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Data-Based Decision Making: School District Examples

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Data-Based Decision Making: School District Examples. “As this (student learning) does not occur by serendipity or accident, then the excellent teacher must be vigilant to what is working and what is not working in the classroom.” John Hattie . Data-Based Decision Making (DBDM). - PowerPoint PPT Presentation
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Data-Based Decision Making: School District Examples “As this (student learning) does not occur by serendipity or accident, then the excellent teacher must be vigilant to what is working and what is not working in the classroom.” John Hattie
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Page 1: Data-Based Decision Making: School District Examples

Data-Based Decision Making: School District Examples

“As this (student learning) does not occur by serendipity or accident, then the excellent teacher must be vigilant to what is working and what is not working in the classroom.”

John Hattie

Page 2: Data-Based Decision Making: School District Examples

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Data-Based Decision Making (DBDM)

Page 3: Data-Based Decision Making: School District Examples

Data Based Decision Making and Problem Solving

Collect Data

Ask Questi

ons (Inquir

e)

Analyze & Summariz

e

Develop

Action Plan

Implement and Evaluat

e Action

Page 4: Data-Based Decision Making: School District Examples

Data Based Decision Making and PLCs

What is it we want our students to learn?

How will we know if our students are learning?

How will we respond when students don’t learn?

How will we enrich and extend the learning for students who have demonstrated proficiency?

PLC Questions

Collect Data

Ask Questi

ons (Inquir

e)

Analyze & Summariz

e

Develop

Action Plan

Implement and Evaluat

e Action

Page 5: Data-Based Decision Making: School District Examples

.

Comparing DBDM & other cycles/models

DBDM

Page 6: Data-Based Decision Making: School District Examples

.

DBDM & PLC Questions

• Data drives process

• Assumes strong data

source, people understand

what the data source tells

them

•Colla

boration driv

es

proce

ss

•Use

ful when

building a

team, c

ommon

langu

age i

s importa

nt

• Both utilize data• Both require teachers to

ask and answer questions, specifically why?

• Both require reflection Both are better with collaboration

• Not a one time thing

DBDM PLC

Page 7: Data-Based Decision Making: School District Examples

Tier I: Core

Tier II: Strategic

Tier III: Intensive

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Data Based Decision Making and Tiered Instruction

Page 8: Data-Based Decision Making: School District Examples

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Data-Based Decision MakingCore Instruction – Guilford County Schools

Page 9: Data-Based Decision Making: School District Examples

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Data-Based Decision MakingDistrict-wide Core Instruction

2008-09

2009-10

2010-11

2011-12

2012-13

First Grade Middle of Year Comparison

DIBELS Composite Score (assessed using mCLASS)

DIBE

LS 6

th E

ditio

nDI

BELS

N

ext

At or Above BenchmarkBelow BenchmarkWell Below Benchmark

Page 10: Data-Based Decision Making: School District Examples

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Data-Based Decision MakingDistrict-wide Core Instruction

DuFour Questions: (asked after each assessment period, district, school, and grade level)

1. What is it we want our students to learn?First Grade – phonemic awareness, phonics, text fluency

2. How will we know if our students are learning?Analyze indicator performance over time. Set an initial goal of 85% of students reaching the benchmark category.

2008-09

2009-10

2010-11

2011-12

2008-09

2009-10

2010-11

2011-12

Phonemic Awareness (PSF) Basic Phonics (NWF)

Page 11: Data-Based Decision Making: School District Examples

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Data-Based Decision MakingDistrict-wide Core Instruction

DuFour Questions:

3. How will we respond when students don’t learn? Give schools, teachers resources to teach phonemic awareness and phonics. 2008-11 – provided resources from mCLASS, FCRR, Reading Foundations2012-13 – explored options for systematic word study in all K-2 classrooms. 2013-14 – begin Fundations K – 2 in 68 elementary schools

4. How will we enrich and extend the learning for students who have demonstrated proficiency? Shift instructional focus on the next building block skill (increase fluency and comprehension)

Page 12: Data-Based Decision Making: School District Examples

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Data-Based Decision MakingDistrict-wide Core InstructionImplementation• Training and materials for all teachers • Strategic, district coaching • Close monitoring of data

Year 1 – Daily word study instruction kindergarten through second gradeYear 2 - Daily word study instruction kindergarten through third grade, supplemental word study kindergarten – second gradeYear 3 - Daily word study instruction kindergarten through third grade, supplemental word study kindergarten – third grade

Evaluate Action• Collect Data• Ask Questions• Analyze and Summarize• Modify Plan

Page 13: Data-Based Decision Making: School District Examples

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Data-Based Decision MakingSchool Level – Charlotte-Mecklenburg Schools

Page 14: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Analyzing Tier I InstructionFive (5) key areas to consider:

Academic StandardsInstructional StrategiesCurricular MaterialsAssessmentSystems of Support

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 15: Data-Based Decision Making: School District Examples

ABC School Overview -Students• 762 students

• 18% LEP• 8% Students with Disabilities• 6% Identified as Gifted

White12%

Data-Based Decision MakingSchool-wide Instruction & Intervention

African American

52%

Asian8%

Caucasian12%

American Indian

24%

Multi-Racial4%

Page 16: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

ABC School Data: Reading EOG 2011-2012

Subject/Measure

# inMembership

#Tested

#Proficient

%Proficient

# inGrowth

Composite

# Making Growth

%MakingGrowth

GrowthSum

Avg.Growth

GrowthStatus

EOG Grade 03 Reading

115 115 67 58.3

      

EOG Grade 04 Reading

144 144 76 52.8 128 34 26.6 -44.414 -0.3470 Not Met

EOG Grade 05 Reading

131 131 78 59.5 114 59 51.8 -1.689 -0.0148 Not Met

EOG Reading Total

390 390 221 56.7 242 93 38.4 -46.103 -0.1905 Not Met

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 17: Data-Based Decision Making: School District Examples

ABC School Data: Reading

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 18: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Data-Based Decision MakingSchool-wide Instruction & Intervention

ABC School Overview: Literacy Lab • 45 minutes of customized

instruction offered to the 20 lowest performing students at each grade level

• Station teaching delivery• Focus on foundational skills • Small group and 1:1 learning opportunities

Page 19: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

0

2

4

6

8

10

12

Grade 1: October DRA

Expected

Below expectancy

At or above expectancy

Served in Literacy Lab

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 20: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

0

5

10

15

20

25

30

Grade 2: October DRA

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 21: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

0

5

10

15

20

25

30

35

40

45

50

55

Grade 3: October DRA

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 22: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

0

5

10

15

20

25

30

35

40

45

50

55

Grade 4: October DRA

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 23: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

0

5

10

15

20

25

30

35

40

45

50

55

60

65

Grade 5: October DRA

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 24: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Grade 1 Grade 2 Grade 3 Grade 4 Grade 5

1%5%

30%33%

28%

99%95%

70%67%

72%

October 2012 DRA Results

Percentage Meeting BenchmarkPercentage Not Meeting Benchmark

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 25: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Data-Based Decision MakingSchool-wide Instruction & Intervention

• Let’s review:– Is our Tier I effective?

• No– Who needs support?

• Approximately 80% of our learners– Who is receiving support?

• Approximately 25% of our learners

Page 26: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate ActionAdditional Data: Teacher Surveys

Teaching:– Lack of trust– Unwillingness to take risks– Lack of non-instructional time

Professional Development Needs:– Differentiated Instruction– Struggling Learners– Reading Strategies

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 27: Data-Based Decision Making: School District Examples

Action Plan:• Provide Professional Development• Augment Tier I with strategies to improve fluency

and comprehension• Provide opportunities for peer shadowing and job

embedded coaching• Progress monitor students• Monitor and provide ongoing feedback to teachers

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Implement and Evaluate Action

Data-Based Decision MakingSchool-wide Instruction & Intervention

Page 28: Data-Based Decision Making: School District Examples

Data-Based Decision Making Student Level –Alamance County Schools

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

Page 29: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Data-Based Decision MakingIndividual Student Level

• 6th Grade Universal Screening Data (AIMSweb):– Fall Math Computation: 7 points: between 10th

and 25th percentile• 5th Grade EOG Math Scores

– Level 2: 16th percentile– Level 1: 6th percentile (retest)

Page 30: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Data-Based Decision MakingIndividual Student Level

Instruction Curriculum Environment Learner*What practices and strategies are currently being used? In previous grades?*What is the pacing/sequencing of instruction?*What are instructional areas of focus for this student based on Scholastic Math Inventory (SMI)?

*What materials are used with the student?* Are there various opportunities for sufficient practice?

*Are classroom distractions limited during classroom?*Are routines and procedures well established and understood for student?

*What instructional strategies work best for the student?*Does student’s learning style match the instruction?*What interventions have been used previously? What was the response based on progress monitoring?*How does student’s work compare to his peers?

Looking for strengths and weaknesses across 4 domains

Page 31: Data-Based Decision Making: School District Examples

• What are possible resources for student’s instructional plan?– TransMath– FasttMath– IXL– Back to Basics– Resources from

Quantile.com

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Data-Based Decision MakingIndividual Student Level

• Which resources best fit student’s need?– SMI Results

• Fluent with addition but not multiplication facts

• Weaknesses in place value and fraction concepts

– Analysis of Math Computation Probe

• Errors in math facts • Errors in reducing

fractions/converting to decimals

Page 32: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Data-Based Decision MakingIndividual Student Level

• SMART Goal– Student will increase

from 17 points correct to 53 points correct on a 4th grade math computation probe by June 10, 2013.

– Student will increase from 7 points correct to 20 points correct on 6th grade math computation probe by June 10, 2013.

• Plan Details– Who:

• Interventionist• Math Teacher

– What & Frequency:• TransMath: 5 days a week

for 40 minutes during intervention block

• FasttMath: 3 days a week for 10 minutes during math warm-ups in classroom

Page 33: Data-Based Decision Making: School District Examples

Collect

Data

Ask Questions

(Inquire)

Analyze &

Summarize

Develop Action

Plan

Impleme

nt and Evaluate Action

Data-Based Decision MakingIndividual Student Level

2/19/2013

2/26/2

013

3/5/2013

3/12/2013

3/19/2013

3/26/2013

4/2/2013

4/9/2013

4/16/2

013

4/23/2

013

4/30/2

013

5/7/2013

5/14/2

013

5/21/2

013

5/28/2

013

6/4/2013

0

10

20

30

40

50

60

70

Student-6th graderTier 3 Progress Monitoring

Math-COMP - 4th grade2012-2013

4th Math -COMP DataTrendline

Num

ber C

orre

ct

Page 34: Data-Based Decision Making: School District Examples

Collect Data

Ask Questions (Inquire)

Analyze & Summarize

Develop Action Plan

Implement and

Evaluate Action

DBDM: One Process…

Page 35: Data-Based Decision Making: School District Examples

Many Data Sources….


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