4-Phase Data Dialog


Introduction by Mary Anne Mather, Managing Editor
TERC’s Using Data for Meaningful Change BlogGroup of teachers analyzing and charting data using 4-pahse dialog
…with a link to Data Quality Campaign’s Flashlight blog on
How Educators Use Data: A Four Step Process
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Effective Use of Classroom Data: It’s a topic that weighs on the minds of many educators these days. It’s also the title of a workshop that TERC Using Data recently facilitated at MESPA (Massachusetts Elementary Principals’ Association). The educators who attended were seeking strategies and resources to bring back to their schools that would help them build a culture of data use that is continuous, meaningful, manageable, sensible, and effective. Who isn’t?

There is little doubt that, in the news, education-related data are routinely discussed, bandied about, and sometimes applied in ways that are not efficacious for supporting effective teaching and learning. TERC is dedicated to making data a sweet and welcomed word, not a dreaded mandate. That’s why we were so excited that Rebecca Shah (@rebecca_shah) from Data Quality Campaign was a surprise workshop attendee! Rebecca took one of the teacher-level data analysis processes shared during the workshop and used it to reflect on the session and its outcomes. Her thoughts and related resources are posted on the Flashlight, Data Quality Campaign’s blog: How Educators Use Data: A Four Step Process. Enjoy!

And if you’d like to learn more about Four-Phase Data Dialogue, visit our Data Tips (see Tips 2-5).

 

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.)

drawing of a figure with a question mark and thought bubbleData 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. (more…)

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

Set aside assumptions, and focus on just the “data facts” before leaping to explanation and interpretation.
The Data Coach’s Guide to Improving Learning for All Students

Teachers are natural problem solvers. When we see evidence of individual students struggling, or indicators in our data that groups of students are underachieving, we are anxious to find solutions. The Using Data process advocates a “hold your horses” mindset that can help teachers to better pinpoint a student learning problem before jumping to explanations, interpretations, and quick-fix solutions. Data analysis is more effective if a team of face showing only one open eyestakeholders takes the time to observe and record as many details as possible about what the data reveal.

Observe is the third stage in a 4-phase dialogue process* that guides deep discussion toward deriving accurate meaning from the data. (See more information about Step 1: Predict and Step 2: Go Visual.) Engaging in this process as a data team, rather than individually, can garner the greatest impact toward improved student achievement. (more…)

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.”
visual of steps in  4-phase data dialog process“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. (more…)