Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Shiawassee County’s Data Project 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. October 25, 2007 AESA Student Achievement is the Goal October 25, 2007 AESA 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 1997, on-line testing began. Seventy-five percent of the districts in the county participated in the project. October 25, 2007 AESA Since 1997… • An on-line testing system was used countywide multiple times a year every year. • K-5 testing requirements were instituted by the state. • NCLB was created and implemented. • Shiawassee County schools expanded their assessment capabilities and activities as well as their data use and analysis abilities. October 25, 2007 AESA 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. October 25, 2007 AESA The Question Now Is… 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? October 25, 2007 AESA A Data Warehouse • 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. October 25, 2007 AESA Many Programs are Data Mining Tools They address the following in isolation: • 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. October 25, 2007 AESA The Answer… 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. October 25, 2007 AESA 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 Solutions Chancery SMS Compass CREST CRM dataMetrics Software, Inc. Edmin.com, Inc Edsmart Enterprise Computing Service, Inc eScholar LLC Executive Intelligence, Inc. IBM Just 5 Clicks Kent ISD MI Tracker Midwest Educational Group National Study of School Evaluation Pearson School Systems Performance Matters Plato QSP Regional Data Services Riverdeep, Inc. Sagebrush Corp. SCHOLARinc SchoolCity, Inc. Schoolnet, Inc. School Interopability Framework Skyward Swiftknowledge, Inc. TetraData Corp. TurnLeaf October 25, 2007 AESA Data Warehouse Timeline September – October 2005 continued RFI received from: Achieve! Data Solutions, LLC Edmin.com, Inc. Edsmart eScholar LLC Kent ISD MidWest Educational Group Pearson School Systems Sagebrush, Corp. SchoolCity, Inc. TetraData Corp. November 1- 3, 2005 Prescreening occurred – RFI eliminated: Edmin.com, Inc. Kent ISD MidWest Educational Group Sagebrush, 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 Solutions Edsmart eScholar, LLC Pearson School Systems SchoolCity, Inc. TetraData Corp. October 25, 2007 AESA RFI Committee Review Criteria 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 OctoberSupport 25, 2007 AESA Critical Important Bonus 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. October 25, 2007 AESA 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). October 25, 2007 AESA Demonstration Criteria 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 October 25, 2007 AESA The Final Selection October 25, 2007 AESA Data Framework for Continuous Improvement Demographics Standardized Tests, Norm/Criterion Referenced Tests, Grade point, Formative Assessments Enrollment, Mobility, Attendance, Dropout/Graduation Rate, Ethnicity, Gender, Grade Level, Teachers, Language proficiency Gaining active insight by analyzing data to improve learning for all students. Student Learning Programs, Instructional Strategies, Classroom practices, Assessment Strategies, Summer School, Finance, Transportation October 25, 2007 2005 TetraData Confidential Perceptions School Process AESA Perceptions of Learning Environments, Values and Beliefs, Attitudes, Questionnaires, Observations Information Foundation Copyright ©1991-2005 Education for the Future Initiative, Chico, CA 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. October 25, 2007 AESA October 25, 2007 AESA 2005 TetraData Confidential October 25, 2007 AESA 2005 TetraData Confidential October 25, 2007 AESA October 25, 2007 AESA 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 October 25, 2007 AESA Available Data in Warehouse Right Now • Achievement Data • MEAP • Grades • GPA • Courses • Credits • Teachers • Process Data • Title One Programs • Extra Curricular Activities • Programming October 25, 2007 • Student Data • Subgroups • Lunch Status • Special Education • Language • Ethnicity • Discipline • Attendance AESA Two Distinct Uses: • Summary Reports – Annual/semi-annual long-term results, after instruction • Monitoring Reports –On-going, check of progress October 25, 2007 AESA Welcome to Our Warehouse http://analysis03.tetradata.com/ease-e/Login.aspx October 25, 2007 AESA 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.) October 25, 2007 AESA 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… October 25, 2007 AESA October 25, 2007 AESA Questions October 25, 2007 AESA