Presentation at JISC CETIS conference 16.11.2010

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

24. Inquiry Science Learning:
Personal Inquiry and nQuire
• Three year project
• University of Nottingham/ Open
University
• Aim:
– To help students engage in effective
science inquiries

25. 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

26. 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

27. 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

28. 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