114,674 research outputs found
Managing the Ethical Dimensions of Brain-Computer Interfaces in eHealth: An SDLC-based Approach
A growing range of brain-computer interface (BCI) technologies is being employed for purposes of therapy and human augmentation. While much thought has been given to the ethical implications of such technologies at the âmacroâ level of social policy and âmicroâ level of individual users, little attention has been given to the unique ethical issues that arise during the process of incorporating BCIs into eHealth ecosystems. In this text a conceptual framework is developed that enables the operators of eHealth ecosystems to manage the ethical components of such processes in a more comprehensive and systematic way than has previously been possible. The frameworkâs first axis defines five ethical dimensions that must be successfully addressed by eHealth ecosystems: 1) beneficence; 2) consent; 3) privacy; 4) equity; and 5) liability. The second axis describes five stages of the systems development life cycle (SDLC) process whereby new technology is incorporated into an eHealth ecosystem: 1) analysis and planning; 2) design, development, and acquisition; 3) integration and activation; 4) operation and maintenance; and 5) disposal. Known ethical issues relating to the deployment of BCIs are mapped onto this matrix in order to demonstrate how it can be employed by the managers of eHealth ecosystems as a tool for fulfilling ethical requirements established by regulatory standards or stakeholdersâ expectations. Beyond its immediate application in the case of BCIs, we suggest that this framework may also be utilized beneficially when incorporating other innovative forms of information and communications technology (ICT) into eHealth ecosystems
Managing the Ethical Dimensions of Brain-Computer Interfaces in eHealth: An SDLC-based Approach
A growing range of brain-computer interface (BCI) technologies is being employed for purposes of therapy and human augmentation. While much thought has been given to the ethical implications of such technologies at the âmacroâ level of social policy and âmicroâ level of individual users, little attention has been given to the unique ethical issues that arise during the process of incorporating BCIs into eHealth ecosystems. In this text a conceptual framework is developed that enables the operators of eHealth ecosystems to manage the ethical components of such processes in a more comprehensive and systematic way than has previously been possible. The frameworkâs first axis defines five ethical dimensions that must be successfully addressed by eHealth ecosystems: 1) beneficence; 2) consent; 3) privacy; 4) equity; and 5) liability. The second axis describes five stages of the systems development life cycle (SDLC) process whereby new technology is incorporated into an eHealth ecosystem: 1) analysis and planning; 2) design, development, and acquisition; 3) integration and activation; 4) operation and maintenance; and 5) disposal. Known ethical issues relating to the deployment of BCIs are mapped onto this matrix in order to demonstrate how it can be employed by the managers of eHealth ecosystems as a tool for fulfilling ethical requirements established by regulatory standards or stakeholdersâ expectations. Beyond its immediate application in the case of BCIs, we suggest that this framework may also be utilized beneficially when incorporating other innovative forms of information and communications technology (ICT) into eHealth ecosystems
A Storm in an IoT Cup: The Emergence of Cyber-Physical Social Machines
The concept of social machines is increasingly being used to characterise
various socio-cognitive spaces on the Web. Social machines are human
collectives using networked digital technology which initiate real-world
processes and activities including human communication, interactions and
knowledge creation. As such, they continuously emerge and fade on the Web. The
relationship between humans and machines is made more complex by the adoption
of Internet of Things (IoT) sensors and devices. The scale, automation,
continuous sensing, and actuation capabilities of these devices add an extra
dimension to the relationship between humans and machines making it difficult
to understand their evolution at either the systemic or the conceptual level.
This article describes these new socio-technical systems, which we term
Cyber-Physical Social Machines, through different exemplars, and considers the
associated challenges of security and privacy.Comment: 14 pages, 4 figure
Creative Gardens: Towards Digital Commons
date-added: 2015-03-04 03:12:21 +0000 date-modified: 2015-04-01 06:49:53 +0000date-added: 2015-03-04 03:12:21 +0000 date-modified: 2015-04-01 06:49:53 +0000This work was supported by the Arts and Humanities Research Council, CreativeWorks London Hub, grant AH/J005142/1, and the European Regional Development Fund, London Creative and Digital Fusion
Connecting teachers and students with science and scientists: The science learning hub
National and international data is raising concerns about levels of student interest and engagement in science in school and student retention into tertiary study. For todayâs students the Internet plays an important role as a source of information and means for communication with peers. This paper reports on a Ministry of Research Technology and Science funded initiative, managed through The University of Waikato, that aims to make New Zealand science research more accessible to New Zealand teachers and students. The New Zealand Science Learning Hub [SLH] illustrates how effective collaboration between research organisations, industries, science educators and teachers has enabled the development of a resource which is dynamic, up-to-date and relevant and that can be used to inform the teaching of science in New Zealand schools. The Science Learning Hub provides teachers with information about current research, which is related to concepts currently taught in year 5-10 classes (8-14 year olds). The site has content arranged in contexts for example, Icy ecosystems, Hidden taonga, Nanoscience, You me and UV, Future fuels, and The see through body. Each context includes text and images describing NZ research, video material such as interviews with scientists and sequences depicting scientists at work, teaching and learning materials, and links to science education literature. A feature is a âconnections toolâ which allows teachers and students to trace their journey through each context. Initial research indicates that teachers appreciate that this range of information is accessible in one place and has been quality assured. Students are keen to engage with an actively explore the range of media within the SLH contexts
Community tracking in a cMOOC and nomadic learner behavior identification on a connectivist rhizomatic learning network
This article contributes to the literature on connectivism, connectivist MOOCs (cMOOCs) and rhizomatic learning by examining participant interactions, community formation and nomadic learner behavior in a particular cMOOC, #rhizo15, facilitated for 6 weeks by Dave Cormier. It further focuses on what we can learn by observing Twitter interactions particularly. As an explanatory mixed research design, Social Network Analysis and content analysis were employed for the purposes of the research. SNA is used at the macro, meso and micro levels, and content analysis of one week of the MOOC was conducted using the Community of Inquiry framework. The macro level analysis demonstrates that communities in a rhizomatic connectivist networks have chaotic relationships with other communities in different dimensions (clarified by use of hashtags of concurrent, past and future events). A key finding at the meso level was that as #rhizo15 progressed and number of active participants decreased, interaction increased in overall network. The micro level analysis further reveals that, though completely online, the nature of open online ecosystems are very convenient to facilitate the formation of community. The content analysis of week 3 tweets demonstrated that cognitive presence was the most frequently observed, while teaching presence (teaching behaviors of both facilitator and participants) was the lowest. This research recognizes the limitations of looking only at Twitter when #rhizo15 conversations occurred over multiple platforms frequented by overlapping but not identical groups of people. However, it provides a valuable partial perspective at the macro meso and micro levels that contribute to our understanding of community-building in cMOOCs
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