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Data: More Than Just a Four-Letter Word

By Elizabeth Stein 鈥 January 22, 2013 5 min read
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I鈥檇 be hard pressed to identify a colleague who isn鈥檛 fed up with multiple-choice standardized testing. Lost instructional time. Data that isn鈥檛 timely or targeted enough to inform our efforts. Data that may only reflect a student鈥檚 performance on a particular day. Data that may say more about a student鈥檚 ability to take a multiple-choice test than it does about her mastery of content and skills.

And then there is the fact that this data is often used as a singular measure to evaluate students鈥 progress and teachers鈥 performance.

If you鈥檙e like me, your blood pressure is rising, just thinking about it.

But I want to make an argument for data-driven instruction. Effective teachers have always defined our students鈥 strengths and needs through classroom observations and by analyzing student work. Then we鈥檝e made choices about how we teach, based on that data 鈥 for it is data, even if it isn鈥檛 presented in terms of percentiles. We can鈥攁nd should鈥攃ontinue to collect, analyze, and apply data to inform instruction.

Here are some ways we can refocus our energy into using data as a powerful tool in teaching and learning:

Set clear, observable, and manageable learning objectives and specific goals for students鈥 learning. Identify the target of your instruction. What skills and knowledge do you expect students to learn? What information will tell you that they are successful?

When you can answer these two questions, you are on the right track to using data successfully. And dare I say, you may even like it. Meaningful data can make lesson planning easier and much more effective. When the target is clearly identified, it is easier to hit the mark.

Ideally, teachers should work collaboratively to identify common objectives reflecting high expectations for students within the same grade level and subject matter.

Ensure that your plans match up with what you are expecting students to do and learn. Ask yourself, 鈥淚s this lesson going to ignite learning and promote meaningful feedback about students鈥 progress toward the objectives I鈥檝e identified?鈥 Accept that there will be times when this seems overwhelming. Look past the 鈥淚 don鈥檛 have time for this鈥 mindset and start small. Team up with another colleague and begin your journey. Ask your peer to review your learning objectives, lesson plans, and assessments.

Collect meaningful data. As a special education teacher, I am accustomed to the logical process of data-driven instruction. I can readily use data to inform my instruction while still keeping true to the personal connection with my students that means so much.

When we鈥檙e truly linking objectives with lesson activities, collecting meaningful data becomes a natural part of the process.

But it鈥檚 important to think about what constitutes 鈥渕eaningful data鈥 for a student. For example, when my student鈥檚 target goal is to increase his literal and inferential levels of comprehension, I collect work that reflects his progress (or lack of progress) toward that measure. I place the work samples鈥攍ike a quick homework assignment, writing sample or classwork鈥攊n a folder for easy reference.

It鈥檚 best to plan formative assessments in advance, counting on them as a roadmap of high quality instruction. Know what you want to know鈥攁nd check for understanding every few weeks, viewing students鈥 progress over time.

Again, it is ideal when teachers work collaboratively to create formative assessments that reflect shared objectives and expectations.

Analyze the data鈥攁nd act on it. Data alone is meaningless. It鈥檚 what we do with the data that counts. When we collect and analyze data, we can get the information we need to create a successful learning environment and to make wise decisions about instruction.

But we must trust the objective information we gain from formative and interim assessments. Resist the temptation to blame students鈥 errors on tricky test questions. Accept the data as useful information.

This is yet another opportunity for teacher collaboration: analyzing one another鈥檚 data. In Paul Bambrick鈥檚 book , he recommends that assessment results be identified and shared with students within 48 hours (maximum one week turnaround). Teachers using common assessments can view cross-class results, creating an item analyses to see the frequency of errors for certain questions.

Which students need additional instruction, and what topics need re-teaching? Your data analysis can help you answer these questions, then create a plan of action. Maybe you will decide to weave specific subject matter, skills, or strategies into upcoming lesson plans. Perhaps you will share clear learning objectives with your students, so they better understand the purpose of each lesson. What鈥檚 more, they learn that you are using the work they share, which may inspire them to put forth their best efforts in the future.

Collaborate with colleagues to support the analysis (and implementation) of meaningful instructional and classroom assessment practice. Build and strengthen relationships with colleagues so that you can create and analyze meaningful instruction and assessment procedures.

Ideally, teachers need support within the culture of a school community. Teachers and administrators need to take part in professional development opportunities that introduce everyone to the basics, extending their understanding of meaningful assessments and data collection.

Yet teachers can be the leaders in developing a data-driven culture within their school. Start small鈥攃onnect with one colleague, or all the colleagues within your grade level or subject area. Consider scheduling weekly or monthly time to 鈥渢alk data,鈥 working together to create assessments, analyze data, and adapt lessons. Once you鈥檝e begun to see results, you can begin to branch out to encourage other teachers to do the same.

Focus on what matters most鈥攖he learning process. No matter how many data-based measures you are mandated to collect, remember that it鈥檚 all about the kids. Do not get bogged down with all the mandates. Translate the meaning of data-driven instruction into positive actions for you and for your students. When teachers concentrate on the learning process within their classrooms, the rest falls into place.

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