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Personalised On-the-Job Reflective Mobile Learning in Fire and Rescue Services

Personalised On-the-Job Reflective Mobile Learning in Fire and Rescue Services. Wichai Eamsinvattana Supervisors Dr.Vania Dimitrova (School of Computing) Dr.David Allen (Business School). Mobile Learning at Fire and Rescue Services Challenges and Current Practices

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Personalised On-the-Job Reflective Mobile Learning in Fire and Rescue Services

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  1. Personalised On-the-Job Reflective Mobile Learning in Fire and Rescue Services Wichai Eamsinvattana Supervisors Dr.Vania Dimitrova (School of Computing) Dr.David Allen (Business School)

  2. Mobile Learning at Fire and Rescue Services Challenges and Current Practices Research goal and questions PORML Framework Background Theories & Technologies Expected Contributions Presentation Plan

  3. M-learning: The acquisition of any knowledge and skills through using mobile technology, anywhere, anytime, that results in an alteration in behaviour (Geddes, 2004) Main Challenge: Need for creative scenarios and applications to integrate m-learning in everyday work practices and tasks. (Frohberg, 2006) Characteristics of effective m-learning: knowledge access directly linked to the current user activities educational material collected or available on the field learning experiences placed in the current user context (Trifonova, 2003) • Mobile Learning at Fire and Rescue Services • Research Goal and Questions • PORML Framework • Background • Expected Contributions Mobile Learning Challenges

  4. Mobile Learning at Fire and Rescue Services • Research Goal and Questions • PORML Framework • Background • Expected Contributions Training at Fire and Rescue Service • Disconnected from the real context • Simulated environment • Off-site • Not very effective

  5. Mobile Learning at Fire and Rescue Services • Research Goal and Questions • PORML Framework • Background • Expected Contributions What Happens in Reality • Conditions rapidly change • Various aspects (e.g. road traffic, lethal chemicals, people in danger) • Previous experience is imprtant • Crew commander’s risk assessment is crucial • Many crew commanders are inexperienced • (from M. Casten from Norfolk FRS)

  6. Mobile Learning at Fire and Rescue Services • Research Goal and Questions • PORML Framework • Background • Expected Contributions Existing Approaches Virtual reality to support reflective learning Mobile technology to support decision making at FRS Aimed at decision making but learning is not considered Learning by reflecting on FRS activities but disconnected from the real environment No research has been conducted to use mobile technologies for reflective on-the-job learning.

  7. Goal:Design personalised mobile learning environments to support reflective on-the-job learning in FRS: Users: Crew Commanders Skills: Risk Assessment • Mobile Learning at Fire and Rescue Services • Research Goal and Questions • PORML Framework • Background • Expected Contributions Research Goal and Questions • Research questions: • How to model the user and context considering on-the-job activities of FRS crew commanders, semantic location-based information, and user’s experiences? • How can these models be used to promote reflection on the risk assessment skills after an incident has finished, by taking into account the current activity and adapting to a crew commander’s experience and skills?

  8. Mobile Learning at Fire and Rescue Services • Research Goal and Questions • PORML Framework • Background • Expected Contributions PORML Framework Learning Objects

  9. Activity Theory (Engestrom, Kofod-Petersen): to define what context aspects are related to the current user activity Conversational Theory(Pask, Taylor): To organise the interaction between the learner and technology Reflection-on-action Model (Shon, Dewey): To decide what reflective questions can be asked and how • Mobile Learning at Fire and Rescue Services • Research Goal and Questions • PORML Framework • Background • Expected Contributions Underpinning Theories

  10. Mobile Learning at Fire and Rescue Services • Research Goal and Questions • PORML Framework • Background • Expected Contributions Semantic Description of Location Data OS Master Map from DigiMap Create Image Map GML File - Semantic GPS Receiver Coordinate Coordinate (x,y) For User Ontology: Place - University of Leeds

  11. A novel framework for personalised mobile learning to support FRS risk assessment training by integrating on-the-job activities, location-based information, and user’s experiences. A prototype of a mobile application which uses custom built services from the framework in an illustrative FRS scenario. • Mobile Learning at Fire and Rescue Services • Research Goal and Questions • Background • PORML Framework • Expected Contributions Expected Contributions

  12. Questions & AnswersThank you!

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