Education Data for Improvement, Not Accountability: Q&A With Paul LeMahieu

Article Tools
  • PrintPrinter-Friendly
  • EmailEmail Article
  • ReprintReprints
  • CommentsComments

Paul LeMahieu is a co-author of Learning to Improve: How America’s Schools Can Get Better at Getting Better. His work on bringing a “continuous improvement” approach to K-12 education spans a career that has included stints as Hawaii’s superintendent of education and the director of research at the National Writing Project. LeMahieu is currently the senior vice president of the Carnegie Foundation for the Advancement of Teaching, an early and ongoing leader in the continuous-improvement push.

In February, LeMahieu talked with Education Week about using educational data to support continuous improvement. The following Q&A has been edited for length and clarity.

How is research for continuous improvement different from that more traditional type of research?

Traditional research tells us something can work. It mostly aspires to build theory and to warrant claims of causation. But the very things you do to warrant that claim also limits and restricts the transfer and utility and generalizability of that knowledge.

Paul LeMahieu
Paul LeMahieu
—Carnegie Foundation for the Advancement of Teaching

Improvement science tells us how to make it work, over and over again, across contexts.

Our work basically is comprised of wedding together two other big sets of ideas: improvement science, and the power of networks.

Can you explain those two ideas?

Improvement science is not new. It’s been around for close to 100 years, but most of that time in business and industry. Over the last 25 or so years, we’ve seen improvement science in professions such as health care, child welfare services, criminal justice, other contexts that are more like education.

We think what we refer to as networked improvement communities are a uniquely effective social organization in which to do improvement work. They are rich sources of ideas and innovation. They also provide diverse contexts. And networks allow you to see patterns. We don’t lack for good ideas in education. We lack for methodology that rigorously helps us to implement those good ideas, so they succeed across contexts.

Most of the data infrastructure in K-12 today has been built for accountability purposes, not continuous improvement. What can be retrofitted, and what needs to be built new?

In an accountability context, the questions are, ‘Did you do what you were supposed to do, and did you realize the outcomes you hoped for?”

That’s not good enough for improvement.

The essential questions of improvement science are, “what works, for whom, under what condition?” To answer those, we need new forms of data. We need data that illuminate the conditions where an outcome is observed. That includes things such as what sort of policies exist in this environment, what sort of programs and practices are prevalent in this environment. We also need to look at so-called positive deviants, or rich places where positive things can be learned.

You’ve talked and written about “balancing measures” and “leading indicators.” What are they?

For improvement, you need both leading and lagging indicators. Take for example improving the teacher workforce. We often cares deeply about outcomes that can be quite distant, like teacher retention. But if our aim to help those teachers get better more quickly and to hold on to them, we don’t just need that lagging indicator. We also need a leading indicator, such as how many of them are staying on track. We need to build structures that capture these sort of things routinely.

How much work will that be?

We’re pretty far off from it. The insight is only now dawning on us.

How should we gauge the capacity of new digital data systems to help?

Follow the data. Ask, “Who is the system for, who gets the data, how are they able to use [them], and to what end?”

Do you expect to see much change in the next five years?

I’m actually quite optimistic. The movement now has some momentum. It’s starting to show up in places where programs and practices get shaped. ESSA makes provision for continuous improvement. The investment by the Gates Foundation is absolutely significant. I’m concerned about quality—what we don’t want is for this to be is this decade’s fad. But I think we’re ready to turn a corner with the dawning of improvement thinking.

Web Only

Notice: We recently upgraded our comments. (Learn more here.) If you are logged in as a subscriber or registered user and already have a Display Name on edweek.org, you can post comments. If you do not already have a Display Name, please create one here.
Ground Rules for Posting
We encourage lively debate, but please be respectful of others. Profanity and personal attacks are prohibited. By commenting, you are agreeing to abide by our user agreement.
All comments are public.

Back to Top Back to Top

Most Popular Stories

Viewed

Emailed

Recommended

Commented

Sponsor Insights

Free Ebook: How to Implement a Coding Program in Schools

Successful Intervention Builds Student Success

Effective Ways to Support Students with Dyslexia

Stop cobbling together your EdTech

Integrate Science and ELA with Informational Text

Can self-efficacy impact growth for ELLs?

Disruptive Tech Integration for Meaningful Learning

Building Community for Social Good

5 Resources on the Power of Interoperability from Unified Edtech

New campaign for UN World Teachers Day

5 Game-Changers in Today’s Digital Learning Platforms

Hiding in Plain Sight - 7 Common Signs of Dyslexia in the Classroom

The research: Reading Benchmark Assessments

Shifting Mindsets: A Guide for Training Paraeducators to Think Differently About Challenging Behavior

All Students Are Language Learners: The Imagine Learning Language Advantage™

Shifting Mindsets: A Guide for Training Paraeducators to Think Differently About Challenging Behavior

How to Support All Students with Equitable Pathways

2019 K-12 Digital Content Report

3-D Learning & Assessment for K–5 Science

Climate Change, LGBTQ Issues, Politics & Race: Instructional Materials for Teaching Complex Topics

Closing the Science Achievement Gap

Evidence-based Coaching: Key Driver(s) of Scalable Improvement District-Wide

Advancing Literacy with Large Print

Research Sheds New Light on the Reading Brain

Tips for Supporting English Learners Through Personalized Approaches

Response to Intervention Centered on Student Learning

The Nonnegotiable Attributes of Effective Feedback

SEE MORE Insights >