Introduction to \u3ci\u3eDoctoral Education and the Faculty of the Future\u3c/i\u3e

[Excerpt] Concern has been expressed, however, that the growing enrollment of foreign students in American PhD programs crowds out potential American citizen PhD holders and discourages them from pursuing PhD study. On the other hand, the aftermath of 9/11, the growth of research infrastructure and research support in other nations, and the growth of other nations\u27 higher education systems all cast doubt on the ability of the United States to continue to rely on foreign PhD holders to meet our nation\u27s need for scientific researchers and to fill future faculty positions. Given all of these issues, in October 2006 the Cornell Higher Education Research Institute brought together a group of researchers from a wide number of science and social science fields, academic administrators, and policymakers for the conference Doctoral Education and the Faculty of the Future. The sessions at the conference focused on efforts to increase and improve the supply of future faculty, and covered topics ranging from increasing undergraduate interest in doctoral study to improving the doctoral experience and the representation of underrepresented groups in doctoral education. The chapters in this book are revisions of the papers presented at that conference

Essays on PhD Output at U.S. Undergraduate Institutions

This dissertation focuses on the production of knowledge that contributes to economic growth through the accumulation of human capital and technological change. More specifically, I look at the proclivity and effectiveness of different types of universities and colleges to send individuals on to pursue a doctoral degree in science or engineering (S&E) and how PhD attainment relates to characteristics of students who attend these institutions and the faculty who teach at these institutions. A tobit estimation is employed to test for institution effects, the effect of student and faculty characteristics, and also the impact of economic factors. To partially control for selection, survey results from the Higher Education Research Institute (HERI) are used to determine students’ desire for a PhD when entering and exiting college. I find that student and faculty characteristics matter, as do economic variables. Unobservable and/or un-measureable characteristics affecting PhD output, which differ systematically by type of institution, however, remain even after controlling for the aforementioned variables. Based on the analysis in this dissertation, I conclude that much of what are typically regarded as tier effects on PhD output are in fact due to the selective matching between students and their undergraduate institutions. By adding measures for selective matching and proxies for individual opportunities, we see that ability, faculty characteristics and accomplishments, and peer effects maintain significant, positive effects on rates of PhD output. Finally, rates vary not only by institution type, but also by field

Liberal Arts Colleges And The Production Of PhD Economists

Data from the National Science Foundation (2014) indicate that at least one PhD in economics was awarded to a Swarthmore College graduate in every year since 1966. The authors’ purpose in this article is to consider factors that may have contributed to the high number of PhDs in economics awarded to Swarthmore College graduates. While there is little doubt that self-selection plays a significant role, they describe curricular and environmental aspects of the economics department at Swarthmore that may have contributed to this outcome

GENDER AND GRADUATE ECONOMICS EDUCATION IN THE US

This paper reports on the ?ndings of a survey of top economics graduate schools as they relate to women and men. The results provide strong evidence that at these top graduate schools, women graduate students are less integrated in their economic disciplines than are male graduate students. In the second part of the paper, this paper relates those ?ndings to alternative theories as to why this is the case. This paper concludes by suggesting that the emphasis on theoretical studies in the current core of the graduate economics program can be seen as a type of hazing process that seems to have a signi?cant cost since many women (and men) with great creative promise are discouraged from continuing in economics and do not bene?t nearly as much as they would have from more policy-driven core courses.

Curriculum Guidelines for Undergraduate Programs in Data Science

The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science

Improving Underrepresented Minority Student Persistence in STEM.

Members of the Joint Working Group on Improving Underrepresented Minorities (URMs) Persistence in Science, Technology, Engineering, and Mathematics (STEM)-convened by the National Institute of General Medical Sciences and the Howard Hughes Medical Institute-review current data and propose deliberation about why the academic "pathways" leak more for URM than white or Asian STEM students. They suggest expanding to include a stronger focus on the institutional barriers that need to be removed and the types of interventions that "lift" students' interests, commitment, and ability to persist in STEM fields. Using Kurt Lewin's planned approach to change, the committee describes five recommendations to increase URM persistence in STEM at the undergraduate level. These recommendations capitalize on known successes, recognize the need for accountability, and are framed to facilitate greater progress in the future. The impact of these recommendations rests upon enacting the first recommendation: to track successes and failures at the institutional level and collect data that help explain the existing trends