24,430 research outputs found

    Evaluating the development of wearable devices, personal data assistants and the use of other mobile devices in further and higher education institutions

    Get PDF
    This report presents technical evaluation and case studies of the use of wearable and mobile computing mobile devices in further and higher education. The first section provides technical evaluation of the current state of the art in wearable and mobile technologies and reviews several innovative wearable products that have been developed in recent years. The second section examines three scenarios for further and higher education where wearable and mobile devices are currently being used. The three scenarios include: (i) the delivery of lectures over mobile devices, (ii) the augmentation of the physical campus with a virtual and mobile component, and (iii) the use of PDAs and mobile devices in field studies. The first scenario explores the use of web lectures including an evaluation of IBM's Web Lecture Services and 3Com's learning assistant. The second scenario explores models for a campus without walls evaluating the Handsprings to Learning projects at East Carolina University and ActiveCampus at the University of California San Diego . The third scenario explores the use of wearable and mobile devices for field trips examining San Francisco Exploratorium's tool for capturing museum visits and the Cybertracker field computer. The third section of the report explores the uses and purposes for wearable and mobile devices in tertiary education, identifying key trends and issues to be considered when piloting the use of these devices in educational contexts

    Locational wireless and social media-based surveillance

    Get PDF
    The number of smartphones and tablets as well as the volume of traffic generated by these devices has been growing constantly over the past decade and this growth is predicted to continue at an increasing rate over the next five years. Numerous native features built into contemporary smart devices enable highly accurate digital fingerprinting techniques. Furthermore, software developers have been taking advantage of locational capabilities of these devices by building applications and social media services that enable convenient sharing of information tied to geographical locations. Mass online sharing resulted in a large volume of locational and personal data being publicly available for extraction. A number of researchers have used this opportunity to design and build tools for a variety of uses – both respectable and nefarious. Furthermore, due to the peculiarities of the IEEE 802.11 specification, wireless-enabled smart devices disclose a number of attributes, which can be observed via passive monitoring. These attributes coupled with the information that can be extracted using social media APIs present an opportunity for research into locational surveillance, device fingerprinting and device user identification techniques. This paper presents an in-progress research study and details the findings to date

    Harnessing Technology in Schools Survey 2007: technical report

    Get PDF
    This technical report provides a detailed review of the methods used and the data gathered for this survey. The report also provides copies of the research instruments used in this survey

    Integrating Mobile Web 2.0 within tertiary education

    Get PDF
    Based on three years of innovative pedagogical development and guided by a participatory action research methodology, this paper outlines an approach to integrating mobile web 2.0 within a tertiary education course, based on a social constructivist pedagogy. The goal is to facilitate a student-centred, collaborative, flexible, context-bridging learning environment that empowers students as content producers and learning context generators, guided by lecturers who effectively model the use of the technology. We illustrate how the introduction of mobile web 2.0 has disrupted the underlying pedagogy of the course from a traditional Attelier model (face-to-face apprenticeship model), and has been successfully transformed into a context independent social constructivist model. Two mobile web 2.0 learning scenarios are outlined, including; a sustainable house design project (involving the collaboration of four departments in three faculties and three diverse groups of students), and the implementation of a weekly ‘nomadic studio session'. Students and lecturers use the latest generation of smartphones to collaborate, communicate, capture and share critical and reflective learning events. Students and lecturers use mobile friendly web 2.0 tools to create this environment, including: blogs, social networks, location aware (geotagged) image and video sharing, instant messaging, microblogging etc
 Feedback from students and lecturers has been extremely positive

    Context Aware Computing for The Internet of Things: A Survey

    Get PDF
    As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
    • 

    corecore