Formative Assessment

1. Formative Assessment Using data teams analysis to inform teaching and learning

2. What is a Data Team Analysis? Data teams are groups of teachers who collect and analyse student data with an aim to improve student achievement. Through data collection and analysis, teachers are able to identify strengths and obstacles affecting student achievement. Once identified, teachers set goals and collaborate with colleagues to plan and implement teaching strategies that will target improvement. james.tania@cathednet.wa.edu.au

3. Data Collection Data is used in three ways • To inform at system level • To inform at a school level • To inform at a classroom level Data Teams Analysis can be used to inform teaching at a classroom level. We refer to this as Formative Assessment because this type of data can be used immediately, to modify teaching and learning programs with an aim to increase student achievement. (Note: Summative Assessment is collected at the end of a unit of work and often measured against a standard or benchmark, e.g. NAPLAN) james.tania@cathednet.wa.edu.au

4. How Do Data Teams Work? 1. Collect, chart and analysedata from common Formative Assessments Teachers develop quality common Formative Assessments that are for learning and not just a summative assessment of learning 3. Prioritize needs and set SMART goalsTeachers set S.M.A.R.T. goals. Goals that are, specific, measurable, achievable, relevant and time-bound. E.g. Johnny will be reading fluently at level 16, two levels above his current level, by week 8 of this term. 2. Identify strengths and obstacles by analysingstudent results and work samplesTeachers identify strengths and highlight celebrations. They also identify what has not been learnt by students and teaching ‘point-of-need’ to target. 4. Select Effective Teaching Strategies & implement theseHow does the data inform lesson and unit planning? Teachers reflect on the data, collaborate and research in order to implement effective teaching strategies that will improve student achievement (based on their S.M.A.R.T. Goals) james.tania@cathednet.wa.edu.au

5. 5. Determine a Results Indicator. Then Monitor & Assess. How will you measure if your strategies worked? (Re-assess your target students?). Was the goal reached? Which strategies do you need to modify and review? What can be improved upon next time? What will you continue to monitor? james.tania@cathednet.wa.edu.au

6. An Example • Decide what data you will be collecting and how (e.g. teacher made test? A test from MTS Online? etc…) • Determine the assessment criteria. Is it reading fluency or comprehension? Is it knowledge or automaticity. • Decide on what you consider either ‘mastery’ or ‘proficiency’ etc… • Collect and analyse your data using the three columns • Meet with your data team and discuss results. Decide on a focus group. Research effective strategies that could be implemented. james.tania@cathednet.wa.edu.au

7. Assessment Criteria & Data Collection james.tania@cathednet.wa.edu.au

8. Sort Student Data Based on Criteria You & your data team decide on this criteria james.tania@cathednet.wa.edu.au

9. Point of Need and Strategies to Implement • Make sure your goals is a S.M.A.R.T. goal! • Specific, • Measurable, • Achievable, • Relevant and • Time-bound Just choose a goal for ONE group. Your target group. james.tania@cathednet.wa.edu.au

10. Data Team Analysis: What Now? • How will you measure if your strategies worked? (Re-assess your target students?Conduct new assessment?) • Reflect on the use of teaching strategies – were these successful? How do you know? • Which aspects will you continue to implement? • What will you continue to monitor • Report back to the professional learning community james.tania@cathednet.wa.edu.au

11. An Quick Look at SMART Goals Goals Must Be S-M-A-R-T (Specific, Measurable, Achievable, Relevant, Timely) • Specific targeted subject area, grade level, and student population • Measurement instrument to be used and the element examined must be measurable • Achievable percentage gains or increases in terms of expected change • Relevant subject areas – Is the goal tending to an urgent need? • Time when the assessment will take place as well as timely in terms of identified need Readmore about SMART goals here: IMAGE SOURCE: http://dreamchoosers.com/s-m-a-r-t-goals/ james.tania@cathednet.wa.edu.au

12. Your Professional Practice When we work with colleagues to analyse data then plan & implement new strategies, we are in fact working to establish our own professional standards. Conducting data teams analysis lends itself to much of the “Highly Accomplished” criteria from the AITSL standards. Using AITSL as a guide, a ‘Proficient’ teacher will plan and implement effective teaching strategies but a ‘Highly Accomplished’ Teacher will collaborate and plan with colleagues to implement effective teaching strategies. james.tania@cathednet.wa.edu.au

13. Your Professional Practice AITSL STANDARD: Professional Practice Standard 1.5 james.tania@cathednet.wa.edu.au

14. Your Professional Practice AITSL STANDARD: Professional Practice Standard 3.6 james.tania@cathednet.wa.edu.au

15. Your Professional Practice AITSL STANDARD: Professional Practice Standard 3.1 & 3.2 james.tania@cathednet.wa.edu.au

16. Resources & Readings The following sources were used to help construct this slideshow. • Data Teams and the Data Driven Decision Making Process: http://www.pvusd.k12.ca.us/departments/GATE/documents/formassess/data_teams__dddm_presentation_summary.pdf • Data Driven Decision Making & Data Teams: Connecticut State Department of Educationhttp://www.sde.ct.gov/sde/cwp/view.asp?a=2618&q=321744 • Achieve Your Goals by being S.M.A.R.T. http://www.dreamchoosers.com/s-m-a-r-t-goals/ james.tania@cathednet.wa.edu.au

17. Formative Assessment Using data teams analysis to inform teaching and learning