1. Shiawassee County’s Data Project

2. October 25, 2007AESA Why a Data Project? Student achievement is the goal of all school districts. Resources (time & money) are limited. NCLB & Education YES! have created a high stakes situation for schools. The use of data to make informed decisions is more crucial than ever.

3. October 25, 2007AESA Student Achievement is the Goal

4. October 25, 2007AESA What are our Needs? In 1995, Shiawassee County Schools determined they had a need and desire to enter into a countywide assessment project. As a result, a county assessment committee was formed and a search conducted for a common assessment. In 1995, Shiawassee County Schools determined they had a need and desire to enter into a countywide assessment project. As a result, a county assessment committee was formed and a search conducted for a common assessment. In 1997, on-line testing began. Seventy-five percent of the districts in the county participated in the project. In 1997, on-line testing began. Seventy-five percent of the districts in the county participated in the project.

5. October 25, 2007AESA Since 1997… An on-line testing system was used countywide multiple times a year every year. An on-line testing system was used countywide multiple times a year every year. K-5 testing requirements were instituted by the state. K-5 testing requirements were instituted by the state. NCLB was created and implemented. NCLB was created and implemented. Shiawassee County schools expanded their assessment capabilities and activities as well as their data use and analysis abilities. Shiawassee County schools expanded their assessment capabilities and activities as well as their data use and analysis abilities.

6. October 25, 2007AESA As Our Expertise Has Grown… One year of Wahlstrom work/study provided a background in the multiple types of data (outcome, demographic, process, and perception). Three years of Data Packets have been used to make limited school improvement decisions. Trainings & experiences took place using a variety of data for decision making purposes (Savy with SASI, Test Wiz, School Improvement Planning Days, etc.). County Assessment Committees were formed & their results analyzed which further stressed the need for data based solutions. Local Service Planning results found county consensus that data organization and analysis was a need. County Assessment Survey and CCIC Surveys discovered districts were looking for similar attributes in a data system.

7. October 25, 2007AESA What do schools need to use data effectively …  as a means to monitor a program’s impact on student achievement  to identify the most critical opportunity areas to focus school improvement efforts? The Question Now Is…

8. October 25, 2007AESA A tool to help districts become data driven in order to meet the requirements of NCLB and Ed YES! A collection of various sets of data found in a variety of unrelated locations and formats brought into one relational database. A system that will allow districts to find answers and ask complex questions that uncover underlying problems – leading to the design of data driven student achievement and school improvement strategies. A program that will incorporate data into a fully relational data warehouse that includes: –Financial data –Personnel data –Building infrastructure data –Student demographic data –Student achievement data –Assessment data and answers a variety of diverse and interactive questions easily. A Data Warehouse

9. October 25, 2007AESA Many Programs are Data Mining Tools Assessments –Most of these tools do not contain data from other sources beyond student demographics. Student Information Systems –These packages were not designed to link data from multiple years with assessment and special program data, or even teacher data. Document Storage –There is no association to student, teacher and assessment data in order to identify areas to target for school improvement. They address the following in isolation:

10. October 25, 2007AESA We have experience with data mining (through MAPS, Data Packets, etc.). We are ready to move to the next level. Our local districts all agree an interactive data warehouse is what would best meet their needs. The Answer…

11. October 25, 2007AESA Data Warehouse Timeline 2004-2005 Academic Year SRESD staff attended multiple vendor demonstrations throughout the state September 2005 RFI requirements and criteria established September – October 2005 The opportunity to submit an RFI was given to: Achieve! Data SolutionsChancery SMSCompass CRESTCRMdataMetrics Software, Inc. Edmin.com, IncEdsmartEnterprise Computing Service, Inc. eScholar LLCExecutive Intelligence, Inc.IBM Just 5 ClicksKent ISDMI Tracker Midwest Educational GroupNational Study of School EvaluationPearson School Systems Performance MattersPlatoQSP Regional Data ServicesRiverdeep, Inc.Sagebrush Corp. SCHOLARincSchoolCity, Inc.Schoolnet, Inc. School Interopability FrameworkSkywardSwiftknowledge, Inc. TetraData Corp.TurnLeaf

12. October 25, 2007AESA September – October 2005 RFI received from: Achieve! Data Solutions, LLCEdmin.com, Inc. EdsmarteScholar LLC Kent ISDMidWest Educational Group Pearson School SystemsSagebrush, Corp. SchoolCity, Inc.TetraData Corp. November 1- 3, 2005 Prescreening occurred – RFI eliminated: Edmin.com, Inc.Kent ISDMidWest Educational GroupSagebrush, Corp. November 10, 2005 RFI Committee Review of candidates by county data project committee consisting of curriculum directors, technology experts, principals and teachers: Achieve! Data SolutionsEdsmart eScholar, LLCPearson School Systems SchoolCity, Inc.TetraData Corp. Data Warehouse Timeline continued

13. October 25, 2007AESA Training Requirements Speed and Efficiency of Data Easy to Query Drill Down Capabilities Longitudinal Data Capabilities (consider # of years as well as ability) Formats (charts, graphs, etc.) (Graphs in system, including longitudinal, & do not require export) Pre-formatted Reports Export Capabilities Web Based Multiple Levels Importability Proven Data Inputs (data elements are cited that are supported by research) Customized Fields Customized Reports/Flexibility Student Work Tracked Michigan Curriculum Frameworks/GLCE Addressed SIF Compliant Testing Capabilities Achievement Data Demographic Data Process Data Perception Data Support Critical Important Bonus RFI Committee Review Criteria

14. October 25, 2007AESA Narrowing the Field November 10, 2005 Final two vendors chosen for in-house demonstrations: Achieve! Data Solutions TetraData Corp. Demonstration requirements and score criteria for the demonstration were determined by the county data committee project committee. December 6, 2005 In-house demonstrations by Achieve! Data Solutions and TetraData Corp.

15. October 25, 2007AESA The Process Vendors received demonstration requirements: Demonstration for users at six different levels: ISD, Superintendent, Curriculum Director, Principal, Teacher, Parent. Samples of queries, pre-formatted reports (drilled down to individual student level), charts and graphs; creation of non-preformatted queries and reports; different types of data “interaction”; a “live” data import. Examples of training model, including content and timing (timeline for set up, data upload and implementation) as well as an explanation of technical and user support available. Explanation of all costs (including: components needed, technology costs, start up costs, annual costs, consultation costs, and training/support costs). Explanation of the frequency of updates (how often is new data added to the warehouse and when will that data “show up” in reports/queries).

16. October 25, 2007AESA SRESD district participants see vendor demonstrations and rate the products based on the following criteria: Ease of use Charts & Graphs Drill down ability Pre-formatted reports Pre-formatted queries Creation of customized reports Creation of customized queries Interaction of process & perception data with achievement & demographic data Data upload speed & efficiency Training Initial setup timeline Technical support User support Frequency of updates Demonstration Criteria

17. October 25, 2007AESA The Final Selection

18. October 25, 2007AESA Data Framework for Continuous Improvement Enrollment, Mobility, Attendance, Drop- out/Graduation Rate, Ethnicity, Gender, Grade Level, Teachers, Language proficiency Perceptions of Learning Environments, Values and Beliefs, Attitudes, Questionnaires, Observations Standardized Tests, Norm/Criterion Referenced Tests, Grade point, Formative Assessments Demographics Student Learning School Process Perceptions Gaining active insight by analyzing data to improve learning for all students. Copyright ©1991-2005 Education for the Future Initiative, Chico, CA Programs, Instructional Strategies, Classroom practices, Assessment Strategies, Summer School, Finance, Transportation Information Foundation 2005 TetraData Confidential

19. October 25, 2007AESA Analyzer and DASH 2 components of the warehouse Analyzer allows for flexibility of complex reports: comparing variables, longitudinal reports, looking at trends, etc. DASH provides a snapshot of an identified issue.

20. October 25, 2007AESA 2005 TetraData Confidential

21. October 25, 2007AESA 2005 TetraData Confidential

22. October 25, 2007AESA

23. October 25, 2007AESA

24. October 25, 2007AESA Building a Warehouse Step 1 – Data Discovery –Defining & acquiring data to be included in the data warehouse Step 2 – Mapping –Mapping data from source system(s) to the data warehouse –Aligning various data elements into common folders Step 3 – Engineering –Building the warehouse & adding the data Step 4 – Quality Assurance –Querying in the warehouse to determine if the data is mapped & loaded accurately Step 5 – Implementation –Using the warehouse to make data decisions

25. October 25, 2007AESA Available Data in Warehouse Right Now Achievement Data MEAP Grades GPA Courses Credits Teachers Student Data Subgroups Lunch Status Special Education Language Ethnicity Discipline Attendance Process Data Title One Programs Extra Curricular Activities Programming

26. October 25, 2007AESA Two Distinct Uses: Summary Reports – Annual/semi-annual long-term results, after instruction Monitoring Reports – On-going, check of progress

27. October 25, 2007AESA Welcome to Our Warehouse http://analysis03.tetradata.com/ease-e/Login.aspx

28. October 25, 2007AESA Using Our Warehouses Summer School Intervention Identification Annual Report Achievement Trends Professional Development Planning Regionally based on Student Achievement (Ds and Fs) District and Building Profiles Program Evaluation NCA Goal Identification and Monitoring Responses to Board Questions Grant Applications (Special Education, Writing, Math, CASM, etc.)

29. October 25, 2007AESA Professional Development Then, Now, and in the Future (Based on Zoomerang Survey) Five Day Analyzer Trainings – All 8 districts have been involved Local District and Board Overview Presentations Dabbling with Data Sessions RtI and Program Evaluation Office Professional Training (2 Days) Report of the Month Specialized Group Trainings Data Ambassador Training Half Day Specialized Skill Ongoing Trainings Annual Report, NCA Goal, Profile Update Topic Work Sessions Etc, Etc, Etc…

30. October 25, 2007AESA

31. October 25, 2007AESA Questions