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Identifier 000416971
Title UXAml framework : user experience evaluation in ambient intelligence environments
Alternative Title UXAml framework: Αξιολόγηση της εμπειρίας χρήσης σε περιβάλλοντα διάχυτης νοημοσύνης
Author Ντοά, Σταυρούλα Ν
Thesis advisor Στεφανίδης, Κωνσταντίνος
Reviewer Πλεξουσάκης, Δημήτρης
Γραμμένος, Δημήτρης
Abstract Ambient Intelligence (AmI) constitutes a new human-centred technological paradigm, where technologically advanced environments that feature interconnected and embedded devices, supported by sensors’ network, computer vision, as well as reasoning and adaptation capabilities, are oriented towards anticipating and satisfying the needs of their inhabitants. In this context, and in view of the not distant realization of AmI environments, evaluation becomes of paramount importance. Evaluation constitutes a central concept in Human-Computer Interaction, exhibiting increased interest and confronting novel challenges, as technology evolves from the desktop paradigm and contexts expand beyond the organizational domain to almost any life activity. To this end, several efforts have attempted to “frame” evaluation and define how it should be pursued in terms of usability, user experience, as well as interaction adaptation and ubiquitousness. Nevertheless, as technology advances, the number of parameters to be assessed becomes too large to be studied through user experiment observators’ notes, or evaluation questionnaires to be filled-in by users (a common current practice when evaluating user experience). On the other hand, despite the fact that the notion of Ambient Intelligence exists for more than a decade and the vital importance of evaluation, efforts in the domain have mainly focused in identifying the challenges in the field and advocating the importance of in situ evaluations, while there is a lack of generic and systematic approaches towards user experience evaluation in Ambient Intelligence. This thesis proposes a novel comprehensive conceptual and methodological framework, named UXAmI, for the evaluation of user experience in AmI environments, aiming to assess a wide range of characteristics and qualities of such environments, taking into account traditional and modern models and evaluation approaches. Adopting an iterative approach, the framework suggests metrics to be assessed through expert-based reviews during the early stages of development, and user-based evaluations for the latter development stages of an AmI system or environment. Taking advantage of the infrastructure of AmI environments, UXAmI framework proposes the automatic assessment of several attributes during user-based evaluation. A combination of automated measurements, user observation, questionnaires and interviews is expected to allow evaluators to gain insight into the composite nature of user experience in AmI environments, studying issues related to intuitiveness, unobtrusiveness, adaptivity, usability, cross-platform and multi-user usage, implicit interactions, appeal and emotions, safety and privacy, as well as user acceptance. Finally, a number of tools are proposed in the context of the current thesis, aiming to assist UX engineers in carrying out evaluations in AmI environments based on the UXAmI framework. These include a tool for expert-based reviews against guidelines, a tool for aggregating experimental data and analysing the results of user testing experiments, and a professional networking platform for UX engineers, which will act as an information resource and a means for collaboration, integrating the other two tools as a reward to active and loyal community members.
Language English
Subject Automated guidelines suggestion
Evaluation framework
Evaluation tools
Expert-based review
Online community
Tool for working with guidelines
User reward scheme
User testing
Αξιολόγηση με εμπειρογνώμονες
Αξιολόγηση με χρήστες
Αυτόματη πρόταση οδηγιών
Διαδικτυακή κοινότητα
Εργαλεία αξιολόγησης
Εργαλείο για εργασία με οδηγίες
Μηχανισμός ανταμοιβής χρηστών
Πλαίσιο αξιολόγησης
Issue date 2018-03-23
Collection   Faculty/Department--Faculty of Sciences and Engineering--Department of Computer Science--Doctoral theses
  Type of Work--Doctoral theses
Permanent Link https://elocus.lib.uoc.gr//dlib/5/e/6/metadata-dlib-1530867684-964906-8445.tkl Bookmark and Share
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