Designing an AI Chatbot GUI to Enhance the Efficacy of Scholarly Article Search

As the volume of scholarly articles grows exponentially, the ability to efficiently discover and filter relevant research becomes critical. This study explores the design and evaluation of a Graphical User Interface (GUI) for an AI-based chatbot tool aimed at improving the search process for scholarly literature. Our work focuses on integrating a date-range filtering feature within the chatbot's interface, evaluating different configurations of the date input method and toggle placement. We conducted a user study involving multiple interface prototypes, collecting both quantitative performance data and subjective user feedback through surveys. Results show that a calendar-based date input with the toggle positioned above the query input field provides superior usability and efficiency. The findings inform best practices for integrating advanced filtering features in research-oriented AI chatbot systems, paving the way for more intuitive, user-friendly interfaces that enhance scholarly search tasks.