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Professional Learning Communities Data Teams

Professional Learning Communities Data Teams. Day One. Guiding Questions of A Professional Learning Community. What do we want students to know? How will we know if they have learned it? What will we do for the students who have not learned it?

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Professional Learning Communities Data Teams

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  1. Professional Learning CommunitiesData Teams Day One

  2. Guiding Questions ofA Professional Learning Community • What do we want students to know? • How will we know if they have learned it? • What will we do for the students who have not learned it? • How will we extend and enrich the learning for students who have?

  3. One of the Six Characteristics of a PLCCollective Inquiry People in a learning community relentlessly question the status quo, seek new methods of teaching and learning, test the methods, and then reflect on the results. • They reflect publicly on their beliefs and challenge each other’s beliefs. • They share insights and hammer out common meanings. • They work jointly to plan and test actions and initiatives. • They coordinate their actions, so that the work of each individual contributes to the common effort.

  4. Today’s Objectives • Establish Triad Grade Level Teams • Review and Begin the Data Team Process Grade Level Meeting Agenda

  5. The data team process for results Data Team Process

  6. Data TEAm Definitions • Data Teams use common priority standards, generate common formative assessments, and use common scoring guides to monitor and analyze student performance. • Data Teams are small, grade-level, department course, content teams that examine work generated from a common formative assessment in order to drive instruction and improve professional practice. • Data Team have scheduled, collaborative, structured meetings that concentrate on the effectiveness of teaching and learning.

  7. Quick Write • Compare your current data team practice with the Data Team description. • How are the structures the same? How are they different? • Data Team Definitions and Reflection Page

  8. ROles • Introduce yourself to your new teammates. • Select one person for each role: • Facilitator • Recorder • Timekeeper • Focus Monitor Grade Level Meeting Agenda

  9. Setting Norms • If we are to have productive data team meetings then we…. (state the expected behaviors) • 1. • 2. • 3. • 4. • 5. Grade Level Meeting Agenda

  10. Analyzing data Review District-wide Cluster Analysis Data

  11. Guiding Questionsto Analyze Data • Which clusters carry the greatest value in terms of • Leverage, or skills to take across curricular areas? • Endurance, or knowledge to take to the next grade levels? • Success in life • State Test • Of those clusters, where is the biggest achievement gap? • As a grade level team agree upon… • the cluster you will focus on • priority standard or standards to take through the data team process.

  12. UnwrapPINGPriority StandardS • Unwrap the standards: Underline the concepts (nouns) and circle the skills (verbs) • Create a T- chart of “unwrapped” standards • Label level of rigor using Bloom’s Taxonomy • Unwrapping Standards Template

  13. UnwrapPINGPriority Standard(S): Example RC 2.5 DISTINGUISH between main idea and supporting details in expository text.

  14. Data teams begin by asking the question….. What evidence do we need to collect in order to know if students have mastered the concepts/skills for this data cycle?

  15. Common formative Assessment

  16. CFA Short constructed response Read the paragraph. Then, answer the questions. Snakes are interesting animals. They do not have any legs, so they move around by wiggling their entire body. They also do not have any eyelids, so their eyes are always open. Most snakes can also swallow things that are bigger than its head. These features and more make snakes interesting animals.  • What is the main idea in this paragraph? Write it in a sentence. 2. Write down 2 details from this paragraph? Write it in a sentence or two.

  17. Creating the CFAScoring Guide and Criteria

  18. Determine Criteriafor analyzing Student datain a Selected-response CFA

  19. Collaboratively creating a CFA

  20. Charting our data

  21. CFACommitments • Review Actions and Agreements • When will students be assessed? • How many days will be spent teaching this standard? • Determine Agenda Items for Next Meeting • Charted results from CFA • Reflection • Logistics for the Next Meeting on Oct. 4th • Rotate Roles • What materials will we need? Grade Level Meeting Agenda

  22. Thank You

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