personalising learning, e-maturity and educational outputs jean underwood philip banyard gabrielle...
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Personalising Learning, e-Maturity and
Educational Outputs
Jean Underwood
Philip Banyard
Gabrielle Le Geyt
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Recognition to the team:
Nottingham Trent University (NTU):
Prof. Jean Underwood
Phil Banyard
Dr Lee Farrington-Flint
Dr Gayle Dillon
Dr Thom Baguley
External collaborators:
Peter Hick (Manchester Metropolitan University)
Ian Selwood (University of Birmingham)
Mary Hayes (Consultant)
Madeline Wright
Gabrielle Le Geyt
Dr Jamie Murphy
Emily Coyne
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IMPACT 2007 and other studies
How can ICT promote thepersonalising of learning?What is the impact of ICT on
scholastic achievement and the practice of teaching?
Research projects for Becta (2000-08)
• Testbed• Connecting with broadband• Impact of broadband• Impact 2007• Personalising learning• Impact 2008
Research methods• Expert seminars• Case studies• Observation• Online surveys• Interviews• Focus groups• Maturity models
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Expectations of technology
•Government priority
“A large part of personalisation isabout self-management and self-provision.”
David Miliband, NCSL 2005
“I see ICT and its potential to transform how we teach, learn and communicate
as crucial to our drive to raise standards.”Ruth Kelly, 2005
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Self-regulated learning (SRL)
•Self-regulated behaviour (SRB)– Goal establishment– Planning– Striving– Revision
(Austin & Vancouver, 1996)
•Self-regulated learning subset of SRB
•Motivation important for SRL– Self efficacy– Task value beliefs– Mastery goal orientation
Self-regulated Learning
Personalised Learning
Standards Site, DCSF, accessed July 2008
school teachers learners parents
Assume every childis different
Variety of teachingstrategies
Innovate and developto meet diverse needsof learners
Partners in learning
Individual needs
Identify weaknesses
Support to succeed
High expectations ofall learners
Wide repertoire ofteaching strategies
Holistic, tailoredprovision for all
Regular updates
Engage in learning
Opportunity to playactive role
Contribution valued
About personalising learning
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IMPACT 2007 data
• Collected from 66 Primary and Secondary schools in the UK
• Online teacher survey (n = 417)
• Online learner survey (n = 1056, Primary, n= 1822, Secondary )
• Interviews with school leaders (n = 30)
• Interviews with ICT coordinators (n = 29)
• Maturity Models (n = 66)
• School level performance data (SATs scores at Key Stages 2,3 & 4)
• School level demographic data (e.g. deprivation)
school teachers learners parents
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Building a learning equation
Opportunity InvestmentEffectivelearning
Barriers and facilitators
Barriers and facilitators
What does itlook like?
ICT and the personalising of learning
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The Educational Equation
Opportunity:What the school, teacher and home provides.
Investment:The learner's ability and decision to investment in his or her own learning.
Effective learning:A sound and coherent knowledge base coupled to critical thinking skills
Empowerment:An educated citizen able to function at an appropriate level in the world
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An effective learner
A potentially empowered citizen
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e-Maturity & Personalising Learning and Learner Behaviour &
Performance. The measures of OPPORTUNITY?
o Learner level: learner perceptions of the opportunities available. Measures from Impact 2007 are
• p-learner scale• p-learner (enlarged scale)• home access scale
o Teacher level: teacher perceptions of the facilities and the learning opportunities
• p-teacher• potentialities scale• outreach scale
o Institution level: institutional perceptions of ICT provision• e-Maturity model• resource provision (teacher questionnaire 8 item scale)
o Community level: measures of institutional culture and economic status• free school meals• learner throughput (starting late / leaving early)• English not first language• absenteeism• socio-economic profile of school catchment
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e-Maturity & Personalising Learning and Learner Behaviour & Performance
2. The measures of INVESTMENT in LearningSubscales from the learner questionnaire to consider are:
o Persistenceo Engagement
3. The measures of EFFECTIVE LEARNINGo School performance measures
• KS tests• value added data
o Learner perception scaleso Expert judgement e.g. Ofsted reports
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Findings
school teachers learners parents
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Schools and personalised learning
• e-maturity is generally associated with pupil perceptions of personalised learning, but not in high performing schools
• Learner performance at Key Stage 3 is associated with teacher perceptions of personalised learning
school teachers learners parents
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Teachers and personalising learning
Primary > Secondary
Effect of ICT on learners
Potential of ICT
Perceived amount of personalised learning
Attitudes to ICT correlated with perceived personalised learning
r = 0.53, p<0.001
school teachers learners parents
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Teachers and personalising learning
13.5 14 14.5 15 15.5 16 16.5 17 17.5 18 18.5
ICT
Science
English
Maths
Design & Tech
Teacher specialism and perceived impact of I CT on learners
64 66 68 70 72 74 76 78
ICT
Sport
Science
English
Maths
Teacher specialism and perceived degree of personalised learning
school teachers learners parents
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Learners and personalised learning
• Measures of perceived personalisation and engagement with learning
• Perceived personalisation declines with year group in school
Personalisation Score by School Year
20
22
24
26
28
30
32
34
36
year 3 year 4 year 5 year 6
Primary School Year
Level of
Perc
eiv
ed
Pers
on
alisati
on
school teachers learners parents
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Learners and personalised learning
• Measures of perceived personalisation and engagement with learning
• Perceived personalisation declines with year group in school
Personalisation Score by School Year
20
22
24
26
28
30
32
34
36
year 7 year 8 year 9 year 10 years 11/13
Secondary School Year
Level o
f P
ers
on
alisati
on
school teachers learners parents
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Learners and personalised learning
• Measures of perceived personalisation and engagement with learning
• Perceived personalisation declines with year group in school
• Boys perceive more personalised learning (Secondary)
• Girls show more engagement with learning (Primary)
school teachers learners parents
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Personalised learning beyond the school
• Anywhere, anyplace, anytime
• The school intrudes into the home
• The home intrudes into the school
• The impact of digital divides
school teachers learners parents
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Variation from Impact 2007 Schools' Mean Performance by Group
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
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LE/LIL HE/LIL LE/HIL HE/HIL
Sta
nd
ard
de
via
tio
n f
rom
me
an
p
erf
orm
an
ce b
y g
rou
p
Standardisedscores
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The Impact of Levels of eMaturity and Pupil Investment in Learning on Whole School Performance
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Two Key Technologies
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Personalised Learning Facilitator: VLEs
What are VLEs?
• Collection of tools to support learning
• Increased modes of learning
• Anyplace, anytime learning
school teachers learners parents
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Personalised Learning Facilitator: VLEs
When do they work?
• Fit-for-purpose
• Pupil-centred
• Interactive
• Intuitive, reliable and easy to negotiate
• Flexible
• Communication resources
• Embedded
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Evidence of successful VLE implementation
“The VLE has been a major influence in developing the personalisation agenda. Teachers can tap into or tailor for small groups of pupils. The parents are involved, therefore there is a whole group approach to learning, and it helps parents to understand where the pupils are. The teachers planning and assessment has always been good, but the VLE has focused the mind and sharpened the offerings”.
school teachers learners parents
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And the Interactive Whiteboard
• Easy Entry Point
• Embedded
• Ubiquitous
• Fast becoming the equivalent of e-mail
• But
• Used for?
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Summary
• There are strong beliefs in the efficacy of ICT and also of personalised learning for enhancing educational performance
• There is some evidence to support both beliefs but the relationship is complex
• VLE is seen as a key driver of ICT development and also personalised learning
• IWB are valuable entry level tools
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Thank you for listening