Mock Data Retreat Pam Lange TIE/ESA 7

2 Agenda  Based on school’s need  May be ½ day/ full day/ two days  Work with district to determine needs – the more time they can devote the more in-depth you can be.

3 Sample: One Day Data Retreat 8:00 – 10:00Welcome Opening Activity Changes to Test Changes to Accountability System Content Revision Cycle District/Middle School Reports 10:00 – 10:15Break 10:15 – 11:30District/Middle School Reports Evaluation of School Improvement Plan 12:00 – 1:30Individual DakotaSTEP Results STAR Results DACS Results 1:30 – 1:45Break 1:45 – 4:00Planning for Individual Student Success

4 Outcomes  To examine district-wide data  To examine building-level data  To examine individual student achievement data  To determine next steps

5 Ice Breaker I always do some type of Ice Breaker - for sake of time, we won’t do one today!

6 Group Norms  Take care of personal needs  Mute cell phones  Limit side conversations  Others???

7 Team Readiness Confidentiality Form Assigning Roles

8 4 Lenses of Data Prioritize & Set Goals Study & Plan Successful Strategies Observe Patterns & Hypothesize Student Data Program & Structures Data Family & Community Data Professional Practices Data

9 District Data Sources  Data Matrix (Handout)  Data Discussion Guide

10 District Audit Tool Categories  Leadership Implications  Academic Content and Achievement Standards  Curriculum/Instruction  Highly Qualified Staff  Professional Development  Assessment and Accountability  School Culture/Climate  Budget and Resources  Parents and Community

11 District Audit Tool Categories  If you have the results from the District Audit Tool and/or School Profile this is where you would discuss some of those results – bring in to data discussion. Show how they fit into the four lenses of data.  Example: Academic Content and Achievement Standards

12 Student Data DakotaSTEP Results

13 “Pure” DakotaStep Items Criterion- referenced “Pure” SAT 10 Items Norm- referenced

14 Data Report Terms  Scaled Score How well did this student score?  Cut Scores What score is good enough?  Advanced  Proficient  Basic  Below Basic  AMO How many students scored proficient and advanced?  AYP Is your school or district above in every category?  Reading  Math  Attendance or graduation rate

15 Annual Measurable Objectives up to 2014 K School Year ReadingMathReadingMath %65%66%54% %65%72%54% %72%72%63% %72%77%63% %79%83%72% %86%89%81% %93%94%90% %100%100%100%

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17 South Dakota State Content Standards Revision Cycle  Science test was given in spring Districts are not be held accountable for science content standards, but did receive results of how students scored.  At this point, the DakotaSTEP will not be aligned to Social Studies

18 Sat/DAT Tool

19 Document Data Findings Observations What patterns do we see in the data? What observations: facts only – no discussion at this point Hypotheses What explanations or theories might we have about the data? What impact might this data have?

20 Willy E. Everlearn High School/District All Students

21 Observation Worksheet  Buff colored handout  Name of report  Who is the “paper” recorder?  Who is the “chart” recorder?

22 SAT/DAT Analysis  Look at ALL four years  Watch number of students who were tested  Compare male to female  Compare number of students advanced in reading versus math

23 Document Data Findings Observations What patterns do we see in the data? What observations: facts only – no discussion at this point Hypotheses What explanations or theories might we have about the data? What impact might this data have?

24 Growth Reports Focus of Report:  Achievement Gaps  Are we on target?

25 Growth Report

26 Growth Reports ► Is ► Is the group “All” students (black line) on target to meet AMO in subsequent years? the group “Below Basic and Basic” students (pink line) on target to meet AMO in subsequent years?

27 Growth Reports Is the achievement gap getting smaller or larger? Are your students on target?

28 Looking at Individual Data  Confidentiality  I will need these reports back

29 Document Data Findings Observations What patterns do we see in the data? What observations: facts only – no discussion at this point Hypotheses What explanations or theories might we have about the data? What impact might this data have?

30 Highlight Color Meaning Proficiency on DakotaSTEP Our Cutoff Levels Blue WOW! Beyond ExpectationsAdvanced or 90% and above Green GOOD! Students performed well on this item -- Meets Expectations Proficient or 65 to 89% Yellow CAUTION! Students had some difficulty with this item -- Below Expectations Basic or 50 to 65% PinkURGENT! Students performed poorly on this item -- In need of Immediate Improvement Below Basic or 0 to 49% Using Highlighting to Illuminate the Data

31 Individual Growth Reports Math – Blue/Reading – Pink  What observations can you make about students who have a negative growth?  What surprises you about this group?  What observations can you make about students who have the greatest amount of growth?  What surprises you about this group?

32 Individual Growth Reports Math – Blue/Reading – Pink  What impact do these observations have at the classroom level?  How can looking at individual student data drive our instructional practices in the classroom? Does it?

33 How close are we – really?  Cut Scores  points above

34 Differentiated Instruction Based on the individual data, if you were asked to differentiate student groups, how would you group them? How would the groups differ for reading versus math?

35 Student Data Non-DakotaSTEP

36 CRT Report (Criterion Reference Testing) Website: E-Metrics

37 Document Data Findings Observations What patterns do we see in the data? What observations: facts only – no discussion at this point Hypotheses What explanations or theories might we have about the data? What impact might this data have?

38 CRT Data (Individual Standards)  Individual building report  Seven questions per indicator (combines standards)  Discuss the bell shaped curve theory  60 to 65 percent

39 Highlight Color Meaning Average % Correct Scores Our Cutoff Levels Blue WOW! Beyond Expectations90% and above Green GOOD! Students performed well on this item -- Meets Expectations 65 to 89% Yellow CAUTION! Students had some difficulty with this item -- Below Expectations 50 to 65% PinkURGENT! Students performed poorly on this item -- In need of Immediate Improvement 0 to 49% Using Highlighting to Illuminate the Data

40 State Content Standards  Explain State Process  Unpacked Standards (see handout)  Math, Reading, Science 

41 CRT Data (Individual Standards)  Brainstorm ideas about the low standards  Why might they be low?  Are these standards that need to be high priority?  What strategies are we currently using?  What are some areas we could look at to make sure we are covering these standards?

42 School Profile If you have school profile – what can you utilize at a data retreat?

43 Other Data Sources  At the building level, what other data sources do you have available?  As a group, prioritize what you would like to focus on next?  Look at assessment matrix

44 4 Lenses of Data Prioritize & Set Goals Study & Plan Successful Strategies Observe Patterns & Hypothesize Student Data Program & Structures Data Family & Community Data Professional Practices Data

45 Where do we go from here?  What data do ALL staff members need to look at?  When/how can this happen?  How can this information be useful to you?  What other information can you add to this form?  What can we pull from other initiatives that will help us when planning for student success?  What can I do to help in the process?

46  Three things that you still have questions about  Two things that you feel really good about  One thing that surprised you Check-Out