Designing LearningTowards a scalable interdisciplinary
design science of learning
Mike SharplesLearning Sciences Research Institute
University of Nottingham
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.
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
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
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
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
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
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
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.
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
Problems of DBR
• Can be lengthy
• How to systematically explore a space of possibilities
• Can lead to ‘hillclimbing’ exploration that misses ‘other peaks’
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
Socio-cognitive EngineeringA scalable method for design-based learning research
Generalrequirements
Theory of Use
Design Concept
ContextualStudies 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.
Socio-cognitive EngineeringExample of use in the MOBIlearn project (www.mobilearn.org)
Generalrequirements
Theory of Use
Design Concept
ContextualStudies Task
model
Design space
System
specification
ImplementationDeployment
EvaluationTheory 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 evaluationLifecycle
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 system
MOBIlearn system
Deployed in Uffizi Gallery, Nottingham
Castle Museum
Deployed in Uffizi Gallery, Nottingham
Castle Museum
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.
Two examples of scalable design based researchSecondary 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
Example of large-scale learning design project: Group Scribbles
Social-constructivist theories of learningSocial-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 networkwww.g1to1.org
NCU TaiwanSRI, United States
Group Scribbles software
Group Scribbles software
SRI International United States,
Taiwan,Singapore,
UK,Spain SceDer for orchestrating
1:1 classroom learningSceDer for orchestrating 1:1 classroom learning
LSRI,United Kingdom
SceDer for orchestrating 1:1 classroom learning
SceDer for orchestrating 1:1 classroom learning
Classroom evaluationsDjanogly City Academy, UK
Sharing of research findings
Sharing of research findings
CSCL workshop,Greece
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
SceDerJitti 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
SceDer authoring tool
SceDer/GS classroom tool
Classroom evaluation at Djanogly Academy, Nottingham
Inquiry Science Learning: Personal Inquiry and nQuire
• Three year project
• University of Nottingham/ Open University
• Aim:– To help students engage in effective
science inquiries
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
Planmy methods,
equipment, actions
Collectmy evidence
Analyseand represent my
evidence
Respondto my question or
hypothesis
Shareand discuss my inquiry
ReflectOn my progress
Find my topic
Decide my inquiry question
or hypothesis
Planmy methods,
equipment, actions
Collectmy evidence
Analyseand represent my
evidence
Respondto my question or
hypothesis
Shareand discuss my
inquiry
ReflectOn my progress
nQuire Inquiry Guide to structure inquiry learning outside the classroom
nQuire web-based toolkitwww.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
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