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Collaborative Learning Teams

Collaborative Learning Teams/Professional Learning Communities

Teachers are experiencing success working in small data teams to promote student growth in the Ritenour School District. By collecting and analyzing student data, teams of teachers work together toward specific curriculum goals. In Ritenour, these teams are known as "CLT"s (Collaborative Learning Teams) or "PLC"s (Professional Learning Communities). Working in teams allows teachers to brainstorm, think critically, and collaborate to find the best way to help students meet their goals. For each goal/cycle, Ritenour data teams follow these guidelines:  

Data Teams Flow Chart 

  1. Examine the expectations. Look at the state standards or frameworks, district power or priority standards, "unwrapped" standards.
  2. Develop a curriculum map. Create a year-long pacing chart/calendar.
  3. Develop a common post-assessment. What must students master as a result of your teaching?
  4. Administer the short-cycle, common formative assessment (pre-instruction). You need to know where students are in their learning before instruction occurs. What data tell you that the lessons you are preparing are the lessons students need?
  5. Follow the Data Teams Process for Results. 
    (See below)
  6. Teach students using common instructional strategies.
  7. Administer the common formative assessment (post-instruction).
  8. Score the assessment and submit the data to the Data Team leader.
  9. Meet as a team to determine if the goal was met. 
    Determine next step for students who did not reach proficiency on the assessment. 
  10. Return to step 1. 
    Begin the process again with the next critical expectation based on the pacing guide. 

Data Teams Process for Results

  1. Collect and chart data. Data teams gather and display data from formative assessment results. Through the disaggregation in this step, teams will be able to plan for the acceleration of learning for all students.
  2. Analyze data and prioritize needs.  Data Teams identify the strengths and needs of student performance and then form inferences based on the data. Data Teams also prioritize by focusing on the most urgent needs of the learners.
  3. Set, review and revise incremental SMART goals. Teams collaboratively set incremental goals. These short-term goals are reviewed and revised throughout the data cycle. 
  4. Select common instructional strategies. Teams collaboratively identify research-based instructional strategies. The determination is based on the analysis in step 2.
  5. Determine results indicators. Data Teams create descriptors of successful strategy implementation as well as improvements to be seen in ongoing student work that would indicate the effectiveness of the selected strategies.
  6. Monitor and evaluate results throughout the entire process


Download a Google Data Workbook to help track student progress.

Case Study: Collaborative Learning Teams at Kratz Elementary

First-grade teachers at Kratz Elementary used their CLT to develop math skills in students, first dividing them into four groups (Proficient, Close to Proficient, Far to Go and Intervention) based on each student's performance on a common pre-test. Over the course of two months, teachers tracked student performance and spent time working with each proficiency level group. Their goal was for each classroom to achieve 59% proficiency in Addition Fluency within 10. By the end of the cycle, all classes met their goal.   Use this video playlist to learn what Collaborative Learning Teams look like for these first-grade teachers at Kratz Elementary, and consider how these same ideas could be utilized across different grade levels and subjects in Ritenour.