Guest Blogger: Jennifer UngerThe Word Leadership Highlighted in Dictionary with Yellow Marker Highlighter Pen.

In Part I*, I offered an insight to educational administrators about the merits of leaning on your busy people—those already involved in other school and district improvement efforts—as your data leaders. In Part 2, I share a few thoughts about the level of support a wise leader provides to ensure that these people are successful.

It’s spring, and a good time to take stock of how using data has informed practice and affected student achievement at your site since the school year began.

Earlier in the year, did you make the decision to integrate broadly-implemented data tools and processes into the assessment/evaluation plan for your school or district? If you have not yet formalized a using-data effort, should you?

As mentioned in Part 1, the first step is identifying the Data Coach and data team members. Some schools refer to these people as their improvement team or teams. Once in place, reflect on the level of support and direction you need to provide. Here are some possible questions and ideas to consider:

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 Guest Blogger: Jennifer Ungercalendar with many red tacks on one day

There’s a familiar saying, “If you want something done, give it to a busy person.” If comments I hear when working with educational leaders can be taken as evidence, then it’s true.

In order to use data for meaningful change, TERC’s Using Data project advocates the identification of a Data Coach to lead a Data Team or multiple Data Teams. When we talk with school leaders about who might best serve as a Data Coach or team member, I hear comments such as, “I really think Dana would be a great data leader (or team member), but she/he is already involved in so many initiatives.”

In my experience, wise leadership makes all the difference. Let’s explore this dilemma more deeply…

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Collaborative inquiry posters showing causal analysis based on San Mateo Elementary School data

Collaborative inquiry posters showing causal analysis based on San Mateo Elementary School data

The Data-Aware Principal: Reflection #1
Guest Blogger: Lindsay P. Sharp, Principal, San Mateo Elementary School, Duval County Public Schools, Jacksonville, FL

As a principal, it’s clear to me that I need to be data informed. My job depends on it—literally, since I am evaluated by my school’s achievement. More importantly, though, my heart depends on it—I am committed to seeing data not as just numbers, but connected to the success of the students and teachers in my school.

As the school’s leader, my thoughts turn to the best way to translate my own state of “data informed-ness” into meaningful action, and I have come to understand the key lies in putting my efforts into creating data leaders beyond the principal’s office. My Using Data colleagues are now in every classroom in my school! Accomplishing this level of a “using data school culture” depends on a process that involves professional development, support, and dedication over time. We work at it every day. (more…)

Guest Blogger: Dr. William L. Heller, Using Data Program Director, Teaching Matters

There is a growing philosophy that every teacher is a literacy teacher, a view that is becoming increasingly important as states prepare for the Common Core State Standards, which place an emphasis on content literacy.

But what does “every teacher is a literacy teacher” actually mean? Will science teachers be expected to put away the BunsenABC letters standing next to an abacus burners and take out the Balzac? Will social studies teachers be responsible for teaching contractions alongside the Constitution? If we misunderstand the idea, we may misapply it, and it may even lead to resentment among teachers who feel they are being asked to take on another’s responsibility.

Part of the confusion may stem from the tendency to refer to the English Language Arts (ELA) class as Literacy class. I’ve done it myself. After all, that is the class where students ultimately learn how to read and write. But as we continue to examine the demands of college and the workplace, we are discovering the need to expand our understanding of literacy as a set of essential skills that are critical for success in every subject area. Teaching literacy in isolation misses the point of why we need to be literate in the first place. (more…)

By Diana Nunnaley, Director, TERC’s Using Data

March Madness annually takes over the country, or at least the media and the minds of U.S. college basketball fans who give itFather and son playing basketball their frenzied attention each spring. At the same time, another March Madness is going on that does not garner the same enthusiasm and  does not make national news in quite the same way. It’s the March Madness going on in schools across the country as teachers and administrators ready for spring, state-initiated student accountability assessments. These tests are considered by some to definitively provide feedback on how much students have learned this year, and correspondingly – how effective their teachers are. (That second-tier “madness” could fill volumes, and I chose to let the pundits continue to hash out that one.) (more…)

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 Einsteinmagnifying glass trained on the word why in red text

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. (more…)

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…)