2,336 research outputs found
An investigation into the perspectives of providers and learners on MOOC accessibility
An effective open eLearning environment should consider the target learner’s abilities, learning goals, where learning takes place, and which specific device(s) the learner uses. MOOC platforms struggle to take these factors into account and typically are not accessible, inhibiting access to environments that are intended to be open to all. A series of research initiatives are described that are intended to benefit MOOC providers in achieving greater accessibility and disabled learners to improve their lifelong learning and re-skilling. In this paper, we first outline the rationale, the research questions, and the methodology. The research approach includes interviews, online surveys and a MOOC accessibility audit; we also include factors such the risk management of the research programme and ethical considerations when conducting research with vulnerable learners. Preliminary results are presented from interviews with providers and experts and from analysis of surveys of learners. Finally, we outline the future research opportunities. This paper is framed within the context of the Doctoral Consortium organised at the TEEM'17 conference
Analyzing the Use of Camera Glasses in the Wild
Camera glasses enable people to capture point-of-view videos using a common
accessory, hands-free. In this paper, we investigate how, when, and why people
used one such product: Spectacles. We conducted 39 semi-structured interviews
and surveys with 191 owners of Spectacles. We found that the form factor
elicits sustained usage behaviors, and opens opportunities for new use-cases
and types of content captured. We provide a usage typology, and highlight
societal and individual factors that influence the classification of behaviors.Comment: In Proceedings of the 37th Annual ACM Conference on Human Factors in
Computing Systems (CHI 2019). ACM, New York, NY, US
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Connected seeds and sensors: co-designing internet of things for sustainable smart cities with urban food-growing communities.
We present a case study of a participatory design project in the space of sustainable smart cities and Internet of Things. We describe our design process that led to the development of an interactive seed library that tells the stories of culturally diverse urban food growers, and networked environmental sensors from their gardens, as a way to support more sustainable food practices in the city. This paper contributes to an emerging body of empirical work within participatory design that seeks to involve citizens in the design of smart cities and Internet of Things, particularly in the context of marginalised and culturally diverse urban communities. It also contributes empirical work towards non-utilitarian approaches to sustainable smart cities through a discussion of designing for urban diversity and slowness
Science Hackathons for Cyberphysical System Security Research: Putting CPS testbed platforms to good use
A challenge is to develop cyber-physical system scenarios that reflect the
diversity and complexity of real-life cyber-physical systems in the research
questions that they address. Time-bounded collaborative events, such as
hackathons, jams and sprints, are increasingly used as a means of bringing
groups of individuals together, in order to explore challenges and develop
solutions. This paper describes our experiences, using a science hackathon to
bring individual researchers together, in order to develop a common use-case
implemented on a shared CPS testbed platform that embodies the diversity in
their own security research questions. A qualitative study of the event was
conducted, in order to evaluate the success of the process, with a view to
improving future similar events
User Perceptions of Smart Home IoT Privacy
Smart home Internet of Things (IoT) devices are rapidly increasing in
popularity, with more households including Internet-connected devices that
continuously monitor user activities. In this study, we conduct eleven
semi-structured interviews with smart home owners, investigating their reasons
for purchasing IoT devices, perceptions of smart home privacy risks, and
actions taken to protect their privacy from those external to the home who
create, manage, track, or regulate IoT devices and/or their data. We note
several recurring themes. First, users' desires for convenience and
connectedness dictate their privacy-related behaviors for dealing with external
entities, such as device manufacturers, Internet Service Providers,
governments, and advertisers. Second, user opinions about external entities
collecting smart home data depend on perceived benefit from these entities.
Third, users trust IoT device manufacturers to protect their privacy but do not
verify that these protections are in place. Fourth, users are unaware of
privacy risks from inference algorithms operating on data from non-audio/visual
devices. These findings motivate several recommendations for device designers,
researchers, and industry standards to better match device privacy features to
the expectations and preferences of smart home owners.Comment: 20 pages, 1 tabl
Understanding Shoulder Surfing in the Wild: Stories from Users and Observers
Research has brought forth a variety of authentication systems to mitigate observation attacks. However, there is little work about shoulder surfing situations in the real world. We present the results of a user survey (N=174) in which we investigate actual stories about shoulder surfing on mobile devices from both users and observers. Our analysis indicates that shoulder surfing mainly occurs in an opportunistic, non-malicious way. It usually does not have serious consequences, but evokes negative feelings for both parties, resulting in a variety of coping strategies. Observed data was personal in most cases and ranged from information about interests and hobbies to login data and intimate details about third persons and relationships. Thus, our work contributes evidence for shoulder surfing in the real world and informs implications for the design of privacy protection mechanisms
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