2026 ASEE Annual Conference & Exposition

Psychometric AI Mapping of Engineering Outcomes: Supporting College–Industry Dialogue Between ABET Outcomes and Workforce Skills

Engineering programs are increasingly expected to articulate how accreditation-driven student outcomes relate to workforce capabilities valued by industry. In college–industry partnership contexts, these conversations often unfold informally, leaving differences in vocabulary and underlying competence logic implicit and difficult to revisit. Our work-in-progress paper introduces Psychometric AI Mapping, a human-in-the-loop methodological framework for interpretive comparison of text-based outcome frameworks.
Drawing on the unified view of construct validity, the method treats accreditation outcomes and workforce skill statements as observable indicators of underlying competencies, and operationalizes their comparison through a transparent workflow of thematic aggregation, interpretive alignment, and matrix construction. Large language models are positioned as structured analytic instruments within this workflow rather than as autonomous interpretive authorities. We demonstrate the method on the ABET EAC Student Outcomes (Criterion 3, outcomes 1–7) and workforce skills from the World Economic Forum’s Future of Jobs Report 2025. A researcher-generated alignment matrix surfaces patterns of conceptual concentration, overlap, and absence revealing, for example, strong alignment around cognitive problem-solving alongside gaps in adaptability and operational capabilities. The contribution is methodological: a transparent, reproducible workflow that supports more systematic dialogue among faculty, assessment leaders, and industry partners.

Authors

Dr. Lilianny Virgüez http://orcid.org/0009-0007-1672-3907 University of Florida [biography]

Dr. Virgüez is an engineering educator who teaches foundational electrical engineering courses for students across multiple disciplines and class standings, with prior experience teaching first-year engineering students. Her work includes curriculum development and program-level coordination, and her research focuses on student motivation, workforce alignment, and the role of emerging technologies, including AI, in engineering education. She brings prior industry experience in the telecommunications sector and holds a Ph.D. in Engineering Education and a Master’s degree in Management Systems Engineering from Virginia Tech, as well as a bachelor’s degree in Telecommunications Engineering.
Dr. Sreyoshi Bhaduri Public Corporation [biography]

Dr. Sreyoshi Bhaduri leads at the intersection of Generative AI, customer-centric innovation, and global business scale. A recognized voice in tech, Dr. Bhaduri is an award-winning leader, global speaker, mentor, and advisory board member. She is deeply committed to democratizing and demystifying AI. She has delivered 100+ talks worldwide, breaking down complex topics and sharing insights on human-centered development. As a founder of ThatStatsGirl, she amplifies the importance of multi-disciplinary collaborations and lifelong learning in technology.
Dr. Debarati Basu http://orcid.org/0000-0002-6205-8510 Embry–Riddle Aeronautical University, Daytona Beach [biography]

Dr. Debarati Basu is an Assistant Professor in the Engineering Fundamentals Department in the College of Engineering at the Embry-Riddle Aeronautical University, Daytona Beach campus. She earned her Ph.D. in Engineering Education from Virginia Tech. She received her bachelor's and masters in Computer Science and Engineering. Her research is at the intersection of Engineering Education (EE) and Computing Education Research (CER) for enhancing individualized experiences, specifically focused on educational technologies including GenAI (for learning, engagement, self-directed learning), student-centered curriculum and pedagogy, and support systems for student and faculty success. She primarily teaches freshmen computing students with active learning techniques and focuses on bringing EE and CER into practice.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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Academia-Industry Connections