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At the University of Adelaide, the total number of students enrolled in any course is controlled by quotas on the number of new entrants to the course each year. A linear relationship is used to forecast total enrolment given the number of new students in each previous year ; for future years, the number of new students is taken to be the size of the quota. Chapter 1 relates the methods in use at the University of Adelaide to the work of other authors and demonstrates how a Markov model may be used to obtain the lifetimes of students in a particular course, namely the Ph.D. degree course. Chapter 2 then develops a linear programming model which mimicks the forecasting method already in use and which determines the intake quotas over a period of years that use as much as possible of the course capacity while satisfying certain constraints. These constraints en - sure that the total enrolment each year is no greater than the capacity in that year and that the intakes are non - decreasing and no greater than some maximum value. In particular, the programme is designed to be used to determine strategies which move the course into a constant enrolment, or non - growth, period while accounting for restrictions on the permissible rate of growth. It is shown that the special structure of the problem may be exploited to find a particular solution which is optimal for several, commonly encountered objective functions. The requirement that the intakes should be integral is discussed and is shown to pose very little additional difficulty. An example from the University of Adelaide is used to illustrate the methods. Chapter 3 considers extensions of the basic model ( the single - grade, single - course case ) to situations where there are several grades within a course with capacities on some of these grades or where several inter - related courses are to be planned at the same time. Finally, chapter 4 contains a discussion of the applicability of the work of the thesis and suggests possibilities for further extensions. / Thesis (Ph.D.)--Department of Applied Mathematics, 1975.

At the University of Adelaide, the total number of students enrolled in any course is controlled by quotas on the number of new entrants to the course each year. A linear relationship is used to forecast total enrolment given the number of new students in each previous year ; for future years, the number of new students is taken to be the size of the quota. Chapter 1 relates the methods in use at the University of Adelaide to the work of other authors and demonstrates how a Markov model may be used to obtain the lifetimes of students in a particular course, namely the Ph.D. degree course. Chapter 2 then develops a linear programming model which mimicks the forecasting method already in use and which determines the intake quotas over a period of years that use as much as possible of the course capacity while satisfying certain constraints. These constraints en - sure that the total enrolment each year is no greater than the capacity in that year and that the intakes are non - decreasing and no greater than some maximum value. In particular, the programme is designed to be used to determine strategies which move the course into a constant enrolment, or non - growth, period while accounting for restrictions on the permissible rate of growth. It is shown that the special structure of the problem may be exploited to find a particular solution which is optimal for several, commonly encountered objective functions. The requirement that the intakes should be integral is discussed and is shown to pose very little additional difficulty. An example from the University of Adelaide is used to illustrate the methods. Chapter 3 considers extensions of the basic model ( the single - grade, single - course case ) to situations where there are several grades within a course with capacities on some of these grades or where several inter - related courses are to be planned at the same time. Finally, chapter 4 contains a discussion of the applicability of the work of the thesis and suggests possibilities for further extensions. / Thesis (Ph.D.)--Department of Applied Mathematics, 1975.

Thesis (M. BM)--University of Adelaide, Faculty of Economics, 1980.

Thesis (Ed.D.)--Teachers College, Columbia University. / Typescript; issued also on microfilm. Includes tables. Sponsor: Esther M. Westervelt. Dissertation Committee: JB Lon Hefferlin. Includes bibliographical references.

Thesis (M.A.)--University of Detroit, 1950. / "August 1950." Includes bibliographical references (p. 49-52).

Thesis (Ph. D.)--University of Toronto, 1993. / Includes bibliographical references (leaves 239-254).

<p> Contemporary social issues, such as poverty, inequality, and climate change, exceed the capacity of a single sector to solve and require the collaboration of the public, private, and nonprofit sectors. In this context, universities play a unique and increasingly comprehensive role in educating students, generating new knowledge, and advancing the social and economic conditions in their communities. </p><p> Over the past decade, explosive growth has occurred in social entrepreneurship and social innovation initiatives on university and college campuses. Whether offered through a center, initiative, or program, a groundswell of curricular, co-curricular, and convening activities has emerged that educates and engages students, faculty, and a range of stakeholders in the pursuit of solving pressing social issues in innovative ways. </p><p> Using qualitative research methodology and a grounded theory approach, the purpose of this study was to explore the broad phenomenon of and the proliferation of university-based social impact centers in the United States. Through the perspectives and lived experiences of 43 social impact leaders, from multiple higher education institutions, this study developed a grounded theory model which explains the forces driving the emergence and evolution of the university-based social impact centers. The phenomenon can be explained by these &ldquo;windows of opportunity&rdquo; where internal, external, and cultural forces intersect, interact, and overlap with one another, within institutional-specific contexts, to produce new centers. While each institution boasts a unique culture and contextual characteristics, the data demonstrated that mission-driven students, market pressures on higher education institutions, and donor support were the most significant forces driving the expansion of social innovation on college campuses. Akin to the double-bottom line, it was both mission and markets that catalyzed the university-based social impact phenomenon. </p><p> While the social impact phenomenon initially evolved out of elite graduate business schools, it has expanded cross-campus into public policy schools and central administrative units, and across all institutional types. Social impact education now expands across and down the curriculum and co-curriculum. Some universities now even have multiple social impact initiatives within their own institutions. Participants described the need to differentiate themselves and to compete for resources, students, and attention given the plethora of existing civic and socially-oriented programs on their campuses. </p><p> This study filled a distinct gap in the literature by studying university-based social impact centers, framed in the broader historical context of the evolutionary role of university engagement in their communities, coupled with the recognition of the realities of contemporary market pressures on higher education institutions. Social impact centers exhibit the intersectionality of a host of issues plaguing higher education, such as resource constraints, access, academic silos, specialization, and bureaucracy versus innovation. Finally, social impact centers are a microcosm of the tension that exists between the marketization of higher education and the pressure to hold true to public purposes&mdash;and ultimately, whether or not institutions can effectively mediate those two pressures.</p><p>

<p> The purpose of this study is to understand how social class background plays a role in student experiences on selective campuses. This study centers the experience of low-income students and extends the work of Ostrove and Long (2007). Previous research has indicated that race, gender, and social class status have each, respectively, been demonstrated to have statistically significant relationships to sense of belonging. This research affirms existing research, but also finds that there are more positive relationships than previously theorized. Minoritized students had higher mean scores related to personal-emotional adjustment and social adjustment. Students from the lowest social class also reported higher scores on the same two adjustment scales than their peers. </p><p> Based in the theory of critical quantitative analysis (Stage, 2007), the research uses the Student Adaptation to College Questionnaire (Baker &amp; Siryk, 1999) in order to assess sense of belonging. This survey measures overall sense of belonging, academic adjustment, social adjustment personal-emotional adjustment and institutional attachment. Examining these measures in an intersectional way revealed results that were more nuanced than was previously found in the literature. The data was analyzed using simple linear regression, analysis of variance, and hierarchical multiple regression. The survey was conducted among undergraduate students at The George Washington University, a private, urban institution in Washington, D.C. </p><p> In demonstrating that minoritized and economically and educationally challenged students may be adjusting better than has been previously stated, this study emphasizes the need to affirm students in the identities they hold for themselves rather than studying them through deficit models. Reinforcing the cultural and social norms of marginalized groups aids in their personal growth and development, which often leads to a university&rsquo;s desired outcome, which is retention and graduation.</p><p>

<p> One in five federal student loan borrowers today is enrolled in income-driven loan repayment (IDR), a set of safety net programs in which loan payment amounts are tied to borrowers&rsquo; incomes. Policymakers across the political spectrum support expanding IDR as a way of reducing loan default and encouraging borrowers to work in public service careers, though there is little evidence of the effects of IDR on borrowers&rsquo; outcomes. Through the lenses of human capital theory and risk aversion theory, this study investigates two key gaps in our knowledge about IDR in comparison to other repayment plans: whether IDR borrowers&rsquo; make different career choices and whether IDR borrowers are more successful at paying their loans. Using the National Center for Education Statistics&rsquo; Baccalaureate and Beyond dataset (B&amp;B:08/12), I weighted borrowers by their propensity to enroll in IDR, based on family, institutional, communities, and political and economic characteristics. This analysis found that IDR borrowers are statistically significantly more likely to be women, of Hispanic origin, and from low-income households. IDR borrowers are no more likely to pursue public service careers four years after graduation, but they are substantially more likely to be in repayment as opposed to being in default, forbearance, or any other loan status. The total estimated costs of loan repayment are more varied for IDR borrowers than for borrowers in other plans. Borrowers of color in IDR are likely to pay more than White borrowers in IDR. I conclude with a discussion of the implications for policy, research, and practice, including how policy makers and researchers should interpret the tradeoffs in these results.</p><p>