DATA T

EAMS A

T W

INDHAM M

IDDLE

SCHOOL

IN T

HE CONTE

XT OF

THE S

EED PILO

T

PRESENTE

D BY

JANE C

OOK

ADAPTED F

ROM MAT

ERIALS

DEVELO

PED B

Y TH

E

LEADERSHIP

AND LE

ARNING C

ENTER

DATA TEAMSSlide

2

WHAT ARE DATA TEAMS?

• Small grade-level, interdisciplinary or vertical content area teams that examine individual student work generated from standardized and non-standardized Indicators of Academic Growth and Development (IAGDs)

• Collaborative, structured, scheduled meetings that focus on the effectiveness of teaching and learning

DATA TEAMSSlide

3

DATA TEAM ACTIONS

“Data Teams adhere to continuous improvement cycles, examine patterns and trends, and establish specific timelines, roles, and responsibilities to facilitate analysis that results in action.”

(S. White, Beyond the Numbers, 2005, p. 18)

ILLUSTRATION OF CORE REQUIREMENTS OF SEED TEACHER EVALUATION PILOT

Student Growth and Development

(45%)

Whole-school Student Learning

Indicators or Student Feedback

(5%)

Observations of Performance and

Practice (40%)

Peer or Parent Feedback (10%)

Practice Rating (based on Cause

Data) (50%)

Outcome Rating(based on Effects

Data) (50%)

All factors are combined to reach each teacher’s final annualrating (as described in the Connecticut guidelines).

Adapted from CSDE Teacher Evaluation Orientation, 8/10/12

Slide 4

Student Learning Objectives (SLOs)

Observations & Surveys

DATA TEAMSSlide

5

THE DATA TEAM PROCESS

Step 1—Collect and chart data AKA “The Treasure Hunt”

Step 2—Analyze strengths and obstacles

Step 3—Establish SMART goals that are Specific, Measurable, Achievable, Relevant/Realistic, and Timely: Set, Review, Revise

Step 4—Select instructional strategies: What effective teaching strategies will adults use to help students achieve SMART goals?

Step 5—Determine results indicators: What measures will we use? How will we know that we have succeeded?

HOW THE DATA TEAM PROCESS ALIGNS WITH SETTING STUDENT LEARNING

OBJECTIVES IN SEEDThe Data Team Process Teacher Goal Setting

Forms A & B

Step 1: Treasure Hunt Baseline Data/Background Information

Step 2: Identify strengths and weaknesses

SLO & Rationale for objective

Step 3: Establish SMART goals Set IAGDs

Step 4: Select instructional strategies

Strategies/Actions to achieve SLOs

Step 5: Identify results indicators

Interim Assessments & Data Collection/Assessment of Progress Toward Achieving the SLO

DATA TEAMSSlide

7

DO DATA TEAMS REALLY WORK?

One district’s story:

80% free and reduced lunch

68% minority student enrollment

40+ languages

(D. Reeves, The Learning Leader, 2006)

ONE DISTRICT’S STORY:7 YEARS OF PROGRESS FROM 1998 TO 2005

Elementary Schools 1998 2005Schools with more than 50% of students proficient in Grade 3

11% 100% 

Middle Schools 1998 2005Schools with more than 50% of students passing English 

0% 100%

High Schools 1998 2005Schools with more than 80% of students passing English Language Arts 

17% 100%

Slide 8

D. Reeves, The Learning Leader, 2006

DATA TEAMSSlide

9

ASKING THE RIGHT QUESTIONS

• What does student achievement look like (in reading, math, science, writing, foreign language, tech ed, music, art, physical education, health)?

• What variables that affect student achievement are within our control?

• How do we currently explain our results in student achievement?

DATA TEAMSSlide 10

DATA WORTH COLLECTING: HAVE A PURPOSE

• How do we use data to inform instruction and improve student achievement?

• How do we determine which data are the most important to use, analyze, or review?

• In the absence of data, what is used as a basis for instructional decisions?

DATA TEAMSSlide 11

TWO TYPES OF DATA

“In the context of schools, the essence of holistic accountability is that we must consider not only the effect variable—test scores—but also the cause variables—the indicators in teaching, curriculum, parental involvement, leadership decisions, and a host of other factors that influence student achievement.”

(D. Reeves, Accountability for Learning, 2004)

DATA TEAMSSlide 12

TWO TYPES OF DATA

• Effect Data: Student achievement results from various measurements, both standardized and non-standardized – Related to SEED Outcome Rating

• Cause Data: Information based on actions of the adults in the system – Related to SEED Practice Rating

DATA TEAMS Slide 13

EFFECT DATA(AKA STUDENT ACHIEVEMENT DATA)

What types of effect dataare you collecting and using? What other

data do you need to analyze?

How does this effect data answer your questions about student achievement?

DATA TEAMSSlide

14

CAUSE DATA (AKA ADULT ACTIONS)

How do you use thiscause datato change instructional strategies?

How does this cause data support your school or team goals and focus?

What types of cause data are you collecting?

DATA TEAMSSlide 15

DATA SHOULD INVITE ACTION

“Data that is collected should be analyzed and used to make improvements (or analyzed to affirm current practices and stay the course).”

(S. White, Beyond the Numbers, 2005, p. 13)

If the data that you are collecting and analyzing is not helping inform your practice, i.e., planning, curriculum, instruction, or assessment, use different data.

- Jane Cook, WMS Data Team Training

DATA TEAMS Slide 16

THE LEADERSHIP/LEARNING MATRIX (L2 MATRIX)

LuckyHigh resultsLow understanding of antecedentsReplication of success unlikely success unlikely

LeadingHigh results High understanding of antecedentsReplication of success likely

Losing GroundLow resultsLow understanding of antecedentsReplication of failure likely

LearningLow resultsHigh understanding of antecedentsReplication of mistakes unlikely

Antecedents – Adult Actions/Interventions

Cause Data

Eff

ects

/Resu

lts D

ata

DATA TEAMS Slide 17

DATA-DRIVEN DECISION MAKING

“Effective analysis of data is a treasure hunt in which leaders and teachers find those professional practices—frequently unrecognized and buried amidst the test data—that can hold the keys to improved performance in the future.”

(D. Reeves, The Leader’s Guide to Standards, 2002)

DATA TEAMSSlide 18

STEPS TO CREATE AND SUSTAIN DATA TEAMS1. Collaborate 2. Communicate

expectations3. Form Data

Teams4. Identify Data

Team facilitators

5. Schedule meetings Data Team

meetings Principal and

Data Team facilitators

6. Post data and graphs

7. Create communication system

DATA TEAMS Slide 19

EFFECTIVE COLLABORATION

Collaborativeteams

Commitment toresults

Shared beliefs about student achievement

Continuousimprovement

Plan, Do, Study, Act (PDCA)

Total Quality cycle

Sharedinquiry

EffectiveCollaboration

DATA TEAMSSlide 20

WHAT IS NEEDED FOR EFFECTIVE DATA TEAMS?• Effect data (student achievement) and cause data

(adult actions)

• Authority to use the data for instructional and curricular decisions

• Supportive, involved building administrators

• Positive attitude

DATA TEAMSSlide 21

COLLABORATION: THE HEART OF DATA-DRIVEN DECISION MAKING• What is collaboration?

• What does collaboration look like?

• How do you start collaborating?

• How do you create a self-sustaining capacity for a collaborative culture?

DATA TEAMSSlide 22

COMMUNICATING EXPECTATIONS

• Do we indeed believe that all kids can learn?

• What does this belief look like in our school?

• How do we know that all students are learning?

• What changes do we need to make to align practices with beliefs?

DATA TEAMSSlide

23

DATA TEAM CONFIGURATIONS - VERTICAL DATA TEAMS

DATA TEAMSSlide

24

DATA TEAM CONFIGURATIONS – HORIZONTAL MIDDLE SCHOOL DATA TEAM

DATA TEAMSSlide

25

DATA TEAM CONFIGURATIONS - SPECIALS TEACHERS DATA TEAM

DATA TEAMSSlide 26

TEAM MEMBER RESPONSIBILITIES

Participate honestly,Respectfully,constructively

Assume a role Come prepared to meeting

Be punctual

Engage fully In the process

DATA TEAMSSlide

27

ROLES OF DATA TEAM MEMBERSRecorder: Takes minutesDistributes to Data Team leader, colleagues, administrators

Facilitator/Focus Monitor:Reminds members of tasks and purposeRefocuses dialogue on processes and agenda items

Timekeeper:Follows time frames allocated on the agendaInforms group of time frames during dialogue

Engaged Participant:ListensQuestionsContributesCommits

Are not expected to:Serve as pseudo-administratorsShoulder the responsibilities of the whole teamAddress peers and colleagues who do not want to

cooperateEvaluate colleagues’ performance

DATA TEAMSSlide 28

DATA TEAM LEADERS

DATA TEAMSSlide 29

DATA TEAM LEADERS

• Reflect on the needs of the staff and/or their team

• Work collaboratively to overcome obstacles

DATA TEAMSSlide 30

DATA TEAM LEADER AND PRINCIPAL DEBRIEFSMeet at least monthly to discussAchievement gapsSuccesses and challengesProgress monitoringAssessment schedules Intervention needsResourcesTeam needs

LESSONS FROM THE GEESE

FACT

1: As each goose flaps its wings, it creates an “uplift” for the birds that follow.   By flying in a “V” formation, the whole flock has 71% greater flying range than if each bird flew alone.

LESSON

People who share a common direction and sense of community can get where they are going quicker and easier, because they are traveling on the thrust of each other.

Source: http://www.leadershipi2i.com/geese.cfm

LESSONS FROM THE GEESE

FACT

2: When a goose falls out of formation, it suddenly feels the drag and resistance of flying alone.   It quickly moves back into formation to take advantage of the lifting power of the bird immediately in front of it.

LESSON

If we have as much sense as a goose, we stay in formation with those headed where we want to go.   We are willing to accept their help and give our help to others.

Source: http://www.leadershipi2i.com/geese.cfm

LESSONS FROM THE GEESE

FACT

3: When the lead bird tires, it rotates back into the formation to take advantage of the lifting power of the bird immediately in front of it.

LESSON

It pays to take turns doing the hard tasks and sharing leadership.   As with geese, people are interdependent on each others’ skills, capabilities, and unique arrangement of gifts, talents, or resources.

Source: http://www.leadershipi2i.com/geese.cfm

LESSONS FROM THE GEESEFACT

4: The geese flying in formation honk to encourage those up front to keep up their speed.

LESSON

We need to make sure our honking is encouraging.   In groups where there is encouragement, the production is much greater.   The power of encouragement (to stand by one’s heart or core values and to encourage the heart and core values of others) is the quality of honking we seek.

Source: http://www.leadershipi2i.com/geese.cfm

LESSONS FROM THE GEESEFACT

5: When a goose gets sick, wounded, or shot down, two geese drop out of formation and follow it down to help and protect it.   They stay with it until it dies or is able to fly again.   Then, they launch out with another formation to catch up with the flock.

LESSON

If we have as much sense as geese, we will stand by each other in difficult times as well as when we’re strong.

Source: http://www.leadershipi2i.com/geese.cfm

Burning Questions