Hillsdale Countys Data Director Initiative: Growing Our Warehouse

Hillsdale Countys Data Director Initiative: Growing Our Warehouse

Hillsdale Countys 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 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 Talking Points for the Purpose of Implementing a Data Warehouse in Hillsdale County Schools 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 Data Warehousing 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. Timeliness Utility Policies & Regulations Security Data Entry Environment

Components Accuracy Superintendent Board Member Principal Data Steward Roles Technology Support Staff Quality Data Culture Teacher Office

Staff Achieving AYP (Adequate Yearly Progress) Technology Hardware Software Network Factors Affecting Standards & Guidelines Training & Professional

Development Timelines & Calendars More Effective Decision-Making Importance Program Funding Other What can we do to help develop a datadriven culture? Ask questions about your districts 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 The Criteria: Title in the form of a question growth based upon Identify the type(s) of data the Fall 2007 and Fall Demographic, student learning, school processes, and/or 2008 Reading MEAP? 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 districts 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 districts 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 Source: Year Two and Three Purposes Presentation by Dr. Victoria Bernhardt, April 2007 Year One Purposes

Mostly student learning Typically mostly student learning disaggregated Most often student learning and demographic. Lets find out why some processes are successful and why some processes lead

to failure Longitudinal, student learning, demographics, school processes, and perceptions All plus statistics from research. All plus financial 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 Teams Open 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 districts 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 districts 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 districts 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 Desired Outcomes for National Professional Development Standards, 2008-2011 Standard Process: DataDriven Teachers

Principals Central Office (Data Coordinators, Technology Support Personnel, and Office Staff) Superintendent 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, 20082011 Standard

Teachers Principals Content: Quality Teaching Uses various classroom assessment strategies Promotes the use of a variety of classroom assessments Context:

Leadership Participates in instructional leadership development Creates a school culture that supports continuous improvement Central Office (Data Coordinators, Technology Support Personnel, and Office Staff)

Superintendent School Board Ensures staff implementation of quality instruction Develop teachers to serve as instructional leaders Ensures improved student achievement is district priority

Adopts policies that support ongoing professional learning and continuous improvement 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 Leads William Yearling Pat Dillon

Informational Technology General Education Director Data in Identification, collection, and organization of data Data out Creation and analysis of data-driven reports Questions?

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