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Thesis (M.S.)--Boston University

In order to understand withdrawal rates in online K-12 schools, it is vital to have detailed documentation of these rates and to describe characteristics of the students who withdraw compared to the students who remain enrolled. Once these characteristics are known schools can develop programs and/or policies that support students who are at risk of withdrawing. This study was a descriptive analysis of (a) attendance, (b) lessons completed, (c) participation, (d) teacher-student communication, and (e) overall performance percentage comparing the means between the enrolled student population and the withdrawn student population using extant data. Four of the five variables, (a) attendance, (b) lessons completed, (c) teacher-student communication, and (d) overall performance percentage, were significant at the p < .01 level. Upon analysis, the results of average lessons per day were not reportable due to problems with the data. The Enrolled group had significantly higher means in the following variables: (a) attendance, (b) lessons completed, (c) teacher-student synchronous contact, and (d) overall performance percentage.

At California State University San Bernardino, students can ordinarily register online and join waiting lists when a course is full. However, the system does not support waiting lists when a course has associated laboratory sections. This project addresses this problem.

Magister Philosophiae - MPhil / Background: In South Africa, many students are not able to register at higher education institutions after receiving their high school diploma. The majority of those who do register do not even complete their tertiary studies. The purpose of this research project is to investigate and analyse higher education institutions’ enrolment and dropout within the Gauteng province, South Africa. Data and Methods: Large-scale secondary data from the General Household Survey (GHS, 2012), obtained from Statistics South Africa were used. The Statistical Package for Social Science (SPSS) and the Statistical Analyst System (SAS) software package were utilised for quantitative analysis. The numerous local and international pedagogical studies synthesised in this research show that finance, unplanned pregnancies, orphanhood and transport to the higher education institutions are some of the main concerns that affect the enrolment rate of students. Further variables such as gender, race, ethnicities and the type of institution have also negatively affected the enrolment rate of students, particularly in sub-Saharan Africa. Results: According to the ICEF Monitor 2015, current higher education enrolment in Sub-Saharan Africa is 8%. The UIS Fact Sheet 2010 revealed that the enrolment ratio is 4.8% for women compared to 7.3% for men. The present study focuses on the Gauteng province's students who have completed their high school education, as well as those who are either registered or not registered within the province’s higher education institutions, and are between the ages of 17 and 35 years. Conclusion: This study hopes to be useful to policy-makers, research managers and other decision makers within education.

Discrete-time Markov chain models can be used to make future predictions in many important fields including education. Government and educational institutions today are concerned about college enrollment and what impacts the number of students enrolling. One challenge is how to make an accurate prediction about student enrollment so institutions can plan appropriately. In this thesis, we model student enrollment at East Tennessee State University (ETSU) with a discrete-time Markov chain model developed using ETSU student data from Fall 2008 to Spring 2017. In this thesis, we focus on the progression from one level to another within the university system including graduation and dropout probabilities as indicated by the data. We further include the probability that a student will leave school for a limited period of time and then return to the institution. We conclude with a simulation of the model and a comparison to the trends seen in the data.

At many traditional universities, the federal timelines for determining financial aid eligibility is based on releasing of the Free Application of Federal Student Aid each January, and the subsequent financial aid processing cycle July 1- June 30th. These federally established dates can conflict with traditional August class starts and creates a backlog and delayed processing of information that, in turn, hinders students from receiving timely information in order to make informed decisions based on financial aid awards. The purpose of this case study of a traditional university in Georgia was to apply net price theory and rational choice theory to evaluate the impact of timeline conflicts and how students make decisions about which institution to attend. Data consisted of internal documents, including the results of a prior survey of 425 freshmen, and 13 alumni focus group and survey participants. All data were inductively coded and analyzed using a constant comparative method to reveal key themes. Key findings indicated decision making by prospective students largely focused on accurate and timely communication and cost of attendance. One discrepant area was the decision maker's ability to differentiate between cost of attendance and net price which impacted some student decisions to enroll. The findings are consistent with both net price and rational choice theory. Recommendations to university leaders include encouraging early communication to prospective students and retraining efforts for financial aid staff in order to meet regulatory demands and timelines, increase student enrollment, and reduce anxieties for potential students and families associated with the financial aid process. These outcomes enhance social change by potentially opening doors to higher education for new generations of students.

The purpose of the study was to examine district, campus, and community determinants of principal’s salaries using a spatial econometric framework. Among the district variables business tax (p = 0.001), property tax (p < .01), and the Herfindahl Index (measure of competition) were statistically significant indicators of principal salaries. The results suggest that more affluent districts tend to pay principals higher salaries, which was expected. Regarding campus characteristics, the percent of economically disadvantaged was not a statistically sound indicator (p = 0.468), but campus enrollment was significant (p = <.01). Interestingly as the percentage of economically disadvantaged students increased, the principal salary decreased. In contrast, as student enrollment increases the salary of principals increases, suggesting that principals of larger campuses earn higher salaries. Interestingly, student achievement was not a statistically significant predictor of principals’ salary given that pay for performance in Texas is at the forefront of political debate. Among the variables examined at the community level, only the percentage of homes owner occupied (p = 0.002) was found to be a statistically significant indicator of principal salary (p = .002). The lack of evidence on reforms, such as determinants of principal salary, points to data and research deficiencies to be addressed in order to learn more about their effects and make sound public policies. The paper utilized a spatial regression approach to examine the determinants of principal salary using data from the local, state, and national data sources. Principal salaries are viewed from several lenses in this study by considering effective outcomes of pay defined by actual salaries and market considerations for pay as defined by community, organizational, and human capital variables. Literature from the private sector as well as from the public school setting was used as a theoretical underpinning for the hypotheses set forth in this study. Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further. The paper includes implications for educational policy development related to pay for contribution, rather than pay based on tenure, experience, or district wealth. The research also fulfils an identified policy need to study how principal salaries are determined.

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