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3 steps to a data-driven PLC

How one school’s professional-learning community uses data to plan and shape instruction.

3 min read


3 steps to a data-driven PLC


Data can provide concrete evidence and valuable insights about the teaching and learning process. As such, my school uses data as an integral part of our professional learning communities (PLCs), and we’ve seen a substantial impact on student achievement – as well as teachers’ professional growth – as a result. 

During our data-driven PLCs, one of our building administrators helps lead a group of grade-level teachers as they collaboratively plan and target instructional strategies to drive student outcomes. We use a three-phase Instructional Learning Cycle as a basis for these PLCs. The three phases include:

Pre-planning. During this phase teachers meet and identify a unit of study and set a start and end date for this unit, such as three to five weeks. Teachers also identify the learning standards addressed by the given unit and work collaboratively to unwrap the standards to create learning targets using student-friendly language, as well as a pre-assessment. Teachers then administer the pre-assessment to students and place students into proficiency categories based on their results.

Instructional planning. During the next PLC meeting, teachers work together to analyze the pre-assessment data, create and agree upon a post assessment, and develop an instructional plan. At our school, we use an online program called i-Ready to help determine standard areas where students’ need extra support based on diagnostic results. We use this data to plan – and deliver – leveled literacy instruction with small group interventions in reading and writing and individualized instruction through i-Ready to meet each student’s unique needs. 

Follow up. After implementing the instructional plan and administering a post-assessment, teachers meet with their PLC to once again analyze students’ assessment data. They reflect on the results and discuss ways to improve their instructional strategies based on these results, and then repeat the cycle.

With the data-driven PLCs, teachers are continuously working together to review data – and make instructional adjustments based on that data – to help support student learning. This is a powerful process that has had a positive impact on students and teachers alike.

Matthew Brown is the principal of Forest View Elementary in Boon, MI. Forest View Elementary was recently recognized as a National Title I Distinguished School in part for its team approach to teaching and learning, focused professional development opportunities for staff, and individualized programs for student success.

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