Abstract

The advancement of Augmented Reality (AR) technology has been remarkable, enabling the augmentation of user perception with timely information. This progress holds great promise in the field of interaction design. However, the mere advancement of technology is not enough to ensure widespread adoption. The user dimension has been somewhat overlooked in AR research due to a lack of attention to user motivations, needs, usability, and perceived value. The critical aspects of AR technology tend to be overshadowed by the technology itself. To ensure appropriate future assessments, it is necessary to thoroughly examine and categorize all the methods used for AR technology validation. By identifying and classifying these evaluation methods, researchers and practitioners will be better equipped to develop and validate new AR techniques and applications. Therefore, comprehensive and systematic evaluations are critical to the advancement and sustainability of AR technology. This paper presents a theoretical framework derived from a cluster analysis of the most efficient evaluation methods for AR extracted from 399 papers. Evaluation methods were clustered according to the application domains and the human–computer interaction aspects to be investigated. This framework should facilitate rapid development cycles prioritizing user requirements, ultimately leading to groundbreaking interaction methods accessible to a broader audience beyond research and development centers.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call