2026 ASEE Annual Conference & Exposition

This Tricks of the Trade paper explores how Generative AI (GenAI) can support early-career engineering education researchers in literature sourcing for research design. Transitioning from technical engineering to engineering education research (EER) requires navigating unfamiliar interdisciplinary literature in sociology, psychology, and education, a time-consuming process that creates barriers to entry for newcomers.

We propose an approach distinguishing GenAI-assisted literature sourcing (finding, organizing, and retrieving scholarship) from literature review (reading, synthesizing, and critiquing). Through six strategies organized into three phases (Orientation, Alignment, and Consolidation), we demonstrate how GenAI can efficiently identify relevant papers, theoretical frameworks, and methodological approaches while preserving the researcher's responsibility for verification, interpretation, and synthesis.

Using a practical case where a graduate student explores an unfamiliar research topic (co-curricular learning in engineering: student motivation in engineering clubs), we illustrate each strategy with concrete prompts and reflections on the output. We include additional verification measures (GenAI triangulation, citation chaining, and peer and mentor discussions) to address concerns about hallucinations, algorithmic bias, and cognitive offloading. All AI-generated citations were verified, revealing that while formatting was inconsistent, all links led to legitimate sources.

While demonstrated in engineering education, this approach is applicable across interdisciplinary fields where the breadth of the literature creates barriers for newcomers. This paper provides students and faculty with a practical toolkit for efficient literature discovery using GenAI, allowing them to devote cognitive resources to critical synthesis rather than exhaustive searching.