Hassan, SaadLee, SooyeonMetaxas, DimitrisNeidle, CarolHuenerfauth, Matt2023-01-132023-01-132022-10-22S. Hassan, S. Lee, D. Metaxas, C. Neidle, M. Huenerfauth. 2022. "Understanding ASL Learners’ Preferences for a Sign Language Recording and Automatic Feedback System to Support Self-Study" The 24th International ACM SIGACCESS Conference on Computers and Accessibility. https://doi.org/10.1145/3517428.3550367https://hdl.handle.net/2144/45440Advancements in AI will soon enable tools for providing automatic feedback to American Sign Language (ASL) learners on some aspects of their signing, but there is a need to understand their preferences for submitting videos and receiving feedback. Ten participants in our study were asked to record a few sentences in ASL using software we designed, and we provided manually curated feedback on one sentence in a manner that simulates the output of a future automatic feedback system. Participants responded to interview questions and a questionnaire eliciting their impressions of the prototype. Our initial findings provide guidance to future designers of automatic feedback systems for ASL learners.en-USPermission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proft or commercial advantage and that copies bear this notice and the full citation on the frst page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). ASSETS ’22, October 23–26, 2022, Athens, Greece © 2022 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-9258-7/22/10.Conference materials2023-01-1010.1145/3517428.3550367778217