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FSI Cohort III
Lisa Guzzardo Asaro
January 22, 2013
Connector Activity
The Leadership by Douglas B. ReevesThe Write Way
•Each person will read for:
•3 Ideas
•2 Insights
•1 Question that Surfaced
As a Table Team, identify 3, 2, and I
TAB 12
The Leadership for Learning Framework, by Doug Reeves
LuckyHigh results,
low understandingof antecedents
Replication of success unlikely
LeadingHigh results,
high understandingof antecedents
Replication of success likely
LosingLow results,
low understanding of antecedentsReplication of
failure likely
LearningLow results,
high understandingof antecedents
Replication of success likely
Ach
ievem
en
t of
Resu
lts
TAB 12
Today’s Outcomes•Provide ASSIST and Requirement updates
•Engage in activities that connect you to Michigan’s continuous school improvement process
•Heighten awareness of how the Ladder of Inference influences data selection
•Receive a presentation from Troy School District
•Use a 3-phase, data dialogue protocol to analyze current school data
•Use the 5 Whys protocol
TAB 12
Today’s Roadmap• Welcome• Connector: Data Overload• Updates and Changes• ASSIST• Components of a CNA• Ladder of Inference• Data Dialogue Protocol• 5 Whys: root cause• Tuckman’s Team Development Model• Tool for Learning Schools• Network and Planning
TAB 12
Key Working Agreements A Facilitation Tool
• Respect all Points of View
• Be Present and Engaged
• Honor Time Agreements
• Get All Voices in the Room
These breathe life into our Core Values
Parking LotA Facilitation Tool
• Rest questions that do not benefit the whole group
• Place questions that do not pertain to content at this time
• Place questions that pertain, but participants do not want to ask at this time
LIVING BELIEF STATEMENT
“Networking is not an option, but a critical part
of how Facilitators of School Improvement learn and share their
learning.”
ADVANCED MIand MDE
UPDATES AND CHANGES
New MDE Website Houses Important URL
http://www.michiganccr.org
This website has been created to connect users with the resources available for helping all students
graduate career and college ready.
• Effective Instruction• Balanced Assessment• Accountability• Supporting Quality Educators• Infrastructure• P-20 Resources• Success Stories
Professional Learning Opportunities
• Assessing the Impact with Joellen KillionMarch 12-13, 2013 NCA Building
• Common Core: Leading the ChangeMarch 19, 2013 MISD Rm. 100 A-C
• MDE/AdvancED Spring SI ConferenceApril 17-18, 2013 Lansing Center
• MAISA Michigan ELA Model Curriculum Units
June 24-27, 2013 Teams Lansing Center• Kagan Structures for Cooperative Learning and Active Engagement
InstituteAugust 12-16, 2013 MISD
Smarter Balanced Assessment Consortium
• In October, higher education faculty and K-12 teachers teamed up at a 5-day workshop to draft initial Achievement Level Descriptors (ALD) for summative assessments.
• This will help students, teachers, and parents interpret student scores on the SBAs.
• The draft initial ALDs are available for public review and comment through January 15. The documents are located on the Smarter Balanced website:
http://www.smarterbalanced.org/achievement-level-descriptors-and-college-readiness/
• ELA and Math Claims: Summative AssessmentHandou
t
TAB 3
Spring 2013 SBA Pilot Test • Smarter Balanced is gearing up to test drive the assessments.
• The Pilot Test will include several thousand items and performance tasks, giving the Consortium important information about how the items and tasks perform in a real-world setting.
• Participation in the Pilot Test is voluntary and all schools in Michigan are eligible. – Two types of schools:
• 1) scientifically-selected schools were notified 12.04.12 and
• 2) schools can volunteer by completing the volunteer registration form at http://www.surveymonkey.com/s/SmarterBlancedPilot To complete the survey, you will need your school’s National Center for Educational Statistics (NCES) number.
– Volunteer schools will be tested in mid-April to mid-May– Only one content area will be assessed/grade within a school– Schools should plan on 3 hours of testing
• Important to remember that the PURPOSE is a tryout of test items and the test interface, not an assessment of student learning. Students will not receive SCORES.
Dynamic Learning Maps (DLM)
Special Education
• Created Common Core Essential Elements (CCEEs) in ELA and Math which are linked to the CCSS
• These provide alternate grade level content standards linked to the CCSS and are available for review
• Visit the MDE MI-Access website at www.michigan.gov/mi-access• Alternate assessments based on the CCEEs are being developed
by the DLM alternate assessment consortium and will be available for use in Michigan starting in the 2014-2015 school year
• See handout
Handou
t
MAISA Collaborative Project Update
• MAISA Units
• Phase III– ELA Curriculum Leadership Team (K-12 timeline)
– Math Curriculum Leadership Team
One Common Voice – One Plan Michigan Continuous School Improvement
Stages and Steps
DoImplement Plan
Monitor PlanEvaluate Plan
PlanDevelop Action
Plan
GatherGetting Ready
Collect School DataBuild School Profile
StudentAchievement
StudyAnalyze Data
Set Goals Set Measurable Objectives
Research Best Practice
(MI-CSI)
One Common Voice – One Plan Michigan Continuous School Improvement
Stages and Steps
• Getting Ready• Collect School Data • Build School Profile
I. Executive Summary IV. School Process Rubrics
• Analyze Data II. School Data Analysis IV. School Process Analysis
• Set Goals• III. Additional Requirements• V. Goals and Plan
• Set Measurable Objectives• Research Best Practice
• Develop Action Plan
• Implement Plan• Monitor Plan• Evaluate Plan
• VI. Evaluation Tool (2014)
Comprehensive Needs Assessment
School Improvement
Plan
Gather
Study
Plan
Do
Handou
t
TAB 12
MDE NCA
Handout
MDE Updates
• ASSIST Updates– Not all School Data Profiles (40/90 OR ISA/SA) have been fully
activated on AdvancED as an assigned task in the Overview Tab. (Was to be done by Break)
– Diagnostics can be started at anytime by logging into ASSIST and using the Diagnostics and Surveys Tab
– Title I Components and SIPs will be available on ASSIST with the 02.09.13 push (schools can activate a SIP by using the Goals and Plan Tab
– Demographic information can be updated by using the Profile Tab and clicking on the Demographic link (EEM trumps everything)
– The old SDP/A questions will be located in the Diagnostic Tab after the 02.09.13 push and will be called School Data Analysis
• Questions Handout
BLUE Report
RED ASSIST TAB
Schools Comprehensive Needs Assessment (CNA)
Component OneExecutive Summary (All Schools Yearly) Due 09.01.13
Component TwoSchool Data Analysis (Updates) Due 09.01.13 • Student Performance Diagnostic (5th year) 4 wks. prior to External Review Date • Stakeholder Feedback Diagnostic (5th year) prior to External Review Date
Component ThreeAdditional Requirements for Title I SW &TA, and Non-Title I Schools Due 09.01.13
Component FourSchool Process Rubrics:
Component FiveGoals and Plan (All Schools every 3 to 5 years) Due 09.01.13
Component SixStrategy Evaluation Tool (All schools 2nd year in Reading and Math)
MDE Rubrics 40/90
AdvancED MI ISA/SA
DUE
04.01.13
Handou
t
TAB 12
District CNAComponent I: Due 04.15.13 OR
4 wks. Prior to an External Review
District Process Rubrics (DPR) OR District Interim Self Assessment (ISA)/District Self Assessment (SA)
Component II: Due 06.28.13District Improvement Plan (DIP)
ALERT: Districts may request submission of SIPS as early as 04.01.13, to complete their DIPs.
ASSIST Technical Guide is located at:Macombfsi.netASSIST TAB
ORhttp://www.advanc-ed.org/webfm_send/372
Executive SummaryComponent I.
• Vision• Mission• Belief Statements• Strengths/Challenges (See Slide 11)
Challenges Matrix I Activities Connection to SPP
SPR 40/90 OR ISA/SAGetting Ready to
ImplementImplement Monitoring Fidelity of
Implementation and Impact
How will we address the targeted areas in your Process Data (SPP)?
What areas in your process data have been identified as challenge
areas during your comprehensive needs assessment process?
ISA/SA
MATRIX
From your Summary
Report
Handout
TAB 5
School Data AnalysisComponent II.
AdvancED Michigan
DiagnosticsStudent Performance DiagnosticStakeholder Feedback Diagnostic
(perception surveys)
External Review (ER) 5thYear
MDE
School Data Analysis
(Was the Data Profile)
Update Yearly
SPDA Type Questions HANDOUT
Additional RequirementsComponent III.
Content has been aligned, unduplicated, and flagged to meet multiple
requirements. Unique diagnostics are available for Title I SW, TA, and Non Title I schools (This could include
Priority and Focus Diagnostics and Reform and Redesign Plans).
School Process Profile Component IV.
MDE NCA
MI-CSI Framework
Michigan School Improvement Framework
Strand I Strand II Strand III Strand IV Strand V
Teaching for Learning Leadership
Personnel &Professional
Learning
School and Community Relations
Data and Information
Management
Standards (12) and Benchmarks (26)1. Curriculum
• Aligned, Reviewed & Monitored
• Communicated
2. Instruction• Planning• Delivery
3. Assessment• Aligned to
Curriculum and Instruction
• Data Reporting and Use
1.Instructional Leadership
Educational Program
· Instructional Support
2.Shared Leadership
• School Culture and Climate
• Continuous Improvement
3.Operational Resource Management
• Resource Allocation
• Operational Management
1.Personnel Qualifications
•Requirements•Skills,
Knowledge, Dispositions
2.Professional Learning
• Collaboration• Content &
Pedagogy• Alignment
1.Parent/Family Involvement
• Communication• Engagement
2.Community Involvement
• Communication• Engagement
1.Data Management• Data
Generation, Identification & Collection
• Data Accessibility
• Data Support
2.Information Management
• Analysis & Interpretation
• Applications
TAB 5
AdvancED Michigan 5 StandardsStandard 3: Teaching and Assessing for Learning
Standard: The school’s curriculum, instructional design, and assessment practices guide and ensure teacher effectiveness and student learning.
3.1The school’s curriculum provides equitable and challenging learning experiences that ensure all students have sufficient opportunities to develop learning, thinking, and life skills that lead to success at the next level.
3.2 Curriculum, instruction, and assessment are monitored and adjusted systematically in response to data from multiple assessments of student learning and an examination of professional practice.
3.3 Teachers engage students in their learning through instructional strategies that ensure achievement of learning expectations.
3.4 School leaders monitor and support the improvement of instructional practices of teachers to ensure student success.
3.5 Teachers participate in collaborative learning communities to improve instruction and student learning
3.6 Teachers implement the school’s instructional process in support of student learning
3.7 Mentoring, coaching, and induction programs support instructional improvement consistent with the school’s values and beliefs about teaching and learning.
3.8 The school engages families in meaningful ways in their children’s education and keeps them informed of their children’s learning progress.
3.9 The school has a formal structure whereby each student is well known by at least one adult advocate in the school who supports that student’s educational experience.
3.10 Grading and reporting are based on clearly defined criteria that represent the attainment of content knowledge and skills and are consistent across grade levels and courses.
3.11 All staff members participate in a continuous program of professional learning.
3.12 The school provides and coordinates learning support services to meet the unique learning needs of students.
TAB 5
Goals & Plan Component V.
One Common Voice – One Plan Michigan Continuous School Improvement
Stages and Steps
DoImplement Plan
Monitor PlanEvaluate Plan
PlanDevelop Action
Plan
GatherGetting Ready
Collect School DataBuild School Profile
StudentAchievement
StudyAnalyze Data
Set Goals Set Measurable Objectives
Research Best Practice
(MI-CSI)
Stage One: GATHERStep 1: Getting Ready
GATHERGetting Ready
Collect School DataBuild School Profile
“In God we trust, everyone else brings DATA”
One Common Voice – One Plan Stage One Gather: Step 2 Collect School Data
What do you already know?What data do you need to know?
What additional information/data do you need to know?Where can the information/data be found?
Definitions
AchievementStudent
Outcome Data
How our students perform on local, state and federal
assessments (subgroups)
Demographic or
Contextual Data
Describes our students, staff, building, and community
Process Data
The policies, procedures, and systems we have
in place that define how we do
business
Perception Data
Opinions of
staff, parents, community and
students regarding our
school
TAB 2 Page 3
What types of data are/are not readily available in your building?
40
Demographic Data Achievement/Outcome Data
Process Data Perception Data
•Enrollment•Subgroups of students•Staff•Attendance (Students and Staff)•Mobility•Graduation and Dropout•Conference Attendance•Education status•Student subgroups•Parent Involvement•Teaching Staff•Course enrollment patterns•Discipline referrals•Suspension rates•Alcohol‐tobacco‐drugs violations•Participation extra‐curriculars•Physical, mental, social and health
•Local assessments: District Common Assessments, Classroom Assessments, Report Cards•State assessments: MME, ACT, MEAP, MI-Access, MEAP Access, ELPA• Nationalassessments: ACT Plan, ACT Explore, ACT WorkKeys, NWEA, ITBS, CAT, MET NAEP, PSAT•GPA•Dropout rates•College acceptance
•Policies and procedures (e.g. grading, homework, attendance, discipline)•Academic and behavior expectations•Parent participation – PT conferences, PTO/PTA, volunteers•Suspension dataSchool Process Profile Rubrics(40 or 90) or SA/SAR (NCA)•Event occurred: who, what, when,where, why, how•What you did forwhom: Eg. All 8th gradersreceived violencePrevention
•Survey data (student, parent, staff, community)•Opinions•Clarified what others think•People act based on what they believe•How do they see you/us?
Tab Two Page 3-4
TAB 2 page 4
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Perc
ent o
f Par
ticip
ants
CollaborativeTeam Work
BuildingAssessment
Literacy
Create aCollectiveProblem
Statement
Digging intoStudent Data
Analyze Data Developing anAction Plan
Planning toAssessProgress
A Piece of Data Perceptions of Data Practices
August, 2012 (n=100)
Does Not Occur Happens Occasionally Happens Frequently
Data StatementsObservation Statements
TAB 4
Ladder of Inference
• We live in a world of self-generating beliefs that remain largely untested.
• We adopt these beliefs because they are based on our conclusions, which are inferred from what we observe, plus our past experience.
• Our ability to achieve the results we truly desire is eroded by our feelings that:– Our beliefs are the truth;– The truth is obvious;– Our beliefs are based on real data;– The data we select are the real data.
Ladder of Inference cont’d
• The ladder of inference explains how we generate assumptions, how we make observations and assessments, then act upon them.
• First, we select data that makes sense to us and we want to hear. Next, we add meaning to the data based on our experience and our frame of reference. Then we make an assumption about the original data, draw a conclusion, and act on or advocate a belief based on the filtered data.
Source: Schools that Learn: A Fifth Discipline
Handbook for Educators, Peter Senge
Each trip up the ladder affects what data we
select next time.
TAB 4
Ladder of Inference
• I take: actions (based on beliefs)• I adopt: beliefs (about the world)• I draw: conclusions• I make: assumptions (based on meaning added)• I add: meanings (cultural and personal)• I select: “Data” (from what I observe)
Observable “data” and experiences start here.
TAB 4
School Data Profile TAB 3
One Common Voice – One Plan
Michigan Continuous School ImprovementStages and Steps
DoImplement Plan
Monitor PlanEvaluate Plan
PlanDevelop Action Plan
GatherGetting Ready
Collect School DataBuild School Profile
StudentAchievement
StudyAnalyze Data
Set Goals Set Measurable Objectives
Research Best Practice
Stage Two: StudyStep 4: Analyze Data
STUDYAnalyze Data
Set GoalsSet Measurable Objectives
Research Best Practice
Reminder of our Adaptive Schools WorkData-Driven Dialogue
• Data have no meaning on its own. Meaning is a result of human interaction (socially mediated) with data.
• Knowledge, meaning and commitment result from dialogue (everything is on the table) around the story the data is telling.
Why Data-Driven Dialogue?
“Assessment illiteracy is surely a prescription for
professional suicide.”
James Popham, 2004
A data-driven dialogue is:•A conversation where members of a professional learning community examine a particular issue using dialogue.
•A way to reflect and learn about our practices, programs, our students, and our teaching.
•A way to facilitate collective meaning-making, connections, and shared understandings.
•A way to turn our insights into actions that promote and improve student and staff learning.
What is a data-driven dialogue?
55
“Dialogue can occur only when a group of people see each other as colleagues in mutual quest for deeper insight and
clarity.”
Peter Senge, The Fifth Discipline
Most Important Point (MIP) Activity
1. Get into groups of three.
2. Locate your book (Got Data? Now What?) and turn to pages 100-104.
3. Each person reads either the Dialogue, Discussion or Decision section and reports out the Most Important Point of the reading to other members of the group.
4. Be prepared to share your conversation with the whole group.
56
Data-Driven Dialogue(Dialogue Discussion Decision)
• Dialogue is a reflective learning process, seeking to understand (use opening tools) another’s viewpoint.
• Discussion is where participants attempt to reach decisions (use narrowing tools) through a variety of voting and consensus techniques.
Dialogue vs. Discussion?
Dialogue Discussion
thinking holistically thinking analytically
making connections making distinctions
surfacing and inquiring into assumptions
surfacing and inquiring into assumptions
developing shared meaning developing agreement or action
seeking understanding seeking decisions
Dialogue vs. Discussion
• Creates shared understanding and shared goals.
• Creates ownership.
• Leads to collaborative planning
• Leads to collaborative problem-solving
• Leads to collective action plans
Why dialogue…
– Careful and active listening – Being open to new ideas – Focusing on the goal of developing a shared
understanding– Depersonalize yourself from the data– Data becomes a “thing” – tells a story– Role of decision making is clear before the
dialogue– Practice
Requires…
To collaborate – A process through which parties who see different aspects of a problem (lens) can constructively explore their differences and search
for solutions that go beyond their own limited vision of what is possible.
Barbara Gray
62
A framework that establishes a learning forum for group exploration
of data.
Collaborative Learning Cycle
Collaborative Learning Cycle
Phase I – Activating & Engaging
Phase 2 – Exploring & Discovering
Phase 3 – Organizing Integrating
The Collaborative Learning Cycle
Collaborative Learning Cycle
Phase I – Activating & Engaging
• Assumptions about learners and learning• Surface predictions and assumptions (note on separate sheets of
chart paper) to the data to be explored• Predictions are accompanied with assumptions• Person who lists a prediction should also share the underlying
assumption• Surface perspectives (lens) and create readiness for looking at data• Seek to understand, not persuade• Share what the data might look like• No right or wrong statements• No debate in this phase• Everyone offers their thoughts – equity focus• Data free
• Members share what they think they will see in the data and make predictions.
• Share underlying assumptions associated with those predictions.
• Explore predictions and assumptions and develop an awareness of them so those feelings and beliefs do not interfere.
Activating and Engaging
Predictions Assumptions
• I know . . .• Something you expect to
see in the data• Experienced-based
conjectures regarding what group members expect might appear in the data
• Because . . .• Something that you think
but that will not show up in the data
• Remain tacit and unquestioned
Use the following questions:
• What are our underlying feelings about data?
• What are some predictions we are making?
• With what assumptions are we entering?
• What are some questions we are asking?
• What are some possibilities for learning that this experience presents to us?
Activating and Engaging
Identifying Predicting or Assumption Statements
1. The boys will outperform girls by at least 10% points in Mathematics.
2. Boys brains are wired differently than girls when it comes to Mathematics.
3. All of the Fall 2011 scores will drop due to the new state cut scores.
4. Economically Disadvantaged early elementary students struggle with Reading because they are not developmentally ready to read.
5. The students in the 5th grade will gain one year’s academic growth in Mathematics from Fall 2011 to Fall 2012.
6. The graduating class of 2014 will display scores less than the state. That group of students never scores well on tests.
Data Driven Dialogue
3 MAIN Phases:
1. Generating Predictions– Surfacing perspectives, beliefs,
assumptions
2. Analyzing the Data (Observations)– Analyzing data for patterns,
trends, surprises
3. Organizing and Integrating: Inferences– Generating hypotheses,
explaining, drawing conclusions
KEY
Writing your personal
reflections, prior to
sharing with team.
Model making PREDICTIONSusing these sentence stems
I assume . . .I predict . . .I wonder . . .Some possibilities for learning that this data may present . . .
TAB 4
Office Referrals Fall 2012(n = 200 in each grade)
INFRACTIONS GRADE
9 10 11 12 Sum
Absenteeism
Physical Altercation
Smoking
Use of Profanity
Drugs/Alcohol
Theft
Major Disruptions/Outbursts
Throwing Objects in Cafeteria
Destroying School Property
Sexual Assault
Bullying Students
Assaulting a Teacher
Sum
School Teams
20 Minutes
A framework that establishes a learning forum for group exploration
of data.
Collaborative Learning Cycle
Collaborative Learning Cycle
Phase I – Activating & Engaging
Phase 2 – Exploring & Discovering
Phase 3 – Organizing Integrating
The Collaborative Learning Cycle
Collaborative Learning Cycle
Phase II – Exploring & Discovering• Purposeful uncertainty• Avoiding jumping to premature conclusion and closure• Intellectual Hang Time• Push to explore multiple storylines• Distinguishing, sorting, analyzing, comparing, and contrasting• Publicly charted• Balanced exploration of the data• Place chairs in a semicircle around a central data display• Two to three minutes of orientation to the data displays before talking• Chart observations in a language that is concise and specific• Neutral language – these data or this chart• It is not the time to explain• Go slow, honor the flow of dialogue.
Phase II – Exploring & Discovering(Intellectual Hang Time)
because
Phase II – Exploring & Discovering
Exploring & Discovering Activity I
1. Get into groups of four or below.
2. Take 2-3 minutes (in silence) to examine the posted data artifacts on the wall and taking note of what you notice about the artifacts.
3. Using the Rough and Refined Observation Handout, record your observations in the Rough Observation column. (List anything you observe.) Each observation should communicate a single idea clearly and concisely and should be observable.
4. Once finished, be prepared to share with your group.
Data Driven Dialogue
Analyzing the DataObservations
1. If you catch yourself using . . .
Because . . . Therefore . . . It seems . . . However . . .
Model making Quantifiable OBSERVATIONS
using these sentence stems
I observe that . . .Some patterns/trends that I
notice are . . .I can count . . .I’m surprised that I see . . .
TAB 4
Office Referrals Fall 2012(n = 200 in each grade)
INFRACTIONS GRADE
9 10 11 12 Sum
Absenteeism 7 1 0 0 8
Physical Altercation 31 14 2 2 49
Smoking 12 7 9 14 42
Use of Profanity 17 12 14 13 56
Drugs/Alcohol 10 8 12 9 39
Theft 4 1 0 0 5
Major Disruptions/Outbursts 15 6 0 0 21
Throwing Objects in Cafeteria 2 0 0 0 2
Destroying School Property 6 1 0 0 7
Sexual Assault 1 0 0 1 2
Bullying Students 36 20 10 7 73
Insubordination 45 22 9 6 82
Sum 186 92 56 52 400
School Teams
30 Minutes
Data Driven Dialogue
Organizing and IntegratingCausation
Phase Three
Sentence Stems
I believe that the data suggests . . . because, Additional data that would help me verify/confirm
my explanation is . . . I think the following are appropriate
suggestions/solutions/responses that address the needs implied by the data . . .
Additional data that would help guide implementation of the suggestions/solutions/responses and determine if they are working . . .
Model making
Organizing and Integrating Statements (Causation) using these sentence stems
I believe that the data suggests . . . because,
Additional data that would help me verify/confirm my explanation is . . .
I think the following are appropriate suggestions/solutions/responses that address the needs implied by the data . . .
Additional data that would help guide implementation of the suggestions/solutions/responses and determine if they are working . . .
TAB 4
Office Referrals Fall 2012(n = 200 in each grade)
INFRACTIONS GRADE
9 10 11 12 Sum
Absenteeism 7 1 0 0 8
Physical Altercation 31 14 2 2 49
Smoking 12 7 9 14 42
Use of Profanity 17 12 14 13 56
Drugs/Alcohol 10 8 12 9 39
Theft 4 1 0 0 5
Major Disruptions/Outbursts 15 6 0 0 21
Throwing Objects in Cafeteria 2 0 0 0 2
Destroying School Property 6 1 0 0 7
Sexual Assault 1 0 0 1 2
Bullying Students 36 20 10 7 73
Insubordination 45 22 9 6 82
Sum 186 92 56 52 400
School Teams
20 Minutes
Probing for Root Cause
Select a concern from the causation or theories generated in Math or Reading
that if focused upon by the school, it will leverage student achievement.
Stage Two StudyStudyStep Four: Analyze DataStep Four: Analyze Data
School Summary Report The Five “Why’s” Consider impact/control
Low DEGREE OF CONTROL High
Low
IM
PA
CT
H
igh
5 Why’s Example
• 4th grade math achievement on the MEAP is below the state average.
WHY?
Create an exhaustive list.
Next, select the one statement; that if addressed, will leverage student achievement.
5 Why’s Example
• Statement: The data indicates that our 4th grade students do poorly on story problems.– (62% of our students score at level 3 and 4 on story
problems).
• Turn this statement into the NEXT question:
Why are our 4th graders scoring poorly on story problems?
Handou
t
TAB 4
One Common Voice – One Plan Michigan Continuous School Improvement
Stages and Steps
DoImplement Plan
Monitor PlanEvaluate Plan
PlanDevelop Action
Plan
GatherGetting Ready
Collect School DataBuild School Profile
StudentAchievement
StudyAnalyze Data
Set Goals Set Measurable Objectives
Research Best Practice
(MI-CSI)
TAB 1 page
66
TAB 1 page
62
TAB 1 page
67
Stage One GATHER Step 1: Getting Ready
4 Considerations
• School Culture– Collaborative Inquiry Process– Vision, Mission, Core Values and Belief Statements
• School Decision Making – From Consensus to Decide and Announce
• Team Building– Stakeholder Analysis– Group vs. Team
• School Current Reality – ‘Where Are We?’
GATHERGetting Ready
Collect School DataBuild School Profile
Tool for Learning Schools• Storyboard
• Thinking Lens
• Four-step reflection process
• Success analysis protocol
Next Steps Time• Network with colleagues
• Place handouts in binder
• Plan what to bring back to share with SI team
• Visit the Smarter Balance Consortium websitewww.smarterbalanced.org
• Visit the Career and College Readiness website www.michiganccr.org
