{"title":"User-Centered Evaluation Framework to Support the Interaction Design for Augmented Reality Applications","authors":"Andrea Picardi, Giandomenico Caruso","doi":"10.3390/mti8050041","DOIUrl":null,"url":null,"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.","PeriodicalId":508555,"journal":{"name":"Multimodal Technologies and Interaction","volume":"25 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimodal Technologies and Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/mti8050041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.
增强现实(AR)技术的发展令人瞩目,它能够通过及时的信息增强用户的感知。这一进步为交互设计领域带来了巨大希望。然而,仅仅技术进步还不足以确保广泛应用。由于缺乏对用户动机、需求、可用性和感知价值的关注,AR 研究在某种程度上忽视了用户层面。AR 技术的关键方面往往被技术本身所掩盖。为了确保未来进行适当的评估,有必要对用于 AR 技术验证的所有方法进行彻底检查和分类。通过对这些评估方法进行识别和分类,研究人员和从业人员将能更好地开发和验证新的 AR 技术和应用。因此,全面而系统的评估对于增强现实技术的发展和可持续性至关重要。本文介绍了从 399 篇论文中提取的最有效的 AR 评估方法聚类分析得出的理论框架。评估方法根据应用领域和需要研究的人机交互方面进行了分组。该框架应有助于快速开发周期,优先考虑用户需求,最终产生突破性的交互方法,供研发中心以外的更广泛受众使用。