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Full-Text Articles in VLSI and Circuits, Embedded and Hardware Systems
Contextualized Mobile Support For Learning By Doing In The Real World, Ray Bareiss, Natalie Linnell, Martin L. Griss
Contextualized Mobile Support For Learning By Doing In The Real World, Ray Bareiss, Natalie Linnell, Martin L. Griss
Martin L Griss
This research addresses the use of mobile devices with both embedded and external sensors to provide contextualized help, advice, and remediation to learners engaged in real-world learn-by-doing tasks. This work is situated within the context of learning a complex procedure, in particular emergency responders learning to conduct urban search and rescue operations. Research issues include the design and delivery of contextualized performance support and the inferring of learner actions and intentions from sensor data to ensure that the right support is delivered just in time, as it is relevant to what the learner is doing.
Leveraging Mobile Context For Effective Collaboration And Task Management In Disaster Response, Faisal Luqman, Martin L. Griss
Leveraging Mobile Context For Effective Collaboration And Task Management In Disaster Response, Faisal Luqman, Martin L. Griss
Martin L Griss
Collaboration and task management is challenging in distributed, dynamically-formed teams, typical in large scale disaster response scenarios. Ineffective collaboration may result in poor performance and possible loss of life. In this paper, we present Overseer, an agent-based system that exploits context information from mobile devices to facilitate collaboration and task allocation. We describe our system architecture and show how mobile context can be used to create dynamic role-based assignments to support collaboration and effective task management.