28
Designing Learning Towards a scalable interdisciplinary design science of learning Mike Sharples Learning Sciences Research Institute University of Nottingham

Designing learning

Embed Size (px)

DESCRIPTION

Presentation at JISC CETIS conference 16.11.2010

Citation preview

Page 1: Designing learning

Designing LearningTowards a scalable interdisciplinary

design science of learning

Mike SharplesLearning Sciences Research Institute

University of Nottingham

Page 2: Designing learning

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.

Page 3: Designing learning

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

Page 4: Designing 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

Page 5: Designing 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 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

Page 6: Designing 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 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

Page 7: Designing learning

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

Page 8: Designing 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

Page 9: Designing learning

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.

Page 10: Designing learning

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

Page 11: Designing learning

Problems of DBR

• Can be lengthy

• How to systematically explore a space of possibilities

• Can lead to ‘hillclimbing’ exploration that misses ‘other peaks’

Page 12: Designing learning

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

Page 13: Designing learning

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.

Page 14: Designing learning

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

Page 15: Designing learning

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.

Page 16: Designing learning

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

Page 17: Designing learning

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

Page 18: Designing learning

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

Page 19: Designing learning

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

Page 20: Designing learning

SceDer authoring tool

Page 21: Designing learning

SceDer/GS classroom tool

Page 22: Designing learning

Classroom evaluation at Djanogly Academy, Nottingham

Page 23: Designing learning
Page 24: Designing learning

Inquiry Science Learning: Personal Inquiry and nQuire

• Three year project

• University of Nottingham/ Open University

• Aim:– To help students engage in effective

science inquiries

Page 25: Designing learning

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

Page 26: Designing learning

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

Page 27: Designing learning

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

Page 28: Designing learning

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