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Decision Making for Results. Decision Making for Results (DMR) DMR is a six-step process that allows you to examine your school or district data at the.

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Presentation on theme: "Decision Making for Results. Decision Making for Results (DMR) DMR is a six-step process that allows you to examine your school or district data at the."— Presentation transcript:

1 Decision Making for Results

2 Decision Making for Results (DMR) DMR is a six-step process that allows you to examine your school or district data at the macro level. After analyzing this data in a collaborative manner, you will be able to make leadership and instructional decisions to guide your continuous school improvement.

3 Principles of Decision Making for Results (DMR) Antecedents Collaboration Accountability Adult Actions (Cause Data) * Instructional Strategies * Administrative Structures * Conditions for Learning * Congruence * Respect for Diversity * Fairness * Specificity * Accuracy * Universality * Feedback for continuous improvement Collaboration has to be built into every step of data management and integrated into every data-driven decision.

4 “Only by evaluating both causes and effects in a comprehensive accountability system can leaders, teachers, and policymakers understand the complexities of student achievement and the efficacy of teaching and leadership practices.” Reeves, 2006

5 Effect data: Outcomes or results Cause data: Professional practices that create specific effects or results Definitions and Examples

6 DMR Six-Step Process Step 1: Conduct a Treasure Hunt Step 2: Analyze Data to Prioritize Needs Step 3: Establish SMART Goals Step 4: Select Specific Strategies Step 5: Determine Results Indicators Step 6: Monitor and Evaluate Results Inquiry: Develop Questions

7 Step 1: Conduct a Treasure Hunt Why? To gather and organize data in order to gain insights about teaching, learning, and leadership practices. Considerations:  Measures of Data  Disaggregation  Triangulation  Reflection

8 Measures of Data can include: Measures of Data Student Performance Data Behavior Data Well-Being Data Demographic Data Perception Data School Process Data

9 Disaggregation To separate something into its component parts, or break apart “Disaggregation is not a problem-solving strategy. It is a problem-finding strategy.” - Victoria Bernhardt, Data Analysis for Comprehensive Schoolwide Improvement 1998

10 Example of Step 1 (The Treasure Hunt): School: Anytown Middle Content Area: Writing Assessment Data: Grade 8 GA Writing Data, Item Analysis, and School/District Assessment Subskill(s):Writing Process Content Areas and School Year Data Represents → Enter Grade Level or Special Subgroups ↓ Content ConventionsContent Content/DevelopmentContent Organization School Year ’11, ‘12, ‘13 ALL1388/118 = 74.5%1382/118 = 69.4%1363/118 = 53.3% 1271/111 = 63.9%1266/111 = 59.4%1251/111 = 45.9% 1174/107 = 69.1%1170/107 = 65.4%1153/107 = 49.5% Caucasian1349/54 = 90.7%1346/54 = 85.1%1335/54 = 64.8% 1242/51 = 82.3%1239/51 = 76.4%1230/51 = 58.8% 1145/52 = 86.5%1142/52 = 80.7%1132/52 = 61.5% African American1325/37 = 67.5%1323/37 = 62.1%1318/37 = 48.6% 1218/35 = 51.4%1217/35 = 48.5%1213/35 = 37.1% 1121/33 = 63.6%1120/33 = 60.6%1115/33 = 45.4% Hispanic1314/27 = 51.8%1313/27 = 48.1%1310/27 = 37% 1211/25 = 44%1210/25 = 40%128/25 = 32% 118/22 = 36.3%118/22 = 36.3%116/22 = 27.2% ELL134/12 = 33.3%134/12 = 33.3%133/12 = 25% 123/11 = 27.2%123/11 = 27.2%122/11 = 18.1% 113/8 = 37.5%113/8 = 37.5%112/8 = 25% Non-ELL1384/106 = 79.2%1378/106 = 73.5%1360/106 = 56.6% 1268/100 = 68%1263/100 = 63%1249/100 = 49% 1171/99 = 71.7%1167/99 = 67.6%1151/99 = 51.5% SPED137/25 = 28%137/25 = 28%135/25 = 20% 127/23 = 30.4%127/23 = 30.4%125/23 = 21.7% 117/22 = 31.8%117/22 = 31.8%115/22 = 22.7% Non-SPED1375/93 = 80.6%1381/93 = 87%1358/93 = 62.3% 1259/88 = 67%1261/88 = 69.3%1246/88 = 52.2% 1163/85 = 74.1%1161/80 = 76.2%1148/85 = 56.4%

11 Triangulation Triangulation is a process that allows you to view achievement results with different lenses and provides a more comprehensive picture of teaching, learning, and leadership. Triangulation can be applied to the data-driven decision-making process by examining the interaction of antecedent data, collaboration data, and accountability data. Each set lends itself to trend tracking and pattern identification. In broad terms, triangulation is a method of extrapolating meaning from raw data – a way to find the critical information, see the big picture, and identify key components (angles). In education, triangulation describes efforts to determine needs or targets from diverse types of data. (Stephen H. White, Beyond the Numbers, 2011, pgs. 103-108).

12 Triangulation Example: GA Grade 8 Writing Assmt. Strong increase in scores ‘12 to ‘13 but significant performance gaps btw. Caucasian, Afr. Am., & Hispanic All students stronger on conventions – 74.5% proficient Organization – all students 53.3% proficient School’s Mock Writing Prompt 90% of students proficient in writing 85% of students proficient in selected Organization Significant performance gaps when compared to PASS results Students’ Writing Portfolios Show frequent drafts with revisions for mechanics, conventions, etc. Show student multiple idea development drafts/feedback Show less evidence of proofreading and editing

13 Step 2: Analyze Data to Prioritize Needs Why? To identify causes for celebration and to identify areas of concern Considerations:  Strengths  Needs  Performance behavior  Inference

14 Example of Step 2 (Analyze Data to Prioritize Needs): Performance Behavior:Rationale Strength(s): Conventions Content Development Obstacle(s): Organization We gave multiple opportunities for students to practice revising their own writing in order to improve conventions, mechanics, etc. We held multiple job-embedded PD sessions on this portion of the Writer’s Workshop. Content/Development – We had PD on developing ideas in student’s planning and drafting samples in portfolios. Organization – Students are able to identify organizing topic and supporting details for their writing but do not transition from that to a well organized paper. PASS results show weak organizational components and students’ writing samples show week transitions.

15 Step 3: Establish SMART Goals Why? To identify your most critical goals for student achievement based on the challenges that were identified throughout the inquiry process. Criteria:  Specific (What exactly will we measure?)  Measurable (How will we measure it?)  Achievable (Is this a reasonable goal?)  Relevant (Are goals aligned with the CIP?)  Timely (Does each goal have a defined timeframe?)

16 Example of Step 3 (Establish SMART Goals): Goal 1 Percentage of ________________________ scoring proficient or higher in _________________ will increase from ____________ to _____________ by the end of the ____________ school year as measured by _________________________ administered in ___________________. Goal 2 Percentage of ________________________ scoring proficient or higher in _________________ will increase from ____________ to _____________ by the end of the ____________ school year as measured by _________________________ administered in ___________________. Grade 8 students Organization 53%68% 2013 - 2014 GA Grade 8 Writing Assmt. Feb 2014

17 Step 4: Select Specific Strategies Why? Adult Actions will impact student achievement Considerations:  Instructional Strategies  Organizational Strategies  Leadership Strategies  Programmatic Strategies Strategies are: Action-oriented Measurable Specific Research-based

18 Example of Step 4 (Select Specific Strategies): Prioritized Needs (2-3 Maximum):Strategies (4 Maximum) Organization Instructional – Engage students in editing and revising for every paper created in the Writer’s Workshop including 2 or 3 times a week mini lessons on transitioning from brainstorm to writing Leadership and Organizational – change the schedule in order to provide a common planning time and schedule Literacy Coach to attend ELA meetings 2 x week Leadership and Instructional – Increase teacher capacity in this component of the Writer’s Workshop through initial PD followed by coaching and feedback provided by building Literacy Coach and District PLS – min 2 x week

19 Step 5: Determine Results Indicators Why? To monitor the degree of implementation and evaluate the effectiveness of the strategies. Considerations:  Serve as an interim measurement  Used to determine effective implementation of a strategy  Used to determine if strategy is having the desired impact  Used to help determine midcourse corrections

20 Example of Step 5 (Determine Results Indicators): Prioritized Needs (2-3 Maximum):Strategies (4 Maximum) Strategy Leadership and Organizational – change the schedule in order to provide a common planning time and schedule Literacy Coach to attend ELA meetings 2 x week Implementation: Master calendar reflects common planning time; Literacy Coach’s calendar shows preserved time for 2 x week ELA meetings; minutes of meetings show evidence of collaboration on writing Effectiveness: Classroom observations show evidence of strategies discussed in collaboration actually in use; Portfolio samples show evidence of collaboratively planned strategy use

21 Step 6: Monitor and Evaluate Results Why? To engage in a continuous improvement cycle that: Identifies midcourse corrections where needed Adjusts strategies to ensure fidelity of implementation

22 Example of Step 6 (Monitor and Evaluate Results): Monitoring Plan Template Cluster or SchoolTeamDateDates of Next Monitoring Cycle GoalTargeted Strategies Has This Strategy Been Implemented? Not Implemented Partially Implemented Implemented Fully Reasons Implementation Was Incomplete or Did Not Occur? Has This Activity Had Impact? Yes No Reasons Expected Impact Did or Did Not Occur: Evidence of Actual Impact on Instructional Practice and/or Student Learning:Suggested Adjustments or Recommendations: Reflections:Other Relevant Information:

23 Additional Support: Data Teams Refresher Courses will be offered during the 2013-14 SY. Check MyPLC for updates and to register. Always Feel free to Contact your Regional Data Analysts in the department of Research & Evaluation for School Improvement: East Region – Stacey L. Johnson (johnsonsl@atlanta.k12.ga.us)johnsonsl@atlanta.k12.ga.us West Region – Curtis L. Grier (clgrier@atlanta.k12.ga.us)clgrier@atlanta.k12.ga.us South Region – Adrienne T. Johnson (adtjohnson@atlanta.k12.ga.us)adtjohnson@atlanta.k12.ga.us North Region – Holly Hayes-Morrisey (hmorrisey@atlanta.k12.ga.us)hmorrisey@atlanta.k12.ga.us CLL – Adam Churney (achurney@atlanta.k12.ga.us)achurney@atlanta.k12.ga.us


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