Togedule: Scheduling Meetings with Large Language Models and Adaptive Representations of Group Availability
Author(s)
Song, Jaeyoon
Ashktorab, Zahra
Malone, Thomas
Date Issued
October 16, 2025
Journal
Proceedings of the ACM on Human-Computer Interaction
Publisher
ACM
Citation
Jaeyoon Song, Zahra Ashktorab, and Thomas W. Malone. 2025. Togedule: Scheduling Meetings with Large Language Models and Adaptive Representations of Group Availability. Proc. ACM Hum.-Comput. Interact. 9, 7, Article CSCW332 (November 2025), 24 pages.
Version
Final published version
Abstract
Scheduling is a perennial-and often challenging-problem for many groups. Existing tools are mostly static, showing an identical set of choices to everyone, regardless of the current status of attendees' inputs and preferences. In this paper, we propose Togedule, an adaptive scheduling tool that uses large language models to dynamically adjust the pool of choices and their presentation format. With the initial prototype, we conducted a formative study (N=10) and identified the potential benefits and risks of such an adaptive scheduling tool. Then, after enhancing the system, we conducted two controlled experiments, one each for attendees and organizers (total N=66). For each experiment, we compared scheduling with verbal messages, shared calendars, or Togedule. Results show that Togedule significantly reduces the cognitive load of attendees indicating their availability and improves the speed and quality of the decisions made by organizers.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3757513
