# The Research Rundown: May 2024 - September 2024 October 18, 2024 Welcome to the research rundown from the User Research Center at Harvard Library. In this quarterly blog post, the URC will share recent research our team has conducted at Harvard Library. If you have any questions about the research or would like to consult with our team about helping you plan or conduct research at Harvard Library, please email . ## **Student Survey on Library Opportunities in Generative AI** In May 2024, the URC surveyed students to gather specific examples of how they use generative AI in their academic work and to explore what library services related to generative AI they would like to see in the future. ### **Ideas for Library Use of Gen AI** - Easier search - Recommend articles - Bibliography creation - Recommend other search terms - Within search, point to other relevant library resources like people or services ### **Use of Gen AI in Academic Work** - Software coding - Explanation generation - Editing writing - Brainstorming ideas - Outlining - Data analysis - Creating summaries - As a search tool - Image or graphic design generation This work is helping the library further understand how students understand and use Generative AI in their classwork and research. ## **DRS Futures Contextual Inquiries** The URC interns and team interviewed library staff to understand areas of improvement for the Digital Repository Service (DRS) platform in support of the DRS Futures project. The DRS is a professionally managed service that ensures the usability of stored digital objects over time. The DRS Futures project is dedicated to updating the infrastructure to make the DRS more usable for staff in the future. The interviews were conducted with library staff who use the DRS in their daily work. The team observed depositing, editing, reporting, and delivery-related tasks. ### **Major Insights** - Staff cites that having to save edits for the edits on an item repeatedly is one of the most problematic elements of the DRS editing workflow. They are forced to halt tasks before completion and engage in repetitive work. - DRS content model requirements limit how materials can be deposited, requiring staff to use workarounds and complete tedious, time-consuming pre-work. - Staff desire more flexible and freeform search parameters and capabilities and are frustrated by the inability to conduct batch or bulk work in the DRS and specify preferences on the platform. - The DRS is not optimized for audiovisual (AV) materials, presenting unique search issues. Staff are required to apply changes across all file components associated with a single AV item. - Staff must maintain external spreadsheets and tracking to work with the DRS, which leads to dependence on additional library departments ​​(e.g., Imaging Services, Media Preservation Services, Library Technology Services) and a desire for improved linking with other platforms (e.g., ArchivesSpace). The results are helping the DRS Futures team prioritize features in planning for the new DRS. Share on:- [ Facebook ](#) - [ Twitter ](#) - [ Linkedin ](#)