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Mobile Data from a Research Perspective Institute of Educational Technology The Open University Agnes Kukulska-Hulme JISC/CNI conference, Edinburgh, 1-2 July 2010
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The Open University's Institute of Educational Technology Book published 2009 Collective experience of mobile learning researchers
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The Open University's Institute of Educational Technology MOTILL – European project on Mobile Technologies in Lifelong Learning: Best Practices, 2009-10 case studies e.g. FÓN project
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Mobile pedagogy in the classroom collaboration interaction instant sharing personalisation instant access instant capture
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The Open University's Institute of Educational Technology Mobile pedagogy outside the classroom Connecting education with work-based learning Connecting leisure activity and informal learning Connecting classroom and field learning
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The Open University's Institute of Educational Technology Anytime learning Life-long learning Life-wide learning
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Mobile learning research oLearning contexts : mobility of the learner; movement between locations; how learning spaces are utilized; ecologies of learning resources on the move; proximity to objects being studied; social/cultural/technological context oThe relationship of mobile tools to other tools that learners use or carry : this includes conflicting and complementary technologies; multiple communication channels oLearning processes and emerging practices : how mobile technologies can stimulate learning innovation and contribute to change; appropriation of a mobile device over time; user-generated content; distributed collection of experiential/scientific data by learners over time
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The Open University's Institute of Educational Technology Some important research themes: Context, control, transition, engagement, time use Context: context-aware applications, learner-generated contexts, personal inquiry Control: learner or instructor Transition: between places, between types of learning, between mental states Engagement: emotional state Time use: pockets of time, dead time
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Research methods/ data Qualitative interviews and focus groups Attitude surveys Device use surveys Observations Video capture Eye tracking Learner diaries Personal concept mapping Audio logs / audio recordings Automatic logging of device use Artefacts produced by learners Twitter messages, Instant messaging Tests to compare learner performance
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The Open University's Institute of Educational Technology Data analysis and interpretation Analysis –Triangulation –Conflicts and contradictions –Critical incidents (breakthroughs and breakdowns) Interpretation –Scenarios –Stories –Narratives
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Issues and challenges Learning spread across locations and times No fixed point to locate an observer Difficulty separating learning from other everyday activities Snapshots and one-off activities: need for longitudinal studies Variety of technologies used (personal and borrowed) Self-reporting may be unreliable Quality of participant-collected data Rich data (spatial, temporal…) Ethical concerns when monitoring activity Scaling up
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The Open University's Institute of Educational Technology Proposals Integrate expertise from other fields to develop remote research methods, including for longitudinal studies Develop data visualizations for aspects such as: space and time use, devices used, transitions, connections between contexts Propose ethical guidelines for mobile data collection (in progress – International Association for Mobile Learning)
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Institute of Educational Technology The Open University Milton Keynes United Kingdom http://www.open.ac.uk/iet a.m.kukulska-hulme@open.ac.uk Thank you
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