Deena Abu-Lughod 1 Children First Intensive Collaborative Data Analysis, ARIS, Network Data...

1Deena Abu-Lughod

Children First Intensive

Collaborative Data Analysis, ARIS, Network Data

Celebration

ESO Network 14Eastwood Manor, May 21, 2009

Facilitator:

Deena Abu-Lughod, SAF

Adapted from Nancy Love, Presentation to SAFs, April 2, 2009

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Provisional Agenda

8:30-8:45 Welcome! Announcements (share fair)

8:45-10:15 Cause-and-Effect/Verifying Causes with Data Protocol

10:15-10:30 Break

10:30-10:45 Network 14 ELA Highlights Celebration

10:50-11:05 Planning for ARIS Parent Link

11:05-11:30 A Word from our Sponsor

11:30 – 11:35 Evaluation

11:35 –12:35 Study Groups

12:35 – 1:30 Lunch

1:30-2:30 Afternoon Consultations: Progress Report Modeler

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Learning Intention

Build capacity to move into and sustain system-level change by learning to use two collaborative data tools to move the level of analysis from the target population to the system:

Cause and Effect Analysis Verifying Causes Tree

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Core Process

Phase II: Move the

Students

Phase I: Identify

Students and

Targets

Phase III: Move the

System

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Analyze systems that

produced conditions of

learning

Design and implement change strategy

Evaluate and revise based on interim progress

measures

A More Detailed Look at the Inquiry Process: Phase III

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Conditions of Student Learning Curriculum (What is taught)

Instruction / Teacher Preparation (How it is taught? How well it is taught? Who is teaching?)

Additional considerations:

> Assessment (How learning is assessed and used to inform instruction?)

> Equity (Teacher assignments, student groupings, access to rigor)

> Critical supports (collaboration, leadership, extra help systems, technology, policies, parent and community engagement, PD)

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What really matters?

•Alignment

•Rigor

•Assessment

•Professional Development

•Critical Supports

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Taught Curriculum

WrittenCurriculum

Assessed Curriculum

STANDARDS

Curriculum Alignment Matters

Adapted from Fenwick English.

From N. Love, K. Stiles, S. Mundry, and K. DiRanna, The Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry, Thousand Oaks, CA: Corwin Press, 2008. All rights reserved.

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Rigor Matters: Two Gr. 7 Writing Assignments

Essay on Anne FrankEssay on Anne Frank

Your essay will consist of an opening paragraph which introduces the Your essay will consist of an opening paragraph which introduces the title, author and general background of the novel. title, author and general background of the novel. Your thesis will state specifically what Anne's overall personality is, and Your thesis will state specifically what Anne's overall personality is, and what general psychological and intellectual changes she exhibits over what general psychological and intellectual changes she exhibits over the course of the book.the course of the book.You might organize your essay by grouping psychological and You might organize your essay by grouping psychological and intellectual changes OR you might choose 3 or 4 characteristics (like intellectual changes OR you might choose 3 or 4 characteristics (like friendliness, patience, optimism, self doubt) and show how she changes friendliness, patience, optimism, self doubt) and show how she changes in this area.in this area.

All About Me (fill in the blanks):

My best friend… A car I want…

A chore I hate… My heartthrob…

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Teaching Matters

Tools we have used:

1) Lesson observation with the differentiated instruction rubric

2) Low inference transcripts

3) Teacher reflections

4) Tuning Protocol

5) Teacher Data Initiative

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Assessment Matters

250 research studies from several countries establish that improving formative assessments raises achievement. Few initiatives in education have had such a strong body of evidence to support a claim to raise standards. – Paul Black et al., 2004, p. 9

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Professional Development Matters

Little Impact: short, episodic, and disconnected from practice has little impact.

High Impact: Well-designed programs offering extended PD (49 hours on average over 6 to 12 months)

Professional Learning in the Learning Profession A Status Report on Teacher Development in the United States and Abroad Linda Darling-Hammond & Nikole Richardson2009 (www.nsdc.org)

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Critical Supports Matter

Factors that support expanding opportunities to learn:

> Collaborative culture and structures> Leadership> Extra help for students who need it> Effective uses of technology > Policies that align with learning> Parent and community engagement

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”“Powerful Words

Research has found that faculty in successful schools always question existing instructional practice and do not blame lack of student achievement on external causes.…The “source of the problem” in ordinary schools is always someone else: the students, the parents/caretakers, the school board, and so on.

— Carl Glickman, 2002, pp. 4, 6

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Review the “Conditions of Learning” slide (#7). Give a one-minute elevator

speech about it. Add any additional research you know.

Partner and Talk

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Cause-and-Effect Analysis and Verification

1: Generate Possible Causes

2: Dialogue about Causes

3: Identify Causes for Further Verification

4: Frame Research Questions Based on Causes

5. Study the Research

6. Frame Questions for Local Data Collection

7. Analyze Local Data and Verify Causes

8. Plan for Engaging Stakeholders and Review School Culture

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Shifts Toward Verifying Causes

Quick fix and knee-jerk

reactions to data

Analysis of root causes using local data (surveys, observations, interviews from diverse voices, enrollment data) and research

Attributing causes to circumstances outside of the school’s control

Looking for causes in beliefs, practices, and policies

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Verify Causes Tree: Placemat Activity

Adapted from Paul G. Preuss, Root Cause Analysis: School Leader’s Guide to Using Data to Dissolve Problems, Larchmont, NY: Eye on Education, 2003. Used with permission.


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Background on Practice School

Grades K-6 urban school

The school did not meet adequately yearly progress and has been placed on the SINI list

35% of students were proficient in Language Arts in 2007

A traditional mathematics textbook program has been offered, and little professional development has been provided in mathematics

In Grade 6, two levels of mathematics are offered: regular mathematics uses the Scott Foresman textbook; high-ability offers the Merrill pre-algebra program

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Student-Learning Problem Statement

Some sixth-grade students have a problem with mathematics achievement. Weak areas include Patterns, Relations, & Algebra and problem-solving. • 34% were proficient and advanced in mathematics on the state test in

2008. • The weakest strand in multiple-choice on state test in was Patterns,

Relations, & Algebra (51% correct)• 52% are below basic on the 2008 district assessment; 70% of students

scored a 1 out of 4 on the open-response section

These performance gaps were noted on the state test: • A 40 percentage point gap between White and Hispanic students• A 34 percentage point gap between Non-LEP and LEP students• A 46 percentage point gap between Non-SPED and SPED• A 24 percentage point gap between Non-Low Income and Low Income

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Verify Causes Tree Directions

1: Generate Possible Causes

Enlarge the graphic organizer, leaving space in all boxes for writing

Write the student-learning problem in the top box (“Sixth grade mathematics problem-solving; achievement gap between White and African American students”)

Generate possible explanations for the problem on large Post-its (or go through the Cause Card deck).

Place them in the first row, organized by the categories provided

Adapted from P. G. Preuss, Root Cause Analysis: School Leader’s Guide to Using Data to Dissolve Problems, Larchmont, NY: Eye on Education. From N. Love, K. Stiles, S. Mundry, and K. DiRanna, The Data Coach’s Guide to Improving Learning for All Students:

Unleashing the Power of Collaborative Inquiry, Thousand Oaks, CA: Corwin Press, 2008. All rights reserved.

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Examples of Possible Causes

The curriculum is not aligned with standards

We are not differentiating instruction to reach students who aren’t learning from traditional approaches

We are not using formative assessments to make adjustments in our teaching

Some of us don’t feel comfortable with mathematics problem-solving approaches; we didn’t learn that way

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2: Dialogue About CausesDialogue about the causes you have generated.

Which causes…> Are within our control to act on? > Reflect cultural competence? (Respect for diversity)> Can have a great impact on solving the student-learning

problem?> Can be verified with additional data and/or research?> Can be addressed given our resources and time

constraints?> Do we want to investigate further?

Would acting on any of these causes do any harm to any student or group of students?

Equity Lens

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4: Frame Research Questions Based on Causes (validating questions)

Questions to determine whether research validates a possible cause:

> Does tracking contribute to achievement gaps between White and African American students?

> Is class size a factor in student achievement?> Does inclusion hurt regular education students?> Does incorporation of literacy strategies in the

content areas improve students’ academic performance in content areas?

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4: Frame Research Questions Based on Causes (discovering questions)

Questions to elicit what we can learn from research about a possible cause:

> What instructional strategies help students become better writers?

> What kind of preparation helps teachers to be successful in teaching science?

> What kinds of grouping practices help students be successful?

> What are the effects of tracking in the short run? In the long run?

> What instructional practices help students acquire academic vocabulary?

> Are there literacy strategies that are particularly effective with African American boys?

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Verify Causes Table: Research(Course Handout pp. 209, 211)

Research Question

Research Source

Research Findings


Task: Based on the possible causes you prioritized, generate three research questions for your own student-learning problem

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Activity 13: Selected Research Sources Course Handout, P. 213

Add your own


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Verify Causes Tree Directions (Course Handouts, p. 209)

Adapted from P. G. Preuss, Root Cause Analysis: School Leader’s Guide to Using Data to Dissolve Problems, Larchmont, NY: Eye on Education. From N. Love, K. Stiles, S. Mundry, and K. DiRanna, The Data Coach’s Guide

to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry, Thousand Oaks, CA: Corwin Press, 2008. All rights reserved.

1. Enlarge the graphic organizer, leaving space in all boxes for writing

2. Write the student-learning problem in the box on top

3. Generate possible explanations for the problem in the first row of boxes, organized by the categories provided

4. Gather research to verify your causes

5. Record your research findings on the Verify Causes Tree

6. Modify, eliminate, or add to your list of possible causes

7. Collect and analyze local data to investigate the causes in your own setting that have been verified through research

8. Record local data findings on Verify Causes Tree

9. Record causes that are verified through research and local data in the Verified Causes boxes in the Tree

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Sample Verify Causes Table: Research (Course Handouts, p. 225)

Research Question Research Source Research Findings

What kind of instruction reaches students who aren’t achieving in mathematics?

EDThoughts, pp. 2-3Course Handouts, pp. 234-235)

Is tracking a factor in student achievement? How does it impact low-track students? High-track students?

EDThoughts, pp. 4-5Course Handout, pp. 236-237

Does teacher preparation impact student learning?

EDThoughts, pp. 26-27(Course Handouts, pp. 240-241)

What strategies contribute to closing achievement gaps in mathematics?

“Achievement Gap,” pp. 586, 590-591(Course Handouts, pp. 242, 246-247)


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Study the ResearchJigsaw, Part I: Divide the Reading

1. EDThoughts, pp. 2-3 (instruction for equity) (Course Handouts, pp. 234-235)

2. EDThoughts, pp. 4-5 (tracking) (Course Handouts, pp. 236-237)

3. EDThoughts, pp. 26-27 (teacher preparedness) (Course Handouts, pp. 240-241)

4. “Achievement Gap,” pp. 586, 590-591 (strategies) (Course Handouts, pp. 242, 246-247)

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Study the Research Jigsaw

1. Read through your research and underline key points

2. Meet in expert groups (optional)

3. Summarize your findings on the Sample Verify Causes Table: Research (optional)

4. Prepare to teach your research to your team

5. Teach your research to your home team members

6. Record your findings on the Verify Causes Tree in the appropriate column in the Research Findings row

7. Modify, eliminate from, or add to your list of possible causes

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Verify Causes Tree: Example of Revising Causes After Research


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Frame Questions for School-Level Data Collection: “to what extent” questionsTo what extent:

> are we implementing our curriculum?> are we using higher-order questioning?> do our teachers feel prepared to teach ______?> are we explicitly teaching academic vocabulary?> are students writing across the curriculum?

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Framing Questions: Correlational Questions

These questions focus on gathering data that provide evidence of whether there is a relationship between two factors.

Who is enrolled in our high-track and low-track Math courses? How are students in different tracks performing on our state assessments? (enrollment and achievement)

Do students in lower tracks receive a different type of instruction than students in high tracks? (tracking and instruction)

How much time are teachers spending teaching Math? Are students in classrooms where more time is spent achieving better? (time spent and achievement)

Do students who are in the reading-in-the-content-area program perform better on exams in other content areas? (What variables would you correlate?)

How much time are teachers spending teaching academic vocabulary? Are students in classrooms where more time is spent teaching vocabulary achieving better? (What variables would your correlate?)

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Develop the School-level Data Collection Plan (Handout, p. 232)

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Verify Causes Table: Local Data (Handout H14.1)

Question for Local Data Collection

Local Data Sources/Tools

Findings

Are diverse voices represented here?Is this doable?Will the data answer our questions?

Equity Lens


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Data-Driven Dialogue

Adapted from B. Wellman and L. Lipton, Data-Driven Dialogue: A Facilitator’s Guide to Collaborative Inquiry, Sherman, CT: MiraVia LLC, 2004.


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Sample Verify Causes Table: Local Data: What do you predict?


Local Data Sources/Tools Findings (Predicted)

Who is enrolling in our mathematics advanced courses? Regular courses? How many classes are offered at each level?

To what extent are students receiving high-quality instruction? To what extent does this differ in advanced vs. regular mathematics courses?

How are students achieving on the state assessment disaggregated by course?

How prepared do teachers feel to teach mathematics?


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Analyze Local Data Jigsaw, Part 1 (Data Example Handout, pp. 248-252)

Data Example 14.1: Student Interview Data (use Key Concepts/Key Words)

Data Example 14.2: Classroom Observation Data (use Key Concepts/Key Words)

Data Example 14.3: Teacher Survey Data (use Stoplight Highlighting)

Data Example 14.4: Enrollment and Achievement Data (use bar graph)

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Complete Verify Causes Table: Local Data (Course Handouts, p. 227)


Local Data Sources/Tools Findings (Actual)

Who is enrolling in our mathematics advanced courses? Regular courses? How many classes are offered at each level?

Enrollment data, Data Example 14.4 and graph

To what extent are students receiving high-quality instruction? To what extent does this differ in advanced vs. regular mathematics courses?

Classroom observation, Data Example 14.2Student interviews, Data Example 14.1

How are students achieving on the state assessment disaggregated by course?

Disaggregated enrollment and achievement data, Data Example 14.4 and graph

How prepared do teachers feel to teach mathematics?

Survey data, Data Example 14.3


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Analyze Local Data and Verify Causes (continued)

Record local data findings on the Verify Causes Tree

Go to Phase 4: Infer/Question: What conclusions are you drawing now about the possible causes based on research and local data?

Record causes that are verified through research and local data in the Verified Causes boxes on the Tree.


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Verify Causes Tree: Example of Revising Causes After Research


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Essential Question

How can we scale up the work of inquiry teams? Bring more students into the sphere of success?

I discovered that I….I intend to…..

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Powerful Words

I wonder how many children’s lives we would save if we educators shared what we knew with each other.

— Roland Barth

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Network ELA Data: Predictions

How many of our schools had overall gains that exceeded the City average of 11%?

What percent of students made 1 year progress?

In what grade were Proficiency Rate gains the highest?

What was the average Proficiency Rate gain for the Level 1+2 students?

What was the average Proficiency Rate gain for the Level 3+4 students?

Was there a difference in the Proficiency Rate gains of Level 1+2 students with IEPs and Level 1+2 General Education students?

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Small increases in proficiency translate into large increases in probability of graduating

93%

80%

51%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5

8th Grade Test Score (Average of ELA & Math)

4-Y

ear

Reg

ents

Gra

duat

ion

Rat

e

4-Year Regents Graduation Rate

Source: 2004 Graduation Cohort (“Class of 2008”) from the 2007/08 Progress Reports

Guiding PrinciplePerformance and Progress

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Acuity Predictive Correlations

In June, most schools will administer the Acuity Predictive assessments.

How reliable are these assessments in predicting the outcomes on the NYS test?

The correlation of the Grade 8 ELA Proficiency Rates with the Fall Acuity Predictive was .759. Very high.

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Grade 8: Scatterplot of Acuity with Prof. Rate

1

1.5

2

2.5

3

3.5

4

4.5

0 20 40 60 80 100

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