ratna dhamija using data to enhnace learning
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Using Data to support Teaching and Learning in
schools
Dr Ratna DhamijaAustralian Council for Educational Research
• private, not-for-profit educational research organisation
•established in 1930 in Australia
• established in 2005 in India
•offices in Melbourne, Sydney, Brisbane, Perth, Delhi, Dubai
Australian Council for Educational Research (ACER)
Undertakes a broad range of research toinform educational policy and practice has astrong program of research and developmentin educational measurement / studentassessment
www.acer.edu.au
Australian Council for Educational Research (ACER)
• How do we measure what students knowand can do?
• How can we use assessments to helpstudents enhance learning?
• How do we use information fromassessment to improve teaching ?
Challenges
• Students need to know how much they have learnt•Teachers need information to be able to supportclassroom teaching• School leaders need information as they would liketo ensure quality• Parents need to know if their child is learning• Education Departments need information to supporteducational reforms
The Context
• 21st century work skills expectations
• Transparency - this is ‘information age’.
• Data and information has always been available,technology has made it easier.
Accountability and data are at the heart of contemporaryreform efforts worldwide. Accountability has become thewatchword of education, with data holding a central place
(Earl, 2005p.6)
Why Now
• Principals and teachers can be reluctant to engage withdata
• Professional intuition leads them to be defensive aboutdata analysis
• Few trained teachers
• Feedback from assessment is not leveraged intoteaching
• Form of analysis not available that separates out thefactors that do lie within the control of teachers, and givesa valid and easily interpreted analysis of these factors
Current Approach
Research has shown that teachersand school leaders who useassessment data to informinstruction improve student learningmore than teachers who don’t useassessment data (Black andWilliam, 1998)
Data
Wisdom
Information
knowledge
Educational system must be built around ‘evidence-based practice’.
ACTIONimprovedlearningoutcomes
improvedlifeconsequences
understandingof currentsituation
knowledgeabout howto improve
requiredresources
feedback / evaluation
ACTIONimprovedlearningoutcomes
improvedlifeconsequences
understandingof currentsituation
knowledgeabout howto improve
requiredresources
Education is ultimately judged by what people learn
Evidence Based Approach to teaching and learning
We need to ‘know’ –to have evidence about the
performance of our students in orderto support them to achieve high quality
educational outcomes.
Decision Making Based on Intuition, Tradition or Convenience
Decision Making based on Data
Professional Development of Staff as and when found suitable
Focused professional development addressing the documented evidence-based problems
Budgetary Decisions based on priorpractice and suitability
Budgetary allocation to program/resources based on data-informed needs
Staff responsibility and involvement as per availability
Staff assignments based on skills as indicated by data
Report to school community about events Factually organized reports about learning progress to the community
Goal-setting by Board, Management Goal-setting based on data about issues faced and possible suggestions and explanations
Staff Meeting – focusing on dissemination and operations
Staff meeting – focus on strategies and issues indicated by data
Decision Making Based on Intuition, Tradition or Convenience
Decision Making based on Data
Parent Communication via PTMs Parent Interaction regarding the progress of their child and discussions around building support for student-learning
Grading system based on each teacher’s criteria of completed work
Grading system based on common student-performance that reports progress on standards as well as skills
Periodic administrative team meetings focusing on operational issues
Periodic team meetings that focus on measured growth based on data
Data collected in School is classified as Primary Data (eg student work, classroom observation) – Formative Assessment –Assessment for Learning
Secondary Data – student test scores, parent surveys – Summative Assessment (Assessment of Learning) or a standardized assessment
Sources of Data
• Standardised Assessment
• Questioning in class
• Quzzies, Projects
• Teacher’s Observations
• Portfolios - Student Work
Potential Sources of Data
Assessment is the process of identifying, gathering and interpreting information about students’ learning. The purpose of assessment is to provide information on progress and set the direction for ongoing teaching and learning
Assessment is not an end in itself but a vehicle for educational improvement – therefore it should not be an exercise of measuring what is easy but in assessing things that are important and valued– even though these are often the most difficult
things to assess.
Assessment should take into account not only what students know but what they can do with
what they know.
Guiding Principles:
Father: Well son, how are your exam results?
Son: They're all under water
Father: What do you mean?
Son: They're all under C level
Analyse Data
Data collected and analysed independently uncovers patterns and relationship
Using student achievement dataSchool level reports
At the school level, the distribution and level of achievement is the focus.
For example, how do the achievements of your students • compare with those in similar schools?
• compare with those in different countries?
• show any differences in the achievements of boys and girls?
• with different country backgrounds compare with the achievement of students in their home country?
Guiding Questions for Analyzing Data
• What are the patterns indicating ?
• What are the problems that are emerging from the data ?
Guiding Questions for Generating Hypotheses
• Why are our students performing the way they are ?
• What in our systems and practices is causing our students to have these problems ?
Item No. 36
Option 1 may be chosen when the students have doubled length (4 cubes added), doubled breadth (4 cubes added), doubled height (4
cubes added) – not maintained the shape required.
Option 2 may have been taken when the students may have taken only two dimensions and found the total number of cubes in them (when
length and breadth are doubled the area is 4 times.
Option 3 to get double length we need 4 cubes, to get double height we need 8 more and for double width we need 8 more cubes behind the
cubes shown (4 beside + 8 top + 8 behind) To sum up the students are not able to visualize the solid as a whole,
they may be able to identify a solid not able to create a solid using shapes (They missed out on the type of shape required but have been
able to identify the dimensions of the solid.
Class Report
Grade 9 Mathematical Literacy : Descriptors for Questions
Descriptor Competency Content
1 Work out which of the given items on sale has the largest percentage decrease in price.
Rp Q
2 Explain whether all items on sale are reduced by 30%. Co Q
3 Find the area of a square after a linear reduction. Rp S
4 Identify the result of a coordinate transformation. Co S
5 Read information from a table given two constraints. Co U
COMPETENCY: Co=Connection Rf=Reflection Rp=Reproduction
CONTENT: C=Change and Relationships Q=Quantity S=Space and Shape U=Uncertainty
Sample HypothesesHypotheses Evidence
Our Students perform well in maths They need further support in say question require reflection
Teachers need to be trained further to teach math
There are more special ability students in regular classes and they bring down our results
Reject / Accept as a possibilityChecked student achievement data. They perform low in primary but stabilize in secondaryORNeed remedial in classes 6 to 8
Student Performance Between Grades
Strand
2010 (Grade-9) 2011 (Grade-10)
Perc
ent (
%)
Corr
ect
Aver
age
Perc
ent (
%)
Corr
ect
(Indi
a)
Aver
age
Perc
ent (
%)
Corr
ect
(Inte
rnat
iona
l)
Perc
ent (
%)
Corr
ect
Aver
age
Perc
ent (
%)
Corr
ect
(Indi
a)
Aver
age
Perc
ent (
%)
Corr
ect
(Inte
rnat
iona
l)
Chance & Data 22.2 53.0 50.8 22.2 28.4 27.2Measurment 33.3 57.6 55.2 25.0 50.1 44.5Number 31.6 60.1 55.5 70.0 58.0 48.7Space 37.5 57.2 58.4 62.5 50.0 46.4Total 31.1 57.7 55.0 51.1 49.2 43.2
To Summarise• Institutions need to have Well-defined system of collecting Data
• Tools that support Analysis and interpretation
• Skills to analyze and interpret data effectively
• Attitude that data are a valuable resource for guiding School Improvement
To Summarise• All Data use needs to be explicitly guided by documented analysis and rigorous discussion of the reliability of the data and validity of interpretations
• The rationale of using data is embedded to support learning
• Finally the suggestions may not be earth-shattering but effects of implementing based on evidence could be profound
Committed to Excellence
• What are the ways you use data?• Who do you share it with?
• What would you do with the data?
• Do you have list of identified areas for improvement Strategies for improvement in each area ?
Questions
Australian Council for Educational Research
Questions