One of my main concerns for teaching is the focus of student data that is increasingly being used to evaluate the quality of a teacher. I agree whole-heartedly that student performance information should inform how a teacher measures progress towards learning targets and should inform the rate and method of instruction he chooses to hit those targets. The truth is, quality teachers have always been engaged enough in their professional work that they spend most of their lives worrying and planning on how to reach students who need a lift or a challenge. The problem is, formalizing and standardizing a practice of using data is not a skillset or disposition that all teachers bring to the classroom. It must be developed, and usually is, with experience. However, policy and laws are accelerating the need for those skills to be developed through punitive timelines that require we learn how to collect, analyze, and provide data that will not only be used to inform our teaching and learning, but may also preserve a livelihood we love.
Consider this: Your team, and the local paper, receives a pile of reports from a state test showing that your students aren’t up to par. Alas, you have been working with your team to determine what academic areas are historically weak in your building, grade, or department. From those discussions, you’ve identified what other assessment opportunities there are to help you understand what and how the kids in front of you are learning in these areas. With support from your principal, district peers, or a coach, the team has made it a point to learn new ways to analyze data together, giving you confidence to debunk any surface-level perceptions of your students’ learning. In fact, this analysis of data points occurs in consistent intervals as part of your “PD” because it informs your problem-solving process for your professional learning and improving instruction for your kids. Invested in this approach to professional learning, you now infrequently hear team members lament on the litany of external variables that keep your students from succeeding. Rather, they discuss how to help kids based on specific measures for the task at hand.
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When a team owns the things they can manage, by measuring it, they are able to explicitly and specifically cite data that supports the quality of instruction and professional learning that supports children. Learning the skills of data analysis (what to measure, how to measure it, how to evaluate it) is not commonly considered pedagogical, but must become part of that book of knowledge of teaching. This professional learning takes time to refine and apply to students, cohort after cohort, but is for their own academic good and our own professional security.
How do you see implementing this model into your work? What might enhance or inhibit it for you?
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