Effects of Unionization on Graduate Student Employees: Faculty-Student Relations, Academic Freedom, and Pay

In cases involving unionization of graduate student research and teaching assistants at private U.S. universities, the National Labor Relations Board has, at times, denied collective bargaining rights on the presumption that unionization would harm faculty-student relations and academic freedom. Using survey data collected from PhD students in five academic disciplines across eight public U.S. universities, the authors compare represented and non-represented graduate student employees in terms of faculty-student relations, academic freedom, and pay. Unionization does not have the presumed negative effect on student outcomes, and in some cases has a positive effect. Union-represented graduate student employees report higher levels of personal and professional support, unionized graduate student employees fare better on pay, and unionized and nonunionized students report similar perceptions of academic freedom. These findings suggest that potential harm to faculty-student relationships and academic freedom should not continue to serve as bases for the denial of collective bargaining rights to graduate student employees.

Using Information on Unconstrained Student Demand to Improve University Course Schedules

We examine how using information on unconstrained demand can improve operational decisions. Specifically, we examine the widespread problem of developing course schedules in not-for-profit university settings. We investigate the potential benefit of incorporating, into the scheduling process, information on the unconstrained demand of students for courses. Prior to this study, the status quo in our college, like that in a large proportion of university settings, was building the course schedule to avoid time conflicts between required courses and to minimize time conflicts between designated groups of courses, such as electives in a particular area. Compared to the status quo approach, we find that, based on three semester's worth of actual data, an approach that explicitly considers students’ course preferences improves a student-based metric of schedule quality on the order of over 4% (which is the equivalent, in our setting, of improving service for over 20% of students).