September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data...

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September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data Analysis Framework

Transcript of September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data...

Page 1: September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data Analysis Framework.

September 12, 2014Lora M. McCalister-Cruel

BDS District Data Coach

Bay District SchoolsData Analysis Framework

Page 2: September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data Analysis Framework.

OBJECTIVESOBJECTIVES

• Discover a Framework for Data Use• Apply Data Literacy• Facilitate Data-Driven Dialogue• Apply Principles of Effective Data Use

“Continual analysis of the gaps between goals for student learning and student performance defines the actions of effective

schools.”- Leading Data by Ellen Goldring and Mark Berends

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AGENDAAGENDA

• Connecting Data to Results• The Data Pyramid• Data-Driven Dialogue Simulation

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ASSUMPTIONASSUMPTION

Collaborative inquiry- teacher teams constructing meaning of student learning problems and testing out solutions together through rigorous use of data and reflective dialogue- unleashes the resourcefulness of educators to continuously improve student learning.

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Leadership & Capacity: The Data Leadership & Capacity: The Data

Coach RoleCoach Role

Use Data

Literacy

Facilitate

Lead for Sustainabilit

y

• Are specially trained teachers, administrators, staff developers, or instructional coaches (school, district, or agency-based)

• Guide Data Teams (PLCs, Grade Levels, Depts.) through collaborative inquiry

• Influence the culture of schools to be one in which data are used continuously, collaboratively, and effectively to improve teaching and learning.

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Core Competencies for High-Capacity Core Competencies for High-Capacity

Data UseData Use

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Structure Collaboration: The Using Data Structure Collaboration: The Using Data

ProcessProcess

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What We’re “Used to”What We’re “Used to”

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Data Data PyramidPyramid

Annually

2-4 times a year

Quarterly or end of the unit

1-4 times a month

Daily-Weekly

TIME FRAME

Data about people,

practices & perceptions

Benchmark Common

Assessments

Formative Common

Assessments

Formative Classroom Assessment

s

Summative District &

State Assessment

s

DATA SOURCES

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Annually

2-4 times a year

Quarterly or end of the unit

1-4 times a month

Daily-Weekly

Data Data PyramidPyramid

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Reflection: Data PyramidReflection: Data Pyramid

• What Does Your Data Pyramid Look Like (school-wide, grade level, depts., etc)?

• Reflect on your school or district’s allocation of time for teachers to analyze each of these sources.

• What would you like to spend more time on and less time on this year?

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A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

Data-Driven Dialogue: Data-Driven Dialogue: DetailDetail

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STEMS

•I assume_____ because ____.

•My expectations are ____ due to ____.

•I predict ____.

•I wonder if ____ .

•Some possibilities for learning that this data may present_____.

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A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

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Just the facts! If you catch yourself using the

following words, then stop.

Because…

Therefore…

It seems… However…

STEMS•I observe ___

•Some patterns/trends that I notice…

•I can count ____ of____...

•I’m surprised to see…

•I don’t see ____.

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STEMS • It seems …

• I believe …

•Based on ___, I think...

• I want to know more about...

•We may need to focus on…

•The student learning problem is…Why ____.***

Curriculum

EquityTeacher

PreparationCritical

Supports

Instruction Assessment

ROOT CAUSES

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DATA-DRIVEN DIALOGUE: DATA-DRIVEN DIALOGUE: AGGREGATE DATAAGGREGATE DATA

Explain the data source

the team will be

analyzing

Generate Solution

s

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• 2014 FCAT 2.0 Math Comparison- % Ach Level 3 and Above – 3rd GRADE

• 2014 FCAT 2.0 Math Reporting Categories – 3rd Grade

Page 20: September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data Analysis Framework.

Just the facts! If you catch yourself using the

following words, then stop.

Because…

Therefore…

It seems… However…

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2014 FCAT 2.0 Math Comparison- % Ach Level 3 and Above

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2014 FCAT 2.0 Math - Reporting Categories -Grade 3

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STEMS • It seems …

• I believe …

•Based on ___, I think...

• I want to know more about...

•We may need to focus on…

•The student learning

problem is…Why ____.***

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Reporting Category 2 Number: Fractions

MA.3.A.2.1Representing fractions; Representing

mixed Numbers3

MA.3.A.2.3Comparing fractions; Ordering

fractions; Ordering mixed numbers4

MA.3.A.2.4 Equivalent Fractions 3

Reporting Category Point Total 10

2014 FCAT 2.0 MathematicsNext Generation Sunshine State Standards

(NGSSS)Grade 3

CONTENT FOCUS REPORT

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DATA-DRIVEN DIALOGUE: Student DATA-DRIVEN DIALOGUE: Student Work Work

TASK DECONSTRUCTION

Generate Solution

s Reteaching/ Enrichment

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Student Work InquiryStudent Work Inquiry• What evidence are we seeing of

student mastery of knowledge and skills required by the task?

• What errors are students making?

• What knowledge and skills seem to be missing?

• What additional insights into student thinking are we gaining?

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Why Did So Many Students Miss Why Did So Many Students Miss

This?This?34. A comet passed by Earth in the year 1835. It passes by Earth every 60 years. Based on this information, in which of the following years can the comet be expected to pass by Earth?

A.2035 – 21%B.2060 – 16%C.2075 – 44%D.2080 – 12%

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Task Deconstruction ProcedureTask Deconstruction Procedure

• Step 1: Do the task and share solutions or strategies

• Step 2: Brainstorm: What do students need to know and be able to do to be successful at this task? Write each piece of knowledge and each skill on a large post-it, one item per post it• Focus on the 3 to 6 key ideas/skills in the

content area being assessed (relevant to re-teaching & enrichment)

• Consider relevant standards and rubrics associated with the task

• Draw on your own experience doing the task

• Step 3: Refine what you have generated to make sure they meet the above criteria

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Step 1 in Task Deconstruction: Do with a Step 1 in Task Deconstruction: Do with a Partner and Share solutions in GroupPartner and Share solutions in Group

34. A comet passed by Earth in the year 1835. It passes by Earth every 60 years. Based on this information, in which of the following years can the comet be expected to pass by Earth?

A.2035 B.2060 C.2075 D.2080

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Step 2: Examining Student WorkStep 2: Examining Student Work

Student Know/Do Know/Do Know/Do

Know/Do

Errors/ Misconcepti

ons

Student A

Student B

Student C

Student D

Student E

Student F

Student G

Page 31: September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data Analysis Framework.

Step 2: Examining Student WorkStep 2: Examining Student Work

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Step 2: GO VISUALStep 2: GO VISUAL

StudentCompute Accuratel

y

Recognize

Patterns

Choose Appropriat

e Operation

Read & Identify

Key Details

Errors/ Misconcepti

ons

Student A

Student B

Student C

Student D

Student E

Student F

Student G

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DATA-DRIVEN DIALOGUE: Student DATA-DRIVEN DIALOGUE: Student Work Work

TASK DECONSTRUCTION

Generate Solution

s Reteaching/ Enrichment

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Data-Driven DialogueData-Driven Dialogue

• Facilitator and Dialogue Monitor• Use No Because Sign• Include Everyone

• Time Keeper

• Recorder• Record team members’ words and

create the chart

• Materials Manager

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Step 2: GO VISUAL (Think Time) & Step 3: Step 2: GO VISUAL (Think Time) & Step 3: ObservationsObservations

StudentCompute Accuratel

y

Recognize

Patterns

Choose Appropriat

e Operation

Read & Identify

Key Details

Errors/ Misconcepti

ons

Student A

Student B 0 Principle in

Multiplying

Student C

Student D

Student E

Student F Adding vs

Multiplying (Simplest Strategy

Student G

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STEMS • It seems …

• I believe …

•Based on ___, I think...

• I want to know more about...

•We may need to focus on…

•The student learning

problem is…Why ____.***

Page 37: September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data Analysis Framework.

OBJECTIVESOBJECTIVES

• Discover a Framework for Data Use• Apply Data Literacy• Facilitate Data-Driven Dialogue• Apply Principles of Effective Data Use

“Continual analysis of the gaps between goals for student learning and student performance defines the actions of effective

schools.”- Leading Data by Ellen Goldring and Mark Berends

Page 38: September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data Analysis Framework.

EXIT SLIPEXIT SLIP• What was your biggest “Aha”

today?

• What is your biggest “Challenge” for building capacity?

• How can we help each other build the bridge between data and results at your site?

Page 39: September 12, 2014 Lora M. McCalister-Cruel BDS District Data Coach Bay District Schools Data Analysis Framework.

Contact InfoContact InfoLora M. McCalister-Cruel

District Data [email protected]

@mccalistercruel 767-5319