A Case Study inside Virtual WorldsUsing Analytics for immersive spaces
Short Paper submitted at LAK13 Vanessa Camilleri, Sara de Freitas, Matthew Montebello, Paul McDonagh-Smith
Overview
• Building the case
• VWs: Immersion & Engagement
• Using Models for Predictions
• Analytics: Tracing the Steps
• Making Sense out of Data
• Implications
• Conclusion10/04/2013 LAK13 2
Introduction: building the case
• Pre-service teachers and technology
• Attitudes & beliefs
• Experience or lack of
• Teacher training programs
• Our problem: Engage through activity
• Our proposal: Immersion through use of 3D spaces
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VWs: Immersion & Engagement
• Immersion: Dede & Barab (2009) – more focused on learner experience, less on tools
• Immersion: Calleja (2011) – not overly dependent on fidelity but more on emotions generated
• Immersion: Dede (2009) & Freedman (2011) – situated, authentic learning experiences
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VWs: Immersion & Engagement
• Engagement: Csìkszentmihàlyi (1991) – reaching the optimal ‘flow’ between challenge and boredom
• Engagement: Portelli & McMahon (2004) – learner achieves a deeper level of critical inquiry; learner is autonomous and responsible for learning
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Using Models for Predictions
• Virtual Worlds – building on the exploratory framework model (de Freitas & Oliver, 2006)
• Technology acceptance – building on the TAM (technology acceptance model) (Davis, 1993)
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TAM (Davis, 1993)
Exploratory Framework (de Freitas & Oliver, 2006)
Analytics: Tracing the steps
• Analytics: Siemens (2010)learner-produced data to discover information and social connections
• Our case study: With a degree of flexibility, and just in time learning environment, what connections have our learners established?
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Analytics: Tracing the steps
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Making sense out of data
• Social Connections + Interactions (analytics)
• Changes in Attitudes (pre/post-test surveys)
• Reflections (focus groups)
• Assessment (theoretical reflective paper)
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Implications
• How do we measure and predict engagement at a ‘deeper’ level given the notions of autonomous learning, using an exploratory learning framework inside an immersive 3D environment?
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Conclusions
• How can we use data to monitor how the learner progresses inside the 3D space, and how can the 3D space adapt itself to the data generated by the learner?
• Finally can we design a predictive model, that would enable us to determine changes in real world behavior arising from the virtual world interactions?
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References
Calleja, G. (2011). In-Game: from immersion to incorporation. London, UK: MIT Press.
Csìkszentmihàlyi, M. (1991). Flow: The Psychology of Optimal Experience. New York, USA: HarperCollins Publisher Inc.
Davis, F. (1993). User Acceptance of Information Technology: system characteristics, user perceptions and behavioural impacts. International Journal of Man-Machine Studies , 475-487.
de Freitas, S., & Oliver, M. (2006). How can exploratory learning with games and simulations within the curriculum be most effectively evaluated? Computers & Education (46), 249-264.
Dede, C. (2009). Immersive Interfaces for Engagement and Learning . Science , 323, 66-69.
Dede, C., & Barab, S. (2009). Emerging Technologies for Learning Science: A Time of Rapid Advances. Journal of Scientific Educational Technology , 18, 301–304.
Freedman, T. (2011). Authentic Learning and ICT. Retrieved June 2011, from ICT in Education: http://www.ictineducation.org/home-page/2011/6/16/authentic-learning-and-ict.html
Portelli, J., & McMahon, B. (2004). Why Critical-Democratic Engagement? . Journal of Maltese Education Research , 2 (2), 39-45.
Siemens, G. (2010). What are Learning Analytics? Retrieved 2012, from ELEARNSPACE: http://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics/
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