Using Data for School Improvement

1
Using Data for School Improvement

• Session 5
• www.eprri.org
• Margaret McLaughlin
• Victor Nolet
• Sue Romansky

2
Purpose of this Session

• Learn how to use student data for school
  improvement
• Learn the meaning of school improvement
• Learn how to avoid random acts of improvement

3
School Improvement Accountability

• High Stakes Accountability is based on the
  premise that schools matter and schools can be
  improved
• High Stakes Accountability is designed to
• focus schools on the important indicators
• identify problems with the indicators
• improve the indicators

4
Indicators are

• Statistical information that tells about
• The current condition of or more components of an
  educational system.
• How well different components of an educational
  system are working together.
• Progress toward a goal or outcome.

5
Indicators should

• Provide information to help policy decisions
• Help policy makers identify new problems as well
  as address old questions (Oakes, 1986)
• Result in choice and action

6
The Challenge How to Move From Accountability
to Improvement
MD State Reading Data
7
The Challenge How to Move From Accountability
to Improvement
MD Math Data
8
Walters ES 2003 Reading 5th Grade
The Challenge How to Move From Accountability
to Improvement
9
The Challenge How to Move From Accountability
to Improvement
Walters ES Math 5th Grade
10
The Challenge How to Move From Accountability
to Improvement
11
All data are not information!

• Data becomes information when it improves the
  knowledge of the people using it so they are
  better able to make a decision
• Often, schools are awash in data but information
  parched.

12
Data become information when it is available

• At the right time
• In the right format
• In the right amount
• In the right context

13
All information is not knowledge!

• Ask the right questions
• What kind of decision are we making?
• Who is going to make the decision?
• Which information do we need in to make this
  decision?
• Is this a decision that involves data and
  information?

14
Choose Your Data Carefully

• Characteristics of quality data
• Technically sound
• Interpretable and actionable
• Formatted appropriately
• Timely

15
Complexity Matters

• Complex problems really do require complex
  solutions (most of the time).
• You might not lose your keys under the street
  light (so carry a flashlight).
• Look for convergence and divergence.