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?