Using Data Process

Assumption #1

• http://www.youtube.com/watch?v=_llFlj6FeQ8

• Making significant progress in improving student learning and closing achievement gaps is a moral responsibility and a real possibility in a relatively short amount of time—two to five years. It is not children’s poverty or race or ethnic background that stands in the way of achievement; it is school practices and policies and the beliefs that underlie them that pose the biggest obstacles.

Assumption #2

• http://www.youtube.com/watch?v=w6NR0edrgWE

• Data have no meaning. Meaning is imposed through interpretation. Conversely, data themselves can also be a catalyst to questioning assumptions and changing practices based on new ways of thinking.

Assumption #3

• http://www.youtube.com/watch?v=pW8TdqF7Pao

• Collaborative inquiry—a process where teachers construct their understanding of student-learning problems and invent and test out solutions together through rigorous and frequent use of data and reflective dialogue—unleashes the resourcefulness and creativity to continuously improve instruction and student learning.

Assumption #4

• http://www.youtube.com/watch?v=9dMzFNQwaqg

• A school culture characterized by collective responsibility for student learning, commitment to equity, and trust is the foundation for collaborative inquiry.

Assumption #5

• http://www.youtube.com/watch?v=HbYiXyUynRk

• Using data itself does not improve teaching. Improved teaching comes about when teachers implement sound teaching practices grounded in cultural proficiency—understanding and respect for their students’ cultures—and a thorough understanding of the subject matter and how to teach it.

Assumption #6

• http://www.youtube.com/watch?v=6d5IWsaDlkE

• Every member of a collaborative school community can act as a leader, dramatically impacting the quality of relationships, the school culture, and student learning.

Summative

Formative

State Assessments

Demographics

Benchmarks

Common Assessments

Classroom Assessments

Task 1:Using Data Project Overview

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

The Using Data Process

S 1.13A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

The Data Divide

S 1.14A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

Core Value

Significant improvement in student learning and closing achievement gaps is

a moral responsibility and a real possibility in a relatively short amount of

time—two to five years.

S 1.15A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

Poverty, Race/Ethnicity, and Achievement

Poverty and Race/ Ethnicity Enrollment

% o

f S

tud

en

ts P

rofi

cie

nt

or

Ab

ov

e

Source: Adapted from Accountability in Action (2nd ed.) by Douglas Reeves, 2004, Denver, CO: Advanced Learning Press.

Possibility

XSchools with a majority

of African American, Latino/a, and/or Native

American students and/or students living in poverty are achieving at

this level.

S 1.16A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

Core Value

Collaborative inquiry—school 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 instruction and student learning.

S 1.17A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

Anne Lieberman

Dan Lorti

Robert Marzano

Milbrey McLaughlin

Jay McTighe

Fred Newmann

Allan Odden

Doug Reeves

Mike Schmoker

Deborah Shifter

Dennis Sparks

James Stigler

Gary Wehlage

Grant Wiggins

and more…

Deborah Ball

Roland Barth

Carol Belcher

Louis Castenell

Jim Collins

Tom Corcoran

Linda Darling-Hammond

Lisa Delpit

Rick DuFour

Karen Eastwood

Richard Elmore

Susan Fuhrman

Carl Glickman

Asa Hilliard

Virtually All Education Researchers Agree: Collaboration is Key

S 1.18A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

Building the Bridge Between Data and Results

Instructional ImprovementData UseCollaborationLeadership &

Capacity

Culture/Equity/Trust

S 1.19A Data Coach’s Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry © 2008 by Corwin Press. All rights reserved.

Culture, Equity, Trust

Instructional Improvement

Collaboration

Data Use

Leadership & Capacity

Shifts That Are Evident in Using Data Schools

Less Emphasis More Emphasis

External accountability, cultural blindness, little trust

Internal and collective responsibility,cultural proficiency, trust

Data to sort, learning left to chance

Data to serve, expanding opportunities for all

Top-down, data-driven decision making Ongoing Data-Driven

Dialogue and collaborative inquiry

Punishment/reward, avoidance

Feedback for continuous improvement, frequent and in-depth use by teachers and students

Individual charismatic leaders as change agents

Learning communities with many change agents

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

Unique Features of the Using Data Process• Builds everyone’s knowledge and skills • Focuses on cultural proficiency, equity, and school

culture• Focuses on data culture and collaboration• Includes both long-term and short-cycle improvement• Is a structured and adaptable process:

– identifies the student-learning problem– verifies its causes– uses research and a logic model to design

interventions– monitors results

• Provides tools for collaboration and sense making

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

Using Data Process is the Intersection

New Baseline Year for Mathematics and Reading

Purpose for Grades 3 – 8 Standard Setting

• Increase rigor by raising standards for Grades 3 – 8 student achievement on the OCCT as a means to be more competitive at the national and international levels.

• Align student expectations on the OCCT more closely with student expectations for the National Assessment of Educational Progress (NAEP).

• Because tests were implemented over multiple years, there were outliers.

• Vertically aligning performance standards for students on the OCCT tests for Grades 3 – 8 allows for consistent expectations.

22

August 27, 2009 State Board of Education Meeting

• A scaled score is derived from the number correct and is used to place a student in one of the given performance levels for each content area.

• Score ranges vary across content areas.

• A scaled score of 700 is Satisfactory or Proficient across all content areas.

Oklahoma Performance Index (OPI)

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• Standard Setting is the process that allows experts to make judgments about the content that a student should know and be able to do in order to be classified in a specific performance level.

• Cut scores are necessary for the categorization of student test scores into the four performance levels utilized in Oklahoma: Advanced, Proficient, Limited Knowledge, and Unsatisfactory.

Standard Setting and Cut Scores

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Standard Setting and Cut Scores

• The experts included on the standard setting committees were educators across Grades 3-8 with significant experience in reading or mathematics instruction, as well as representatives from higher education and business.

• One panel of experts conducted standard setting for reading and another panel conducted standard setting for mathematics.

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Oklahoma Core Curriculum Tests Performance Benchmarks or "Cut

Scores”• The standard setting panelists determined cut

score recommendations based on test content, performance standards, and test item difficulty, NOT based on number of test items answered correctly.– Raw scores were mapped to scale scores as is

standard procedure with large-scale assessments such as the NAEP, ACT, or SAT.

– Scale scores provide a consistent interpretation of assessments across years.

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•No blaming students.•No blaming teachers.•Data is just information.•Use data for instructional

purposes.•“De-emotionalize” data.

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Ground Rules

• The median is the middle score in a set of ordered scores.

• The median is a better measure of central tendency than the mean (average) because it is not affected by extreme scores.

• Remember: Comparing Median % Correct does not take into account difficulty of items across years, yet it will show general trends in strengths and weaknesses.

Median

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1. What does the data show? (Factual Information)

2. Why might this be? (Hypotheses)

3. How should we respond? (Plan for action)

4. How will you measure success?

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Key Points When Analyzing Data

QUESTIONSCOMMENTSCONCERNS