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Coaching Data Teams

Developed by the Alliance of Regional Educational Service Centers for the Connecticut State Department of Education for

the CT Accountability for Learning Initiative (CALI)

by Jane Cook, Literacy and Technology Coach, EASTCONN &Beth McCaffery, School Improvement Coordinator, LEARN

Available in electronic format at http://calicoaches.wikispaces.com

Revised 10/14/10

http://calicoaches.wikispaces.com/

Table of Contents

Agenda...............................................................................................................................iiiSeven Norms of Collaboration..........................................................................................1Norms of Collaboration:...................................................................................................2Assessing Consistency in a Group or Key Work Setting...............................................2Affinity Diagram................................................................................................................3

Caution!...........................................................................................................................4Affinity Process...............................................................................................................4

Tools for Data Coaches: Affinity Diagram Characteristics of Effective Coaches.....5Tools for Data Coaches: Jigsaw.......................................................................................6Chapter 3 from Taking the Lead.....................................................................................6Roles and Responsibilities of Group Members...............................................................7Data Coach.........................................................................................................................8

Introduction......................................................................................................................8Knowledge and Skills......................................................................................................9Challenges........................................................................................................................9SNAPSHOT OF A COACH AS A DATA COACH.....................................................10

Characteristics of Effective Coaches..............................................................................11The Roles of the Data Coach...........................................................................................12Reflect and Write.............................................................................................................13Tools for Coaching Data Teams: Consensograms.......................................................14Consensogram Questions................................................................................................15Tools for Data Coaches: Task Deconstruction Protocol from Nancy Love..............16Deconstructing the Task A Looking at Student Work Protocol from Nancy Love.......17Multiple Measures...........................................................................................................18Concerns Based Adoption Model (CBAM)...................................................................20Adopting a Change..........................................................................................................21Data Coach Scenarios......................................................................................................22

Scenario A.....................................................................................................................22Scenario B......................................................................................................................24Scenario C......................................................................................................................26Scenario D.....................................................................................................................28

Collaborative Assessment Conference: Overview.......................................................29Technology Tools to Support Coaching Data Teams...................................................30

Retrieving CMT or CAPT Data for Performance Levels by Grade..............................30Simple Data Analysis with Microsoft Excel: Using Conditional Formatting to Apply Stoplight Highlighting to Data.......................................................................................31

Apply conditional formats to cells.............................................................................31About Filtering...........................................................................................................32

Taking Advantage of Some of Excel’s Special Features...................................32Specific Features of Excel.............................................................................................32

The COUNTIF Function............................................................................................32Example of Using the COUNTIF Function...........................................................32

COUNTIFS................................................................................................................33

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Example of COUNTIFS: Counting the Number of Boys at the Proficient or Above Level...........................................................................................................33

The COUNTA Function............................................................................................33Example of COUNTA: Counting the Number of Students by Using Their Names...............................................................................................................................34

Help with Creating Microsoft Excel Charts............................................................34Examples of Common Chart Types...........................................................................34Column......................................................................................................................34Bar..............................................................................................................................34Line............................................................................................................................34Pie..............................................................................................................................34Doughnut...................................................................................................................34Cone, Cylinder, and Pyramid Data Markers..............................................................35Creating a chart..........................................................................................................35Create a chart.............................................................................................................35Create a chart from nonadjacent selections...............................................................35

Reflecting on Coaching....................................................................................................36Microlabs Protocol...........................................................................................................37

Purpose..........................................................................................................................37Time allotted..................................................................................................................37Group format.................................................................................................................37Facilitation Tips.............................................................................................................37The Activity...................................................................................................................37Reflection questions following the activity...................................................................37

Activity Questions for Reflecting on Coaching.............................................................37Text Rendering Experience............................................................................................38COACHES HELP MINE THE DATA..........................................................................39“Willing to Be Disturbed”...............................................................................................41Questions for Data Team Leaders to Use When Facilitating Data Team Meetings..43

Step 1. Collect and chart data and results: What do the data say?.................................43Step 2. Analyze strengths and obstacles: Analyze, then prioritize................................43Step 3. Establish goals: set, review, revise....................................................................43Step 4. Select instructional strategies............................................................................44Step 5. Determine results indicators..............................................................................45Suggested Resources.....................................................................................................45

Introductory Level.....................................................................................................45Advanced Level.........................................................................................................45

Questions That Promote Reflection...............................................................................46Bibliography.....................................................................................................................49

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Coaching Data Teams8:30 AM - 3:30 PM

Time Agenda topics Outcomes8:30 - 9:30 AM Welcome!

Warm-up: Name Tent with Numbers (10 minutes) Picture Walk of Agenda and Handouts Overview of the Training – Purpose, Objectives, CALI

Initiative, SRBI Framework and Essential Questions to Consider (Slides 2-6) (5 minutes)

Norms for Collaboration (Slide 7) (15 minutes)

Meet and greet. Discuss what is planned for the training and participate in a warm-up activity to activate your schema.

9:30 – 10:30 AM Laying the Foundation Affinity Diagram: Characteristics of an Effective Data

Coach (Slides 8-12, Handout pp. 3-5) (30 minutes) Data Coaches Jigsaw Activity - Chapter 3 from

Taking theLead (Slides 13-20, Handout, pp. 6-10) (30 minutes)

Learn about the roles and characteristics of effective Data Coaches by using a total quality tool and an Effective Teaching Strategy.

10:30 – 10:45 AM Break Relax

10:45 – 12:00 Building Data Literacy Data Literacy - Consensogram Tool (Slides 21-22,

Handout pp. 14-15) (30 minutes) Task Deconstruction (Slides 23-25, Handout pp. 16-

17) (40 minutes) Multiple Measures of Data (Slide 26, Handout pp.

18-19) (20 minutes)

Experience a total quality tool to assist with coaching Data Teams. Lean how to use the Task Deconstruction protocol. Discuss the importance of Multiple Measures of Data.

12:00 – 12:30 PM Lunch Eat and enjoy!

12:30 – 12:45 PM CBAM (Slides 27-28, Handout pp. 20-21) (15 minutes)

12:45 – 1:45 PM Scenarios and Sustainability (Slides 29-30, Handout pp. 22-28) (60 minutes)

Apply learning through Case Study Scenarios.

1:45 – 2:15 PM Looking At Student Work: Collaborative Assessment (Slides 31-32, Handout pp. 29) (30 minutes)

Apply a LASW protocol that helps to create a shared understanding of text.

2:15 – 2:30 PM Break Relax

2:30 - 3:15 PM Technology Tools & Resources to Support Coaching Data Teams (Slides 33, Handout pp. 30-35) (45 minutes)

Excel Templates Exploring http://calicoaches.wikispaces.com and

other Web-based resources Text-based resources

View a demonstration of technology tools to support the work of Data Teams and Data Coaches. Learn about electronic & text-based resources .

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http://calicoaches.wikispaces.com/

3:15 - 3:30 PM Closure and Next Steps (Slides 34-35) (15 minutes) Debrief and share questions, comments, insights Reminder about other resources in handout (pp. 35-

48) Give feedback on today’s session

Debrief the session. Give feedback on the session.

Objectives: As a result of participating in this PD session, participants will be able to:1. Examine the research on coaching that supports DDDM. 2. Identify the roles and responsibilities of a coach and effective models for

coaching.3. Observe and apply coaching behaviors that influence best practices and

result in high student achievement.

Special notes: Please bring your good will and good humor and share them liberally.Contact info: Jane Cook, [email protected], 860-455-1510Beth McCaffery, [email protected], 860-434-4800

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mailto:[email protected]

mailto:[email protected]

Seven Norms of CollaborationSource: Center for Adaptive Schools Web site at http://csi.boisestate.edu/Improvement/7%20Norms.pdfFrom The Adaptive School: A Sourcebook for Developing Collaborative Groups (Garmston and Wellman,

1999, pp. 37-49)

1. Promoting a Spirit of InquiryExploring perceptions, assumptions, beliefs, and interpretations promotes the development of understanding. Inquiring into the ideas of others before advocating for one’s own ideas is important to productive dialogue and discussion.

2. PausingPausing before responding or asking a question allows time for thinking and enhances dialogue, discussion, and decision-making.

3. ParaphrasingUsing a paraphrase starter that is comfortable for you – “So…” or “As you are…” or “You’re thinking…” – and following the starter with an efficient paraphrase assists members of the group in hearing and understanding one another as they converse and make decisions.

4. ProbingUsing gentle open-ended probes or inquiries – “Please say more about…” or “I’m interested in…” or “I’d like to hear more about…” or “Then you are saying…” increases the clarity and precision of the group’s thinking.

5. Putting ideas on the TableIdeas are the heart of meaningful dialogue and discussion. Label the intention of your comments. For example: “Here is one idea…” or “One thought I have is…” or “Here is a possible approach…” or “Another consideration might be…”.

6. Paying Attention to Self and OthersMeaningful dialogue and discussion are facilitated when each group member is conscious of self and of others, and is aware of what (s)he is saying and how it is said as well as how others are responding. This includes paying attention to learning styles when planning, facilitating, and participating in group meetings and conversations.

7. Presuming Positive IntentionsAssuming that others’ intentions are positive promotes and facilitates meaningful dialogue and discussion, and prevents unintentional put-downs. Using positive intentions in speech is one manifestation of this norm.

© 2006 Center for Adaptive Schools at http://www.adaptiveschools.com/

Coaching Data Teams Handout Developed by the Alliance of Regional Educational Service Centers – Page 1

http://www.adaptiveschools.com/

http://csi.boisestate.edu/Improvement/7%20Norms.pdf

Norms of Collaboration:Assessing Consistency in a Group or Key Work Setting

1. Promoting a Spirit of Inquiry

Low High1 2 3 4

2. Pausing

Low High

3. Paraphrasing

Low High

4. Probing

Low High

5. Putting ideas on the table

Low High

6. Paying attention to self and others

Low High

7. Presuming positive intentions

Low High


© 2006 Center for Adaptive Schools at http://www.adaptiveschools.com/


http://www.adaptiveschools.com/

Affinity Diagram

What?The Affinity Diagram is an interactive data collection method which allows groups of people to identify and process large quantities of ideas in a very short time frame.

When?The Affinity process is used when teams need a non-judgmental process for collecting ideas.

Where?Affinity Diagrams work best with a large table (preferably round). People can rotate around the table to see contributions from other team members.

Why?Affinity Diagrams:

Are very spatial and interactive.

Allows groups to quickly collect and organize hundreds of ideas.

Give all ideas equal weight.

Encourage everyone to contribute.

Allow ideas to be grouped according to their natural relationships.

Are effective with all ages.

Give team members the opportunity to view ideas of other team members.


1993 Total Quality Learning, Inc.

1. A topic is chosen and clearly stated such as: “What do we need to know about TQL?”

2. All team members brainstorm ideas relating to the stated question or topic.

3. As brainstorming takes place write each idea on a 3” x 3” sticky note or note card.

4. Place team members’ ideas in the middle of a table or stick them on a smooth surface such as a mirror or Mylar board.

5. As a group silently place ideas in like categories.

6. Place a header card, describing the category, at the top of each column.

Brainstorming should be done in silence. Talking at this point tends to inhibit participation.

Ideas should be stated as briefly as possible; one word is often too brief, a sentence is often too detailed. Usually two to four words can adequately convey the idea.

Allow enough time for everyone to generate ideas, but not so much time that some members lose focus; three to five minutes is often adequate. However, remember that some of the most creative ideas come near the end of the brainstorming session.

It is important that all members of a team working on the task be able to see all of the ideas. Sometimes team members need to rotate the ideas in order for all to participate.

If a team member is being excluded it is the responsibility of the group to see that everyone participates.

If a stated idea is unclear any individual can ask for a clarification from its author, otherwise no talking is the rule.


Affinity Process Caution!

1993 Total Quality Learning, Inc.


Tools for Data Coaches: Affinity Diagram Characteristics of Effective Coaches

Instruction Sheet

1. Individually write 5 characteristics that an effective coach should possess on the post it notes provided.

2. At your table, share your responses and eliminate any that are exact duplicates.

3. Have one member of your group place your group’s large post it note responses on the chart paper posted around the room.

4. When directed, go to the chart paper and organize the post it notes into logical groupings, building an Affinity Diagram.

5. When asked, suggest a logical header for each group. The trainer will write a header card based on the group’s suggestions.

6. Summarize the results gathered by the coaches and debrief the Affinity Diagram activity.

7. Reflect and Write: Using the modified T-chart below to respond to this question: How might an affinity diagram be useful in your work as a Data Coach?

Characteristics of Affinity Diagrams

How I Can Use Affinity Diagrams When I Can Use Affinity Diagrams


Tools for Data Coaches: Jigsaw

Chapter 3 from Taking the LeadInstruction Sheet

Directions: 1. Count off by 4’s and get into your Expert Group by number. Use the Roles and

Responsibilities of Group Members on the next page to ensure that your work is productive.

2. Read the following sections in the chapter on pp. 9-11 in your handout: The 1’s will read the Introduction section. The 2’s will read the Knowledge and Skills section. The 3’s will read the Challenges section The 4’s will read the Snapshot of a Coach as a Data Coach section

3. In your group, develop a method and materials to teach your Home Group about your section. You’ll have 2.5 minutes to teach your section.

4. Return to your Home Group.5. Refer to p. 8 in your handout and assign roles for your Home Group.6. Teach your section to your Home Group. You’ll have 2.5 minutes to teach your section. 7. Each group will report out the insights from their learning in 1 minute or less.


Roles and Responsibilities of Group Members

Make sure that each person in your group is serving in at least one role. If you have more than 5 people in your group, have more than one Gatekeeper. If you have less than 5 people in your group, have group members serve in more than one role. Everyone should serve as a secondary facilitator, helping make the group’s work easier.

FACILITATOR... The Facilitator leads the discussion, making sure that everyone is fully participating. The word Facilitator comes from the word facilitate which means make easy.

SECONDARYFACILITATOR… Everyone in the group serves as a secondary

facilitator, helping make the group’s work easier.

SCRIBE... The Scribe writes for the group. In your Expert Group, everyone needs to serve as a Scribe as you’ll be taking the information back to share with your Home Group.

REPORTER... The Reporter reports the small group's work to the whole group. In your Expert Group, everyone needs to serve as a Reporter as you’ll be taking the information back to share with your Home Group.

TIMEKEEPER... The Timekeeper keeps track of the time and makes sure that the group finishes their task on time.

GATEKEEPER... The Gatekeeper makes sure that everyone is on task.


Data CoachSource: Chapter 3 from Taking the Lead: New Roles for Teachers and School-based Coaches

By Joellen Killion and Cindy Harrison, NSDC, 2006 pp. 35-39

Purpose: To ensure that student achievement data drives instructional decisions at the classroom and school level.

Introduction A relatively new role for instructional coaches is assisting teachers to look at a variety of data such as the four types of data recommended by Victoria Bernhardt (2004); student achievement, perception, demographic, and school process data. To help teachers use data most effectively and to facilitate their understanding of data, coaches can engage teachers in discussions about data. When data are available, teachers benefit from opportunities to work together to analyze data and to make decisions about how to use the data.

In this role, coaches help teams of teachers and/or individual teachers to examine data, understand their students’ strengths and weaknesses, and identify instructional strategies, structures, programs, or curriculum to address identified needs. Looking at and discussing cohort and student growth data enable teachers to move beyond the data to what needs to happen in their classrooms based on the data. Analyzing school and department - or grade level trends in the data is only the first step toward designing and adjusting classroom instruction to address the identified needs of students. Too often, the data dialogue stops here…patterns are identified along with student strengths and weaknesses but there is no collaboration or discussion on next steps for instruction.

Coaches frequently facilitate data dialogues with teams of teachers. Coaches often work with building administrators to identify which data to examine and how to display the data so that the analysis process with teachers is effective and efficient. Many coaches use student achievement data plus survey data. Giving teachers the opportunity to identify additional data they want to examine increases their buy-in to the discussion. Sometimes, a particular team of teachers will not buy into state or district tests but they will believe their common assessments are an accurate measure of learning.

In their work as data coaches, coaches use a process map about the data analysis cycle (see Figure 3.1) to help teachers make sense of the data.

It is important that time is not spent arguing about the validity of the tests but time is spent talking about teaching and learning.

During data dialogues, coaches facilitate interaction about what types of data are being examined, what the data mean, and what the next steps are by asking probing questions to guide data analysis.

Ensuring the use of more than one source of data for the discussion, coaches engage teachers in discussions on what each piece of data tells them along with what all pieces of data tell them. When data are analyzed, coaches help teachers find root causes, those factors contributing to what the data indicate.

Together, coaches and teachers generate theories about how the root causes impact student learning and use additional data to determine which of the multiple potential causes is a major contributor and something with the school’s circle of control. For example, schools often recognize that poverty is a major contributor to low achievement. When the root cause(s) are identified, both the coach and teachers work together to create and instructional plan to address the root cause. While schools cannot directly control poverty, teachers can


Act//instruct and assess

Plan actions/instruc

tion

Generate theory

Understand data

Analyze and interpret data

Identify root causes

Figure 3.1Analyzing formative

and summative student achievement data

integrate instructional approaches, such as building background knowledge and vocabulary to address poverty. Teachers implement the plan and assess student achievement on an ongoing basis to determine if the instructional plan is working and what adjustments they can make to improve it. When coaches focus conversations on data about student learning in a positive and productive way, the dialogue empowers teachers rather than threatens them. Assuming positive intentions for all teachers in the data dialogue will create a blame-free environment in which to have data discussions. Creating opportunities to identify areas of need is the first step in planning how to address those needs.

Knowledge and Skills

To lead data dialogues, coaches know how to establish a risk-free and blame-free environment that allows teachers to feel safe. An essential part of creating this environment is building effective norms for those discussions.

Coaches want to help teachers share data on what and how well their students are learning with one another rather than feel competitive or threatened by their peers. Coaches require a thorough understanding of various types and forms of available data, an understanding or what each data source assesses, and what conclusions can be validly drawn from any data set. Ensuring that more than one source of data is considered is a responsibility for coaches. Coaches use strong facilitation and questioning skills to formulate appropriate questions and to guide teachers in examining data thoroughly and accurately.

Coaches use questions to ensure deep discussions about the meaning of data, the patterns in the data and the actions to be taken based on results of analysis of the data. Knowing the types of questions as well as the sequence in which to ask the questions are skills coaches use to encourage thorough examination of the data.

Coaches also know how to assist teachers to plan and take specific actions based on the data to later their instruction. To determine what actions to take, coaches help teachers indentify the potential causes of problems they identify in the data.

The Fishbone Diagram is a quality management tool that allows teams to identify possible causes of identified problems. Knowing the most likely cause of gaps in student achievement helps teachers decide what to do to best address the problem. Coaches need to have knowledge (or know where to find it) about what actions to take to address the learning issues that are identified through the data. are often stymied by what to do next when they have tried their best to do what they knew how to do the first time around.

Organizational skills are essential for coaches as they do this data work. Being able to accurately assess team members’ reactions, questions, and types of discussions lead coaches to have the appropriate tools and structures available to design the data conversations. To facilitate data conversations, coaches use plans or agendas. The coach is also flexible enough to adjust the plan as the conversation moves ahead. The coach is well versed in a variety of tools and structures that can be used to analyze patterns in the data. Knowing what questions to ask to ensure that teachers deeply examine the available data for patterns and discrepancies among different groups of students or different teachers is essential for effective coaching.

Challenges

Coaches face four challenges in this role. One challenge, displaying the data in user-friendly formats, requires coaches to consider the level of sophistication of teachers in analyzing and interpreting data and adjusting the data displays to accommodate variations in teachers’ understanding of data. For example, coaches can help teachers make sense of data by displaying data in charts and graphs, such as bar and pie charts rather than tables. Using color, clear labels, and multiple different displays of the same data help teachers understand the data more easily.

A second challenge is the coaches’ preparation to understand the data before facilitating data dialogues. Coaches prepare a protocol — a series of questions —- to guide data analysis and interpretation and action


planning. Part of this conversation ensures that teachers address all inequities in the data and do not make excuses for some of the data being the way it is.

Assisting grade levels or departments to make decisions based on the data, the third challenge, is a necessary and difficult part of effective data dialogues. Coaches help teachers move beyond what the data mean to what actions will close the gap between where their students are and where they want them to be. This may mean spending time talking about possible theories of causation for certain results and then what to do about the results. Coaches ensure teachers move beyond why the data may be the way it is to what actions should occur in the classroom because of what has been learned from examining the data. Coaches are willing to push the hard conversation to ensure all inequities in the data are addressed.

The fourth challenge is creating a non-threatening, supportive environment that encourages teachers to be open and honest in the data analysis. Coaches assess what Bryk and Schneider (2004) call “relational trust” and design strategies to increase this trust between teachers and between teachers and administration if the school is to move forward with increasing student achievement through data conversations.


SNAPSHOT OF A COACH AS A DATA COACH

Nicky Romero, the student achievement coach at Cherokee Elementary School, works with the principal and assistant principal to plan the upcoming data conversation with 5th grade teachers. Everyone knows they are a tough group and resist changing their classroom practices. The coach and administrators look through the 5th grade data and identify trends and patterns. Following the meeting with administrators, Romero designs a data analysis protocol to use in the meeting with 5th grade teachers.

Romero facilitates the meeting and invites the principal to explain the 5th grade data and provide a short overview of the whole school’s results. Romero gives the team a structure data analysis protocol to guide their examination of grade-level data. The 5th grade teachers spend several hours examining data. First, teachers celebrate student successes and identify strategies they believe contributed to those successes. The protocol then guides the team to identify gaps between what they want students to know and be able to do and actual student performance.

Next, teachers complete an advanced organizer (created earlier by the coach) that tracks individual student achievement in literacy and math. Teachers record each student’s performance level and add comments about other factors that may influence a student’s performance. Focused on student needs and with problem areas identified, Romero encourages teachers to examine their instruction, curriculum, and resources to find leverage points for addressing gaps in student learning. Teachers identify possible interventions, including flexible grouping, ways to differentiate upcoming lessons, and alternative instructional resources and strategies. As teachers leave the meeting, they agree to meet with the coach and principal in five weeks to re-examine student progress.

Characteristics of Effective CoachesSource: Excerpt from Chapter 12 in

Taking the Lead: New Roles for Teachers and School-based Coaches By Joellen Killion and Cindy Harrison, NSDC, 2006, p. 99

Beliefs Is willing to learn Has a passion for ongoing development

and learning Holds the attitude that everyone is

important Believes in the capacity of others to

grow and develop Does not presume to have “The

Answer” Is committed to continuous

improvement Has moral purpose Can let go of being responsible for

another person’s behaviors

Coaching Skills Understands and applies knowledge

about adult development Listens skillfully Communicates effectively Uses effective questioning skills Understands and employs a specific

reflection process Diagnoses the needs of teachers Aligns support to the identified needs

of teachers

Content Expertise Possesses and applies appropriate, in-

depth content knowledge

Leadership Skills Understands and applies the knowledge

about change Communicates the vision of the school Aligns work with school goals Uses data to drive decisions Engages others in developing plans for

improvement Maintains a productive culture

Relationship Skills Desires to be a part of a team Works effectively with teachers and

principals Builds trusting relationships Is respected by peers Has patience for the learning process

Teaching Expertise Is skilled in instructional planning Has strong classroom organization and

management Has fluency with multiple methods of

delivering instruction Uses multiple methods for student

assessment Demonstrates success in their work as

classroom teachers Articulates their practice Reflects on their own practice Understands and uses national, state,

and local content standards and curriculum.


The Roles of the Data CoachSource: The Data Coach’s Guide to Improving Learning for All Students

by Nancy Love, et al, Corwin Press, 2008


Reflect and Write

Consider the knowledge, skills, roles and responsibilities that coaches have. Reflect and write

– At least one aspect of the work of coaches in the left-hand column – What you need or want to work on related to this aspect of your coaching work

Aspects of the Work of Data Coaches What I Need or Want to Work on Related to This Aspect of My Coaching Work


Tools for Coaching Data Teams: Consensograms

Consensograms are vivid visual displays of data generated by a group. The focus can be a group’s perception of commitment, belief, interest, knowledge, skill level, etc. The questions can be generated by a facilitator, the organization, the group, or several members. The consensogram offers an efficient way of gathering and displaying information from a large group that can be used immediately for processing.

Directions:1. Provide each member of the group with a small post-it note for each question to

be explored. (Be sure the post-its are all of the same size.)

2. Display the questions for consideration on a chart or overhead.

3. Ask participants to respond to each question, based on their own perceptions, using a scale of 0-100 (responses must be in increments of 10, with no negative numbers); and to place their response on a post-it note that will correspond to the question. NOTE: Numbers or colors can be useful to discriminate between questions.

4. Once all participants have created their response post-its, they should place them on the prepared charts in the form of a bar graph.

5. When all responses have been posted, the group can begin processing the data.


Consensogram

1. I believe that Data Coaches provide essential services to support the work of Data Teams.

0 10 20 30 40 50 60 70 80 90 100

ConsensogramPlease respond to the following on a scale from 0 to 100 in increments of 10.


0 10 20 30 40 50 60 70 80 90 100

3. I possess the knowledge I need to be a highly effective Data Coach.

0 10 20 30 40 50 60 70 80 90 100

4. I apply specific data coaching strategies and tools to support the work of Data Teams.

0 10 20 30 40 50 60 70 80 90 100

5. My school or district ensures that all Data Teams have an assigned Data Coach that supports and facilitates their work.

0 10 20 30 40 50 60 70 80 90 100

Consensogram Questions

Please respond to the following on a scale from 0 to 100 in increments of 10.


0 10 20 30 40 50 60 70 80 90 100

2. I possess the knowledge I need to be a highly effective Data Coach.

0 10 20 30 40 50 60 70 80 90 100

3. I apply specific data coaching strategies and tools to support the work of Data Teams.

0 10 20 30 40 50 60 70 80 90 100

4. My school or district ensures that all Data Teams have an assigned Data Coach that supports and facilitates their work.

0 10 20 30 40 50 60 70 80 90 100


Tools for Data Coaches: Task Deconstruction Protocol from Nancy Love

1. Share task (assessment item) with teachers.

2. Direct teachers to complete the task.

3. Brainstorm with teachers the concepts and skills students must know and be able to do in order to successfully / accurately complete the task.

4. Complete the task deconstruction matrix (see next page).

5. Examine student work for evidence of knowledge and skills in the work presented.

6. Identify patterns or areas of concern presented in the data resulting from analysis of student work.


Deconstructing the Task A Looking at Student Work Protocol from Nancy Love

Task:

Student

Know Know Know Know Know Do Do Do Do Do


Multiple Measures


Multiple Measures of DataVictoria Bernhardt

Examples of questions that encourage more focused data collection and deeper analysis.

When looking through one measure (lens):Snapshot Questions: How did the students in the school or grade score on a test? (Student

Learning) How many students are enrolled in the school this year?

(Demographics) What are parent, student, or teacher perceptions of the learning

environment? (Perceptions) What programs are operating in the school this year? (School

Processes)

‘Over Time’ Questions Are there differences in student scores on standardized tests over the

years? (Student Learning) How has enrollment in the school changed in the past three years?

(Demographics) How have parent, student, and/or teacher perceptions of the learning

environment changed? (Perceptions) What programs have operated in the school in the past five years?

(School Processes)

When looking through two measures (lenses):Digging In: Intersecting Two Measures Do students who attend school every day get better

grades? (Demographics by Student Learning) Do students with positive attitudes about school do better

academically, as measured by teacher assigned grades?(Perceptions by Student Learning)

Did students who were enrolled in interactive math programs, this year, perform better on Standardized Achievement Tests than those who took traditional math courses? (Student Learning by School Processes)

What strategies do third grade teachers use with students with native languages different from their own? (Demographics by School Processes)

Is there a difference in the way students enrolled in different programs perceive the learning environment? (Perceptions by School Processes)

Is there a gender difference in students’ perceptions of the learning environment? (Perceptions by Demographics)

Digging In: Understanding the Interaction of Two Measures Over TimeStandardized Achievement Scores (Student Learning) disaggregated by ethnicity (Demographics) over the past three years can help us see if the equality of scores, by ethnicity, is truly a trend or an initial fluctuation.

When looking through three measures (lenses):Drilling Down: Intersecting Three Measures Do students of different ethnicities perceive the learning environment

differently, and do they score differently on standardized achievement tests consistent with these perceptions? (Demographics by Perceptions by Student Learning)

Which program is making the biggest difference, with respect to student achievement for at risk students this year, and is there one group of students that is responding “better” to the processes? (School Processes by Student Learning by Demographics)

Is there a difference in students’ reports of what they like most about the school, by whether or not they participate in extracurricular activities? Do these students have higher grade point averages than students who do not participate in extracurricular activities? (Perceptions by Student Learning by School Processes)

What instructional process did the previously non-English speaking students enjoy most in their all-English classrooms this year? (Perceptions by Demographics by School Processes)

Drilling Down: Understanding the Interaction of Three Measures Over Time

Looking over time allows us to see trends, to really begin to understand the learning environment from the students’ perspectives, and to know how to deliver instruction to get the results we want from and for all students.

When looking through four measures (lenses):Mining Data: Intersecting Four Measures Are there differences in achievement scores for 8th grade

girls and boys who report that they like school, by the type of program and grade level in which they are enrolled? (Demographics by Perceptions by School Processes by Student Learning)

Are we achieving the purpose of our school, in all respects, for all students? (Student Learning by Demographics by Perceptions by School Processes)

Mining Data: Understanding the Interaction of Four Measures Over Time

Looking at the interaction of all four over time that we are allows us to predict if the actions, processes, and programs that we are establishing for students will meet the needs of all students.


Concerns Based Adoption Model (CBAM) Typical Expressions of Concern about an Innovation

Adapted from: http://www.nas.edu/rise/backg4a.htm

What stage are you in?Instructions: Circle the stage closest to the way you are feeling with regard to the initiative; whole numbers only, please .

Area of Focus

Stages of Concern Expression of Concern

IMPACT 6. Refocusing I have some ideas about something that would work even better.

5. Collaboration How can I relate what I am doing to what others are doing?

TASK 4. Consequence How is my use affecting learners? How can I refine it to have more impact?

3. Management I seem to be spending all my time getting materials ready.

SELF 2. Personal How will using it affect me?

1. Informational I would like to know more about it.

0. Awareness I am not concerned about it.Hall, George, & Rutherford, 1986


http://www.nas.edu/rise/backg4a.htm

Adopting a ChangeThe only person who likes change is a wet baby!

--Roger von Oech

What interests or excites you about the changes that will be taking place here?

What scares you about the changes that will be taking place here?


Data Coach Scenarios

Scenario AThe Grade 8 team recently administered a pre-instruction common formative assessment that consisted of six selected and two constructed response items relating to the C (reader-text connections) and D (examining content and structure) strands. Team’s norms are:Come preparedBe fully engaged and participate in the meetingRespect opinions that may differ from your ownEngage in active listening

Classroom Teacher A: “The data shows that 64% of our students scored below proficient on our most recent Reading Comprehension CFA.” Classroom Teacher B: “How do you know that?”Classroom Teacher C: “Let’s complete the chart and see if Teacher A’s math is correct.”Special Education Teacher: “Most of my kids names are in either the “far to go” or “In need of intensive intervention” columns.”Administrator: Sits quietly making notes in a notebook.

Data Facilitator: What are some things the data facilitator can say or do to help this team move forward and use their time more efficiently?

Suggestion 1: Suggestion 2: Suggestion 3:



Data Team Meeting Process and Minutes

Department/Grade/Team: 8th Grade Meeting Date: 10/12/10 Start/End Times: 9:00 – 10:00

Leader: Facilitator: Timekeeper: Focus Monitor: Recorder:

Members Present:

Academic Focus: Reading Comprehension: Reader-Text Connections and Examining Content and Structure

S.M.A.R.T. Goal:

Teacher Names # of Students Who Took the Assessment

# Students and names - Proficient or Higher

8 or higher

# and Names of Students likely to be Proficient at end of instructional time – Already Close6-7

# and Names of Students likely to be Proficient at end of instructional time – Far to go5-4

# of students Not Likely to be Proficient – Intervention Group and in need of extensive support3 or below

Teacher A 24 Leah, Carlos, Andy, Heather, Brendan, Connor, Kevin, Phoebe

Terri, Jane, Sue, John, Matt, Susan, Zach

Beth, Jennifer, Don, Chris, Amanda

Cameron, Lynn, Winston, John

Teacher B 23 Anne, Marie, Stephen, Jay, Kathryn, Joel, Veronica, Alyssa

Arthur, Kelvin, Brianna, Kelsey, Jack, Elizabeth

James, Vincent, Morgan, David, Thomas, Aaron, Lou, Keither

Darius, Devon,

Teacher C 21 Lia, Carlos, Andy, Heather, Mike, Steve, Daniel, Christopher

Terri, Jane, Sue, John, Matt, Susan, Zach,

Lisa, Kevin, Jan Lauren, Cody

Total 68 24 20 16 8

Progress towards goal:

We met our goal: __Yes __ No __ N/A

We did not meet our goal of ____ proficient and are ____ percentage points below our target goal.


Scenario BThe Grade 2 team just analyzed data from a recently administered pre-assessment CFA in Math designed to assess what students know and understand about patterns.Team’s norms are:Come preparedListenShare ideasStay on task

Classroom Teacher A: “You all have the data in front of you. Please consider our results and we will discuss what we can infer from those results.” Classroom Teacher B: “It seems that we have 44% of students struggling with understanding and generating / replicating patterns.”Classroom Teacher C: “Yes, I notice that Ellie struggled. She’s my most problematic student. I can’t get to follow classroom rules or behave. She is a distraction and I find her to be very difficult.”Special Education Teacher: “I have Ellie sometimes for extra support and the same things happen when she is with me.”Administrator: “Is there a plan for Ellie? Perhaps we should speak with Ronnie (School Psychologist) to see if there are any behavior plans we can implement to help Ellie be successful in the classroom.”Data Facilitator: What are some things the data facilitator can say or do to help this team refocus their discussion?





Department/Grade/Team: Grade 2 Meeting Date: 10/15/10 Start/End Times: 12:05-12:50


Members Present:

Academic Focus: Mathematics: Patterns

S.M.A.R.T. Goal:



10 or higher




Teacher A 18 Carlos, Jannette, Leisha, Ellen, Christy, Ray, Dana, Olivia, Tommy, Joey (10)

Brandon, Keith (2)

Sam, Kerwin, Rafael, Margaret (4)

Ruthie, Alex (2)

Teacher B 21 Louis, Erin, Taniah, Patrick, Anna, Francis, Larry, Ricky, Jeff, Aimee (10)

Tory, Brittany, Trevor, Kimberly (4)

Dylan, Courtney, Katie, Gervais (4)

Rebekkah, Nick, Alfred (3)

Teacher C 20 Lexi, Kenya, Terry, Dennis, Jan, Kevin, Zach, Matt, Susan, John, Sue (11)

Terri, Jane, John, Danielle (4)

Lisa, Kevin, Curtis (3)

Lauren, Cody (2)

Total 59 31 / 52%

10 / 17%

11 / 19%

7 / 12%





Scenario C

The Grade 6 interdisciplinary team recently administered a reading comprehension common formative assessment relating to Science content. The team is focusing on students’ ability to generate quality open-ended responses relating to author’s purpose and forming a general understanding. The assessment included multiple choice, true/false, and open-ended questions.

Team’s Norms are:Come prepared / on timeRespect all perspective and ideasHave an agenda

Language Arts Teacher: “Sorry I’m late, my substitute came in late. What are we doing?” Math Teacher: “Don’t worry, we’re all a little confused. I don’t think the agenda was created or if it was, it wasn’t sent to us.”Science Teacher: “I think I can get us on course. I have data from the CFA I administered for the team. Here it is. Let’s take a look.”Social Studies Teacher: “Does this include all students on our team? It doesn’t seem like all the sections are listed here.”

Data Facilitator: What are some things the data facilitator can say or do to help this team understand the important of having the right information available to them at the onset of the meeting?





Department/Grade/Team: Grade 6 Meeting Date: 10/18/10 Start/End Times: 11:20 – 12:30


Members Present:

Academic Focus: Reading Comprehension – Author’s Purpose and Forming a General Understanding

S.M.A.R.T. Goal:



15 or higher




Section 1 20 Michael, Bill, Laura, Rita, Rory (5)

Arthur, Marcus, Marybeth, Jill, Jonas, Brad, Pam, Kaylee (8)

Todd, Elaine, Angie, Will, Nick (5)

Eric, Greg (2)

Section 2 19 Nora, Lorna, Gayle, Seth, Nate (5)

Jordan, Kelsey, Mike, Madison, Allen, Bernadette, Harry (7)

Hailey, Oliver, Ben, Tim (4)

Victor, Suzanna, Casey (3)

Section 3 20 Shawn, Mark, Adam, Elise, Robyn, Nick, Kerrie, Paul, Breana (9)

Danny, Cathy, Owen, D.J., Leslie, Barbara (6)

Cindy, Donald, Karyn (3)

Axel, Anthony (2)

Section 4 21 Kathryn, Dillon, Audrey, Joanna, Kurt, Tristan, Hank (7)

Jennifer, Debra, Gregory, Hunter (4)

Josh, Shaina, Adam, Holly, Jonathan (5)

Jake, Andrew, Steve, Anna, Ernie (5)

Section 5 22 Meaghan, Marc, Matt, Clarissa (4)

Peter, Nick, Maddy, Nina, Derek (5)

Lily, Emma, Jesse, Jacob, Bryan, Karly, Aaron (7)

Harley, Bella, Zoey, Penny, Oscar, Brendan (6)

Total 102 30 / 29%

30 / 29% 24 / 24% 18 / 18%





Scenario DThe Grade 4 team has met, analyzed data, student work and decided on using graphic organizers as a way to help students draft / create their responses to open-ended questions. This team meeting will be spent discussing the specific ways in which to implement the instructional strategy that they have determined will be most helpful to their students.

Team’s Norms are:Be on timeEngage in the workEqual air timeBe committed to the process

Classroom Teacher A: “I brought samples of student work for us to look at.”Classroom Teacher B: “Yes, I did, too. By doing this we can better understand what some students are doing well and what other students are struggling with.”Classroom Teacher A: “Okay, so let’s take a look at Student #1’s work. What do we see this student doing well?”Classroom Teacher C: “I see that they are able to use specific details from the text through the use of a quotation, however, I don’t see any explanation or rationale for why the student chose the quote.”Classroom Teacher D: “Well, I recognize this handwriting and I know that this student meant that he also felt the same as the character by choosing the “frustrated and helpless” quote from the passage.Data Facilitator: What are some things the data facilitator can say or do to help this team analyze student work and have the essential instructional strategy conversation?




Collaborative Assessment Conference: OverviewSource: Excerpted, with slight adaptations, from Looking Together at Student Work

by Tina Blythe, David Allen, and Barbara S. Powell (New York: Teachers College Press, 1999)

http://www.nsrfharmony.org/protocol/doc/cac.pdf

A piece of student work has the potential to reveal not only the student’s mastery of the curriculum’s goals, but also a wealth of information about the student him/herself: his/her intellectual interests, his/her strengths, and his/her struggles. The Collaborative Assessment Conference was designed to give teachers a systematic way to mine this richness. It provides a structure by which teachers come together to look at a piece of work, first to determine what it reveals about the student and the issues s/he cares about, and then to consider how the student’s issues and concerns relate to the teacher’s goals for the student. The last part of the conversation – the discussion of classroom practice – grows out of these initial considerations.

The structure for the conference evolved from three key ideas:

• First, students use school assignments, especially open-ended ones, to tackle important problems in which they are personally interested. Sometimes these problems are the same ones that the teacher has assigned them to work on, sometimes not.

• Second, we can only begin to see and understand the serious work that students undertake if we suspend judgment long enough to look carefully and closely at what is actually in the work rather than what we hope to see in it.

• Third, we need the perspective of others — especially those who are not intimate with our goals for our students — to help us to see aspects of the student and the work that would otherwise escape us, and we need others to help us generate ideas about how to use this information to shape our daily practice.

Since 1988, when Steve Seidel and his colleagues at Project Zero developed this process, the Collaborative Assessment Conference has been used in a variety of ways: to give teachers the opportunity to hone their ability to look closely at and interpret students’ work; to explore the strengths and needs of a particular child; to reflect on the work collected in student portfolios; to foster conversations among faculty about the kind of work students are doing and how faculty can best support that work.

In the Collaborative Assessment Conference, the presenting teacher brings a piece of student work to share with a group of five to ten colleagues (usually other teachers and administrators). The process begins with the presenting teacher showing (or distributing copies of) the piece to the group. Coaching Data Teams Handout Developed by the Alliance of Regional Educational Service Centers – Page 31

http://www.nsrfharmony.org/protocol/doc/cac.pdf

Throughout the first part of the conference, the presenting teacher says nothing, giving no information about the student, the assignment, or the context in which the student worked.Protocols are most powerful and effective when used within an ongoing professional learning community such as a Critical Friends Group® and facilitated by a skilled coach. To learn more about professional learning communities and seminars for new or experienced coaches, please visit the National School Reform Faculty website at www.nsrfharmony.org.


Technology Tools to Support Coaching Data Teams

Retrieving CMT or CAPT Data for Performance Levels by Grade

1. Log into CMT and CAPT Reports with your district login at http://www.ctreports.com/.2. Choose Performance Level Report.3. Choose the year and the grade level and click on Submit.4. When the graph comes up, click on Report Type and choose Report Table and then click

on Submit.

5. To get individual student names and levels, click on the number for the level, e.g., 30.6 in the Below Basic in Math in the Performance Level Report above. This will launch another table with individual student names.

6. To download any of these as reports, click on Download Report and then click on As Excel CSV and a copy will download into Excel where you can manipulate the data more easily. Be sure to save it with a new name as an Excel file, not a CSV file, when you save it on your computer.


http://www.ctreports.com/

Simple Data Analysis with Microsoft Excel: Using Conditional Formatting to Apply Stoplight Highlighting to Data

Source: Adapted from Microsoft Excel Help Index

Conditional formatting allows you to highlight formula results or other cell values that you want to monitor. For example, suppose a cell/s contains the level for the CMT test. Microsoft Excel can be told to apply red shading to the cell if the score falls below a certain number such as a 1 which identifies the Below Basic level on the CMT. A second condition can be set to format the cell/s in yellow for 2, which is the Basic level on the CMT. A third condition can be set to format the cell/s in green for >2, which is the Proficient or above level on the CMT. If the value of conditionally formatted cells changes and no longer meets the specified condition, Microsoft Excel no longer applies the red, yellow or green shading. Conditional formats remain applied to the cells until you remove them, even though none of the conditions are met and the specified cell formats are not displayed.

What do you want to do?Apply conditional formats to cellsChange, add, or remove conditional formatsFind cells that have conditional formats

Apply conditional formats to cells1 Select the cells you want to format.2 On the Format menu, click Conditional Formatting.3 To use values in the selected cells as the formatting criteria, click Cell Value Is, select the comparison phrase and then type a value in the appropriate box. You can enter a constant value or a formula; you must include an equal sign (=) before the formula.NOTE: To evaluate data or a condition other than the values in the selected cells, use a formula as the formatting criteria. Click Formula Is in the box on the left, and then enter the formula in the box on the right. The formula must evaluate to a logical value of TRUE or FALSE.4 Click Format.5 Select the font style, font color, underlining, borders, shading, or patterns you want to apply. NOTE: Microsoft Excel applies the selected formats only if the cell value meets the condition or if the formula returns a value of TRUE.6 To add another condition, click Add, and then repeat steps 3-5. You can specify up to three conditions.Tips: You can copy conditional formats to other cells. Select the cells that have the conditional

formats you want to copy, click on the Format Painter (the small paintbrush icon on the Standard toolbar), and then select the cells you want to have the same conditional formats. To copy only the conditional formats, select the cells you want to format and include at least one cell in the selection that has the conditional formats you want to copy. Click Conditional Formatting on the Format menu, and then click OK.

To examine data such as scores on the CMT, select the data and specify three conditions. Use red font color or cell shading for cell values less than the specified minimum (below


intervention level), yellow for values within a specified range (at basic level), and green for values greater than a specified maximum (at proficient level).

About Filtering

Filtering is a quick and easy way to find and work with a subset of data in a list. A filtered list displays only the rows that meet the criteria that you specify for a column. Microsoft Excel provides two commands for filtering lists:

AutoFilter, which includes filter by selection, for simple criteria Advanced Filter, for more complex criteria

Unlike sorting, filtering does not rearrange a list. Filtering temporarily hides rows you do not want displayed and displays rows that meet the criteria that you set.

When Excel filters rows, you can edit, format, chart, and print your list subset without rearranging or moving it. However, you can also copy and paste the filtered data into a new worksheet if you wish so that it becomes a new dataset that you can further manipulate without affecting the data in the original worksheet.

Taking Advantage of Some of Excel’s Special Features

Specific Features of Excel

The COUNTIF Function

The COUNTIF function counts the number of cells within a range that meet a given criteria.

The Syntax for COUNTIF includes identifying the range of cells that contain the given criteria and the actual criteria which can be numbers or words.

Range is the range of cells from which you want to count cells.

Criteria is the criteria in the form of a number, expression, or text that defines which cells will be counted. For example, criteria can be expressed as 32, "32", ">32", "apples".

Example of Using the COUNTIF FunctionTo use the COUNTIF function, do the following:1. Put the cursor in the cell where you want the total count, click on the Function (fx) icon, type

in COUNTIF in the Insert Function dialog box and click on OK (or type the equals [=] sign and click on the down arrow next to the functions and select COUNTIF).

2. Use the mouse to highlight the cells that you want Excel to count – that will automatically appear in the range line within the Function Arguments dialog box.

3. On the Criteria line within the Function Arguments dialog box, type in the criteria that you want Excel to look for as it is counting.


4. Click on OK. A total count should appear in the cell.

In the example below, Excel is being asked to look at the variables in all of the cells between cell L2 and cell L244. It is being asked to count any that are greater than 910. The total returned value will be the number of cells that contain any number that is larger than 910.

You can also get Excel to count words or phrases, not just numbers or values. Just make sure that all of words that you are asking Excel to count are spelled exactly the same way or you will get an inaccurate count.

COUNTIFSIn Excel 2007 and above, the COUNTIFS function has been added. The COUNTIFS formula is a powerful feature that allows you to count based on more than one criteria. When you use COUNTIFS, Excel will count only those items that meet all of the criteria.

Example of COUNTIFS: Counting the Number of Boys at the Proficient or Above LevelYou’ve received or downloaded student data that has CMT or CAPT scores in a worksheet with the student demographic data. You can use the COUNTIFS formula to count how many boys scored at the Proficient or above level. To do this, create a COUNTIFS formula to count the column that contains the Level data (Proficient or above is a Level of 3, 4 or 5) and the column that contains the Gender data (boys are M or Male, depending on your dataset). Within seconds, Excel will return the N of boys that scored at the Proficient or above level.

The COUNTA FunctionIf you wish to count for any cell that is not blank, use the COUNTA function instead of the COUNTIF function. You can put your cursor in the cell at the bottom of the column that you wish to count and follow the steps above using Excel’s Function Arguments Wizard or you can just type in the formula. Use the following syntax if you are typing in a COUNTA function:

=COUNTA(A3:A210)


The formula above is asking Excel to look at the contents of each cell in Column A from Row 3 to Row 210 to determine whether it contains any information (regardless of whether it is text or numbers). If the cell is not totally blank, Excel will count it. An example of when this would be helpful is:

Example of COUNTA: Counting the Number of Students by Using Their NamesYou’ve received or downloaded student data that has a column with the students’ names. The spreadsheet also contains several header rows above where the data begins. If you want to count the number of students whose data you have received, run a COUNTA formula at the bottom of the names in the column or row. Make sure that you don’t include the header row in your COUNTA formula. This is a very quick way to get the N of students in the dataset.

Help with Creating Microsoft Excel Charts

Once you have entered spreadsheet data, you can then use Excel to create charts and graphs to display the data. Charts and graphs are linked to the worksheet data they are created from and are updated when you change the worksheet data. Once data is displayed visually, it is much easier to analyze and interpret. Use Excel to "let your data do the talking".

Examples of Common Chart Types

ColumnA column chart shows data changes over a period of time or illustrates comparisons among items. Categories are organized horizontally, values vertically, to emphasize variation over time. Stacked column charts show the relationship of individual items to the whole. The 3-D perspective column chart compares data points along two axes.

BarA bar chart illustrates comparisons among individual items. Categories are organized vertically, values horizontally, to focus on comparing values and to place less emphasis on time.

LineA line chart shows trends in data at equal intervals.

PieA pie chart shows the proportional size of items that make up a data series to the sum of the items. It always shows only one data series and is useful when you want to emphasize a significant element.

DoughnutLike a pie chart, a doughnut chart shows the relationship of parts to a whole, but it can contain more than one data series. Each ring of the doughnut chart represents a data series.


Cone, Cylinder, and Pyramid Data MarkersThe cone, cylinder and pyramid data markers can lend a dramatic effect to 3-D column and bar charts.

Creating a chartYou can create charts from cells or ranges that are adjacent and from cells or ranges that are not next to one another. What do you want to do?

Create a chartCreate a chart from nonadjacent selectionsCreate a default chart in one step

Create a chart

You can create either an embedded chart or a chart sheet. An embedded chart stays in the same worksheet with the data. A chart sheet is a new worksheet that contain only the chart.

1 Select the cells that contain the data that you want to appear in the chart. If you want the column and row labels to appear in the chart, include the cells that contain them in the selection.2 Click Chart Wizard (the button on the Standard Menu that looks like a column graph). The Chart Wizard will guide you through the steps of making or modifying a chart. 3 Follow the instructions in the Chart Wizard.

Tip: If your worksheet has multiple levels of row and column labels, your chart can also display those levels. When you create the chart, include the row and column labels for each level in your selection. To preserve the hierarchy when you add data to the chart, change the cell range used to create the chart.

Create a chart from nonadjacent selections1 Select the first group of cells that contain the data you want to include.2 While holding down CTRL, select any additional cell groups you want to include.The nonadjacent selections must form a rectangle.3 Click Chart Wizard button.4 Follow the instructions in the Chart Wizard.


Reflecting on CoachingAs an individual, review the quotes below and put an asterisk in front of the one or two that most intrigue you. Spend three minutes writing about why those quotes resonate for you and how they apply to coaching.

I cannot teach anybody anything, I can only make them think. – Socrates

You cannot teach a man anything. You can only help him discover it within himself.- Galileo Galilei

The only kind of learning which significantly influences behavior is self-discovered or self-appropriated learning - truth that has been assimilated in experience.

- Carl Rogers

I never teach my pupils; I only attempt to provide the conditions in which they can learn. - Albert Einstein

The real voyage of discovery consists not in seeking new lands, but in seeing with new eyes.

- Marcel Proust, French novelist

The mediocre teacher tells. The good teacher explains. The superior teacher demonstrates. The great teacher inspires

- William Arthur Ward

The biggest enemy to learning is the talking teacher. - John Holt

The art of teaching is the art of assisting discovery. - Mark Van Doren, poet

Nothing is more terrible than activity without insight. - Thomas Calyle, Scottish essayist and historian

Creative thinking may mean simply the realization that there's no particular virtue in doing things the way they have always been done.

- Rudolph Flesch

Before you become too entranced with gorgeous gadgets and mesmerizing video displays, let me remind you that information is not knowledge, knowledge is not wisdom, and wisdom is not foresight. Each grows out of the other, and we need them all.

- Arthur C. Clarke

“In the sixteenth century the English language defined ‘coach’ as a carriage, a vehicle for conveying valued people from where they are to where they want to be.”

Source: http://coaching.gc.ca/documents/coaching_mentoring_apex_presentation_e.asp


http://coaching.gc.ca/documents/coaching_mentoring_apex_presentation_e.asp

Microlabs ProtocolSource: National School Reform Faculty - http://www.nsrfharmony.org/protocol/a_z.html

PurposeTo address a specific sequence of questions in a structured format with small groups, using active listening skills.

Time allottedAbout 8 minutes per question — this works best with a series of no more than three questions.

Group formatForm triads — either with the people you’re sitting near — or find others in the group you don’t know well. Number off — 1, 2, 3.

Facilitation Tips“I’ll direct what we will talk about. Each person will have one minute (or, sometimes, 2 minutes, depending on the group and the question) to talk about a question when it’s their turn. While the person is speaking, the other two in the group simply listen. When the time is up, the next person speaks, and so on. I’ll tell you when to switch.” Emphasize that talk has to stop when you call time, and conversely, that if the person is done speaking before time is up, the three people should sit in silence, using the time to reflect. Review the Guidelines (previous page).

The quality of the questions matter in this exercise. The questions should be ones that are important to the group.

The ActivityAfter instructing the group, read the first question aloud (twice). Give everyone time to write in preparation. Then, tell people when to begin, and then tell them when each one/two minute segment is up. On the first question, begin with person #1, then #2, then #3. Then read the next question aloud. On the second question, begin with #2, then #3, then #1. On the third question, begin with #3, then #1, then #2.

Reflection questions following the activity What did you hear that was significant? What key ideas or insights were shared? How did this go for you? What worked well, and what was difficult? Why? How might your conversations have been different had we not used this protocol? What are the advantages/disadvantages of using this activity? When would you use this

protocol? What would you want to keep in mind as someone facilitating this activity?

Activity Questions for Reflecting on Coaching1. Which quote did you most resonate with? Why?2. What connections can you make between the quote and coaching?3. How does your conversation inform your practice as a coach of Data Teams?


http://www.nsrfharmony.org/protocol/a_z.html

Text Rendering ExperienceDeveloped in the field by educators affiliated with National School Reform Faculty

Source: http://www.nsrfharmony.org/protocol/learning_texts.html

PurposeTo collaboratively construct meaning, clarify, and expand our thinking about a text or document.

Roles A facilitator to guide the process.

A scribe to track the phrases and words that are shared.

Set UpTake a few moments to review the document and mark the sentence, the phrase, and the word that you think is particularly important for our work.

Steps1. First Round: Each person shares a sentence from the document that he/she

thinks/feels is particularly significant.

2. Second Round: Each person shares a phrase that he/she thinks/feels is particularly significant. The scribe records each phrase.

3. Third Round: Each person shares the word that he/she thinks/feels is particularly significant. The scribe records each word.

4. The group discusses what they heard and what it says about the document.

5. The group shares the words that emerged and any new insights about the document.

6. The group debriefs the text rendering process.


http://www.nsrfharmony.org/protocol/learning_texts.html

COACHES HELP MINE THE DATA Joellen Killion, Deputy Executive Director of NSDC

Data-driven decisions and actions target identified needs and fit more appropriately within the context in which they are implemented. Teacher leaders acting as data coaches create a culture that values data as information for improved professional practice. When those data relate to student learning, coaches have five key responsibilities to help teachers use data effectively. They include: Creating a safe, blame-free environment for data analysis; Teaching data access and organization; Teaching analysis and interpretation of data from multiple sources; Engaging teachers in data analysis and interpretation to determine student and teacher needs; and Designing an action plan that incorporates professional learning to improve student achievement based on data analysis.

Creating a safe environment

When the culture of a school in which teachers work provides a safe, blame-free environment for data use, teachers more eagerly seek data to inform their practice. The key to creating safety in data analysis is keeping individual teacher data private, beginning with developing teachers’ skills in understanding and analyzing data, and setting norms that include keeping the focus on student learning. A safe environment keeps the focus on issues rather than people, engages people in an appreciative inquiry approach rather than a deficit approach to a situation, and results in a plan that energizes and motivates people. Teachers can identify and analyze what is working for their students by focusing on what is working, seeking to understand the reasons for the success, and replicating those practices. Key questions coaches and teachers ask are: “What’s working? How do we know? What makes it work? Teachers will have an easier time confronting the realities of student learning gaps and how to address them if they are comfortable with the data and trust the process and the facilitator.

Facilitation of data analysis promotes safety. The facilitator works with the team of teachers to set Norms and uses a protocol, or a guideline, for the data conversation. The protocol makes the process known to all. A data analysis protocol offers a set of guiding questions for looking at student data whether those data are from state tests, common district assessments, or classroom assessments.

Teaching data access and organization

The accessibility and format of data make a difference in how easy they are to use. When data coaches help teachers know how to access data and organize them into use-friendly formats, teachers are likely to use data more readily. The opposite is true, too. When teachers can’t access data easily from their classroom or school computers or when they wait weeks to receive data reports, they are likely to avoid using data. Data coaches can begin by teaching how to access data and how to request various forms of reports. In the process, the coach provides tips on which reports will answer specific questions.

Teaching data analysis and interpretation

Data coaches help teachers know how to analyze and interpret data. Essentially, the coach prepares teachers to engage in analysis by ensuring that they have fundamental knowledge. Questions such as the one below can be used to prepare teachers for analyzing any data set.

1. What is this assessment measuring?2. What are the characteristics of the students

involved in this assessment?3. What type of assessment was used?4. What type of conclusions can be drawn

from this type of assessment?5. How many students were assessed?

The coach may model or engage teachers in analyzing school-wide or district data using a protocol so teachers are familiar with the process before they work on their own data.


Designing action plans with professional learning

The data analysis and interpretation process includes moving from data to action. Once data are analyzed, the work continues with forming conclusions, identifying potential root causes, and developing plans of action that include goals, indicators of success, timelines for achieving the goals, and benchmarks to mark progress. For example, if teachers discover from an analysis of state tests and the district common benchmark assessments that students’ problem-solving skills are below standard, then they consider give possible root causes that might contribute to the problem and which they can control. These areas are instruction, curriculum, time, teachers’ content knowledge and/or pedagogy, and instructional resources. Frequently, when teachers engage in indentifying root causes they will identify causes that are not within their realm of control, such as student demographics. Coaches can accelerate identification of appropriate interventions if they help teachers focus on what teachers can change to improve student academic success. Teachers might write a goal such as: Third quarter math goal: 85% of the 5th grade students will demonstrate proficiency in problem solving on the third quarter benchmark assessment. Coaches, working collaboratively with teachers, identify the specific actions to incorporate into their plan. For example, teachers may commit to learn multiple problem-solving strategies and ways to help students determine which is most appropriate to use. Then teachers may develop common lesson plans in which they integrate their new knowledge. Teachers may look at the number of opportunities they provide students to practice problem solving in both guided and independent situations. Finally, they may develop a common assessment to measure student progress midway through the third quarter. When data coaches build teachers’ knowledge about data analysis and assessment, develop their competence and comfort with data analysis, and facilitate teacher professional learning and planning to move from data to action, teachers and students benefit. Teachers have the information to focus instruction more specifically on student learning needs. They can also focus their own professional learning on specific student learning needs thereby increasing its purposefulness and its results.

Students are the big winners because they are the beneficiaries of refined teacher instructional practice.

DATA ANALYSIS PROTOCOLAnalyzing data: Guiding questions

1. What areas of students’ performance are at or above expectations?

2. What areas of student performance are below expectations?

3. How did various groups (e.g. gender, race, socioeconomic, disability, English proficiency) of students perform?

4. What are other data telling us about student performance in this area?

5. What confirm what we already know? What challenges what we thought?

6. What important observations seem to “pop out” from the data? Surprising observations? Unexpected observations?

7. What patterns or trends appear?

8. What similarities and differences exist across various data sources?

9. What do we observe at the school level? The grade level? The classroom level?

10. What are some things we have not yet explored? What other data do we want to examine?

Source: Teachers Teaching Teachers, February 2008, National Staff Development Council. Copied with permission of the National Staff Development Council, www.nsdc.org, 2008. All rights reserved.


http://www.nsdc.org/

“Willing to Be Disturbed”

Source: Wheatley, Margaret J. Turning to One Another: Simple Conversations to Restore Hope to the Future, San Francisco: Berrett-Koshler Publishers, Inc., 2002http://www.ode.state.or.us/opportunities/grants/saelp/willing-to-be-disturbed.pdf

As we work together to restore hope to the future, we need to include a new and strange ally—our willingness to be disturbed. Our willingness to have our beliefs and ideas challenged by what others think. No one person or perspective can give us the answers we need to the problems of today. Paradoxically, we can only find those answers by admitting we don’t know. We have to be willing to let go of our certainty and expect ourselves to be confused for a time.

We weren’t trained to admit we don’t know. Most of us were taught to sound certain and confident, to state our opinion as if it were true. We haven’t been rewarded for being confused. Or for asking more questions rather than giving quick answers. We’ve also spent many years listening to others mainly to determine whether we agree with them or not. We don’t have time or interest to sit and listen to those who think differently than we do.

But the world now is quite perplexing. We no longer live in those sweet, slow days when life felt predictable, when we actually knew what to do next. We live in a complex world, we often don’t know what’s going on, and we won’t be able to understand its complexity unless we spend more time in not knowing.

It is very difficult to give up our certainties—our positions, our beliefs, our explanations. These help define us; they lie at the heart of our personal identity. Yet I believe we will succeed in changing this world only if we can think and work together in new ways. Curiosity is what we need. We don’t have to let go of what we believe, but we do need to be curious about what someone else believes. We do need to acknowledge that their way of interpreting the world might be essential to our survival.

We live in a dense and tangled global system. Because we live in different parts of this complexity, and because no two people are physically identical, we each experience life differently. It’s impossible for any two people to ever see things exactly the same. You can test this out for yourself. Take any event that you’ve shared with others (a speech, a movie, a current event, a major problem) and ask your colleagues and friends to describe their interpretation of that event. I think you’ll be amazed at how many different explanations you’ll hear. Once you get a sense of diversity, try asking even more colleagues. You’ll end up with a rich tapestry of interpretations that are much more interesting than any single one.

To be curious about how someone else interprets things, we have to be willing to admit that we’re not capable of figuring things out alone. If our solutions don’t work as well as we want them to, if our explanations of why something happened don’t feel sufficient, it’s time to begin asking others about what they see and think. When so many interpretations are available, I can’t understand why we would be satisfied with superficial conversations where we pretend to agree with one another.


http://www.ode.state.or.us/opportunities/grants/saelp/willing-to-be-disturbed.pdf

There are many ways to sit and listen for the differences. Lately, I’ve been listening for what surprises me. What did I just hear that startled me? This isn’t easy – I’m accustomed to sitting there nodding my head to those saying things I agree with. But when I notice what surprises me, I’m able to see my own views more dearly, including my beliefs and assumptions.

Noticing what surprises and disturbs me has been a very useful way to see invisible beliefs. If what you say surprises me, I must have been assuming something else was true. If what you say disturbs me, I must believe something contrary to you. My shock at your position exposes my own position. When I hear myself saying, “How could anyone believe something like that?” a light comes on for me to see my own beliefs. These moments are great gifts. If I can see my beliefs and assumptions, I can decide whether I still value them.

I hope you’ll begin a conversation, listening for what’s new. Listen as best you can for what’s different, for what surprises you. See if this practice helps you learn something new. Notice whether you develop a better relationship with the person you’re talking with. If you try this with several people, you might find yourself laughing in delight as you realize how many unique ways there are to be human.

We have the opportunity many times a day, every day, to be the one who listens to others, curious rather than certain. But the greatest benefit of all is that listening moves us closer. When we listen with less judgment, we always develop better relationships with each other. It’s not differences that divide us. It’s our judgments about each other that do. Curiosity and good listening bring us back together.

Sometimes we hesitate to listen for differences because we don’t want to change. We’re comfortable with our lives, and if we listened to anyone who raised questions, we’d have to get engaged in changing things. If we don’t listen, things can stay as they are and we won’t have to expend any energy. But most of us do see things in our life or in the world that we would like to be different. If that’s true, we have to listen more, not less. And we have to be willing to move into the very uncomfortable place of uncertainty.

We can’t be creative if we refuse to be confused. Change always starts with confusion; cherished interpretations must dissolve to make way for the new. Of course it’s scary to give up what we know, but the abyss is where newness lives. Great ideas and inventions miraculously appear in the space of not knowing. If we can move through the fear and enter the abyss, we are rewarded greatly. We rediscover we’re creative.

As the world grows more strange and puzzling and difficult, I don’t believe most of us want to keep struggling through it alone, I can’t know what to do from my own narrow perspective. I know I need a better understanding of what’s going on. I want to sit down with you and talk about all the frightening and hopeful things I observe, and listen to what frightens you and gives you hope. I need new ideas and solutions for the problems I care about. I know I need to talk to you to discover those. I need to learn to value your perspective, and I want you to value mine. I expect to be disturbed by what I hear from you. I know we don’t have to agree with each other in order to think well together. There is no need for us to be joined at the head. We are joined by our human hearts.


Questions for Data Team Leaders to Use When Facilitating Data Team Meetings

Source: Data Teams Manual Copyright © 2006 Center for Performance Assessment

The following questions are intended to serve as a resource to assist the Data Team leader during the meeting. Select questions based on the needs that arise during your Data Team meeting.

Step 1. Collect and chart data and results: What do the data say?• What are we attempting to measure/monitor?• Did our assessment measure the skills and/or concepts that we need to monitor?• Did we notice anything unusual during the assessment that should be addressed?• Did we include too many items on the assessment, or was it the right length?• Did the assessment questions require rigorous thinking? (higher levels on Bloom’s

Taxonomy: evaluation, synthesis, analysis)• Should we revise any questions for the post-assessment? (Remember that we want

to compare pre- and post-assessment results.)

Step 2. Analyze strengths and obstacles: Analyze, then prioritize• What are the strengths of the student responses we have collected?• Do any responses stand out?• What is a sample of an ideal/proficient response? (Do we know what we consider

proficient? Do we agree on what proficiency looks like?)• Which questions had a high number of correct responses?• Which questions were left blank or had a very low response rate? (We will consider

these for targeted instructional/learning objectives.)• What question or questions seem most difficult for students? On which concepts

will we need to give focused and direct instruction?• What learning needs are evident?

Step 3. Establish goals: set, review, revise• Is our goal a SMART (Specific, Measurable, Achievable, Relevant, and Timely)

goal?• Specific: students, group, content area, objective(s)• Measurable: can be measured with an assessment• Achievable: is our goal within our reach? We need to consider increases in

proficient students, advanced students, and students who showed growth.• Relevant: are these concepts and skills stated in the Power Standards?• Timely: how much time do we expect to spend focusing on this topic? Three

weeks? Six weeks? Not all goals are monthly. Short-term goals often encourage teachers because progress is measured more frequently and teachers see results more quickly.

• Did we complete all the details related to a powerful goal?• Are we all committed to helping students reach their learning goal?


• What obstacles stand in the way of reaching our student learning goal? (This question could also be asked in step 2. This way any obstacles or reservations are addressed during the meeting.)

Step 4. Select instructional strategies• What specific best practices and effective teaching strategies will we emphasize

during this teaching/learning cycle? (The strategies listed on the template are from Classroom Instruction That Works by Marzano, Pickering, and Pollack (2001)).

• Do we need any resources to learn more about the strategies?• Does everyone know what the strategies look like in action?• Do we need to model application of the effective teaching strategies during this

meeting?• What does the research say about the effectiveness of the strategies we have

chosen?• Let’s revisit the daily strategies that we will use/implement on a daily basis.• Let’s review the strategies we will focus on for a specific skill, process, or concept.• Do we need to improve our environment for optimal learning?• Does any aspect of the physical environment have to be addressed (desks, centers,

access to materials, cooperative learning, etc.)?• Do we need to improve the classroom environment to increase the motivational

level for all students? How do we encourage risk-taking? How do we motivate students who don’t care? How do we invite students who have been disconnected for too long?

• What is our anticipatory set?• What materials do we need for instruction?• What materials do students need to accomplish the tasks they must complete? Do

we need materials to provide opportunities for additional practice?• How many days will we focus on students learning [name specific]

concepts/content?• How many days will we focus on students learning [name specific]

skills/processes?• How many days will we focus on practicing the knowledge?• What will the assessments and assignments be for all students, and on what days

will we assign them?• After three days of focused instruction, what will confirm to us that the required

learning has occurred?• How will we monitor progress and rigor?• What exactly will tell us if proficiency has been achieved? Define proficient for a

given skill/concept/process.• How will we prioritize our actions to address these learning needs? Based on these

priorities, how should we align and plan instruction?• How long do we need to spend on the various concepts, skills, and processes we

EXPECT students to master by the end of the overall learning time (chapter, unit, time period)?


• What strategies will we implement for those students who lack the foundation necessary to be successful on the new material we will present? (Intervention strategies are usually discussed here.) What short-term intervention should occur? What short-term, flexible grouping is needed for targeted learning to occur? (These small, flexible groups may last for only 20 minutes a day for 4 days, and must not be viewed as permanent groups.) When we prioritize the instructional needs of our students, we focus our efforts and increase the likelihood of their success.

Step 5. Determine results indicatorsResults indicators can include teacher and student behaviors, and can use both qualitative and quantitative data.

• How will we know if students are learning as a result of our specific instructional strategies?

• Exactly what should we see students applying after 5 days of instruction, 10 days of instruction, 15 days of instruction?

• What will directly link learning with specific strategies? (For example, teachers use the flow map (a nonlinguistic representation) during instruction of concepts and ideas. Teachers then assess student learning by giving students a flow map to complete, noting the important information of cause/effect.)

• In our quick-writes, administered at the end of each day/session/period, what questions will reveal specific but on-target learning?

• What overall application behaviors will we be able to see/note if the desired learning is occurring as a result of our focused instruction and use of instructional strategies?

• How will we confirm that the entire team has implemented the strategies that were collaboratively and collectively agreed upon? To what degree will we know whether the strategies are being implemented as intended and described during our team meeting? (This is the teacher-to-teacher accountability key.)

Suggested ResourcesAinsworth, L., & Viegut, D. (2006). Common formative assessments: How to connect

standards-based instruction and assessment. Thousand Oaks, CA: Corwin Press.

Introductory LevelPiercy, T. (forthcoming). Compelling conversations. Englewood, CO: Advanced

Learning Press.

Advanced LevelWhite, S. (2005). Beyond the numbers. Englewood, CO: Advanced Learning Press.White, S. (2005). Show me the proof! Englewood, CO: Advanced Learning Press.


Questions That Promote Reflection

What pleased you most about this lesson? Can you talk more about that? Why do you think that happened? What evidence do you have for that? Has anything like this happened before? Help me to understand... What has worked for you in the past? What have you tried so far? What did you take into account in planning this? What did you expect would happen? What conclusions can you draw? If you could replay the class, would you make any changes? What would they be?


Data Coach’s Action PlanDeveloped by Beth McCaffery, LEARN, and Jane Cook, EASTCONN, for CALI Coaching Data Teams Module, August 2008

__ ____ __ (Identify Data Team) (Date Action Plan Was Created) (Date Action Plan Was Updated)

Identified Need:

Based on (data):

Goal:

Individual(s) to Whom Support Will Be Provided: Resources Required and Associated Cost, if any:

Action to Be Taken: Date Work Will Begin:

What I think will happen as a result of my taking this action:

Date Work Will Be Completed:

What happened as a result of my taking this action:

Monitoring: List at least 3 specific things that will be observed to demonstrate that the action taken is producing the intended effect:


Data Coach’s Action Plan - ExampleDeveloped by Beth McCaffery, LEARN for CALI Coaching Data Teams Module, Aug. 2008

Grade 5 Data Team November 15, 2007 January 31, 2008______ (Identify Data Team) (Date Action Plan Was Created) (Date Action Plan Was Updated) Identified Need:Data Team Meetings are regularly cancelled, postponed (and not rescheduled) or start late.

Based on (data):August 27 through November 15, 2007: There were six data team meetings scheduled.2 were cancelled - 33%1 was postponed – 16%3 were 15 minutes late getting started – 50%There is no system to communicate meeting dates or times.

Goal: 100% of Data Team meetings will occur on the date they are scheduled and will begin on time.

Individual(s) to Whom Support Will Be Provided:

All Grade 5 Data Team members: Ms. Burke, Mrs. Lawson, Mr. Campbell, and Mr. Kane

Resources Required and Associated Cost, if any:

N/A

Action to Be Taken:

1. Communicate with the building administrator to ensure that data team meetings hold the same priority and expectation for attendance as other meetings, e.g. PPTs

2. Work with building administrator to communicate this expectation to all data team members

3. Create a substitute coverage schedule- with alternates, together with the building administrator to ensure that data team members are able to attend each meeting.

4. Publish a master calendar of all data team meeting dates and times and send a reminder via email 3 days, and then 1 day before each meeting.

5. Employ the roles and responsibilities embedded in the DT process to ensure accountability.

Date Work Will Begin:November 15, 2007

What I think will happen as a result of my taking this action: Teachers will understand the expectation that they are

to attend Data Team meetings. Teachers will enjoy the coverage they need in order to

do the work of and participant in data team discussions. A system will be created and employed to provide

substitute coverage to teacher and communicate meeting dates to teachers.

Teachers will take on the data team roles and responsibilities as part of their ongoing work to improve student learning.

Date Work Will Be Completed:January 31, 2008

What happened as a result of my taking this action: Teachers attend Data Team meetings. Teachers have the coverage they need to attend data

team meeting and arrive on times. A system exists to find and provide coverage for

teachers and communicate meeting dates and times in advance so that teachers attend data team meetings that begin on schedule.

Monitoring: List at least 3 specific things that will be observed to demonstrate that the action taken is producing the intended effect:.

Meeting takes place between building principal and data coach to ensure that data team meetings are a priority and the priority is communicated to staff. Individuals who are able to provide coverage in classrooms are identified and a schedule is created to support the work of data teams. A system is created and data team schedules are communicated in advance to both teachers who will attend data team meetings and substitutes who will

provide coverage for teachers.


Bibliography

Bernhardt, Victoria L. Data Analysis for Continuous School Improvement. Larchmont, New

York: Eye on Education, 2004.

Killion, Joellen, and Cindy Harrison. Taking the Lead. Oxford, Ohio: NSDC, 2006.

Killion, Joellen. Coaches Help Mine The Data. Teachers Teaching Teachers (February 2008).

Knight, Jim. Instructional Coaching: A Partnership Approach to Improving Instruction.

Thousand Oaks, California: Corwin Press, 2007.

Love, Nancy, Katherine E. Stiles, Susan E. Mundry, and Kathryn DiRanna. The Data Coach's

Guide to Improving Learning for All Students: Unleashing the Power of Collaborative

Inquiry. Thousand Oaks, California: Corwin Press, 2008.

Love, Nancy. Using Data to Improve Learning for All. Thousand Oaks, California: Corwin

Press, 2008.

Matthews, Jan, Susan Trimble, and Anne Gay. But What Do You Do With The Data?, Principal

Leadership, v7 n9 p31-33 May 2007.

Reeves, Douglas B. The Learning Leader. Alexandria, Virgina: Association for Supervision and

Curriculum Development, 2006.

White, Stephen. Beyond the Numbers. Englewood, Colorado: Advanced Learning Press, 2005

White, Stephen. Show Me the Proof. Englewood, Colorado: Advanced Learning Press, 2005


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