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Decision Making for Results

Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

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Page 1: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Decision Making for Results

Page 2: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Part One: Objectives

• Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

• Increase awareness of the relevance of data and its impact on leadership, teaching, and learning

• Reinforce the importance of collecting both cause and effect data

Page 3: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Objectives

• Apply the Decision Making for Results: Data-Driven Decision Making process to monitor leadership, teaching, and learning

• Implement the Decision Making for Results: Data-Driven Decision Making process to monitor school improvement

Page 4: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Principles ofDecision Making For Results

Antecedents

CollaborationAccountability

Page 5: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Seminar Overview

• Introduction• Building the foundation• Process and application• Action planning

Page 6: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Becoming Data Driven

How are you currently embracing a data-driven decision making process that leads to results?

Page 7: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Results-Driven Schools• Where is the proof?

• 90/90/90 Schools, Reeves 2003• Education Trust, 2002• NCREL, 2000• Consortium for Policy Research in

Education, 2000• EdSource, 2005• Northern Illinois University Center

for Governmental Studies, 2004

Page 8: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Reflection

“The value of the data emerges only when analysis provides insights that direct decisions for students.”

S. White, 2005

Page 9: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Part TwoBuilding the Foundation

• Cause data and effect data• Continuous improvement cycle• Principles and processes of

Decision Making for Results: Data-Driven Decision Making

Page 10: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

“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

Page 11: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Definitions and Examples

Effect data: Outcomes or results

Cause data: Professional practices that create specific effects or results

Page 12: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

The Leadership & Learning Matrix

Effects/Results (stud.out.)

LuckyHigh results, low understanding of antecedentsReplication of success unlikely

LeadingHigh results, high understanding of antecedentsReplication of success likely

Losing GroundLow results, low understanding of antecedentsReplication of failure likely

LearningLow results, high understanding of antecedentsReplication of mistakes unlikely

Antecedents/Cause Data (Adult Actions)

Page 13: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

PIM

Monitoring

Frequency Evaluation

ImplementationStrategies Professional

DevelopmentParental

Involvement

PlanningNeeds Assessment Inquiry Goals

Page 14: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Part Three:Process and Application

Page 15: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Ocean View Elementary School A Look at Collaboration

Page 16: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

The Process for Results

Analyze toPrioritize

Monitor & Evaluate Results

Treasure Hunt

SMART Goals

Specific Strategies

Results Indicators

Inquiry;Develop Questions

Page 17: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Inquiry

“Data-driven decision making begins by asking fundamental questions.”

Doug Reeves

• What questions do you have about teaching and learning in your school?

• What data sources are you using to gather the specific information?

Page 18: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Step 1: Conduct a Treasure Hunt

• Why? To gather and organize data in order to gain insights about teaching and learning practices

• Considerations• Measures of data• Disaggregation • Triangulation • Reflection

Page 19: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Measures of Data

• Student learning • Demographics• Perceptions• School processes – Behaviors within

our control: instructional and leadership strategies, programs and resources, and organization

Page 20: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

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, 1998

Think, pair, share:

What data do you disaggregate, and how do you use the information?

Page 21: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

TriangulationA Look at Learning

DRA

BenchmarkRunning Records

Page 22: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Case Study

• Read case study

• Part 1: How did they categorize the different data sets and record their observations?

• Part 2: What did they discover?

Page 23: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Conduct a Treasure Hunt Application

1. Review inquiry questions

2. Conduct a “Treasure Hunt”

3. Organize data on templates

4. Use rubric to monitor and evaluate your work

Page 24: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Can You Identify with This?

“It is not so much a lack of data, but an absence of analysis, and an even greater absence of actions driven by the data.”

White, 2005

Page 25: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Step 2Analyze Data to Prioritize Needs

Data Analysis at Northside Middle School

Page 26: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process
Page 27: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Analyze Data to Prioritize Needs

• Why? To identify causes for celebration and to identify areas of concern

• Considerations

• Strengths• Needs• Behavior• Rationale 0

1

2

3

4

5

6

Page 28: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Quality Prioritization

• Why? To take immediate action on the most urgent needs

• Quality prioritization requires a thorough understanding of:• Student population• Curriculum and Power/Priority Standards

(leverage, readiness)• Antecedents affecting student achievement• Quality of program implementation

White, 2005

Page 29: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Case Study

• Review case study • What insights did you gain after

reading analysis of student performance?

• Make a recommendation: What is the most urgent need?

Page 30: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Review, Analyze, and Prioritize Application

1. Review data from Step 1

2. Conduct analysis using the guiding questions

3. Prioritize urgent needs using the suggested criteria

4. Record your work on the templates

5. Use rubric to monitor and evaluate your work

Page 31: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Step 3Establish SMART Goals

• Why? To identify our most critical goals for student achievement based on the challenges that were identified through the inquiry process

• Specific, Measurable, Achievable, Relevant, Timely

Page 32: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Establish Your SMART Goals Application

• Review prioritized needs • Review Treasure Hunt baseline data• Apply SMART goal formula, use

templates• Use rubric to monitor and evaluate

your work

Page 33: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Goals – Application

1. Review prioritized needs

2. Review Treasure Hunt baseline data

3. Apply SMART goal formula; use templates to record your work

4. Use rubric to monitor and evaluate your work

Page 34: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Share Your Findings with Colleagues

• Meet in the middle of the room

• Be prepared to share your findings from Steps 1-3

• Highlight one celebration from a colleague

Page 35: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Step 4Select Specific Strategies

Let’s watch Lake Taylor High School as they discuss strategies.

Page 36: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process
Page 37: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Select Specific Strategies

• Why?

• Adult actions will impact student achievement

• Strategies are –

• Action-oriented• Measurable/accountable• Specific• Research-based

• Considerations: Instructional, organizational, leadership, programmatic

Page 38: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Research-Based Strategies

• Reeves, D.B. (2003). 90/90/90 schools. Retrieved from www.LeadandLearn.com

• Reeves, D.B. (2006). Ten things high schools can do right now to improve student achievement.

• Learning 24/7 Observation Study (2005). What’s happening in schools? Or not?

Page 39: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Additional Evidence in Support of Research-Based Strategies

• Zemelman, S., Daniels, H., & Hyde, A. (2005). Best practice. Portsmouth, NH: Heinemann.

• Marzano, R. (2007). The art & science of teaching. Alexandria, VA: ASCD.

• Barr, R., & Parrett, W.H. (2007). The kids left behind. Bloomington, IN: Solution Tree.

• Marzano, R., Waters, T., & McNulty, B. (2005). School leadership that works. Alexandria, VA: ASCD.

Page 40: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Let’s Do It!

Guided Practice

Page 41: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Case Study

• Revisit case study analysis

• What types of strategies (instructional, organizational, leadership, programmatic) did they select?

• How will the strategies help students overcome the obstacles?

Page 42: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Select Your Specific Strategies

1. Revisit your prioritized needs

2. Research the best possible strategies to meet the learner needs

3. Group by type of strategy: Instructional, organizational, programmatic, and leadership

4. Use rubric to monitor and evaluate your work

Page 43: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Step 5Determine Results Indicators

Why? To monitor the degree of implementation and evaluate the effectiveness of the strategies

Page 44: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Results Indicators

• Considerations

• Serve as an interim measurement

• Used to determine effective implementation of a strategy

• Used to determine if strategy is having the desired impact

• Help to determine midcourse corrections

Page 45: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Case Study

• Review case study

• How will their results indicators serve as an interim measurement?

• How clearly will the results indicators help to monitor implementation and impact?

Page 46: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Results Indicator Application

1. Revisit strategies (Step 4)

2. Develop results indicators

3. Use rubric to monitor and evaluate your work

Page 47: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

“Improvement cycles require leadership follow-up and relentless efforts to maintain the focus on data if decisions are truly going to be driven by informed data.”

White, 2005

Page 48: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Step 6Monitor and Evaluate Results

Why? To engage in a continuous improvement cycle that –

• Identifies midcourse corrections where needed

• Adjusts strategies to assure fidelity of implementation

Page 49: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Case Study

• Review the case study

• How did they monitor strategies?

• Was there any evidence of midcourse corrections?

Page 50: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Develop Your Monitoring Plan• Review your work from developing questions to

determining results indicators then determine how you will monitor the strategies. When you create your monitoring plan consider:

• Teacher or administrator teams• Monitoring cycles• Goals• Strategies• Impact on student and adult behavior• Ability to make midcourse corrections

Page 51: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Educators Matter

“Many people live their lives aspiring to make a difference and lead a life that matters. There need be no such uncertainty in the life of an educator or school leader. Every decision we make, from daily interactions with students to the most consequential policies at every level of government, will influence leadership and learning…

Page 52: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

… After all these words, statistical analyses, and graphs,…

What we do matters.”Reeves, 2006

Page 53: Decision Making for Results. Part One: Objectives Develop a deeper understanding of the Decision Making for Results: Data-Driven Decision Making process

Questions and Discussion

Your ideas and reflections are important to us. Please take time to complete the short evaluation form that we reviewed at the

beginning of this seminar.

The Leadership and Learning Center866.399.6019

LeadandLearn.com