{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T18:57:01Z","timestamp":1774983421217,"version":"3.50.1"},"reference-count":0,"publisher":"Project MUSE","issue":"3","license":[{"start":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T00:00:00Z","timestamp":1748390400000},"content-version":"vor","delay-in-days":116,"URL":"https:\/\/www.crossref.org\/license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["lib"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:p xml:lang=\"en\"> Abstract: Librarian-patron exchanges parallel chatbot-user interactions: Experienced librarians provide better reference service by prompting users with clarifying questions; likewise, chatbots can improve their responses with better-engineered prompts. A chatbot\u2019s self-assessment mechanisms transform prompt components into predictions formed into responses, a process that enables large language models to continually learn and improve from prompts engineered to produce desired outcomes. Kuhlthau\u2019s Information Search Process (ISP), created to describe library patrons\u2019 information-seeking stages and dispositions, may be useful for understanding and improving users\u2019 interactions with AI-driven chatbots. Kuhlthau has detailed seven stages of information-seeking, with intervention zones and reference mediation levels, for librarians to assist users in reaching satisfying outcomes in offline and online environments. We hypothesize that generative AI agents can use ISP\u2019s zones of intervention and levels of reference mediation to improve their large language models to assist users better. Guided by the overarching question \u201cTo what extent does applying ISP to virtual reference transactions present strategies for improving prompt engineering?\u201d we explored a recent virtual reference dataset ( N = 1,959) to determine whether users\u2019 questions reflected Kuhlthau\u2019s ISP and how librarian-patron interactions used clarifying questions and interventions to ascertain users\u2019 information-seeking stage and provide satisfying responses. Our investigation demonstrated that authentic patron questions clustered in ISP\u2019s focus formulation and information gathering stages. When exemplar questions were posed to a chatbot, it demonstrated a strong ability to detect and respond to the information need, often providing scaffolds to the next step of the information-seeking process. These results suggest that chatbots can be improved by blending web searching, database searching, and generative AI to seamlessly meet user needs, while task definition, topic selection, and search assessment should remain human-mediated aspects of information-seeking.<\/jats:p>","DOI":"10.1353\/lib.2025.a961195","type":"journal-article","created":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T09:17:59Z","timestamp":1748423879000},"page":"267-296","source":"Crossref","is-referenced-by-count":3,"title":["AI on the Shoulders of Giants: Using Kuhlthau\u2019s Information Search Process to Improve AI Support for Information-Seeking"],"prefix":"10.1353","volume":"73","author":[{"given":"Benhur","family":"Ravuri","sequence":"first","affiliation":[]},{"given":"Marcia A.","family":"Mardis","sequence":"additional","affiliation":[]}],"member":"147","container-title":["Library Trends"],"original-title":[],"language":"en","deposited":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T09:18:01Z","timestamp":1748423881000},"score":1,"resource":{"primary":{"URL":"https:\/\/muse.jhu.edu\/article\/961195"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,2]]}},"URL":"https:\/\/doi.org\/10.1353\/lib.2025.a961195","relation":{},"ISSN":["1559-0682"],"issn-type":[{"value":"1559-0682","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2]]}}}