Mobile Data from a Research Perspective Institute of Educational Technology The Open University Agnes Kukulska-Hulme JISC/CNI conference, Edinburgh, 1-2 July 2010

The Open University's Institute of Educational Technology Book published 2009 Collective experience of mobile learning researchers

The Open University's Institute of Educational Technology MOTILL – European project on Mobile Technologies in Lifelong Learning: Best Practices, case studies e.g. FÓN project

Mobile pedagogy in the classroom collaboration interaction instant sharing personalisation instant access instant capture

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

The Open University's Institute of Educational Technology Anytime learning Life-long learning Life-wide learning

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

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

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

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

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

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)

Institute of Educational Technology The Open University Milton Keynes United Kingdom Thank you