Putting Data Back Into the ‘Palms’ of Duval County’s Teachers

By Mary Anne Mather, Managing Editor
TERC’s Using Data for Meaningful Change Blog

TERC’s Using Data facilitators have been working for the past two years with 30 elementary schools in Duval County Florida. This is possible through funding from a U.S Department of Education, Institute of Education Sciences (IES) grant to study the efficacy of the Using Data for Meaningful Change processes.

As our time together winds down, the Duval schools are sharing stories about transformation in practice, focus, and student achievement.

 

Using Data Tip #9: Disaggregating Data Makes the Invisible Visible

GUEST BLOGGER: Mary Anne Mather, Using Data Senior Facilitator & Social Media Liaison on Twitter & FaceBook

If you want to tap one of the most powerful uses of data, disaggregate! Disaggregation means looking at how specific subgroups perform. Typically, formal student achievement data come “aggregated,” reported for the population as a whole—the whole state, school, grade level, or class. Disaggregating can bring to light critical problems and issues that might otherwise remain invisible.

For example, one district’s state test data indicated that eighth-grade math scores steadily improved over three years. When the data team disaggregated those data, they discovered that boys’ scores improved, while girls’ scores actually declined. Another school noticed increased enrollment in their after-school science club. However, disaggregated data indicated that minority students, even those in more advanced classes, weren’t signing up. These are just some of the questions that disaggregated data can help answer:

• Is there an achievement gap among different demographic groups? Is it getting bigger or smaller?

• Are minority or female students enrolling in higher-level mathematics and science courses at the same rate as other students?

• Are poor or minority students over-represented in special education or under-represented in gifted and talented programs?

 

One Teacher Talks About Using Data to Drive Instruction in the Classroom

GUEST BLOGGER: Mary Anne Mather, Using Data Senior Facilitator & Social Media Liaison on Twitter & FaceBook

I very much enjoyed Part I of Jill Thompson’s blog series about “Using Data to Drive Instruction in the Classroom.” According to her bio, Jill is an elementary math and science facilitator.

I applaud her for sharing her insights and passions about this subject. As a former classroom teacher, and currently as a facilitator for TERC’s Using Data process, I find myself in step with her thinking. Regularly integrating formal and informal assessments into the instructional planning process is a must. It’s not adding more to the plate — it IS the plate…understanding the impact of the teaching process on student learning and using that information to plan the necessary next steps—not only what to teach, but how to engage kids in the learning.

These days there is so much negative emphasis on testing, and I understand the rub when I see test scores being used to punish teachers and categorize kids. But let’s be clear that using data and testing are not the same thing. Data comes in many shapes and forms, well beyond test results and grades (these are just one data point). Teachers have the opportunity to use data as a valuable resource to guide a teaching and learning approach that can ignite learning for all students. As Jill notes–it just takes time and know-how (and an understanding that it’s a non-negotiable).

I plan to follow Jill’s blog series on this topic, and I recommend it to you. Thank you, Jill, for sharing your experiences and helping those who might be uncertain about how to put their data to work as an instructional tool. Your ideas illuminate understanding of a process for using data that can profoundly impact student engagement and achievement.

 

Using Data Tip #6: Beginning a Causal Analysis Process: Why Asking “Why” Once is Not Enough

GUEST BLOGGER: Mary Anne Mather, Using Data Senior Facilitator & Social Media Liaison on Twitter & FaceBook

“Learn from yesterday, live for today, hope for tomorrow. The important thing is not to stop questioning.” Albert Einstein

Once a school or grade-level data team has analyzed several data sources to pinpoint a student learning problem, they often feel ready to leap into action and solve it. To ensure that the solution pursued produces the hope-for results, it’s essential to engage in a collaborative process of causal analysis to identify the “root” cause of the problem.

There are many tools that support root cause analysis, one of them is referred to as Why-Why-Why—a question-asking technique used to explore cause and effect relationships. Why-Why-Why helps a group look beyond symptoms to underlying causes by taking the identified problem and asking why it exists at least three times—each time probing more deeply.

 

Using Data Tip #5: Getting to the Bottom of “Why” Before Investing in Solutions — Make Inferences and Question Your Data’s Story

GUEST BLOGGER: Mary Anne Mather, Using Data Facilitator & Social Media Liaison on Twitter & FaceBook

“Make data observations. Then generate possible explanations that inform next-steps to finding the best teaching and learning solutions.”
(from: Love, Nancy et al. The Data Coach’s Guide to Improving Learning for All Students, 2008.)

Data analysis is more effective, and more on-target for getting student achievement results, if a team of stakeholders first observe and list as many details as possible about what the data reveal, followed by making inferences about these observations, and then asking “why is this happening?” “what else do we need to know to be sure?”.

Infer/Question is the fourth stage in a team-based, 4-phase dialogue process* that guides deep discussion toward deriving accurate meaning from performance data. (See more information about Step 1: Predict, Step 2: Go Visual, and Step 3: Make Observations.)

These action steps will help you and your data team share inferences about the story the data reveal—inferences that will inform important next-steps toward identifying a valid student learning problem and its true causes.

 

Data Blind Spots—Data Use Continuum Tool Can Improve a School’s Vision

By Diana Nunnaley, Director, TERC’s Using Data

Depending on where you sit, and which frame of reference shapes your work, you either celebrate charter school efforts or think charters reflect a “right” wing or “left” wing  (take your pick) conspiracy to undermine the role of public education in the United States.

A blog post is too short a space to weigh into the considerable arguments both pro and con that can be made regarding the place for charter schools in America. To my thinking, charters are a natural consequence of Americans seeking a solution to a social problem. We may not agree on the substance of the problem or the direction of the solution, but in a society that values and applauds entrepreneurial efforts, charters are here to stay. That is, they have a place until we learn more about the experience (hopefully by examining the data) or, have a collective epiphany about the impact of poverty on kids’ success in learning and activate the collective will to change the way we fund and support local education.

Charter School Vision Equally Blurred

Based on my experience working in schools across the country, the reality is that teachers in charter schools bring the same passion and desire to help children learn as teachers in any other public or private setting. They face the same staggering challenges and then some. And they bring the same blind spots to the table when examining their student learning data.

 

The Portico Problem: In Praise of Item-Level Data Analysis

GUEST BLOGGER: Dr. William L. Heller, Using Data Program Director, Teaching Matters*

As a facilitator of the TERC Using Data institute, I try not to play favorites among the different stages of the process. Every link in the chain is important towards improving student outcomes. But I must confess that I always look forward to the item-level analysis with just a little extra bit of enthusiasm. This is where the school-based data teams that I work with are most likely to achieve a breakthrough and gain new understandings about the problems their students are having. Even the teachers who arrive being the most skeptical about the importance of data are subject to “Aha!” moments when they actually look at the questions their students got wrong on the exams and are able to specifically target a cause and a solution.

 

Bibbidi-Bobbidi-Boo: Wouldn’t it be great?

GUEST BLOGGER: Jennifer Unger Director, The GroupWorks, Grafton, MA. Jennifer is a senior facilitator for TERC’s Using Data.

As a facilitator of learning, one of the great conundrums I see participants grappling with is the growing realization that I, as the facilitator of their learning, may not be a magician, and that they must actually use the tools, resources and processes that I provide in order to initiate the changes that they desire. It is simply not enough to attend a working session and leave saying, “Been there-done that.”

Now I know this for a fact because I do it all the time—whether I am attending a Michael Fullan workshop or reading a really great book (most recently, Mike Schmoker’s FOCUS). Somehow, there is that deep, abiding belief that just engaging with their ideas will change me. While it may be a first miniscule beginning step, alas, I know that it will not change me any more than watching tons of exercise videos will help me lose weight. Change is something that I must DO and, as Ghandi said, BE

Which leads me to the Concerns Based Adoption Model (CBAM) that was introduced to me by my colleagues Susan Loucks-Horsley and Susan Mundry, and, its sister, the Innovation Configuration. Two of the foundational underlying assumptions of these models/frameworks are that change takes time and that change is a process, not an event.

 

Using Data Tip #3: Go Visual!

GUEST BLOGGER: Mary Anne Mather, Using Data Facilitator & Social Media Liaison on Twitter & FaceBook

“’Go Visual’ with your data to help construct meaning, make sense,
and prepare to engage in meaningful dialogue.“
The Data Coach’s Guide to Improving Learning for All Students

Teachers have access to rich and varied student data, often provided in a variety of computer-generated documents with lots of numbers. Where does a data team begin their dialogue about what the numbers show? How can the team integrate multiple sources of data to tell a coherent story? How can a data team bring to life pages of numbers, so that the data can paint a picture about student learning? One way to illuminate the stories within the data is for data teams to create their own visual display of the data. We call it “Go Visual.”
“Go Visual” is the second stage in a four-phase process that guides data teams through deep discussion about data and helps them derive meaning from the data.

 

Data Wars Aside: What’s the Point?

COMMENTARY On-the-News
GUEST BLOGGER: Mary Anne Mather, TERC Using Data Facilitator & Social Media Liaison

Rhee speaking at NOAA, June 2008

The recent media outcry about whether or not Michele Rhee, former Chancellor of the D.C. Public Schools, exaggerated her students’ test scores has died down a bit this week. But in mulling over last week’s news (See Larry Ferlazzo’s The Best Posts About Michelle Rhee’s Exaggerated Test Scores), I’m reminded of a simple measurement a long-time teacher friend uses before making any important education decision. She calls it the “What’s the Point” (WTP) assessment. She even considered having t-shirts made to remind us always to consider WTP before deciding what we teach and why.

Let’s set aside all the press, subsequent commentary, and or own feelings about the Rhee controversy. It’s not all that useful a discussion. But it does surface, for me, three WTPs.  These points are the bottom line for using data, reporting data, or discussing data for any meaningful purpose, and they might even resonate with those who regularly caution that test scores are unreliable gauges of performance.