Uncovering Information Behavior: AI-Assisted Citation Analysis of Mechanical Engineering Technology Senior Capstone Reports

Abstract Citation analysis has been used by librarians and researchers to guide collection development decisions, assess information literacy, and to gain insight into the development of scholarship within a discipline. This project builds on this foundation by using citation analysis to better understand the information behavior of Mechanical Engineering Technology students. For this project, librarians analyzed citations in Mechanical Engineering Technology (MET) capstone reports published in the last five years to better understand the sources students are using in their final undergraduate work. Given the scope of analyzing citations in more than 100 PDF documents, cutting-edge AI tools were piloted throughout the project to ease data collection and analysis and to explore the capabilities and limitations of these tools for similar research projects. The citation analysis conducted during this project provides insights into senior MET student information behavior and source use as well as a clearer understanding of whether these have changed over time. This information will help librarians to better support MET students and faculty by allowing for targeted information literacy instruction and outreach.