2026 ASEE Annual Conference & Exposition

As engineering education research expands in scope and scale, understanding how the field has evolved becomes essential for guiding future inquiry and practice. For new engineering educators and engineering education researchers who may be coming from a variety of discipline-based research areas, understanding the history of our field is important, yet difficult to trace, given the scope and size of the American Society of Engineering Education (ASEE) conferences. This study conducts a corpus analysis of ASEE conference papers spanning 2000–2025 to systematically map trends in research topics over the past 25 years. Using natural language processing and topic modeling techniques, we analyzed more than 40,000 ASEE papers to reveal patterns that are difficult to detect through traditional literature reviews. A corpus-level approach provides unique advantages: it enables objective, data-driven insight into how engineering education discourse has shifted over time and identifies emerging and declining themes. Data visualizations provide opportunities for readers to find trends of relevance to themselves. This analysis supports educators and researchers in benchmarking their efforts against broader trends, identifying underexplored areas, and recognizing methodological shifts within the community. Preliminary results show clustering of 25 years of ASEE scholarship into 160 topics. Exploration of these topics highlights growth in specific research and pedagogical areas and evaluation methods. Our analysis also shows the expected shifts in pedagogical and research topics following 2020, and the sharp increase in papers discussing artificial intelligence (AI) in the past 5 years. By creating a longitudinal, quantitative overview of ASEE scholarship, this study provides a history of the field for new engineering educators and may help drive innovation in our field. For the engineering education community, this analysis may inform conference programming, journal priorities, and collaborative research agendas aimed at the most pressing challenges in engineering education.

An interactive visualization of this corpus is available here: https://www.hollygolecki.com/asee-corpus