Transforming Graduate Education in Transportation Engineering: Applying Cognitive Apprenticeship to Translate Doctoral Student Skills from Research-to-Practice

Rowan University, Glassboro NJ

Investigators

Abstract

Transportation Ph.D. students increasingly choose jobs within industry or government agencies upon graduation. Despite the in-depth training during their degree programs, most of these students do not have the broad skills needed to start positions at a mid-career level (equivalent to 5+ years of work experience). This NSF Innovations in Graduate Education (IGE) award to Rowan University will pilot a new research-to-practice training model to bridge this gap. Students will progressively build their skills and learn how to apply them to the transportation industry through intentional learning experiences built around a cognitive apprenticeship model. In this program, transportation Ph.D. and Master’s students who are conducting research and writing a thesis will develop technical competencies, business and communication skills, leadership and team development approaches, and build their networking capabilities. The training program is novel as few programs focus on applying a cognitive apprenticeship model to assist students with learning how to apply their research skills in a non-academic setting. The training program also collaborates closely with industry and government partners, which will help ensure that the transportation Ph.D. students are prepared for mid-career level positions upon graduation. Moreover, this experience will benefit all participating graduate students because it provides practical experiences that will assist in professional development. The revised structure of the transportation Ph.D. program with an emphasis on industrial/government applications will attract a diverse student population interested in creating value for the local and broader community. This pilot transportation Ph.D. training program will seek to answer “How can a research-to-practice model assist students in preparing for a transportation engineering career outside of academia?” More specifically, it will address three research questions: (1) What impact does the research-to-practice graduate model have on developing transportation engineering doctoral students’ professional identity? (2) How does the cognitive apprenticeship framework prepare doctoral students for professional practice in transportation engineering? and (3) What influences does the research-to-practice graduate model have on doctoral students’ motivation towards degree completion? The research design uses qualitative and explanatory mixed methods approaches, including student reflections, interviews, and surveys, to address the proposed research questions. As both professional identity and motivation are related to persistence and retention within graduate degree programs, particularly for students from groups that are underrepresented in the field, this research will help address the preparation of a diverse doctoral student population for careers in transportation engineering. This effort is also anticipated to lead to better retention of students in the transportation Ph.D. program. This project’s completion will improve understanding of how a cognitive apprenticeship model can be applied to scaffold doctoral students’ professional development in preparation for non-academic careers. Although the results will be specific to the transportation engineering doctoral population, using a mixed methods approach will help achieve results that could be transferable to other engineering programs and contexts. The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.