Document Type

Conference Paper

Publication Date

2026

DOI

10.18260/1-2--58971

Publication Title

2026 ASEE Annual Conference & Exposition

Pages

14 pp.

Conference Name

2026 ASEE Annual Conference & Exposition, June 21-24, 2026, Charlotte, North Carolina, USA

Abstract

In recent years, Artificial Intelligence (AI)-based solutions, particularly Large Language Models (LLMs), have been applied to a variety of domains, such as energy, finance, transportation, healthcare, and education. Among these domains, education has become increasingly popular due to strong interest among educators and students. This study proposes an academic advising assistant system that uses LLMs to help Engineering Technology (ET) students plan their course load based on their educational history, departmental course offerings, and personal constraints, such as their preferred semester course load. The proposed LLM-based academic advising assistant system maintains a database of students' course histories and upcoming course availability to provide personalized recommendations for which courses to take based on user input. It also explains course dependencies and adapts its suggestions according to user constraints, such as course difficulty (inferred from grade distributions) and maximum credit limits per semester.

Rights

© 2026 American Society for Engineering Education.

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2026 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference.

Original Publication Citation

Kuzlu, M., Jovanovic, V. M., Smith, K., Popescu, O., El-Shahat, A., Cotton, R., Seegers, K. M., & Henderson, W. A. (2026). A large language model-based academic advising assistant for engineering technology student [Conference paper]. 2026 ASEE Annual Conference & Exposition, Charlotte, North Carolina. https://doi.org/10.18260/1-2--58971

ORCID

0000-0002-8719-2353 (Kuzlu), 0000-0002-8626-903X (Jovanovic), 0000-0002-5026-4501 (Smith), 0000-0002-5975-6529 (Popescu), 0000-0003-0148-5014 (El-Shahat)

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