2024 ASEE Annual Conference & Exposition

Systematic reviews, as well as other comprehensive literature reviews, require a rigorous and structured approach for an exhaustive literature search. Identifying the relevant keywords that encapsulate the research topic and then combining them using the appropriate search technique demands expertise in both search techniques and in-depth domain knowledge. As a result, librarians are frequently asked to join research teams to assist researchers unfamiliar with this intricate process. These subject specialists have expertise in using search tools and techniques to formulate search statements, yet they often need to conduct extensive literature surveys to identify relevant search terms, especially in rapidly evolving fields. Although controlled vocabularies and keywords supplied by authors and database companies are useful, they are often insufficient in capturing all relevant terms used in the literature. This paper explores how Generative Artificial Intelligence (AI) and Natural Language Processing (NLP) could be harnessed by librarians to refine the formulation of search terms for these reviews. This pilot study suggests that the use of Generative AI and NLP helps users identify relevant search terms for developing search strategies, although users must be cautious about the reproducibility of Generative AI's responses.