AI, Acronyms, and the Future of Facets: Mnemonics as Heuristic Instructional Tools for Structuring GenAI Prompts

Authors

Keywords:

artificial intelligence, acronyms, facets, mnemonics, information literacy instruction

Abstract

This paper explores the evolving landscape of library discovery through the lens of generative artificial intelligence (GenAI), focusing on potential impacts on traditional faceted search interfaces. As AI-driven conversational search begins to reshape information retrieval, concerns arise regarding the potential to obscure facets, which are critical to search result refinement. This study introduces mnemonic acronyms as a heuristic device to guide users in structuring effective prompts for AI-based search. Observational studies in academic settings demonstrate how acronyms can enhance precision and user understanding of AI-driven search. Findings indicate that providing heuristic tools can be an effective strategy to guide initial AI searches, but challenges such as accuracy and bias highlight the ongoing need for critical evaluation.

Author Biographies

  • Lucy Campbell, San Diego State University

    Lucy is a Faculty Librarian specializing in content organization and management. Her areas of interest include electronic resource management,  collection analysis tools, and technology as research in design education. She is currently researching artificial intelligence for faceted information seeking habits, DEI in open access journal publishing, and applied business research methods in collection assessment.

  • Keven Jeffery, MLIS, San Diego State University

    Keven Jeffery is the Digital Technologies at San Diego State University. His responsibilities include investigating and implementing emerging digital technologies and applications. Keven has authored articles that have been published in journals such as Library Hi Tech, the Journal of Web Librarianship, and Evidence Based Library and Information Practice.

  • Rebecca Nowicki, MLIS, San Diego State University

    Online Learning Librarian Rebecca Nowicki leads San Diego State University Library’s online instruction program. She designs learning objects that foster active engagement and meet students and faculty at their point of need to empower information literate learners that are adaptable to the changing information landscape of the 21st Century.

References

Association of College and Research Libraries. (2015). Framework for information literacy for higher education. https://www.ala.org/acrl/standards/ilframework

Birss, D. (2023). How to research and write using generative AI tools. [Video] LinkedIn. https://www.linkedin.com/learning/how-to-research-and-write-using-generative-ai-tools

Broughton, V. (2004). Essential Classification. Facet Publishing.

Caulfield, M. (2019, June 19). SIFT (The Four Moves). Hapgood. Retrieved from https://hapgood.us/2019/06/19/sift-the-four-moves/

Ex Libris. (2024). The impact of generative AI on libraries [pdf]. Available at https://img06.en25.com/Web/ClarivateAnalytics/%7B37f46f03-0f23-406c-a2bb-6e0b22d318fe%7D_ExLibris_GenerativeAI_Whitepaper_1023_WEB.pdf

Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62(1), 451–482. https://doi.org/10.1146/annurev-psych-120709-145346

Khazaei, T., & Hoeber, O. (2017). Supporting academic search tasks through citation visualization and exploration. International Journal on Digital Libraries, 18 (1), 59-72. https://doi.org/10.1007/s00799-016-0170-x

Korzyński, P., Mazurek, G., Krzypkowska, P., & Kurasinski, A. (2023). Artificial intelligence prompt engineering as a new digital competence: Analysis of generative AI technologies such as ChatGPT. Entrepreneurial Business and Economics Review, 11(3), 25-37. https://doi.org/10.15678/EBER.2023.110302

Meriam Library, California State University-Chico. (2024). Evaluating information – Applying the CRAAP test. Retrieved July 18, 2024, from https://library.csuchico.edu/sites/default/files/craap-test.pdf

Pollitt, A. Stephen, Amanda Tinker and Patrick A.J.Braekevelt. 1998. “Improving Access to Online Information Using Dynamic Faceted Classification.” In Online Information 98: Proceedings of the 22nd International Online Information Meeting, London, 8-10 December, 1998. Oxford: Learned Information Europe, 17-21.

Richardson, W. S., et al. “The Well-Built Clinical Question: A Key to Evidence-Based Decisions.” ACP Journal Club., vol. 123, no. 3, 1995, pp. A12–13.

Schreur, P. E. (2012). The Academy Unbound: Linked Data as Revolution. Library Resources & Technical Services, 56(4), 227-237. https://www.proquest.com/scholarly-journals/academy-unbound-linked-data-as-revolution/docview/1112542219/se-2

Spiteri, L. F., & Tarulli, L. (2012). Social Discovery Systems in Public Libraries: If We Build Them, Will They Come? Library Trends, 61(1), 132-147. https://doi.org/10.1353/lib.2012.0019

Stohn, C. (2024, May 17). Generative Artificial Intelligence (AI) at Clarivate: From Research to Real-World Applications. [Conference Presentation]. ELUNA 2024, Minneapolis, MN, United States. https://exlkdelunaddam2024.dryfta.com/program-schedule/program/301/generative-artificial-intelligence-ai-at-clarivate-from-research-to-real-world-applications

Downloads

Published

2025-04-25

Issue

Vol. 14 No. 1 (2025): March issue 2025

Section

Articles

License

Copyright (c) 2025 Qualitative and Quantitative Methods in Libraries

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.