Cooking up a better AR experience: notification design and the liabilities of imperfect cues in augmented reality

Abstract

This dissertation investigates optimizing user experience in Augmented Reality (AR). A virtual cooking environment (ARtisan Bistro) serves as a testbed to explore factors influencing user interaction with AR interfaces. The research starts with notification design, examining strategically placed visual and audio notifications in ARtisan Bistro (Chapter 4). Building on this, Chapter 5 explores optimizing these designs for user awareness and delivering critical information, especially when audio is impractical. This involved exploring visual-only notifications, revealing consistent user performance and attention capture comparable to combined visual-audio notifications (no significant difference found). The research demonstrates that well-designed notifications can significantly improve user experience, but it also raises a crucial question: can users always trust the information presented in AR environments? The possibility of imperfect information delivery underscores the importance of reliable information delivery. Chapter 6 explores the impact of imperfect cues generated by machine learning (ML) on user performance in AR visual search tasks. This research highlights the potential for automation bias when users rely heavily on unreliable cues. By investigating both notification design and the limitations of ML systems for reliable information delivery, this dissertation emphasizes the importance of creating a well-rounded user experience in AR environments. The findings underscore the need for further research on optimizing visual notifications, mitigating automation bias, and ensuring reliable information delivery in AR applications.