Digital Mobility Research Group
Led by Associate Professors Angsana Techatassanasoontorn and Antonio Díaz Andrade, the group adopts a multi-disciplinary approach to explore the evolving use, experiences and impacts of digital technology on individuals, organisations and society.
Tensions and accommodations: ICT-mediated activities by visually impaired professionals
Workplace accommodations for blind employees continue to be a challenge not only to these workers but also to their co-workers and the existing organisational practices. This study aims to understand the ways information and communication technology (ICT) supports and transforms work activity of visually impaired professionals and provide an account of the tensions introduced into the organisation. Cultural-historical activity theory and its principle of contradictions informs this research, whose findings will offer useful insights for organisations to evolve their policies and practices to simultaneously accommodate to visually impaired workers’ needs and minimise tensions in the work system.
Key researchers: Antonio Díaz Andrade and Angsana A. Techatassanasoontorn
Video about this research:
Visual Impairment at Work
Visual Impairment at Work (with subtitles)
Mobility in action: A user experience
The wide acceptance and broad integration of mobile devices into work activities have brought a new set of challenges associated with conflicting demands, roles, perspectives and practices. This research aims to develop empirically-grounded theory to understand the use of mobile devices in work activities, emerging paradoxes from usage, and personal strategies in managing mobile use and their impact. The findings will give insights to understand complex process of mobility in use and offer practical suggestions to workers and their employers on strategies to manage the use of mobile devices.
Key researchers: Angsana A. Techatassanasoontorn, Antonio Díaz Andrade and Paweena Wanchai
A novel technique for processing of live mobile streaming data with persistent big data
Researchers in mobile technology face the challenge of processing big data. There are two main flavours of big data with respect to its processing. There is offline processing of persistent big data (e.g., historical mobile-users data) and there is big data in the form of continuous streams (e.g., streaming of live data coming from mobile devices) that need to be processed in real-time. In many situations the two flavours of big data, streams and persistent data, need to be joined – e.g., the joining of stream of live mobile users data with persistent historical data in the context of mobile technology. This is called semi-stream join. There are various techniques to perform semi-stream joins with exact matches between stream and persistent data, so-called equijoins. However, as soon as the matches are not exact these techniques fail. In this case, non-equijoins are needed. This project develops Semi-Stream NonEquijoins (SSNEs) for big data in the context of mobile technology.
Key researchers: Muhammad Asif Naeem
Simulation and critique of student-generated critical care scenarios in paramedicine education
This project explores the application of mobile Virtual Reality (VR) for simulating and critiquing authentic environments for paramedicine education. It tests and refines a framework for designing and deploying authentic real-life work simulations for training and assessment purposes for paramedicine students using mobile VR that can utilise their own smartphones via a portable head mounted display. The simulation environment enables students to generate scenarios and perform peer review of 360-degree videos of critical care environments. Under this approach, users design and create VR scenarios that identify critical and potential hazards for their peers to formulate a response plan of action. This creates an experiential link between the theory and practice of critical care education and leverage innovative pedagogical strategies enabling self-determined learning using mobile learning technologies.
Key researchers: Thomas Cochrane and Claudio Aguayo
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