Research: Developing the Engineering Workforce: Examining Faculty Beliefs to Connect School to Work

Virginia Polytechnic Institute And State University, Blacksburg VA

Investigators

Abstract

Engineering programs across the United States are committed to developing an industry workforce capable of maintaining and enhancing the nation’s economic success and technological leadership. Today’s graduating engineers must be fully prepared to enter the workplace and contribute to both the economic success of their employers and the national priorities of the country from Day 1. Despite this commitment from colleges and universities, employers continue to report critical gaps in how well new engineers are prepared for work. To develop effective professional engineers, programs need to do a better job of connecting what happens in the classroom to what happens on the job. One potential challenge to this work is the lack of industry experience among the faculty who teach engineering. Without practical work experience, faculty may not fully understand what engineers do and may struggle to connect classroom teaching to industry needs and practices in ways that most effectively prepare new graduates for the standards, norms, and practices of engineering work. This project will help address that problem by first determining what engineering faculty across the country do know about engineering work, and then understanding if and how they use that knowledge in their teaching. We will use our findings to create workshops, handouts, and other resources to help faculty better connect their teaching to the needs of employers and new graduates making the transition from school to work. We will work with teacher development programs, professional organizations, and others to help ensure that the people who teach the nation’s engineers know what their students will do after graduation and know how to connect their teaching to the real world. To address this gap, we propose a three-phase study that integrates Mental Models Theory (MMT) with the Theory of Planned Behavior (TPB) to address four research questions: 1) What experiences have engineering faculty members had with engineering work? 2) What are engineering faculty members’ mental models of engineering work? 3) In what ways do those models interact with faculty decisions about teaching? 4) How do the results vary by factors such as institution type and discipline? The study will begin with a national survey, followed by focus groups and then individual interviews, to better understand how faculty beliefs about engineering work impact courses and curricula. First, we will conduct the first large-scale national survey of engineering faculty member’s work experience in more than 30 years to generate reliable data on how much and what kinds of experiences the country’s engineering educators have with current industry practices. Second, we will conduct focus groups at a targeted set of universities, using data from each program’s own graduates, to test our protocols and develop a preliminary model of faculty mental models of engineering work and the impact of those models on teaching. Third, we will conduct semi-structured interviews with a purposive sample survey of respondents to elicit mental models and connections between teaching and post-graduation work in more detail across a wider population. These interviews will help us fully understand how engineering teachers connect what they do in the classroom to what they think their students will do after graduation. The outcomes will enable us to identify specific gaps, problems, or challenges, including gaps in what faculty know about current engineering industry practices and challenges they experience in trying to connect their teaching to those practices. The results will then be used to develop interventions, including faculty development workshops, handouts, and web resources, that can address the gaps identified through the project. 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.