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Professional Learning Communities Data Teams Day One

Professional Learning Communities Data Teams

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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? - PowerPoint PPT Presentation

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Page 1: Professional Learning Communities Data Teams

Professional Learning Communities

Data TeamsDay One

Page 2: Professional Learning Communities Data Teams

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?

Page 3: Professional Learning Communities Data Teams

One of the Six Characteristics of a PLC

Collective InquiryPeople 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.

Page 4: Professional Learning Communities Data Teams

Today’s Objectives

Establish Triad Grade Level Teams

Review and Begin the Data Team Process

Grade Level Meeting Agenda

Page 5: Professional Learning Communities Data Teams

The data team process for results

Data Team

Process

Page 6: Professional Learning Communities Data Teams

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.

Page 7: Professional Learning Communities Data Teams

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

Page 8: Professional Learning Communities Data Teams

ROles•Introduce yourself to your new

teammates.•Select one person for each role:

•Facilitator •Recorder•Timekeeper•Focus Monitor

Grade Level Meeting Agenda

Page 9: Professional Learning Communities Data Teams

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

Page 10: Professional Learning Communities Data Teams

Analyzing dataReview District-wide Cluster Analysis

Data

Page 11: Professional Learning Communities Data Teams

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.

Page 12: Professional Learning Communities Data Teams

UnwrapPING Priority 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

Page 13: Professional Learning Communities Data Teams

UnwrapPING Priority Standard(S): Example

Concepts: (KNOW & UNDERSTAND)

Skills: ( DO & APPLY)

Main ideaSupporting details

(4) Distinguish (main ideas and supporting details)

RC 2.5 DISTINGUISH between main idea and supporting details in expository text.

Page 14: Professional Learning Communities Data Teams

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?

Page 15: Professional Learning Communities Data Teams

Common formative Assessment

Assessment Type Definition Examples

Selected Response Choosing the answer from a set of alternatives

-Multiple Choice-T/F Questions-Matching-Fill in the blank

Short Constructed Response

Providing a brief answer in writing or by drawing a diagram or picture

-Thinking Maps-Outline the major concepts-Brief written response questions

Extended Written Response

Writing the answer -List and explain the most important causes of an event-Compare and contrast two concepts Choose from a set of alternatives and justify the choice

Page 16: Professional Learning Communities Data Teams

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. 

1. 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.

Page 17: Professional Learning Communities Data Teams

Creating the CFAScoring Guide and Criteria

 4 3 2 1

Topic sentence is phrased in their own words.There are 2-3 details that are stated in their own words.

Topic sentence is restated.There are 2 general details.

No main idea is stated/confuses main idea with details.There are 1 - 2 details.

No main idea.There is 1 or no details.

Page 18: Professional Learning Communities Data Teams

Determine Criteriafor analyzing Student data

in a Selected-response CFA

 Already Advanced or Proficient.

Most Likely to be proficient at the end of the instructional time.

Likely to be proficient at the end of the instructional time.

Not Likely to be proficient at the end of the instructional time.

How many items correct?

9 or 10 correct out of 10 items on the CFA.

How many items correct?

7 or 8 correct out of 10 items on the CFA.

How many items correct?

6 or 5 correct out of 10 items on the CFA.

How many items correct?

Less than 5 correct out of 10 items on the CFA.

Page 19: Professional Learning Communities Data Teams

Collaboratively creating a CFA

Page 20: Professional Learning Communities Data Teams

Charting our data

Page 21: Professional Learning Communities Data Teams

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

Page 22: Professional Learning Communities Data Teams

Thank You