SASD Data Retreat 2013

1. SASD Data Retreat 2013

2. Agenda • Welcome • Purpose and Outcomes of Day • School Learning Objectives (SLO) • Overview & Connection to Educator Effectiveness • SLO Development Template • SMART Goal Process • Data Analysis • Team Work Time • Q & A • Wrap-up

3. Purposes & Outcomes • Provide information on how to develop and write School Learning Objectives (SLOs) • Review SMART Goal process • Learn about various student data sources (state and local) • Provide time and support to school teams as they work to develop SLOs • School teams will write two SLOs • School teams will be able to use the SMART Goal format as part of the SLO process • School teams will be able to access and analyze student data • School teamswill productively use time to work on their SLOs

4. Today’s Resources https://www.sheboygan.k12.wi.us/intech/plc/resources.html

5. School Learning Objectives An Introduction to SLO’s

6. Dual Meaning of the SLO Acronym • Building Administrators – School Learning Objectives • Goals established by building principal and staff, but are focused at the school level • **The Focus of Today** • Teachers – Student Learning Objectives • Goals established by a classroom teacher (or a team of teachers) for an entire classroom or a targeted population within a classroom or grade level

7. Definition Student/School Learning Objectives (SLOs) are detailed, measurable goals for student academic growth to be achieved in a specific period of time (typically an academic year), and based upon prior student learning data.

8. Key Characteristics of an SLO Baseline Data and Rationale Why did you choose this SLO and what sources of data did you examine? Student Population Who are you going to include in this SLO? Interval How long will you focus on this SLO? Growth Goal/Target What is the expected outcome of students’ level of knowledge? Instructional Strategies What methods or interventions will teachers apply to support this SLO? Evidence How will you measure the outcome of your SLO? **See SLO Development Template & DPI’s SLO Selection and Approval Rubric

9. Developing SLOs – Step 1 Review data to understand student learning and root cause problems and needs (baseline data and rationale) • Existing student datacould include trend data on state and district assessments, behavioral data, attendance data, other assessment data, etc. Disaggregation of data will be the key in determining target population(s). • Existing instructional practice dataare important for understanding ‘root causes’ and these data may include classroom observations/walkthroughs, unit/lesson plans, teacher created student work tasks, teacher surveys or interviews regarding instructional practices.

10. Developing SLOs – Step 2 Identify the student population to include in the SLO Based upon the data… • Which student group(s) is/are targeted? Some examples: • All students • Students from a particular grade level • A racial/ethnic group • Students performing below a predetermined criteria (i.e. students scoring below the 30%ile OR students with less than 15 credits)

11. Developing SLOs – Step 3 Use SMART goal format to develop growth goal/target Specific goals are well defined and free of ambiguity Measurable goals have appropriate and concrete evidence sources identified for measuring progress toward achievement Attainable goals are rigorous, yet within reach Results-based goals are aligned with the expectations and direction provided by the district Time-bound goals occur within a specified and realistic timeframe

12. SMART Goals – Key Question/Decision: Are all students expected to make the same amount of growth, regardless of where they start? OR Should differentiated goals be set?

13. Developing SLOs – Step 4 Determine instructional strategies and supports • Identify the strategies that will be used to address root causes to current student learning problems/needs and to achieve student learning goals. • What instructional methods will best support student achievement? • How will instruction be differentiated for the target group? • What new or existing materials and/or resources will be used to support student achievement? • What professional development opportunities will be needed to support the attainment of the goal?

14. Major Within Organizational Levers for Goal Achievement Administrative Leadership Student Engagement and Student Learning Outcomes Teaching/Instruction Organizational Context & Improvement Capacities Most proximal lever for improving student learning outcomes Gamoran, et al., 2000; 2003; Bryk et al. 2006

15. Logic Model: Teacher Learning to Impact on Student Engagement and Learning • Teacher Learning • Professional Development • Department Collaboration • Peer Observation/Coaching • Teacher Evaluation • Changes to Teacher’s: • Knowledge • Attitudes • Beliefs • Desire to practice new skills • Changes & Improves: • Decision-making • Planning • Instruction • Classroom environment • Curriculum and/or assessment practices Improved Student Learning and Engagement

16. Developing SLOs – Step 5 Determine evidence source – how will you measure the outcome of the SLO? • Need to identify sources that are most appropriate for measuring achievement of student outcome goal – valid and reliable • Sources need to provide data so that progress toward goal can be monitored overtime • Evidence for goal attainment should not overly rely on one source of data • Evidence sources used to measure achievement of outcome may be different than the data sources used to develop the goal

17. The SLO Process – A final thought… Student/School Learning Objectives will have the greatest impact on student learning when teachers and administrators: • Examine classroom practice • Collaborate on the goal-setting process • Set rigorous, yet attainable goals • Tie instructional strategies to goal attainment • Engage in regular data analysis

18. DATA Analysis

19. Sources of Data • What data sources (state and local) can be used to determine your school’s baseline data and rationale?

20. DPI Data sources WISEdash

21. Data Models The DPI uses four different data models to analyze student performance data: • Achievement • Gain • Growth • Value-Added

22. Data Models The DPI uses four different data models to analyze student performance data: • Achievement – student performance compared to a predetermined standard • Gain – documented change in a student’s score from one test administration to another • Growth – compares student performance gain to the gain made by students with similar starting scores • Value-Added – determines how the school is affecting student growth (uses growth model + variable control)

23. Confidentiality DPI’s Agreement to Protect Student Privacy LDS users are required to agree to each of the statements below: • I will respect and safeguard the privacy of students and the confidentiality of student data. • I will comply with state and federal privacy laws and all district regulations, policies, and procedures established to maintain the confidentiality of student data. • I will not disclose or transmit confidential LDS data to persons not specifically authorized access to these data by the district LDS Administrator, superintendent, or school board. • I will use the confidential LDS data for legitimate educational purposes only as necessary to perform my district-assigned tasks. • I understand that my password is as important as my signature. It is my obligation to keep my password confidential. I will not share my password with anyone. • I will not use other users' login names or passwords. • I have viewed the student privacy training presentation and understand my obligation to protect the confidentiality of the student data that I will be accessing.

24. Secure Home Access http://dpi.wi.gov

25. School Report Cards http://dpi.wi.gov

27. Annual measurable Objectives (AMO)

28. In the ESEA waiver request, DPI submitted ambitious but achievable AMOs based on proficiency rates resulting from Wisconsin’s new WKCE performance level cut scores. Using 2011-12 data, AMOs were set to move all schools in the state to the level of the schools that are now performing at the 90th percentile within six years. By 2016-17, the expectation is for all schools to have all student groups reach 50% reading proficiency and 65% mathematics proficiency. Some subgroups have steeper AMO trajectories because they are further behind in proficiency rates. A minimum 1% of growth is expected annually. This would apply to those schools/subgroups that are already meeting the AMOs but for whom we expect continued growth. AMOs

29. Reading AMOs

31. Math AMOs

33. For a school’s reading and mathematics AMOs, a group’s performance compared to its AMO is measured by the higher of (1) the proficiency rate in the current year; or (2) the average proficiency rate in the current and prior year. A cell size of 20 is used and a 95 percent confidence interval is applied to determine whether or not an AMO is met. Meeting AMOs

34. Confidence Intervals • A confidence interval (CI) is a type of estimate used to indicate the reliability of a statistic. • The CI gives an estimated range of scores (interval) within which the school’s or group’s “true score” falls. • The level of confidence of the CI indicates the probability that the confidence range captures this true population parameter given a distribution of samples. It does not describe any single sample. • The confidence interval gives us 95% certainty of the group’s performance. If the performance is within the confidence interval, it is determined to have met the AMO. We are 95% confident that the true value is in our confidence interval.

35. Meeting AMOs

36. Schools also have an AMO for graduation rate. Wisconsin uses the graduation rate goal of 85 percent. A cell size of 20 and a 95 percent confidence interval are used to determine whether an AMO was met. • Separate graduation rate improvement targets are used for the four- and six-year rates. A school meets the graduation rate AMO for graduation if: • (1) the graduation rate for the most recent year, or for the most recent two years combined, meets the 85 percent goal; or • (2) the improvement in graduation rate meets the applicable target. DPI will first evaluate whether a school met the goal or target for the four-year rate. If it does not, the school will be evaluated using the six-year rate. • In 2011-12 only, the first year of this accountability system, a five-year rate was used in place of the six-year rate because we do not have the data to run a six-year rate until 2012-13. Graduation AMO

37. Graduation AMO Improvement Targets

38. Meeting AMOs

39. Impact of AMOs on Subgroups

40. The AMOs expect an increase of 1% or more in proficiency rates annually. This assures that the top-performing subgroups continue to make progress. The six-year targets of 49.9% proficiency in reading and 65.3% proficiency in mathematics reflect dramatic increases in performance for most subgroups. Dramatic increases in performance will require dramatic effort. Subgroup AMOs

41. Subgroup AMOs

42. Subgroup AMOs

43. AMO Performance • AMO data is found on the last page of each school’s Report Card

44. Question & Answer

45. Team Work Time Analysis of School Data & Development of SLOs