2026 ASEE Annual Conference & Exposition

This methods/theory work-in-progress paper overviews the methodological decision-making in an effort to model engineers’ career trajectories. Available data and current studies on the engineering workforce offer a limited perspective on postgraduate engineering career trajectories. In particular, engineering careers are commonly assumed to be linear evolving from entry-level positions to managerial or technical expert roles. In reality, careers are more complex. This misalignment between career expectations and realities is concerning because assumptions about “successful” careers inform the priorities of engineering curricula, individuals’ career decision-making processes and self-concepts, and occupational reward structures and evaluation systems.

This paper, framed by the Boundaryless Career Framework, presents a study that begins to address this gap by introducing a methodological approach to systematically observe and analyze the dynamics of engineering career pathways. So far, we have developed a codebook to categorize our data and ethically web-scrapped 303 career profiles of alumni of one engineering department from LinkedIn. We selected cohorts from 1999, 2004, 2009, and 2014 to capture how the career trajectories of engineers were shaped by global economic events like the 2008 Recession and the COVID-19 pandemic. Additionally, we used separate pilot data from 20 LinkedIn profiles to develop a code book that standardizes career data across individuals, roles, and organizations. This codebook categorizes professional experiences by sector (determined by the organization), occupation (job task), and hierarchy (job task). In this paper, we present our current progress and introduce alternative methods for studying career data to the engineering educational research community. We raise and address key methodological issues expecting to receive feedback from the community. Looking ahead, we expect this work to support engineering faculty in career advising roles and departmental/program-level decision-making processes.