Creating a Data-Driven Classroom Blog Series (3 of 3)
All About the How: Using Data for Desired Results
In my first post about data, Demystifying Data-Driven Instruction, I stated that “the ability to leverage data in the form of leading indicators of learning, leveraging time differently, and leveraging technology to inform, influence, and impact teaching and learning” are critical to transformative impact at the classroom, school, and school system level. Similarly, in What Can Cereal Teach Us About Data, I posited a framework to select the “right” data, as well as a theory of action for professional learning to assist with building and sustaining a foundation for effective use of data. In this third and final installment of my blog series, I’ll now explore how to use data to achieve the results you desire. This isn’t intended to be a quick theoretical musing. Rather, I will build upon my previous posts and share insights resulting from the difficult, challenging, and rewarding work being done by incredibly dedicated educators.
The Alice Effect
In a recent discussion with several of my superintendent colleagues, we talked about the increase of data over the past 20 years and the expectation placed on classroom teachers as well as principals to consume, interpret, and take action. There is a data set for just about every function, program, demographic, and practice in education. However, with all this data, determining its use as well as its importance remains—quite frankly—pretty darn daunting.
Believe it or not, a passage from Lewis Carroll’s classic novel Alice’s Adventure in Wonderland (1865) helped put the use of data into perspective for me during my tenure as a superintendent. One memorable exchange between Alice and the Cheshire Cat reveals an extremely salient point about how to use data:
Alice asked, “Would you tell me, please, which way I ought to go from here?”
“That depends a good deal on where you want to get to,” said the Cat.
“I don’t much care where—,” said Alice.
“Then it doesn’t matter which way you go,” said the Cat.
The first portion of the exchange is commonly known, but Alice’s response as the Cat evades her question carries a tone of sarcasm, skepticism, and cynicism. And I think teachers, at times, feel the same way—especially given the amount of data collected and the time they spend analyzing, interpreting, and planning for its use.
Unlike Alice, however, I am convinced that we do care about where we want to go. We want to follow the path to improved teaching and learning for all. One of our problems is choosing data that is of the most worth for the desired end result we hope to achieve.
This leads me to the next comment Alice makes, and one I find most applicable to how to use data:
“—so long as I get somewhere,” Alice added as an explanation.
“Oh, you’re sure to do that,” said the Cat, “if you only walk long enough.”
Finding Your How
In my experience, we would spend a great deal of time pouring over data to get somewhere, only to realize that we always had more walking to do—so to speak—to find authentic, actionable meaning. In many respects, the amount, type, and purpose of data as well as the skill, knowledge, and experience of educators to interpret, analyze, and apply data in a timely manner have limited how we use data effectively. In our work to turn around a persistently low performing school system, the somewhere was clear. We needed to close the teaching and learning feedback loop in the following ways:
• Immediacy of feedback
• Simplicity of data
• Relevancy of data to specific lessons
Immediacy of Feedback
The loop of feedback is critical for both teacher and learner. The more efficient we are in closing the time gap between instruction and learning effect, the more effective the data becomes to make adjustments and corrections within the teaching and learning cycle. Yet, immediacy alone is not sufficient. The accuracy and authenticity of feedback to both the teacher and the learner are equally important and can’t be compromised. Combined immediacy, accuracy, and authenticity of data provide for the monitoring and measuring of both the process and progress of learning by each learner, therefore creating access and opportunity for authentic personalization.
Simplicity of Data
We invested time in differentiating summative from formative data, concluding that both data sets were important but for different purposes. Creating common language and common understanding resulted in creating common practice.
We purposefully set out to reduce our walking around time with respect to analyzing and interpreting data by focusing on formative data rather than summative data. Our staff created, discussed, and assessed data of leading indicators for each of their learners, constructed “data war rooms” for classes and grade-level groupings, and met in grade level, common content or course specific, and cross grade or interdisciplinary teams. In doing so, it was important not to dismiss or disparage summative data as non-important or irrelevant. The use of summative data including unit, course, or program evaluation for determining growth, intervention strategies, or for future planning was essential. However, it was very clear that summative data was limiting for purposes of informing and influencing learning that had already occurred. Simply put, summative data does not by design efficiently and effectively complete the teaching and learning feedback loop in a timely manner.
The lag in closing the teaching and learning feedback loop is what leads to delays in timely, personalized interventions. The more at-risk as well as in-risk learners are, the greater the adverse impact. In some instances, the loop is never closed, resulting in ever increasing gaps in the acquisition of the skills, knowledge, and experience critical to proficiency let alone mastery of essential learning. Formative data, on the other hand, has and will continue to be the most effective for the purpose of instructional and learner insight as well as informing teaching and learning decisions if it meets important criteria.
Relevancy of Data to Specific Lessons
As proficient as our staff became with their use of data, we continued to struggle with closing the feedback loop for each learner. This is where we were intentional in seeking technology to assist us. If technology cannot close the teaching and learning loop, provide specific, meaningful, actionable, relevant, and timely feedback about the process and progress of learning, it will remain limiting. Had Alice been more specific about where she wanted to go, it is possible the Cat may have responded differently. In a like manner, our individual and collective response to failed learning and the failure to learn will be different based on how we use data effectively.
I am convinced that now, more than ever, data to improve teaching and learning is available through adaptive math technology like DreamBox Learning whose new Educator Experience provides rich data and learning insights to educators. This is how educators can impact change, by having the tools to surface immediate actionable insights to data that informs, creates awareness and understanding of the learning effect of an instructional moment, lesson, or activity in real time. School leaders must demand that the immediacy of feedback be simple (not complex), accessible (not restricted), relevant, specific, and personalized to the instructional lesson and each learner—and actionable for instructional adjustments or correction. Anything less will prevent the transformative impact that data can and must make to drive instructional decisions effectively and efficiently.
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Read my previous blogs posts on creating a data-driven classroom
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