using data to inform instruction dr. grant a. chandler director of professional learning office of...

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Using Data to Inform Instruction

Dr. Grant A. ChandlerDirector of Professional Learning

Office of K-12 Outreach, College of EducationMichigan State University

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Data Conversationsusing the

Collaborative Learning Cycle

Dr. Grant A. ChandlerDirector of Professional Learning

Office of K-12 Outreach, College of EducationMichigan State University

Office of K-12 Outreach, Michigan State University

Powerful data conversations can lead to powerful changes in instruction and dramatic improvement in student achievement.  This session will engage administrators in how to create and sustain high performing groups of educators who can skillfully implement Wellman and Lipton’s Collaborative Learning Cycle. This simple yet powerful protocol will equip teachers and administrators alike with the tools to effectively and efficiently use multiple measures of data to solve instructional and systemic problems to increase student learning.

Session Description

Office of K-12 Outreach, Michigan State University

Finding Common Ground

Task Groups:

Find at least 3 things that your entire group has in common --

that would NOT be obvious to others

(and that might surprise us)

Groups at Work – Copyright MiraVia LLC – All rights reserved

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Characteristics of High Performing Groups

Wellman and Lipton

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Seven Qualities of High Performing Groups

Maintain a clear focus

Embrace a spirit of inquiry

Put data at the center

Honor commitments to learners and learning

Cultivate relational trust

Seek equity

Assume collective responsibility

Office of K-12 Outreach, Michigan State University

Maintain a Clear Focus

HPGs clarify desired results and define success criteria.

HPGs agree on and protect priorities for themselves and their students, preserving precious time for focused engagement about the things that matter.

Office of K-12 Outreach, Michigan State University

Establish a Spirit of Inquiry

HPGs are both problem seekers and problem solvers. These groups seek external resources and data outside their own experience.

They inquire into data to explore who is learning and who is not, seeking patterns and root causes before pursuing solutions and planning actions.

Office of K-12 Outreach, Michigan State University

Put Data at the Center

HPGs use data to inform and guide group and student learning.

HPGs are assessment literate. They keep data central to the conversation, seeking out and using multiple sources and multiple types to inform their choices and plans.

Office of K-12 Outreach, Michigan State University

Honor Commitments to Learners and Learning

HPGs keep learning at the focus of their conversations.

HPGs keep their focus on what is good for students, not just convenient for themselves. They explore the process, performance, and products of learning.

They assess and monitor their own learning, reflecting on their processes and products and set goals for continuous improvement.

Office of K-12 Outreach, Michigan State University

Cultivate Relational Trust

HPGs operate with high expectations and positive intentions as central assumptions. It is safe to display both high competence and vulnerability.

HPGs rely on the integrity and competence of their colleagues inside and outside of the meeting room.

They hold high expectations for themselves and each other and have faith that those expectations will be met and even exceeded.

Office of K-12 Outreach, Michigan State University

Assume Collective Responsibility

HPGs make and honor agreements about who they want to be as a group/team and what they want to produce for their students.

They make data driven choices and are willing to be answerable for these choices.

This collective efficacy, or the shared belief that together the group will successfully achieve its goals, is a prime resource for sustained improvements in student learning (Goddard, Hoy, & Woolfolk Hoy, 2004).

Office of K-12 Outreach, Michigan State University

High Performing Groups

Recognize that their individual choices, both in the meeting room and in their own classrooms, affect everyone.

They willingly invest their time and energy, setting aside personal agendas to support the group’s work and its development.

Office of K-12 Outreach, Michigan State University

Peter Senge (1990)

Learning communities are groups of individuals who come together with a shared purpose and agreement to construct new understandings. A learning community is a critical contributor to becoming a learning organization – a place where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collection aspiration is set free and where people are continually learning how to learn together.

Office of K-12 Outreach, Michigan State University

What Matters . . .

Two different meta-analyses of research on the factors that impact student achievement found that the quality of instruction students receive in their classrooms is the most important variable in student achievement.

Office of K-12 Outreach, Michigan State University

Assumptions for Our Work

Schools can only be as good as the people within them.

If one of the most important variables in student achievement is instruction, schools must ensure high quality instruction in every classroom.

If substantive school improvement requires a coordinated, systemic, and collective effort (rather than isolated individual efforts), schools must use professional development strategies that are specifically designed to improve the collective capacity of educators to meet the needs of students.

Office of K-12 Outreach, Michigan State University

Assumptions . . .

The best strategy for improving schools and districts is developing the collective capacity of educators to function as members of professional learning communities – a concept based on the premise that if students are to learn at higher levels, processes must be in place to ensure the ongoing-job embedded learning of the adults who serve them.

(DuFour & Marzano, 2012)

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Collaborative Learning Cycle

Based on the book, Got Data? Now What?Bruce Wellman & Laura Lipton, 2012

Office of K-12 Outreach, Michigan State University

Analyzing data is like or not like . . . (choose one)

because . . .

Office of K-12 Outreach, Michigan State University

Collaborative Learning Cycle

Activate and Engage Generate predictions & surface assumptions

Explore and Discover Analyze data & develop narrative statements

Organizing and Integrating Generating causal theory and exploring solutions

Office of K-12 Outreach, Michigan State University

Activating and Engaging

Discuss what the data might look like.

Make predictions and assumptions.

Provides psychological and emotional safety and readiness for interacting with colleagues and with data.

Process: develop predictions and assumptions concurrently, record them, use facsimile of the data display, accept different predictions or assumptions.

Office of K-12 Outreach, Michigan State University

Exploring and discovering: analyzing the data

Embrace the spirit of exploration and discovery.

Avoid explaining why the data look as they do.

Create a shared focus, provide time to orient to the data, develop a sequence and process for exploration, and apply protocols to balance participation, establish public record keeping, use concise language, depersonalize the data.

Office of K-12 Outreach, Michigan State University

Organizing and integrating: generating theory

Establishes the transition to formal problem finding and problem solving in two phases: causation and action.

Causation (curriculum, instruction, teachers, students, infrastructure)

Effective plans are SMART plans

Generate multiple theories of causation, allow multiple theories, seek triangulation of data, generate multiple theories of solution, utilize SMART plans, use decision-making process.

Office of K-12 Outreach, Michigan State University

What’s the Big Picture:

Utilize the collaborative learning cycle to carefully examine data: Student performance data. Demographic data Perception data Process data

Establish causal theories aligned to student data.

Establish narrative statements/causal theories in order to establish meaningful plans that will successfully impact student achievement and be the driving force behind our every day work.

Create building level school improvement plans that align with the district improvement plan but recognize the individual student needs of each building within the district.

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Writing

Exploring student achievement in

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Activate and EngagePhase I

Office of K-12 Outreach, Michigan State University

Building-Level Writing Grade 4by Proficiency Levels

Proficiency Level 2013 2012

Blue (Advanced)

Green (Proficient)

Yellow (Partially Proficient)

Red (Not Proficient)

Office of K-12 Outreach, Michigan State University

Building Writing – Grade 14by Proficiency Levels – 2013

Proficiency Level

Econ. Advan.

Econ. Disadv.

Regular Ed

Special Ed

Boys Girls

Blue (Advanced)

Green (Proficient)

Yellow (Partially Proficient)

Red (Not Proficient)

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Predict

What do your top and bottom 30% look like in terms of proficiency levels in 2013? How do they compare to 2012? % Blue % Green % Yellow % Red

Office of K-12 Outreach, Michigan State University

Predictions and Assumptions

Purpose is to surface and understand assumptions (not about right/wrong) Prediction: something you expect to see in the data Assumption: something that you think but that will not show

up in data

Predictions Assumptions

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Pair, share, discuss

Share your predictions with one person

Discuss – why? (your thoughts)

Form groups of 4 (or more)

Put your predictions on chart paper, discuss

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Activating and Engaging

What are some of our predictions and assumptions about student achievement in WRITING at Pleasantville Elementary School?

What questions are we bringing to this discussion? What are some possibilities for learning that this

experience presents to us?

Office of K-12 Outreach, Michigan State University

Activating and Engaging – FACILITATORS’ DEBRIEF

Discuss what the data might look like.

Make predictions and assumptions.

Provides psychological and emotional safety and readiness for interacting with colleagues and with data.

Process: develop predictions and assumptions concurrently, record them, use facsimile of the data display, accept different predictions or assumptions.

Office of K-12 Outreach, Michigan State University

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Explore and Discover Phase II

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Explore and Discover

What important points pop out to us? What patterns, categories, or trends are emerging? What is surprising or unexpected?

Office of K-12 Outreach, Michigan State University

Analyzing Data - Process

1. Individuals look at data silently.

2. Individually document observations.

3. Report out in groups (Round Robin). Chart observations.

Office of K-12 Outreach, Michigan State University

Analyzing Data - Process

1. Individuals look at data silently. (2-3 min)

2. Individually document observations. (3-4 min)

3. Report out in groups (Round Robin). Chart observations. (10 min)

4. Refine observations by increasing specificity. (8 min)

Office of K-12 Outreach, Michigan State University

Narrative Statements

The girls did better than the boys.

In 2012 on the MEAP assessment in reading, the girls were 74% proficient and the boys were 53% proficient.

Chart five (5) narrative statements.

Office of K-12 Outreach, Michigan State University

Writing Grade 4by Proficiency Levels

Proficiency Level 2013 2012

Blue (Advanced) 8 3Green (Proficient) 54 62

Yellow (Partially Proficient)

35 30Red (Not Proficient) 3 5

Office of K-12 Outreach, Michigan State University

Writing – Grade 4by Proficiency Levels – 2013

Proficiency Level

Econ. Advan.

Econ. Disadv.

*Regular Ed

*Special Ed

Boys Girls

Blue (Advanced)

8 0 8 0 6 9

Green (Proficient)

58 46 55 20 53 55

Yellow (Partially Proficient)

32 43 34 20 37 33

Red (Not Proficient)

2 11 3 60 4 3

Office of K-12 Outreach, Michigan State University

Exploring and Discovering – FACILITATORS’ DEBRIEF

Embrace the spirit of exploration and discovery.

Avoid explaining why the data look as they do.

Create a shared focus, provide time to orient to the data, develop a sequence and process for exploration, and apply protocols to balance participation, establish public record keeping, use concise language, depersonalize the data.

Office of K-12 Outreach, Michigan State University

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ORGANIZING AND INTEGRATING

Phase III

Office of K-12 Outreach, Michigan State University

Organizing and Integrating

Establishes the transition to formal problem finding and problem solving in two phases: causation and action. Generate multiple theories of causation, allow multiple

theories, seek triangulation of data. Generate multiple theories of solution (SMART plans) Use decision-making process to choose the strongest

solution.

Office of K-12 Outreach, Michigan State University

Causal Theories

Office of K-12 Outreach, Michigan State University

Causal Theories

Leadership Systemic planning and implementation, knowledge, skills,

disposition

Infrastructure Schedules, programming, and resources

Curriculum Design and implementation

Instruction Methods, materials, and resources

Teachers Knowledge, skills, and disposition

Students Knowledge, skills, and disposition

Office of K-12 Outreach, Michigan State University

Causal Theory

As a group select TWO observations to explore further

Individually generate multiple causation theories (why?) Stay focused on things that we can control Generate theories from MORE than one category Identify additional data needed

Share theories, narrow to one or two, and identify additional data needs

Repeat for other observation

Prepare to share

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Example

Observation

The gap from 11-12 for ED students compared to Non-ED students was nearly 24%. This gap was closed to nearly 1% in 12-13.

Causal Theories

Our PD has increased our teacher’s ability to reach poorer students (Teachers)

The number of ED student’s drastically increased from 11-12 to 12-13 (Students)

Office of K-12 Outreach, Michigan State University

Prepare to Share

Create TWO posters, one for each observation Include on the poster:

The observation At least two theories from different causal categories Additional data needs/questions

Review other posters Observations

• Similarities• Differences• Surprises

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Potential Solutions

In groups, identify 3-5 possible solutions

Can be very specific (professional development program) or general (align curriculum)

Create chart labeled “Potential Solutions” Review other posters

Observations• Similarities• Differences• Surprises

Office of K-12 Outreach, Michigan State University

Organizing and Integrating– FACILITATORS’ DEBRIEF

Establishes the transition to formal problem finding and problem solving in two phases: causation and action.

Causation (curriculum, instruction, teachers, students, infrastructure)

Effective plans are SMART plans

Generate multiple theories of causation, allow multiple theories, seek triangulation of data, generate multiple theories of solution, utilize SMART plans, use decision-making process.

Office of K-12 Outreach, Michigan State University

Process Debrief

How did it feel using a structured process to have a conversation?

How might this structured conversation assist you in doing your work with your team?

What additional support do you need in order to facilitate this protocol with your team?

Office of K-12 Outreach, Michigan State University

References

DuFour, R. & Marzano, R. (2012). Leaders of learning: How districts, school, and classroom leaders improve student achievement. Bloomington, IN: Solution Tree Press.

Lipton, L., & Wellman, B. (2012). Got data? Now what? Bloomington, IN: Solution Tree Press.

Office of K-12 Outreach, Michigan State University

Additional Information

www.mitoolkit.org

Office of K-12 Outreach, Michigan State University

Dr. Grant A. Chandler

Director of Professional Learning

Office of K-12 Outreach

Michigan State University

chand107@msu.edu