee Member; Duane Akroyd, Committee Co-Chair; Leila Gonzalez-Sullivan, Committee Co-Chair
    There is a perception in the Jamaican postsecondary education system that students who begin baccalaureate studies at community colleges do not perform as well academically as those who begin at the public universities. Therefore, the purpose of this study was to compare the academic performance of transfer students who began their baccalaureate studies under a franchising arrangement between a community college and a university with the academic performance of native university students. Grade point average, time to degree, and baccalaureate degree attainment were used as proxies for academic performance. The study’s conceptual framework was developed from existing models of student attrition. Based on these models, it was hypothesized that institutional type and student characteristics were significant factors in determining a student’s academic success in baccalaureate degree studies. T-tests, one-way ANOVA, and logistic regression were used to analyze data from a stratified sample of transfer and “native†juniors selected from a Jamaican public university. The study compared the academic performance of the two groups as each progressed toward attaining the baccalaureate degree. The study found no significant difference between the academic performances of the two groups. It was determined that the students’ likelihood of degree attainment was not affected by the institution where they started their baccalaureate studies but, instead, by their lower division grade point average. Based on these findings, the study presented a number of recommendations for policy, practice, and future research.
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    Formulating a Prediction Model of Retention Rate in the University of North Carolina System
    (2005-04-26) Ukpabi, Chinasa Victor; Robert Serow, Committee Chair; Duane Akroyd, Committee Co-Chair; Dennis Daley, Committee Member; Troy Chen, Committee Member
    Institutional effectiveness has become an issue in American Higher Education as governing bodies now require evidence of quality in accountability and funding issues. One measure widely used today to assess effectiveness is retention rate. In response to the above as well as to demographic changes, increasing costs, and the intense competition for new students, educational institutions are seeking new methods to increase the retention rate of their institutions. Most research on retention focused on individual student- level variables, which only predict persistence. There is an obvious need to understand the impact of some uncontrollable external influences on retention rates. In light of the importance that retention rate has assumed, this study sought to develop a predictive model of retention rate in the 16-campus University of North Carolina System. In an effort to develop a comprehensive model, this study employed selected institution-level variables. The study will fill a void, as the UNC system does not currently have a general statistical model for predicting retention rates in its multi-campus system. The central research question for the study is whether an institution's retention rate is a function of the demographic characteristics, economic conditions, college management, and fiscal policy of the state in which the institution resides? Pooled cross-sectional time series technique was employed and the method of Ordinary Least Squares (OLS) was used in the estimation of the regression equation. Data was pooled for ten years to provide greater number of data points to overcome a potential degree of freedom problem that would arise studying only 15 institutions. Four themes emerged from the analysis: headcount enrollment, amount of education and general expenditure on instruction and academic support, the county population where institution is located and the rate of unemployment in the county, are significant predictors of retention rate for an institution. Future research including developing prediction models for minority institutions and employing only external variables will perhaps provide additional insights in our understanding of retention rate behavior.