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Using Data to Create Productive Disequilibrium

Using Data to Create Productive Disequilibrium. What Are the Consequences When Students Do Not Learn ?. What Are the Consequences When Students Do Not Learn?. School Improvement Plans? Funds? Staff Evaluation? Scholastic Audit? Change Agents/Highly Skilled Educator (HSE)?. Objective.

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Using Data to Create Productive Disequilibrium

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  1. Using Data to Create Productive Disequilibrium

  2. What Are the Consequences When Students Do Not Learn ?

  3. What Are the Consequences When Students Do Not Learn? • School Improvement Plans? • Funds? • Staff Evaluation? • Scholastic Audit? • Change Agents/Highly Skilled Educator (HSE)?

  4. Objective To provide a staff development model that Change Agents can use to analyze the state’s student performance report scores in a timely, effective, and meaningful way so that student learning will improve.

  5. Data Because organizationsonly improve… “where the truth is told and the brutal facts confronted” Jim Collins

  6. Student Performance Report Workbook 8/29/08 OAA 6

  7. Instructional Questions How far from 100 (absolute goal for an Academic Index) is each content area index? Reading- Mathematics- Science- Social Studies- Writing - Total Academic Index- Which content areas showed improvement from 2007 to 2008? Compare each content area to the absolute goal of 100. How close is the academic index to 100? Did any content areas decline between 2007 and 2008? HS ONLY: How did students perform on the PLAN and ACT? This page lists the numbers used to generate the accountability index. Two years of data for comparison High schools only Nonadjusted Accountability Index 8/29/08 OAA 7

  8. Instructional Questions For each group listed indicate how far the group is from the target of 100. Female- Male- White- African American- Hispanic- Asian- Free/Reduced lunch- LEP- Students with disability- Place an asterisk beside the group that is farthest from the goal. Rank order the remaining groups from farthest to closest to the goal. Which groups showed improvement from 2007 to 2008? Are there groups that did not improve? Shows academic index for each group Two years of data for comparison 8/29/08 OAA 8

  9. Overview Form analysis teams using the school staff. The teams will be assigned to one or two specific areas to explore. After the analysis, teams are to report to the large group and discuss future action.

  10. Who’s Involved • It’s suggested that as many staff as possible be involved. In large schools, it may mean you have several teams addressing one area, but that’s okay since the more people involved the more insight can be gained.

  11. The Materials • State Student Performance Report • Analyzing Student Performance Data: A Staff Workshop Model • School Findings Form • Chart Paper • Markers • Colored Dots

  12. The Steps Form analysis teams around the report headings…usually by content areas. • Reading Data • Math Data • Science Data • Other

  13. Step 2 Provide each team with individual sets of the school report, the Analyzing Student Performance Data: A Staff Workshop Model document, and the School Findings Form. For best results have these reports on the designated tables before arrival of the staff.

  14. Step 3 Review the purpose and goals for the session.

  15. Step 4 • Review the documents, • The steps, and • Findings Form • Ground Rules

  16. Step 5 • Communicate team assignments and team task; • Randomly divide the staff; • Direct each team to analyze the data answering the questions listed in the Analyzing Student Performance Data: A Staff Development Model. • Ask each team to complete the School Findings Form.

  17. Probing Questions • Accountability • Instruction • Gaps • Curriculum • Trends • District • Discussion

  18. District Instructional Questions Compare to district report…where are the significant differences for the school? Describe any significant differences found in the school’s subgroups that are not found at district or state levels. Are there any subgroups at the school level where no significant differences exist? Explain. How does this type of disaggregation impact instructional choices and decisions? What might be the next steps toward closing the gaps? Scale scores broken out by group. Data from school, district and state shown. Difference in performance of groups reported. Index Score for each sub-population is reported. Standard Error in ( ) for each scale score mean. 8/29/08 OAA 18 Asterisk denotes significant difference.

  19. Step 6 Allow 30-60 minutes for analysis and completion of form.

  20. Step 7 • Ask each team to report their findings and suggestions for priorities to the group. Have another facilitator record findings and priorities on chart paper as each group shares out. • Post completed charts around the room.

  21. Step 7 Continued • Facilitate agreement by asking participants to go to the charts and place dots on the top three priorities they believe will best improve student learning in the coming school year.

  22. Step 8 Collect the School Findings Forms for further use and analysis by the Instructional Leadership Team and Instructional Teams.

  23. Total Time Needed • Introduction/Purpose 10 minutes • Review Materials/Ground rules 10 minutes • Make team assignments 10 minutes and delegate task • Team analysis 30-60 minutes • Group reports 15-20 minutes • Future Steps 10 minutes • Total Time Approx 60-120 minutes

  24. Results This method provides wide dissemination of student achievement data while actively engaging staff members. More ownership and insights into the scores occur. Additionally, this method offers a safe way to initiate candid and structured conversations about the issues raised in the data review.

  25. Staff can directly analyze strengths, weaknesses, low performance, achievement gaps, grade level discrepancies, and immediately start to envision next steps and meaningful actions to improve.

  26. Group Reflection Using the School Findings Form information, what implications for change agents could be discussed from this analysis process?

  27. What Else? Triangulating Data Sources… • State Results • Web-based Walkthroughs • Classroom Assessments

  28. Which Standards Best Distinguish between Successful and Struggling Schools?

  29. Data Collection: Standardized Walkthrough Template • 3 curriculum elements • 4 assessment elements • 7 instruction elements • Student engagement

  30. The Data

  31. The Data

  32. The Data

  33. Questions?

  34. Data • About 7% of low-income students will ever earn a college degree Haycock

  35. Data • Five years of effective teaching can completely close the gap between low-income students and others. Marzano; Kain & Hanushek

  36. Data • “Most of us in education are mediocre at what we do” Tony Wagner Harvard Graduate School of Education

  37. THE LEADERSHIP ILLUSION “Direct involvement in instruction is among the least frequent activities performed by administrators of any kind at any level.” Richard Elmore 2000 This is not a matter of work ethic; it is a matter of misplaced priorities.

  38. Professional Learning Communities…astonishing impact! “The most promising strategy for sustained, substantive school improvement is building the capacity of school personnel to function as a professional learning community.” Milbrey McLaughlin (cited in Professional Learning Communities at Work by Dufour and Eaker)

  39. PLANNING PROCESS? Typical Strategic or improvement planning models are: • superficial • time-consuming/overwhelming • counterproductive, distracting • contain actions that we wrongly believe will have an impact on instruction

  40. SMART GOALS • Strategic and Specific • Measurable • Attainable • Results-Oriented • Time-bound

  41. SMART GOALS SET measurable goals for: Reading, Math, Science that are tied to an ASSESSMENT GOAL: Our team will improve in Math from: 47% (2009) to: 52% (2010)

  42. DATA DRIVEN PRIORITIES 1. IDENTIFY lowest scoring standards from ASSESSMENTS • Reading: developing understanding; interpretation of text • MATH: measurement; statistics/probability 2. Use formative assessment data…measurable results from lessons, units, etc., to determine progress and individual student needs

  43. Data Smart To use student assessment wisely, staffs need skills and abilities to: • Understand data correctly • Use software to collect and display data • Participate productively in group discussions and decisions • Create effective action plans Data Wise: Fellows of Harvard College

  44. It’s About Inquiry • Organize into work teams; • Develop assessment literacy; • Delve into the data; • Inquire about instruction, curriculum, gaps, district interventions, etc.; • Craft short/simple effective action steps; • Monitor impact on student learning…doing what we said we’d do; and • Adjust…model the work.

  45. Take Away Points for Change Agents FIRST: Guide the use of data to adopt “SIMPLE PLANS” for turnaround; SECOND: Direct development of Instructional Leadership Teams to create and sustain focused professional learning communities; THIRD: Lead sustained and substantial improvements in the instructional core through implementation of student progress monitoring to promote appropriate and effective instruction.

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