TY - GEN
T1 - Enhancing Augmented Reality (MAR) Interaction Experience
T2 - 26th International Conference on Human-Computer Interaction, HCII 2024
AU - Liang, Xiaozhan
AU - Ma, Xiaona
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - Purpose: This study introduces a novel approach to enhance handheld mobile augmented reality (MAR) experiences through user mental models. By analyzing MAR characteristics, we construct a user mental model based on “execution" and “evaluation" dimensions alongside six attributes, guiding MAR interaction design. Methods: We analyze MAR traits like interactivity, information display, and physical comfort, deriving two dimensions (execution and evaluation) and six attributes (usage habits, information attention, interactive behavior, usage experience, cognitive experience, and workload). Through user interviews and affinity diagrams, we construct the mental model. To demonstrate its practical application, we utilize a MAR exhibition with a miniature model theme. Results: Through case application and user testing, we validate the effectiveness of the mental model-driven design in enhancing MAR interaction. Users perceive improvements in ease of use, learnability, and satisfaction with systems designed using this approach. Conclusion: This study underscores the value of leveraging user mental models rooted in “execution" and “evaluation" dimensions to guide MAR system design. Utilizing the affinity diagram method, our approach not only enhances system adaptability but also boosts user satisfaction, marking a significant advancement in MAR HCI research.
AB - Purpose: This study introduces a novel approach to enhance handheld mobile augmented reality (MAR) experiences through user mental models. By analyzing MAR characteristics, we construct a user mental model based on “execution" and “evaluation" dimensions alongside six attributes, guiding MAR interaction design. Methods: We analyze MAR traits like interactivity, information display, and physical comfort, deriving two dimensions (execution and evaluation) and six attributes (usage habits, information attention, interactive behavior, usage experience, cognitive experience, and workload). Through user interviews and affinity diagrams, we construct the mental model. To demonstrate its practical application, we utilize a MAR exhibition with a miniature model theme. Results: Through case application and user testing, we validate the effectiveness of the mental model-driven design in enhancing MAR interaction. Users perceive improvements in ease of use, learnability, and satisfaction with systems designed using this approach. Conclusion: This study underscores the value of leveraging user mental models rooted in “execution" and “evaluation" dimensions to guide MAR system design. Utilizing the affinity diagram method, our approach not only enhances system adaptability but also boosts user satisfaction, marking a significant advancement in MAR HCI research.
KW - Mobile augmented reality
KW - User experience
KW - User mental models
UR - https://www.scopus.com/pages/publications/85213382767
U2 - 10.1007/978-3-031-76812-5_8
DO - 10.1007/978-3-031-76812-5_8
M3 - 会议稿件
AN - SCOPUS:85213382767
SN - 9783031768118
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 99
EP - 116
BT - HCI International 2024 – Late Breaking Papers - 26th International Conference on Human-Computer Interaction, HCII 2024, Proceedings
A2 - Chen, Jessie Y.C.
A2 - Fragomeni, Gino
A2 - Streitz, Norbert A.
A2 - Konomi, Shin'ichi
A2 - Fang, Xiaowen
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 29 June 2024 through 4 July 2024
ER -