Admissions processes for health professions programs result in students entering these programs academically homogeneous. Yet some students have great difficulty with the programs. Research has shown a limited ability of traditional academic indicators to predict successful outcomes for health professions education. The purpose of this study was to examine the relationship between learning motivation and academic outcomes for students in health professions programs. The Modified Archer Health Professions Motivation Scale (MAHPMS) and a demographic survey were administered at orientation to 131 medical and 29 physician assistant students at the University of North Texas Health Science Center in the fall of 2005. At the end of the semester, the same version of the MAHPMS was administered, and final course grades and semester averages were collected. Descriptive statistics were analyzed for all the study variables. Analysis of variance was utilized to examine within subjects and between subjects differences for the learning motivation scores among programs and demographic categories. Linear regression analyses were used to determine the relationship between learning motivation scores and end-of-semester grades. And finally, logistic regression was performed to explore the ability of the motivation scores to predict academically high-risk students. Approximately three-fourths of the students indicated a preference for mastery learning and an internal locus of control. For the PA students, alienation to learning and performance goal scores statistically related to semester grades, and alienation to learning scores predicted high-risk academic performance almost 90% of the time. For the medical students, mastery goal scores statistically related to semester grades, but no motivation score predicted high-risk performance. External locus of control scores predicted high-risk performance 81% of the time for the total group of students at the end of the semester. Students in this study exhibited learning motivation preferences similar to those of other health professions students reported in the literature. The findings of this study agreed with the literature on achievement motivation theory and raised questions regarding the effect of health professions curricula on student learning goals. Similar studies, measuring larger samples longitudinally need to be conducted in order to further validate or elucidate the results of this study.

Online courses in higher education have a reputation for having a lower course completion or retention rate than face-to-face courses. Much of this reputation is based upon anecdotal evidence, is outdated, or is on a small scale, such as a comparison of individual courses or programs of instruction. A causal-comparative analysis was conducted among 11 large, high research public universities. The universities were compared to each other to determine if differences existed between online and face-to-face course completion; undergraduate and graduation online course completion was analyzed for differences as well. The findings suggested the magnitude of the differences between online and face-to-face completions rates was small or negligible. The area which showed a higher magnitude of difference was in the comparison between undergraduate and graduate online course completion; the practical significance could be worth considering for educational purposes.

This research investigated the association between academic lineage and student performance in medical school. The purposes of the study were to: (1) determine whether the Carnegie classifications of medical school applicants' institutions of origin are associated with academic performance in medical school; (2) consider the relationship between the admission selectivity of the schools of origin and the academic performance of medical school students; (3) compare the performance of medical students from institutions under public governing control with students from privately controlled institutions; and (4) establish a model by which the relative academic strengths of applicants from a variety of undergraduate institutions can be understood more clearly based on the previous performance of medical students from schools with similar institutional characteristics. A review of the literature on medical school admissions was completed and used to develop this research. Medical students from the University of Texas Southwestern Medical Center at Dallas who enrolled between the years 1990 and 1994 and graduated or were dismissed between the years 1994 and 1998 were selected as the sample for the study (n=933). The undergraduate institution of origin for each student was coded based on its Carnegie classification, admissions selectivity group, and whether its governing control was public or private. Because the sample was not randomly selected and the data likely would not meet the assumptions of equal means and variance with the population, nonparametric analyses of variance and multiple comparison tests were completed to compare the groups of the independent variables over each dependent variable. The analyses revealed that for the sample of medical students selected for this study there was an association between academic lineage and student performance in medical school. Differences were found among Carnegie classifications on the dependent variables of cumulative medical school grade point average, class rank, failure rate, and score on Step 1 of the United States Medical Licensure Examination. Further, it was found that admission selectivity was also associated with student performance in medical school for each dependent variable except failure rate. Finally, the study results indicated no association between public or private governing control and student performance in medical school.

published_or_final_version / Education / Master / Master of Education

In this dissertation a study will be made of university performance in the Science Faculty of the University of Natal, Durban. In particular, we will develop models that can be used to predict the success rate of a student based on his or her matriculation results. These models will prove useful for selecting students to universities. They may also be used to assist sponsors, bursars and donors in allocating funds to deserving students. In addition, these models may be used to identify students who might experience difficulties in their studies at university. / Thesis (M.Sc.)-University of Natal, Durban, 1994.

This study was a quantitative multiple regression investigation into the relationships between campus factors of high school students graduating in 2013 who immediately enrolled in first-year college freshman level remedial coursework at a large, Central Texas two-year postsecondary institution. The goal of this study was to determine which high school campus-level factors predicted enrollment into college remedial education coursework. The dependent variable was a continuous variable representing the percentage of students from Texas public high school campuses enrolled into at least one student credit hour of remedial education during their first semester as a first-year college student. Eight high school campus-level independent variables were included in the regression model at the campus-level: at risk percentage, economically disadvantaged percentage, limited English proficient percentage, advanced course/dual-enrollment percentage, college ready math percentage, college ready English percentage, ACT average, and SAT average. Pearson correlations and linear regression results were examined and interpreted to determine the level of relationship between the eight selected variables and first-year college student remedial coursework. The multiple regression model successfully explained 26.3% (F(8,286) = 12.74. p < 0.05, r2 = 0.263) of the variance between first-year college students enrolled into remedial coursework at a large, Central Texas two-year postsecondary institution and the campus-level variables from high schools from which they graduated and indicated campus-level economic disadvantaged percentage and campus-level SAT average to be statistically significant at the p < 0.05 level.

The aim of this research was (1) to provide empirical data of learning potential and English language proficiency for work performance; (2) to establish whether race and gender influence work performance; (3) to evaluate practical utility and to propose recommendations for selection purposes. The Learning Potential Computerised Adaptive Test and the English Literacy Skills Assessment were used as measuring instruments to measure learning potential and English language proficiency respectively. Work performance data were obtained from the normal performance data system of the company where the research was conducted. ANOVA results showed differences between race and gender groupings. A regression analysis confirmed the predictive validity of learning potential and English language proficiency on work performance. The Spearman rho correlation coefficient (p < 0.05) showed a significant positive correlation between the investigated variables / Industrial and Organisational Psychology / M. A. (Industrial and Organisational Psychology)

The purpose of the present correlational, ex post facto study was to evaluate the predictive ability and academic achievement criterion outcomes of two district-developed interim mathematics assessment programs for a sample of 5,801 grade 6 students in a large urban school district. Average scores for both interim assessment types were statistically significantly more related to 2013 FCAT 2.0 scores (r = .75 and .72; p < .001) than all other predictors (i.e., student demographics, Florida school grade, and student course GPA) except for 2012 FCAT 2.0 scores (r = .78; p < .001). Further, the newer interim assessment program with an instructional purpose and curriculum-based sequencing had slightly stronger overall predictive power (rs = .88) and a higher criterion mean score (M = 218.08) than the older, state-test mirror interim assessment program (rs = .85; M = 215.47). Regression models by prior year FCAT 2.0 Achievement Level yielded some predictor ranking discrepancies by prior achievement level. Although not statistically significant at the .01 level, groups of students with a more moderate total number of interim assessments outperformed groups with all or nothing. Overall, the two types of interim assessment programs evaluated in the present study were good predictors of the state high-stakes test, 2012 Grade 6 Mathematics FCAT 2.0. However, more research must be done to identify with certainty whether or not the act of taking the interim tests and receiving feedback contributes to improved student learning.

This thesis contributes to the ongoing global discourse in ICT4D on ICT and its effect on socio-economic development in both theory and practice. The thesis comprises five studies presented logically from chapters 5 to 9. The thesis employs Mixed Methods research methodology within the Critical Realist epistemological perspective in Information Systems Research. Studies 1-4 employ different quantitative research and analytical methods while study 5 employs a qualitative research and analytical method. Study 1 proposes and operationalizes a predictive analytics framework in Learning Analytics by using a case study of the Computer Science Department of the University of Jos, Nigeria. Multiple Linear Regression was used with the aid of the Statistical Package for Social Sciences (SPSS) analysis tool. Statistical Hypothesis testing was then used to validate the model with a 5% level of significance. Results show how predictive learning analytics can be successfully operationalized and used for predicting students’ academic performances. In Study 2 the relative efficiency of ICT infrastructure utilization with respect to the educational component of the Human Development Index (HDI) is investigated. A Novel conceptual model is proposed and the Data Envelopment Analysis (DEA) methodology is used to measure the relative efficiency of the components of ICT infrastructure (Inputs) and the components of education (Outputs). Ordinary Least Squares (OLS) Regression Analysis is used to determine the effect of ICT infrastructure on Educational Attainment/Adult Literacy Rates. Results show a strong positive effect of ICT infrastructure on educational attainment and adult literacy rates, a strong correlation between this infrastructure and literacy rates as well as provide a theoretical support for the argument of increasing ICT infrastructure to provide an increase in human development especially within the educational context. In Study 3 the relative efficiency and productivity of ICT Infrastructure Utilization in Education are examined. The research employs the Data Envelopment Analysis (DEA) and Malmquist Index (MI), well established non-parametric data analysis methodologies, applied to archival data on International countries divided into Arab States, Europe, Sub-Saharan Africa and World regions. Ordinary Least Squares (OLS) Regression analysis is applied to determine the effect of ICT infrastructure on Adult Literacy Rates. Findings show a relatively efficient utilization and steady increase in productivity for the regions but with only Europe and the Arab States currently operating in a state of positive growth in productivity. A strong positive effect of ICT infrastructure on Adult Literacy Rates is also observed. Study 4 investigates the efficiency and productivity of ICT utilization in public value creation with respect to Adult Literacy Rates. The research employs Data Envelopment Analysis (DEA) and Malmquist Index (MI), well established non-parametric data analysis methodologies, applied to archival data on International countries divided into Arab States, Europe, Sub-Saharan Africa and World regions. Findings show a relatively efficient utilization of ICT in public value creation but an average decline in productivity levels. Finally, in Study 5 a Critical Discourse Analysis (CDA) on the UNDP Human Development Research Reports from 2010-2016 is carried out to determine whether or not any public value is created or derived from the policy directions being put forward and their subsequent implementations. The CDA is operationalized by Habermas’ Theory of Communicative Action (TCA). Findings show that Public Value is indeed being created and at the core of the policy directions being called for in these reports. / School of Computing / Ph.D. (Information Systems)

Mathematics achievement has been of great concern to researchers involved in mathematics education. This concern has resulted in research seeking to determine for example, the factors that positively or negatively contribute to student performance in mathematics. Many of the reported studies in the literature have investigated the factors within the context of mathematics teaching and learning in general. Very few studies have investigated the factors contributing to student achievement in mathematics when learning takes place in a computer aided environment. With the pervasiveness of computers in education in general, studies in this direction become imperative. The present study fills this gap in the literature by examining the extent to which selected variables (mathematics attitude, mathematics aptitude, computer attitude, computer prior experience, computer ownership, proficiency in language of instruction, and learning style) contribute to students' achievements in pre-calculus algebra classes that are supplemented with a computer lab program. The participants in the study were 120 students sampled from the population of students enrolled in the second pre-calculus algebra course at the preparatory year program of King Fahd University of Petroleum & Minerals during the 2003/2004 academic session. The instruments used to measure the study constructs were the mathematics attitude scale (Aiken, 1979), the computer attitudes scale (Loyd & Gressard, 1984a), and the learning styles questionnaire (Honey & Mumford, 1992). New instruments to measure computer prior experience and computer ownership were developed for the present study. Hypotheses formulated for the study were tested using multiple regression and other statistical techniques. The results show that mathematics aptitudes and English language proficiency are the most significant contributors to students' mathematics achievement. No other variables show statistically significant effects on students' achievement. Together, the selected variables explain more than 41 percent of the total variance of students' achievement. Theoretical and policy-making implications of the results are outlined and discussed. / Mathematical Sciences / D. Phil. (Mathematics, Science and Technology Education)