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Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

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Page 1: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Interlake SD

Data and School Planning Manitoba Education : Working Group on

Planning in EducationKen Horton

Joan ZaretskyLarry Budzinski

Page 2: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Assignments

I like an agenda something like 1) Welcome 2) Opening activity of some sort to activate thinking-Ken 3) Activity 1 Set priorities based on actual school data-

Larry 4) Introducing a Metaphor. Ken 5) Why we use Data and how – Ken- Larry 6) Bernhardt – Portfoilio Contents - Joan 7) Samples , examples, critique of their own plans 8) Maybe some Action research examples 9) Questions etc

Page 3: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

How will we know we are improving?

Page 4: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Welcome Logistics-, breaks etc Email address- Wiki Active – Participatory Advanced topic Interactive and Informative Look at School

Improvement Planning with focus on data

Page 5: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

REM. Not related to sleep nor an old Rock Band

R = Responsibility-for your comfort, learning, attitude

E = Engagement “you get what you give”

M = Misery Totally Optional

If you have a question and you don’t ask it …. I’m not answering it

You have to laugh at my jokes

And swear that you won’t say

“I can’t do that “ “ We tried that before”

or “ It will never work”

instead say

“ It may be worth a try”

Session Norms

Page 6: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Agenda

1) Why collect data ? 2) What data do we have readily

available, What is easy and simple to use?

Using the: how do we know if we have a “good neighbour” metaphor, we could have a brainstorming session along the lines of:

3) Tools and examples- this could evolve from the discussions above

4) Newer trends in data: School Portfolios, Authentic Artifacts .- you’re

5) Your ideas and examples 6) other

Page 7: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Kens Activity

Page 8: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Table Share

Take a moment and consider how you set and monitor priorities in your personal life

Describe a time in your personal life when you used data to answer a question.

Page 9: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Planning is essentially describing a Desired State and developing a course to achieve it.

Existing State Desired

State

What is our existing state?

What is the best we can imaging?

Page 10: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Why?...Use Data

Page 11: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

School Profile- Context- Fictional School

9- 12 Building in North Region of Manitoba 900 students

Currently focus is on increasing Graduation Rates

Changes in Administration- Staff Disengagement

Course completion Student surveys

Page 12: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Activity 1 Steps

1. Break into groups2. There are several sections of the profile information.

1. Student Surveys2. Course completion3. Behaviour Stats4. Staff Surveys

3. Group :Discuss and advocate for priority areas for the school based on your readings and personal experiences.

4. Decide upon 2 priorities for the school as a group5. Present and defend your choices as a group6. There are correct answers!

Page 13: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Debrief Process observer

• How did the group decide on priorities?

• Was there an agreed upon process?

• How did data help or hurt the establishing of priorities?

Page 14: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

BUDZINSKI

“In God we trust, everybody else bring data.”

“ Without data you are just another opinion”

Page 15: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

What to do with the Data

Identify Priority Areas Clarify Issues Hold Conversations Inform Planning Monitor Progress Celebrate Success

Page 16: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

What ….Uses of Data

To establish planning priorities? Activity • What type of data would we need ?

• How would we get it?

Page 17: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

What…Uses of Data …..continued

To monitor progress Activity 2• How do we know we are making progress?

• How much progress are we making?

Page 18: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

What..Uses of Data continued

To establish cause and effect• Analysis and Dialogue

Page 19: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Ask yourself …What causes student achievement?

Page 20: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

High Inquiry

% of students scoring proficiency or higher

43.6 in Low Inquiry Leadership Teams

64.8 High Inquiry Leadership Teams

When the answers are about adults in the school ( Curriculum, Assessment practice, Engaging lessons )= High Inquiry

When the answers were about students ( poverty, motivation, ethnicity ,parenting ) =Low Inquiry

Ask yourself …What causes student achievement?

Page 21: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Douglas Reeves Power of Monitoring

• Monitor adult actions not just scores

• Frequently

• Treasure hunt not Witch Hunt Rule of Six Learning Walks SMART ( Specific and Measurable) Action Research Public Displays “ Adult Science Fairs”

Page 22: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Activity 2 What sources of data would inform this question?At your table brainstorm 5 sources of Data that you would collect to answer the question.

Are we a good School?

Parent SurveysStandards Scores

College Admissions

Dropout Rates Student Surveys

Teacher Surveys

Credit Completion

Behaviour Incidents

Page 23: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

What types of Data?Quantitative

• Numbers

Qualitative• Words:,anecdotal,

stories

Intuitive• Opinions,

Perceptions

Page 24: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Data-Informed Planning

WISDOM

KNOWLEDGE

INFORMATION

DATA

Page 25: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Data is not wisdom

During WWII in order to bolster defenses, reduce Bomber and Pilot

Loss and to manufacture better armored planes. Abraham Wald

Bombers returning to base after missions were extensively “mapped” to determine exactly where the bullet holes were likely to hit. A meticulous grid system was used over a long period of time.

They found that planes were generally hit evenly all over except for a few limited areas.

In deciding where to put the additional armor plating to best protect the bombers it was reasoned that the additional armor would be most useful if placed on the limited areas that the mapping revealed were rarely or never hit by bullets

Counterintuitive- However the insight was that if planes who were hit in those

limited “unhit “areas they simply did not return. These were the most highly vulnerable target areas which when hit caused a crash and destruction.

Page 26: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

London Taxi Company Problem with turnover and training new drivers London is a very difficult city to become

knowledgeable with its streets system. Doesn’t follow grid system, Thames River, etc

Resorted to a study of their rider-ship• Found that about ½ of riders new exact directions for their

proposed route As a result they introduced a slightly reduced fare

to use a new service for those people who knew where they we going

Results: More Traffic, Better Trained Drivers , less turnover.

Page 27: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Joan

Page 28: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Victoria Bernhardt California State DemographicsEnrolment, attendance, Drop out rate, Ethnicity, Gender ,

Grade levelTells us What processes – programs different groups like best

PerceptionsPerceptions of Learning environmentValues and beliefs, Attitudes, ObservationsTells us about environmental improvements

Student LearningStandards Assessments, Teacher Grades, Observations,

Standardized assessmentsTells us about student performance on different measures

School ProcessesDescriptions of programs, processesTells us how classrooms change

Page 29: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Critique Sample

TEACHERS: PLEASE REVIEW AND COMMENT AS REQUIRED IN THE SPACES BELOW

2008–2009 Plan

Expected Outcomes  Strategies Indicators Data Sources (Tools)  

1. By the end of June 2009, K-8 teachers will have reported an increase in student engagement.

Teachers and students will plan a spirit week, implement math games, students will be given more opportunities for reading material and building technology skills.

Quality of Work, Independent Study, Increased Student Participation, Increased number of students asking for help and staying after school

Observations, Assignments, Report Cards, Portfolios, Electronic Portfolios, Quality of work, presentations

Staff, parents and student relationship building.

 

Students given opportunities to express their opinions on what types of activities they would like to be engaged in.

 

2. By the end of June 2009, students will have reported an overall increase in the school climate, a sense of belonging.

Students will be given opportunity to voice their opinions on what’s important in their learning.

Less referrals on behavior and discipline, Increased student engagement, more students participating in school functions, increased numbers of students participating extra-curricular activities.

Student School Climate Survey, Observations, Parent Conferences, Student Led conferences.

Students will be actively involved in planning fun fair, spirit week activities, and other school functions.

Students will participate in a school survey.

3. By the end of June 2009, K-8 teachers will have reported that their students have a better understanding of assessment as learning takes place.The outcome here could be something more concrete such as by Jan 2009 all students will report on their progress toward personal learning goals .

Teachers will review and discuss what needs to happen when students are assessing their own learning, including online learning.

Student engagement increases, students are proud of their work, the quality work continues to improve, students continue enjoy school, less students depending on resource.

Portfolios, Electronic Portfolios, Student Led Conferences, Observations, Assignments, Report Cards, Parent Feedback, Peer Assessments/Self Assessments.

Students need to be given the opportunity to monitor their own learning.

Students must be able set some goals for learning.

Teachers must continue to model best practices for learning and improvement.

Page 30: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Data Critique Activity 3

Another Team critique Do the data tools listed align with the outcomes? Are there a mix of Quantitative- Perceptual

Data? Are baselines established? Does the data collected make sense? What suggestions would you provide this

planning team?

Page 31: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Data for Generating Strategies

What do we think will make a difference What research exists? What do other schools do? Do we have enough information? What have we done in the past? Can we enlist the help of others? Is this educationally sound? Action Research

Page 32: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Quick Hits

Things to consider..good ideas, etc.

Page 33: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Triangulation

Multiple independent sources of data to establish the accuracy of a claim

• Richard Sagor Guiding School Improvement with Action Research

Engineering – Architecture• Estimate new positions or data based on the existing

position or data

Education Use• Verifying progress and setting direction

Page 34: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

1= Not influential 4= Very Influential

What Influences Teacher Practice?• Undergrad Courses

• Professional Reading

• Graduate Courses

• Motivational Speaker

• Bonus Pay

• Advice from Colleagues

• Action Research

1.8

2.3

2.6

?

?

3.6

4.0

Page 35: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Action Research Start with a guiding hypothesis

• “If we increase narrative writing teaching in our school we will get better academic results across the board.”

What is the research question or outcome we want ?• Writing skills will improve by 2 levels on our writing

continuum by May 2010

• In what other subject areas will achievement increase?

Page 36: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

1- Action Research

Compelling QuestionsSense or urgencyPersonal RelevanceAnswers “What’s in it for me ?”How can we reduce failure within a year?How can we improve engagement ?

Action ResearchPublic Exposure

Page 37: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Benefits Action Research

Greatest Single impact on Teacher Practices

Redefines PD 7: 1 Rule 7 hrs implementation for every 1

hour Research Question Method- Plan- Strategies- Analysis

Page 38: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Action research

Page 39: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Lewin's description of the process of change involves three steps [2]: Unfreezing: Faced with a dilemma or disconfirmation, the individual or group becomes aware of a need to change.

Changing: The situation is diagnosed and new models of behavior are explored and tested.

Refreezing: Application of new behavior is evaluated, and if reinforcing, adopted.

Figure 1 summarizes the steps and processes involved in planned change through action research. Action research is depicted as a cyclical process of change. The cycle begins with a series of planning actions initiated by the client and the change agent working together. The principal elements of this stage include a preliminary diagnosis, data gathering, feedback of results, and joint action planning. In the language of systems theory, this is the input phase, in which the client system becomes aware of problems as yet unidentified, realizes it may need outside help to effect changes, and shares with the consultant the process of problem diagnosis.

The second stage of action research is the action, or transformation, phase. This stage includes actions relating to learning processes (perhaps in the form of role analysis) and to planning and executing behavioral changes in the client organization. As shown in Figure 1, feedback at this stage would move via Feedback Loop A and would have the effect of altering previous planning to bring the learning activities of the client system into better alignment with change objectives. Included in this stage is action-planning activity carried out jointly by the consultant and members of the client system. Following the workshop or learning sessions, these action steps are carried out on the job as part of the transformation stage. [3]

The third stage of action research is the output, or results, phase. This stage includes actual changes in behavior (if any) resulting from corrective action steps taken following the second stage. Data are again gathered from the client system so that progress can be determined and necessary adjustments in learning activities can be made. Minor adjustments of this nature can be made in learning activities via Feedback Loop B (see Figure 1). Major adjustments and reevaluations would return the OD project to the first, or planning, stage for basic changes in the program. The action-research model shown in Figure 1 closely follows Lewin's repetitive cycle of planning, action, and measuring results. It also illustrates other aspects of Lewin's general model of change. As indicated in the diagram, the planning stage is a period of unfreezing, or problem awareness. [2] The action stage is a period of changing, that is, trying out new forms of behavior in an effort to understand and cope with the system's problems. (There is inevitable overlap between the stages, since the boundaries are not clear-cut and cannot be in a continuous process). The results stage is a period of refreezing, in which new behaviors are tried out on the job and, if successful and reinforcing, become a part of the system's repertoire of problem-solving behavior.

Action research is problem centered, client centered, and action oriented. It involves the client system in a diagnostic, active-learning, problem-finding, and problem-solving process. Data are not simply returned in the form of a written report but instead are fed back in open joint sessions, and the client and the change agent collaborate in identifying and ranking specific problems, in devising methods for finding their real causes, and in developing plans for coping with them realistically and practically. Scientific method in the form of data gathering, forming hypotheses, testing hypotheses, and measuring results, although not pursued as rigorously as in the laboratory, is nevertheless an integral part of the process. Action research also sets in motion a long-range, cyclical, self-correcting mechanism for maintaining and enhancing the effectiveness of the client's system by leaving the system with practical and useful tools for self-analysis and self-renewal.

Page 40: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Activity 4

Develop an Action Research Question to guide your Priority established in Activity 1

Remember Compelling Questions have

• Sense or urgency

• Personal Relevance

• Answers what’s in it for me ?

Page 41: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Questions to consider as we work

Who is the plan for? ( Division, Schools, Teachers, Kids,Parents )

What role will school plans play in setting division priorities? What data do we have that can help set our priorities Who will be involved and have input? ( Trustees,

Administrators, Staff Groups, Students , Parents) How will we monitor progress? Who will do the work, when, how? Will we plan to plan?

Page 42: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

How do you recognize a good neighbor?

How do we know anything? How do we determine what is good. e.g. a good neighbour.

The four categories below are very arbitrary- they just came easily to mind. School routines, regularities, participation rates, attendance, extracurricular,

office referrals, phone calls, inclusiveness Neighbour- ??? frequency of lawn cutting/ snow removal, dog walking,

recycling. Levels and frequency of social interaction School documents: paper evidence of student achievement/progress/growth:

exemplars, samples, mean scores, portfolios Neighbour??? Willingness to lend possessions- tools, provide help etc School attitudinal and perceptual self reported data: surveys, interviews, focus

groups Neighbour:  friendly chats, exchange of opinions School Exhibitions, celebrations, special occasions/functions/displays and

competitions and collections Neighbour-??? Sharing of special occasions: holiday/baby photos, invitations to

birthday and Christmas parties/bbqs

Page 43: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Data

Data “information or evidence collected through a systematic method of selection, observation or analysis. Data are symbolic representations of information that can be expressed in numbers or words.”

(Earl, 1999)

Identifying data sources that are:- presently available- easily accessed

or- electronically generated

Page 44: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Examples of Commonly Available Data Sources

Information about students

• Enrollment records

(enrollments, transfers &

dropouts)

• Achievement

• Daily attendance records

• Student records (demographics, extracurricular activities

• Transcripts (course enrollments and levels, credits earned, grades)

– Student Portfolios– Standards tests results– Exit exams– Counselling reports – Employer evaluations

(co-op placements)– Student survey results– Post-secondary results– Student Surveys

Page 45: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

…More

Information about teachers or administrators

• Personnel files (teacher training and certification, staff development activities, continuing education credits)

• Attendance records

• In-service records

• Community Surveys

School-level information• Funds/expenditures per pupil

• Reports prepared for/or by the school

• Partnerships with post-secondary institutions/businesses/other

• Dropout & completion rates

• Student-faculty ratios

Page 46: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

What to do with the Data

Measure Progress Identify Priority Areas Clarify Issues Hold Conversations Inform Planning

Page 47: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Victoria Bernhardt California State U

DemographicsEnrolment, attendance, Drop out rate, Ethnicity, Gender ,

Grade levelTells us What processes – programs different groups like best

PerceptionsPerceptions of Learning environmentValues and beliefs, Attitudes, ObservationsTells us about environmental improvements

Student LearningStandards Assessments, Teacher Grades, Observations,

Standardized assessmentsTells us about student performance on different measures

School ProcessesDescriptions of programs, processesTells us how classrooms change

Page 48: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Data Critique

Another critique Do the data tools listed align with the

outcomes? Are there a mix of Quantitative-

Perceptual Data? Are baselines established? Does the data collected make sense?

Page 49: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Data to Support School Improvement

Quantitative (numbers)

e.g., test scores, statistics, provincial results Qualitative (descriptors)

e.g., questionnaires, interviews, observations

Page 50: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Tools

Quantitative – Student Performance

• Provincial Assessments• Divisional Assessments• School – Grade Level Assessments• Standardized Assessment• Individualized Assessments• Classroom Profiles• Behaviour Inventories• Social Maps• School Reviews

Qualitative – Perceptual• Student Surveys• Parent • Community Surveys• Focus Groups• Web Surveys

Survey MonkeyPoll AnywhereExamples of Data Provincial TrendsBaragars Data ServicesEISStats CanadaCenter for Health Policy – RHA’sCanadian Council on Learning

Page 51: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Useful Websites

http://www.baragar.com/index.cfm?event=products.dynamics

http://maps.ccl-cca.ca/cli10/carto.php?lang=en

Page 52: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Poll Everywhere

Page 53: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

How To Vote via Texting

1. Standard texting rates only (worst case US $0.20)2. We have no access to your phone number3. Capitalization doesn’t matter, but spaces and spelling do

TIPS

EXAMPLE

Page 54: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

How To Vote via Poll4.com

Capitalization doesn’t matter, but spaces and spelling doTIP

EXAMPLE

Page 55: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

How To Vote via Twitter

1. Capitalization doesn’t matter, but spaces and spelling do2. Since @poll is the first word, your followers will not receive this tweetTIPS

EXAMPLE

Page 56: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Interlake Poll

Page 57: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Story of a conductor He was a mediocre conductor of a mediocre

orchestra. He had been having problems with the basses; they were the least professional of his musicians. It was the last performance of the season, Beethoven’s 9th Symphony, which required extra effort from the basses at the end. Earlier that evening, he found the basses celebrating one of their birthdays by passing a bottle around. As he was about to cue the basses, he knocked over his music stand. The sheet music scattered. As he stood in front of his orchestra, his worst fear was realized;

A midget fortune teller Queen Nyteshade had two claims to fame. She could

tell fortunes and she was a midget. The local authorities frowned on her because they thought that fortune telling was fraudulent. They had Queeny arrested. She was placed in a holding cell. Since she was so small she was able to squeeze between the bars of her cell and escape. This to incensed the judge that he ordered the local newspaper to print an article about the culprit. The following was printed in the paper the next day. Small medium at largeSmall medium at large

it was the bottom it was the bottom of the 9th, no of the 9th, no score and the score and the basses were basses were loaded.loaded.

Page 58: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

Questions or Comments

Page 59: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

How To Vote via Texting

1. Standard texting rates only (worst case US $0.20)2. We have no access to your phone number3. Capitalization doesn’t matter, but spaces and spelling do

TIPS

EXAMPLE

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How To Vote via Poll4.com

Capitalization doesn’t matter, but spaces and spelling doTIP

EXAMPLE

Page 61: Interlake SD Data and School Planning Manitoba Education : Working Group on Planning in Education Ken Horton Joan Zaretsky Larry Budzinski

How To Vote via Twitter

1. Capitalization doesn’t matter, but spaces and spelling do2. Since @poll is the first word, your followers will not receive this tweetTIPS

EXAMPLE

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