Gerald W. McLaughlin

Size and Efficiency.

It has been long assumed that it takes some optimum size in order to obtain a sufficient critical mass to have an economy of scale operation, but there has been little substantive study of the topic. This paper looks at the relationship between enrollment and costs at colleges and universities. The question under study is whether large size provides economy of scale for operating. The question, unfortunately, is masked by the complexity of an institution. The manner in which complexity, size, costs, and enrollment interrelate is the substance of this paper. The findings suggest that curricula and complexity have an exceedingly important bearing on per-student costs.

Assessing the Integrity of Web Sites Providing Data and Information on Corporate Behavior

A significant trend in higher education evolving from the wide accessibility to the Internet is the availability of an ever-increasing supply of data on Web sites for use by professors, students, and researchers. As this usage by a wider variety of users grows, the ability to judge the integrity of the data, the related findings, and the Web site is becoming increasingly important. This article lays the groundwork for developing a set of Generally Accepted Standards of Data Integrity to guide users in evaluating data and information available on Internet Web sites.

Using composite metrics to measure student diversity in higher education

The role and impact of diversity in higher education has permeated conversations about student access and achievement for many years. Language articulated by various courts suggests that higher education policies should reflect a broad conceptualisation of diversity beyond that of the magnitude and proportion of race and ethnicity, yet institutions struggle to measure diversity in a manner that effectively supports the management of diversity goals and meets the legal requirements for targeted strategies. Building on methodologies from biology and political science, this paper proposes a new way of conceptualising and measuring diversity that addresses the limitations of traditional diversity metrics and accounts for race and race-neutral attributes within a single model. Using data from over 1500 colleges and universities, the development of a composite diversity index is demonstrated as a strategy for meeting organisational need to account for and measure multiple diversity attributes.

Higher education institutional rankings: Evaluating their credibility for branding and marketing

This chapter focuses on the importance of addressing two concerns before using the rankings—how rankings are used by stakeholders and whether the rankings are credible. Higher education institutions (HEIs) are ranked on almost every conceivable attribute. As a result, HEI ranking has emerged as a robust marketing component in branding and is used extensively by institutions. This chapter provides an overview of whether stakeholders are influenced by HEI rankings and a discussion of three important ranking issues—source legitimacy, data integrity, and methodology. A discussion of professional schools identifies the unique issues that surface when rankings focus on specialized programs. We conclude with a description of the International Ranking Expert Group initiative to create a framework for developing and evaluating credible HEI rankings.

Using Simpson's diversity index to examine multidimensional models of diversity in health professions education

Objectives This study explored new models of diversity for health professions education that incorporate multiple attributes and examined differences in diversity based on urbanicity, geographic region, and institutional structure. Methods Simpson’s Diversity Index was used to develop race, gender, and interprofessional diversity indices for health professions schools in the United States (N = 318). Sullivan’s extension was used to develop a composite diversity index that incorporated multiple individual attributes for each school. Pearson’s r was used to investigate correlations between continuous variables. ANOVA and independent t-tests were used to compare groups based on urbanicity, geographic region, and Basic Carnegie Classification. Results Mean (SD) for race, gender, and interprofessional diversity indices were 0.36(0.17), 0.45(0.07), and 0.22(0.27) respectively. All correlations between the three indices were weak. The composite diversity index for this sample was 0.34(0.13). Significant differences in diversity were found between institutions based on urbanicity, Basic Carnegie Classification, and geographic region. Conclusions Multidimensional models provide support for expanding measures of diversity to include multiple characteristics and attributes. The approach demonstrated in this study enables institutions to complement and extend traditional measures of diversity as a means of providing evidence for decision-making and progress towards institutional initiatives.