New Voices RGU Student Series 2025 – Elizabeth Montgomerie
Category: Blog, RGU Student Series 2025
In the 2025 New Voices Student Series, the CILIPS Students & New Professionals Community will be sharing the views of Robert Gordon University students from the MSc in Information and Library Studies.
With special thanks to Dr Konstantina Martzoukou, Teaching Excellence Fellow and Associate Professor, for organising these thought-provoking contributions.
Today’s blog post author is Elizabeth Montgomerie, who works at the University of Lincoln as an Academic Subject Librarian (Maths,Physics and Engineering) and is currently studying part-time for the MSc Information and Library studies.
Information seeking and use in the age of Generative AI: The evolving role of information professionals in higher education
Figure 1: Librarian with AI assistant [Digital art] (Copilot, 2024a).
The rapid development of Generative AI is transforming information seeking. Large Language Models (LLMs), a type of Generative AI, are designed to understand and generate natural language text. Obtaining search results when using LLMs, involves writing a natural language query or prompt, a process called prompt engineering (Frederick, 2024). Keyword searching, traditionally used to search academic databases, is a more iterative process, queries are revised as results are retrieved and assessed against research topics or questions (Frederick, 2024). It is a more time-consuming, skilled process. The ability to search for information using natural conversational language, as opposed to searching only by words and phrases has the potential to revolutionise information seeking in higher education (Frederick, 2024).
ChatGPT, an LLM, was estimated to have 100 million monthly users in January 2023, only two months after launch, making it the fastest-growing consumer app in history (Hu, 2023). Software that has, until recently, been used as standard by students and sanctioned for use by universities (such as Grammarly), now has Generative AI built in. Universities can continue to change the tools it allows students to use, but the technological changes taking place will eventually need to be confronted. Generative AI is here to stay and reducing its misuse by students and researchers is a more realistic goal than attempting to ban it (Gruenhagen et al., 2024).
Academic library services should adapt to the advances in technology taking place, to best meet the needs of their students and researchers (Khan et al., 2023). Currently, academic librarians and information professionals in higher education teach the searching of academic databases and finding information using keyword searching (Lan, 2024). They are experts in constructing and improving keyword search queries to effectively find relevant information; refining prompts for Generative AI involves a similar process (Zhang, 2023). Information professionals are well-positioned to teach prompt engineering techniques to support academic research and learning (Lan, 2024).
Prompt engineering will be an important skill for academic librarians going forward, helping them use Generative AI more effectively for teaching information literacy and literature searching (Lo, 2024). Understanding the mechanics of prompt engineering and learning to formulate effective queries will help librarians meet the needs of their students (Lo, 2024). Teaching keyword searching for academic databases will continue to be part of a Librarian’s role for the present, but prompt engineering will become a necessary skill, both for them and their students.
If Generative AI is to have a successful place in learning and information searching in the higher education sector, information professionals must continue to teach information literacy and critical thinking skills (Damiano et al., 2024). Information professionals currently have a significant role in supporting information literacy, which encompasses the skills needed for tasks such as discovering, analysing, creating, and communicating information (CILIP, 2018). LLMs currently have limitations, including creating misinformation (hallucinating), incorrectly attributing sources and amplifying biases obtained through training processes (Li and Sinnamon, 2024). As Generative AI becomes increasingly embedded in information searching, both in the education sector and the workplace, it’s essential that students and researchers develop the skills to evaluate and interpret information accurately.
Information specialists need to meet changing demands, expanding their roles as facilitators of research and teachers of information literacy, and becoming specialists in helping students and researchers navigate digital information and new technological tools (Mintz, 2024). The teaching of information literacy strengthens transferable and employability skills, preparing students for the workplace (CILIP, 2018). In an increasingly digital world, to be information literate requires people to have the skills to use technologies to access and create information (UNESCO, 2023).
The role of the information professional is evolving, and it is one that has always adapted to technological change. Embracing change will ensure a continuing role for information professionals in higher education going forward.
Figure 2: Digital Books [Digital art] (Copilot, 2024).
References
CILIP (2018) CILIP Definition of Information Literacy 2018. Available at: https://cdn.ymaws.com/www.cilip.org.uk/resource/resmgr/cilip/information_professional_and_news/press_releases/
2018_03_information_lit_definition/cilip_definition_doc_final_f.pdf (Accessed: 20 November 2024).
Copilot (2024a) Librarian with AI assistant [Digital art]. Created for Elizabeth Montgomerie, 10 November.
Copilot (2024b) Digital Books [Digital art]. Created for Elizabeth Montgomerie, 26 November.
Damiano, A. D., Lauría, E. J. M., Sarmiento, C., & Zhao, N. (2024) ‘Early Perceptions of Teaching and Learning Using Generative AI in Higher Education’, Journal of Educational Technology Systems, 52(3), pp. 346-375. Available at: https://doi org.ezproxy.rgu.ac.uk/10.1177/00472395241233290
Frederick, D.E. (2024) ‘Prompt engineering–a disruption in information seeking?’, Library Hi Tech News, 41(3), pp. 1-7. Available at: https://doi.org/10.1108/LHTN-03-2024-0037
Gruenhagen, J.H. et al. (2024) ‘The rapid rise of generative AI and its implications for academic integrity: Students’ perceptions and use of chatbots for assistance with assessments’, Computers and Education: Artificial Intelligence, 7, article number 100273. Available at: https://doi.org/10.1016/j.caeai.2024.100273
Hu, k. (2023) ChatGPT sets record for fastest-growing user base – analyst note. Available at: https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/ (Accessed: 1 November).
Khan, R. et al. (2023) ‘Impact of Conversational and Generative AI Systems on Libraries: A Use Case Large Language Model (LLM)’, Science & Technology Libraries, pp. 1–15. Available at: https://doi.org/10.1080/0194262X.2023.2254814
Lan, H. (2024) ‘Prompt Engineering for Academic Librarian: Implications and applications of Prompt Engineering in Academic Librarianship’, Journal of Web Librarianship, pp. 1-7. Available at: https://doi.org/10.1080/19322909.2024.2399055
Li, A. and Sinnamon, L. (2024) ‘Generative AI Search Engines as Arbiters of Public Knowledge: An Audit of Bias and Authority’, Proceedings of the Association for Information Science and Technology, 61(1), pp.205-217. Available at: https://doi.org/10.48550/arXiv.2405.14034
Lo, L.S. (2024) ‘The CLEAR path: A framework for enhancing information literacy through prompt engineering’, The Journal of Academic Librarianship, 49(4), article number 102720. Available at: https://doi.org/10.1016/j.acalib.2023.102720
Mintz, S. (2024) ‘The Evolving University Library: What’s gained, what’s lost’, Higher ED Gamma. Available at: https://www.insidehighered.com/opinion/blogs/higher-ed-gamma/2024/10/28/whats-gained-whats-lost-evolving-university-library (Accessed: 11 November 2024).
UNESCO (2023) Information Literacy. Available at: https://www.unesco.org/en/ifap/information-literacy (Accessed: 11 November 2024).
Zhang, B. (2023) ‘Prompt engineers or librarians? An exploration’, Medical Reference Services Quarterly, 42(4), pp. 381–386. Available at: https://doi.org/10.1080/02763869.2023.2250680