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Hillsdale County’s Data Director Initiative: ‘Growing Our Warehouse’ Implementation Plan. August 4, 2010. Pat Dillon and William Yearling Hillsdale ISD Jennifer DeGrie and Stan Masters Lenawee ISD. Professional learning around analyzing State data analyzing school data - PowerPoint PPT Presentation
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Hillsdale County’sData Director Initiative:
‘Growing Our Warehouse’Implementation Plan
August 4, 2010
Pat Dillon and William YearlingHillsdale ISD
Jennifer DeGrie and Stan MastersLenawee ISD
Professional learning around• analyzing State data• analyzing school data• analyzing student work• monitoring classroom achievement
School Improvement Process
What We Already Know About Using Data Analysis to
Change Instructional Practices• Zellmer (1997)
– Without specific expectations and professional development, teachers will simply ignore data and continue to use the same instructional practices.
• Price-Baugh (1997)– Without data regarding alignment to State standards,
teachers will not supplement their use of instructional resources to help students meet the standards.
• Moss-Mitchell (1998)– Student learning increases across socio-economic and gender predictors when
coupled with:• filling in gaps between tests and instructional materials• supervision to monitor curriculum alignment• focused professional development• public copies of aligned district curriculum• the involvement of school principals
Source: English and Steffy, (2001), Deep Curriculum Alignment, pp. 91-97.
Source: Presentation by Dr. Victoria Bernhardt, April 2007
Current State of Data Collection• Student Learning
– Statewide assessments– Other standardized assessments– Few common classroom assessments
• Demographic– Three Years (2007-2008, 2008-2009 and 2009 2010) of data
School Processes– Little data on programs, curriculum maps, and School improvement efforts
• Perceptions– Data on stakeholder beliefs and feelings taken from self-reported needs on
EXPLORE and PLAN
Future State of Data Collection
• Student Learning– Use of statewide assessments for diagnostic purposes– Creation of common, summative assessments for end-of-unit and end-of course
purposes– Move toward standards-based grading and use of formative assessment strategies
• Demographic– Development of historical demographics from using data from former student
management systems– Collection of teacher, parent, and community demographic data, especially
environmental data sets• School Processes
– Numeric and alpha data collected on school instructional and management programs, curriculum maps, and school improvement plans
• Perceptions– Stakeholder beliefs and feelings surveys/inventories disaggregated by student and
teacher data
WE MUST UTILIZE AN INQUIRY APPROACH
TO DATA ANALYSIS
WE MUST USE MULTIPLE SOURCES OF
DATA
We need a data warehouse
for our 21st century schools
WE MUST FOCUS ON DATA TO INCREASE STUDENT ACHIEVEMENT
Talking Points for the Purpose of Implementing
a Data Warehouse in Hillsdale County Schools
Building Blocks of Core Data in the Warehouse
• Data is pulled from (student information system) and then imported into Data Director (the warehouse).– Demographics – Student demographic information– Teachers – Teacher name and building information– Courses – Courses in the Master Schedule– Rosters - Makes students visible in warehouse
• “Garbage in/Garbage out” is our warning!– The point of entry into the student management system is
crucial. – The warehouse does not “create” or “fix” data, just reports on
the data.
Quality Data
Culture
Components
Importance
Factors Affecting
Timeliness Security
Utility
Accuracy
Policies & Regulations Standards &
Guidelines
Training & Professional Development
Data Entry Environment
Timelines & Calendars
Technology
Roles
Data StewardSuperintendent
Board Member
PrincipalTechnology
Support Staff
Office Staff
Teacher
More EffectiveDecision-Making
Achieving AYP
(Adequate Yearly
Progress)
Program Funding
Other
HardwareSoftwareNetwork
What can we do to help develop a data-driven culture?
• Ask questions about your district’s involvement in the data warehouse initiative
• Think of questions regarding student achievement that can be answered with data.
Subgroup Analysis
• Which 4th grade students are not making adequate growth based upon the Fall 2007 and Fall 2008 Reading MEAP?
• The Criteria:– Title in the form of a question– Identify the type(s) of data
• Demographic, student learning, school processes, and/or perceptions
– Identify the source and year(s) of data
Strategies to Build a Data Director Culture
• Professional development each month at the principal meetings
• Additional trainings for local leaders with identified data warehousing roles
• Calendar of reporting results to inform local leadership • Development of each district’s curriculum alignment with
State standards, • Professional development around
– student learning summative assessments – use and analysis of multiple measures of data– standards-based grading and reporting– formative assessment strategies– studying student work through collaborative inquiry
• Review the following data roles, starting with the principal.– What data roles/responsibilities do you have?
• Reviewing your list of trained professional staff:– What data roles/responsibilities will these people play?
• What roles still need to be filled?
Sample Principals’ Meeting Agenda
• Purpose:– Ongoing, work-embedded professional development
using DataDirector• Objectives
– developing questions for customized DataDirector reports – identifying roles for data team members– identifying professional development for spring, summer, and fall of
2009• Procedures
– PowerPoint slides as prompt for dialogue– DataDirector for reports– Data Team lists
Action Plans• Plan out how you will meet with your learning team to
identify and support data roles• Plan out how you will collect and analyze additional data• Who can support you?
– HCISD – creates permissions, upload data from OEAA, supports templates for uniform field headers
– HCISD – dialogue about field headers for data collection, supports new reports, refine reports, dialogue about instructional decisions
– HCISD consultants – support for the content areas, professional development, and use of inquiry to build reports dialogue about field headers for data collection, supports new reports, refine reports, dialogue about instructional decisions
Strategies to Build a Data Director Culture
• Professional development each month at the principal meetings, supported by local superintendents
• Additional trainings for local leaders with identified data warehousing roles
• Calendar of reporting results to inform local leadership
• Development of each district’s curriculum alignment with State standards, – frontloaded from State standards– backloaded from statewide assessment results
• Professional development around – student learning summative assessments – use and analysis of multiple measures of data– standards-based grading and reporting– formative assessment strategies– studying student work through collaborative inquiry
Mostly student learning
Typicallymostly student
learning disaggregated
Most oftenstudent learning
anddemographic.
Longitudinal,student learning,
demographics,school processes, and perceptions
All plus statistics
from research.
All plus financial
Year One Purposes
Let’s find out why some processes are successful and why some processes lead to failure
Year Two and Three Purposes
Source:
Presentation by Dr. Victoria Bernhardt, April 2007
Big Picture… 2009 2010
– Overview of Data Director • Principals, Superintendents, “Data Coordinators”
• Fall 2010 • --- Basics of Data Director
District Data Teams • Winter 2011 --- Assessment Creation
District Data Teams
• Spring 2011 --- Putting It All Together
District Data Teams
• Summer 2011
--- Data Camp (two days)District Data TeamsOpen to Classroom Teachers
Summer Data Camp
– Using State Data to Inform School Improvement Goals– Using School Data to Clarify and Address the Goals
Follow up Professional Development
2010-2011– Examining Student Work to Inform Instruction – Using Classroom Data to Monitor Student Progress
Strategies to Build a Data Director Culture
• Professional development each month at the principal meetings, supported by local superintendents
• Additional trainings for local leaders with identified data warehousing roles
• Calendar of reporting results to inform local leadership
• Development of each district’s curriculum alignment with State standards, – frontloaded from State standards– backloaded from statewide assessment results
• Professional development around – student learning summative assessments – use and analysis of multiple measures of data– standards-based grading and reporting– formative assessment strategies– studying student work through collaborative inquiry
Assessment Calendar
Strategies to Build a Data Director Culture
• Professional development each month at the principal meetings, supported by local superintendents
• Additional trainings for local leaders with identified data warehousing roles
• Calendar of reporting results to inform local leadership
• Development of each district’s curriculum alignment with State standards, – frontloaded from State standards– backloaded from statewide assessment results
Professional development around – student learning summative assessments – use and analysis of multiple measures of data– standards-based grading and reporting– formative assessment strategies– studying student work through collaborative inquiry
Curriculum Alignment
• frontloaded Curriculum Mapping– Implementation of
Michigan Merit Curriculum
• TECH Center offerings• Personal Curriculum
– Implementation of Science GLCE and Social Studies GLCE/HSCE
• backloaded
– Analysis of standardized test results
– Develop SIP goals
Strategies to Build a Data Director Culture
• Professional development each month at the principal meetings, supported by local superintendents
• Additional trainings for local leaders with identified data warehousing roles
• Calendar of reporting results to inform local leadership • Development of each district’s curriculum alignment with State standards,
– frontloaded from State standards– backloaded from statewide assessment results
• Professional development around – student learning summative assessments – use and analysis of multiple measures of data– standards-based grading and reporting– formative assessment strategies– studying student work through collaborative inquiry
Standard Teachers Principals Central Office (Data Coordinators, Technology Support Personnel, and Office Staff)
Superintendent
Process:Data-Driven
Works with colleagues to use disaggregated data to establish professional learning goals
Analyzes with the faculty disaggregated student data to determine school improvement/professional development goals
Support administrator and teacher analysis of data
Work with the school board, central office staff, and school faculties to establish adult learning priorities
Analyzes relevant student data in order to monitor and revise school and classroom improvement strategies
Engages teachers, parents, and community members in data-driven decision making
Use staff data to design district wide professional development experiences
Analyzes relevant staff data to design teacher professional development
Desired Outcomes for National Professional Development Standards, 2008-2011
Standard Teachers Principals Central Office (Data Coordinators, Technology Support Personnel, and Office Staff)
Superintendent School Board
Content:Quality Teaching
Uses various classroom assessment strategies
Promotes the use of a variety of classroom assessments
Ensures staff implementation of quality instruction
Context:Leadership
Participates in instructional leadership development
Creates a school culture that supports continuous improvement
Develop teachers to serve as instructional leaders
Ensures improved student achievement is district priority
Adopts policies that support ongoing professional learning and continuous improvement
Desired Outcomes for National Professional Development Standards, 2008-
2011
Lessons Learned from Others• Go slow to go deep to go fast• Create a working environment that
demonstrates collaboration between technology and instruction
• Support necessary capacity for data roles
HCISD Data LeadsPat Dillon
General Education Director
• “Data out”• Creation and analysis of
data-driven reports
William YearlingInformational Technology
• “Data in”• Identification, collection,
and organization of data
Questions?