developing and implementing the personalised learning and ... · developing and implementing the...

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PUBLIC SCHOOLS NSW WWW.SCHOOLS.NSW.EDU.AU

Developing and Implementing thePersonalised Learning and SupportSignposting Tool (PLASST)

Presentation by Brian Smyth King (NSW DEC)and Stuart Shinfield (PwC)

PUBLIC SCHOOLS NSW WWW.SCHOOLS.NSW.EDU.AU 2

Public Education NSW 2014/15

23% of Australian schools20.9% of school aged students(ABS 2013)


Our Commitment

For every child and young person attending a publicpre-school or school to:

If you are successful at school you will live longer, have betterquality of adult life and employment outcomes, be healthierand have better social inclusion.


Context for the PLASST and professional teacher judgement

Quality ofthe learningexperience

TeacherCapabilities

Relationships

Quality of each student’s learningexperience

1 Personalised learningand support

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• Changes to curriculum,instruction andenvironments that arebased on evidence andpersonalised to needs

• Judgements aboutthe effect and valueof adjustments basedon evidence throughmonitoring andreview

• Identifying strengthsand needs and workingout what is neededbased on evidence

• Working withparents, students,teachers, externalproviders

Educational context for leading, strengthening and sustainingprofessional teacher judgement

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Quality of each student’s learning experience

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TeacherCapabilities

Relationships


Personalised learning and support

• Changes to curriculum,instruction andenvironments that arebased on evidence andpersonalised to needs

• Judgements about theeffect and value ofadjustments based onevidence throughmonitoring and review

• Identifying strengthsand needs and workingout what is neededbased on evidence

• Working with parents,students, teachers,external providers

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What is the PLASST?

The PLASST assists teachers and

learning and supportteams to profile the functional

educational needsand strengths

personalisedlearning andsupport associated with

StatisticalModel

StudentReport

Website

Instrument

The PLASST

Four critical components of the PLASST

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disability as defined by the Disability

Discrimination Act 1992 (DDA) and Disability

Standards for Education 2005.

of students who may need


Also available on youtube:http://youtu.be/BywQacA4R84 or http://tinyurl.com/PLASST

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How did we get here?

2008

Design of theFunctional

AssessmentTool begins

2010

Pilot 1 inSSPsonly

2012

Pilot 2 in SSPswith parentalinvolvement

2013

Developmentand Trial

of the PLASST

2014

ParentalInvolvement

Trial

2015

InitialImplementationof PLASST in all

NSWPublic Schools

9 PUBLIC SCHOOLS NSW WWW.SCHOOLS.NSW.EDU.AU

7 years of development havecontributed to the PLASST,leveraging the expertise of:academics; teachers; statisticians;and consultants. Strengthenedprofessional teacher judgement isat the core of this development.

7years

Over 26,000 student profiles havebeen generated since the start of the2013 Trial

Estimates indicate that 15-20% ofstudents could benefit from thePLASST.

Over 500 schools have already createdstudent profiles using the PLASST.

Any student whose learning isimpacted by disability could benefitfrom the PLASST

26kstudents

100k+target group

500+schools

The PLASST in practice in NSW Public Schools in 2015

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What people have said about the PLASST

“This report was a relief. I’m used to teacherstelling me what’s wrong with [my child], but thelanguage here was overwhelmingly positive. Wespoke about what we were going to do, ratherthan just having the teacher tell me what waswrong.”

Parent/Carer of Year 8 student,NSW Public School

“This report was a relief. I’m used to teacherstelling me what’s wrong with [my child], but thelanguage here was overwhelmingly positive. Wespoke about what we were going to do, ratherthan just having the teacher tell me what waswrong.”


“As soon as I looked at the report I could see[my child]. Knowing that [the teacher] knew herthis well instantly made me trust both [theteacher] and the report.”


“As soon as I looked at the report I could see[my child]. Knowing that [the teacher] knew herthis well instantly made me trust both [theteacher] and the report.”


“I wish I had read one of these when I firstbecame a learning and support teacher – itwould have made the learning curve muchgentler.”

Learning and Support Teacher,NSW Public School

“I wish I had read one of these when I firstbecame a learning and support teacher – itwould have made the learning curve muchgentler.”

Learning and Support Teacher,NSW Public School

“With the PLASST report, I felt much moreconfident meeting with [the student’s parents].The report gave me a structure to work throughand positive things to talk about. [The parents]responded well.”

Classroom teacher with <5 years experience,NSW Public School

“With the PLASST report, I felt much moreconfident meeting with [the student’s parents].The report gave me a structure to work throughand positive things to talk about. [The parents]responded well.”

Classroom teacher with <5 years experience,NSW Public School


The four Critical Components of the PLASST

StatisticalModel

StudentReport

Website

Instrument

The PLASST

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A question set developedthrough expert input andexperimental research to berelevant to the full range oflearning and support needs

01 – Instrument

63questions

15minutes to

completeonce familiar

3 to 5categories foreach question

Instrument


https://www.plasst.nsw.edu.au/

02 – An intuitive and user friendly intranet websiteWebsite

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Website

Fast to start

All progress savedautomatically

A focus on theuser experience

On-demand PLASSTreport generation

Optimised for desktop,tablet, and smartphone

School-level informationfor principal and specialistteachers

02 – An intuitive and user friendly intranet website


Advanced statistical modellingundertaken to:

• map questions to domains ofneed (Factor Analysis)

• and scale within those domains(Rasch Scaling)

By clustering and scalingresponses, the student’s areas ofrelative strength and need wereprofiled. This creates a set ofsignposts to support the classroomteacher to engage with the familyand develop reasonableadjustments.

03 – Statistical ModelStatistical Model

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03 – Statistical ModelStatistical Model

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“It has been a pleasure to work as part of such a strong, creative and rigorous team.

At its heart the project need was to refine, validate and report upon a set of measures of thefunctional needs of students with disabilities, an activity that had conceptual parallels with theprocess of constructing and validation measures of educational outcomes.

With this recognition, the team drew upon state-of-the-art item response methods – in particular theGeneralised Partial Credit Model – in conjunction with a range of other complementarymethodologies. These methodologies were used to develop empirical support for the conceptuallybased reporting dimensions. These methods were used to:

- develop empirical support for the conceptually based reporting dimensions

- provide information for improving the items and response categories for those items

- appropriately target the instrument and

- develop a unique and powerful approach to reporting.

This innovative use of the methods not only ensured a rigorous approach to this particularinstrument’s validation, it has also made an important wider methodological contribution to the field,perhaps most importantly with regard how it allowed the reporting of student need to be expressedcoherently and with substantive meaning. ”

Professorial Fellow Ray Adams, University of Melbourne.

“It has been a pleasure to work as part of such a strong, creative and rigorous team.

At its heart the project need was to refine, validate and report upon a set of measures of thefunctional needs of students with disabilities, an activity that had conceptual parallels with theprocess of constructing and validation measures of educational outcomes.

With this recognition, the team drew upon state-of-the-art item response methods – in particular theGeneralised Partial Credit Model – in conjunction with a range of other complementarymethodologies. These methodologies were used to develop empirical support for the conceptuallybased reporting dimensions. These methods were used to:

- develop empirical support for the conceptually based reporting dimensions

- provide information for improving the items and response categories for those items

- appropriately target the instrument and

- develop a unique and powerful approach to reporting.

This innovative use of the methods not only ensured a rigorous approach to this particularinstrument’s validation, it has also made an important wider methodological contribution to the field,perhaps most importantly with regard how it allowed the reporting of student need to be expressedcoherently and with substantive meaning. ”

Professorial Fellow Ray Adams, University of Melbourne.


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Statistical Model

03 – Colour shows strength of correlation

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Statistical Model

03 – Questions vs Questions


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Statistical Model

03 – Heatmap shows patterns in the data

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03 – Factor Analysis detected 6 Domainsof need...

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Statistical Model


Social Skills

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Statistical Model


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Social Skills

Cognitive

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Statistical Model



Social Skills

Cognitive

Independence

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Statistical Model


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Social Skills

Cognitive

Communication

Independence

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0.0

Statistical Model



Social Skills

Cognitive

Communication

Attentiveness

Independence

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Statistical Model


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Social Skills

Cognitive

Communication

Attentiveness

Social Adjustment

Independence

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0.2

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Statistical Model



Social Skills

Cognitive

Communication

Attentiveness

Social Adjustment

Independence

Sensory*

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Statistical Model


* Sensory is not a domain but rather a collection of independent responses

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03 – Interrelationships between domains

Social Skills

Cognitive

Communication

Attentiveness

Social Adjustment

Independence

Sensory

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Statistical Model


03 – Calculating underlying need, foreach domain, using independent Rasch Scales Statistical Model

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04 – The Student Profile report is informativeand engaging for those that know the student Student Report


04 – The domains are treated as independentand are presented on distinct Rasch Scales

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Student Report


04 – Within domains, each student’suniqueness is highlighted

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Student Report


Giving each student every opportunity toexperience quality learning every day

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Usingquantitativeanalysis to

supportpersonalisation

rather thanstandardisation


TeacherCapabilities

Relationships

A tool thatvalidates

professionalteacher

judgementrather than

diminishing it.


PLASST future potential to explore

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Analysis across time(Longitudinal)

Analysis across areas(Geospatial)

Access across jurisdictions / systemsDevelopment of a PLASST learning and user community

NSW is looking to extend this community and connect with other school systemsand jurisdictions (within Australia and internationally)

Expressions of interest: [email protected]


Questions

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