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Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
Designing learning
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Designing learning

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Presentation at JISC CETIS conference 16.11.2010

Presentation at JISC CETIS conference 16.11.2010

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  • 1. Designing Learning Towards a scalable interdisciplinary design science of learning Mike Sharples Learning Sciences Research Institute University of Nottingham
  • 2. Big challenges, big opportunities • Transforming higher education – Flexible institutions – Open learning – Blended and distance learning – Personalised learning • Transforming school education • Enabling global access to education “We also should implement a new approach to research and development (R&D) in education that focuses on scaling innovative best practices in the use of technology in teaching and learning, ... creating a new organization to address major R&D challenges at the intersection of learning sciences, technology, and education.” Transforming American Education: Learning Powered by Technology. US National Education Technology Plan, 2010.
  • 3. New complexities of learning • New interactions – Mediation of technology – Between learners, education institutions, commercial providers • New connections – Learning at a distance – Learning between formal and informal settings • New opportunities – Trans-national learning – Massively social learning – Mobile and contextual learning – Life-long and life-wide learning
  • 4. New Science of Learning A.N. Meltzoff, P. K. Kuhl, J. Movellan, & T. J. Sejnowski (200) Foundations for a New Science of Learning, Science 325 (5938), 284. • Computational learning – Infer structural models from the environment – Learn from probabilistic input • Social learning – Learning by imitation – Shared attention • Neural learning – Learning supported by brain circuits that link perception and action • Developmental learning – Behavioural and cognitive development – Neural plasticity • Teaching and learning – Principles of effective teaching • Contextual and temporal learning – Learning within and across contexts – Cycle of engagement and reflection • Technology-enabled learning – Learning as a distributed socio-technical system
  • 5. New Science of Learning A.N. Meltzoff, P. K. Kuhl, J. Movellan, & T. J. Sejnowski (200) Foundations for a New Science of Learning, Science 325 (5938), 284. • Computational learning – Infer structural models from the environment – Learn from probabilistic input • Social learning – Learning by imitation – Shared attention • Neural learning – Learning supported by brain circuits that link perception and action • Developmental learning – Behavioural development – Neural plasticity • Teaching and learning – Principles of effective teaching • Contextual and temporal learning – Learning within and across contexts – Cycle of engagement and reflection • Technology-enabled learning – Learning as a distributed socio-technical system “Insights from many different fields are converging to create a new science of learning that may transform educational practice” Meltzoff et al., p284 “Insights from many different fields are converging to create a new science of learning that may transform educational practice” Meltzoff et al., p284
  • 6. New Science of Learning A.N. Meltzoff, P. K. Kuhl, J. Movellan, & T. J. Sejnowski (200) Foundations for a New Science of Learning, Science 325 (5938), 284. • Computational learning – Infer structural models from the environment – Learn from probabilistic input • Social learning – Learning by imitation – Shared attention • Neural learning – Learning supported by brain circuits that link perception and action • Developmental learning – Behavioural development – Neural plasticity • Teaching and learning – Principles of effective teaching • Contextual and temporal learning – Learning within and across contexts – Cycle of engagement and reflection • Technology-enabled learning – Learning as a distributed socio-technical system “A key component is the role of ‘the social’ in learning. What makes social interaction such a powerful catalyst for learning?” Meltzoff et al., p288 “A key component is the role of ‘the social’ in learning. What makes social interaction such a powerful catalyst for learning?” Meltzoff et al., p288
  • 7. Changing behaviour Neuroscience Behavioural science Enhancing skills Cognitive development Storing information Cognitive sciences Gaining knowledge Cognitive sciences Epistemology Making sense of the world Social sciences Socio-cultural and activity theory Interpreting reality in a different way Phenomenology Interdisciplinary science of learning
  • 8. Interdisciplinary design science of learning • How do people learn as individuals, groups, organisations, societies? • How can we design and share effective systems for learning? • How can we evaluate the success of learning? • Across contexts, throughout a lifetime
  • 9. Design-based research “A systematic but flexible methodology aimed to improve educational practices through iterative analysis, design, development, and implementation, based on collaboration among researchers and practitioners in real- world settings, and leading to contextually- sensitive design principles and theories” Wang, F., & Hannafin, M. J. (2005). Design-based research and technology- enhanced learning environments. Educational Technology Research and Development, 53(4), 5-23.
  • 10. Benefits of DBR • Problem driven – Not only understand, document, and interpret, but also change and improve • Systematic exploration of a space of possible designs • Combines engineering and evaluation • The designed context is subject to test and revision, and the successive iterations that result play a role similar to that of systematic variation in experiment
  • 11. Problems of DBR • Can be lengthy • How to systematically explore a space of possibilities • Can lead to ‘hillclimbing’ exploration that misses ‘other peaks’
  • 12. Scalable interdisciplinary design science of learning “No longer can one community attempt to design TEL tools; communication and sharing of expertise amongst them is of paramount concern” Yishay Mor & Niall Winters (2007) Design Approaches to Technology- Enhanced Learning, Interactive Learning Environments, 15, 1, 2007, 61- 75
  • 13. Socio-cognitive Engineering A scalable method for design-based learning research General requirements Theory of Use Design Concept Contextual Studies Task model Design space System specification ImplementationDeployment Evaluation Sharples, M., Jeffery, N., du Boulay, J.B.H., Teather, D., Teather, B., and du Boulay, G.H. (2002) Socio-cognitive engineering: a methodology for the design of human-centred technology. European Journal of Operational Research 136, 2, pp. 310-323.
  • 14. Socio-cognitive Engineering Example of use in the MOBIlearn project (www.mobilearn.org) General requirements Theory of Use Design Concept Contextual Studies Task model Design space System specification ImplementationDeployment Evaluation Theory of learning for the mobile world Theory of learning for the mobile world OMAF design framework for mobile learning OMAF design framework for mobile learning Lifecycle evaluation Lifecycle evaluation Studies of informal learning practices Studies of informal learning practices General requirements for a mobile learning platform General requirements for a mobile learning platform M-learning task model M-learning task model MOBIlearn systemMOBIlearn systemDeployed in Uffizi Gallery, Nottingham Castle Museum Deployed in Uffizi Gallery, Nottingham Castle Museum
  • 15. Lifecycle evaluation • Micro level: Usability issues – technology usability – individual and group activities • Meso level: Educational Issues – learning experience as a whole – continuity of learning across settings – critical incidents: learning breakthroughs and breakdowns • Macro level: Organizational Issues – effect on the educational practice – emergence of new practices – take-up and sustainability Vavoula, G. & Sharples, M. (2009) Meeting the Challenges in Evaluating Mobile Learning: a 3-level Evaluation Framework. International Journal of Mobile and Blended Learning, 1,2, 54-75.
  • 16. Two examples of scalable design based research Secondary education, but also being extended to higher education •Group scribbles/SceDer –Orchestrating individual and group learning in a 1:1 classroom (where each student has a wireless laptop or tablet) •Personal Inquiry –Supporting inquiry-based science learning within and beyond the classroom
  • 17. Example of large-scale learning design project: Group Scribbles Social-constructivist theories of learning Social-constructivist theories of learning Theory and practice of 1:1 learning in classrooms Theory and practice of 1:1 learning in classrooms Scenarios of successful classroom practice Scenarios of successful classroom practice G1:1 global research network www.g1to1.org NCU Taiwan SRI, United States Group Scribbles softwareGroup Scribbles software SRI International United States, Taiwan, Singapore, UK, Spain SceDer for orchestrating 1:1 classroom learning SceDer for orchestrating 1:1 classroom learning LSRI, United Kingdom SceDer for orchestrating 1:1 classroom learning SceDer for orchestrating 1:1 classroom learning Classroom evaluations Djanogly City Academy, UK Sharing of research findings Sharing of research findings CSCL workshop, Greece
  • 18. Classroom Orchestration: Group Scribbles & SceDer • Developed by SRI International Centre for Technology in Learning • System to support 1:1 classroom learning • Based on Post-its metaphor • Design and evaluation in US, Taiwan, Singapore, UK, Spain Group scribbles in Singapore Group scribbles in the USA
  • 19. SceDer Jitti Niramitranon, University of Nottingham PhD research • Design-based research to extend Group Scribbles for teacher authoring and classroom management • Based on scenarios of classroom interactions from SRI and NCU, Taiwan • Teacher support for orchestration of individual, group and whole class learning
  • 20. SceDer authoring tool
  • 21. SceDer/GS classroom tool
  • 22. Classroom evaluation at Djanogly Academy, Nottingham
  • 23. Inquiry Science Learning: Personal Inquiry and nQuire • Three year project • University of Nottingham/ Open University • Aim: – To help students engage in effective science inquiries
  • 24. Design based research • Co-design of technology and pedagogy • Personal inquiry learning • Scripted inquiry learning – Guided learning activities on a personal mobile computer Find my topic Decide my inquiry question or hypothesis Plan my methods, equipment, actions Collect my evidence Analyse and represent my evidence Respond to my question or hypothesis Share and discuss my inquiry Reflect On my progress
  • 25. Find my topic Decide my inquiry question or hypothesis Plan my methods, equipment, actions Collect my evidence Analyse and represent my evidence Respond to my question or hypothesis Share and discuss my inquiry Reflect On my progress nQuire Inquiry Guide to structure inquiry learning outside the classroom
  • 26. nQuire web-based toolkit www.nquire.org • Open source (Drupal) • Web-based • Runs on Windows, Linux, Mac • Variety of devices including iPhones • Authoring, teacher, and student applications • Individual, group and whole class activities
  • 27. Scalable design science of learning • Transformational vision – Orchestrating 1:1 classroom learning – Personal inquiry learning • Interdisciplinary science of learning • Design based research • Open sharing and scaling of best practice • Large scale embedding and evaluation

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