Exploring the motivations involved in context aware services
Author(s) -
Chris Roast,
Xiaohui Zhang
Publication year - 2012
Publication title -
electronic workshops in computing
Language(s) - English
Resource type - Conference proceedings
ISSN - 1477-9358
DOI - 10.14236/ewic/hci2012.37
Subject(s) - computer science , ubiquitous computing , relevance (law) , context (archaeology) , perception , empirical research , human–computer interaction , preference , context awareness , knowledge management , adaptation (eye) , end user computing , human centered computing , data science , psychology , utility computing , cloud computing security , neuroscience , linguistics , phone , epistemology , biology , paleontology , cloud computing , law , information science , library science , philosophy , political science , economics , microeconomics , operating system
This paper reports on research focused upon understanding the factors influencing the effective use of context aware adaptive systems. Unlike many desktop applications, ubiquitous computing supports users in dynamic situations by utilizing surrounding context to help them manage and utilise technology. It is by its nature highly dynamic since it responds to changes in context of use, and this brings new challenges to interaction design. In particular, there is still little research into human factors relating to the effectiveness and appropriateness of ubiquitous computing concepts. We review theoretical factors regarding human user's motivation, emotion, perception and preference that are relevant to evaluating ubiquitous computing. Here we then report on empirical research relating these theoretical factors to the use of contextually aware adaptive systems. The results show that there is a significant difference in users' preferences between intrinsic and extrinsic motivations. The other findings identify the importance and role of user involvement in decision-making processes. Overall the work raises interesting questions about the nature of empirical research as a methodology of relevance to adaptive system design.
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