User evaluation of mobile augmented reality in architectural planning

Using human-values as a guide for understanding worthy design directions in augmented reality

“…There is also research exploring AR's potential [10]. Attention has been drawn to the relative lack in studies focusing specifically on user acceptance, user expectations and user experience in this area [11,12,13,14]. Furthermore, when considering user studies, studies have mostly focused on specific devices and applications, to be used in particular use contexts, often with standard user groups (e.g., university student participants, ages [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35].…”

“…Many of these studies examine task performance, cognition, perception and other usability issues [12,15,16]. As Thomas Olsson and colleagues [13] point out, userrelated AR studies generally focus on usability, often applying conventions and methods which were created for the evaluation of other systems, which vary in nature. Thus, there are still practical and scientific gaps pertaining to AR specific user study methodologies and techniques, and misalignments with unquestioningly applying established user-study methodologies straight to the AR domain.…”

“…These components are: 1) mobility; 2) context-sensitivity; 3) embedded information; and 4) AR output (p. 2). Olsson and associates [13] continued this examination through utilizing the scenario evaluation of MARs in order to identify and elaborate user concerns or risks perceived by users in regards to the technology. In this instance, users were found to exhibit distrust towards MAR in terms of a perceived flood or overload of information.…”

Modelling Spatio-Temporal Relevancy in Urban Context-Aware Pervasive Systems Using Voronoi Continuous Range Query and Multi-Interval Algebra

“…The user's satisfaction with the services provided is a key issue in modeling context-aware systems [11,13]. It is obviously crucial for adoption and acceptance of such technologies [12,39]. This study considered seven elements for estimating user satisfaction from the model and context-aware services, namely: (1) the usefulness of the prediction in the user's decision making process for choosing his/her related contexts [2,13], (2) the usefulness of the presentation of contexts that have spatial relationships behind the user and in the opposite direction, (3) the effect of the contexts introduction based on the velocity (this factor is derived from the "adapt to varying situations of the user" parameter pointed by [12], (4) the order of the contexts presentation and (5) the responding time of the algorithm to the user [3,12], (6) number of navigation steps [13], and (7) task success [13].…”

Introduction to the thematic issue on Human-centric computing and intelligent environments

“…[7,8,10]. Recent developments and opportunities have resulted in the interface between Human-Centric Computing and Intelligent Environments being once again highly topical, and hence the initiative for this special thematic issue that emphasizes the human viewpoint: user-friendliness, efficient service support, userempowerment, and support for human interactions in AmI and IEs.…”