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Taking a Statewide Longitudinal Data System (SLDS) From Fundamentals to Advanced Capabilities

This presentation provides a detailed overview of the development and implementation of a statewide longitudinal data system (SLDS), including the collection, storage, and analysis of student and school data. It covers the evolution of the system, from basic data collection to advanced analytics using growth, achievement, and value-added measures. The presentation also includes demonstrations of the SLDS dashboards and reporting tools.

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Taking a Statewide Longitudinal Data System (SLDS) From Fundamentals to Advanced Capabilities

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  1. Taking a Statewide Longitudinal Data System (SLDS) From Fundamentals to Advanced Capabilities Melissa Straw, Wisconsin DPI Brian Pritzl, VersiFit Technologies Ernie Morgan, Value Added Research Center (VARC) Mike Christian, Value Added Research Center (VARC) 25th Annual STATS-DC 2012 Data Conference July 12, 2012

  2. Agenda

  3. Data and Reporting Fundamentals

  4. Data System BackgroundPre-Grant • Implementation of an individual student enrollment system data collection in 2004-05. Included third Friday enrollment, year end indicators, discipline, and IDEA child count. • Creation of a Unique Student ID (WSN) for all WI public students through Wisconsin Student Locator System (WSLS). • Student data available starting with the 2005-06 school year.

  5. SLDS Grants 1st Generation Data Projects • LDS Data Warehouse or ODS • First student-centric data warehouse at DPI • Stored and linked student and school data from a variety of sources including collection systems, spreadsheets, and external files for reporting and analysis • ISES YE, ISES CD, ISES Discipline, WSAS, ACT, AP, SGP, ACCESS ELL, Graduation, School Data, WSLS, State Outcomes Data, P20 NSC Enrollment Data, Student Growth Percentile (SGP) Data, Graduation Cohort and Rate Data • Coursework Completion System (CWCS) • Course data including a student-teacher-course link

  6. SLDS Grants1st Generation Dashboard and reporting Projects

  7. SLDS GrantsNext Generation Data, Dashboards, Reporting • DPI purchased a suite of data, dashboard and reporting tools • Data Model & Dashboard from VersiFit Technologies • Based in Appleton • Serves MMSD, MPS, Chicago Public Schools, Oregon State, Hawaii, etc. • Focus on business intelligence solutions specific to education • Contract signed 02/16/11 • ETL and Reporting tools from Microsoft • Reporting tool will also be utilized throughout the agency for operational reporting. • The LDS ODS is now currently being used as a data store as we transition to our new data warehouse system • Wisconsin Information System for Education Dashboard solution or WISEdash, powered by Edvantage

  8. WISEdash Architecture Dashboards & Reports ETL DW/LDS Users Clean Conform Create Collections Data Statewide SIS State Students Schools Assessments P20/NSC Value Added SGP Licensure ECE

  9. Program Membership Test Scores Financial Balances Budgets Student Marks Purchasing, Accounts Payable, Inventory Student Health & Medical Conditions Transport Behavior Enrollment Period Attendance Daily Attendance Edvantage™ Domains Test Participation Alumni Actions Graduate Outcomes Metrics Support Student-Staff Associations Schedules Special Education Instruction Practices Student Cohorts Staff Absences Program Attendance Student Housing Performance Impact Diploma Requirements Students, Schools, Calendars, Accounts, Staff Staff Effectiveness Data Quality Staff Qualifications & Development Engagement Staff Recruitment & Evaluation Enrollment Snapshots Surveys School/ Department Metrics Highly Qualified Mobility Stability Financial Aid At-Risk Students Recruitment Truancy

  10. SLDS GrantsDashboards and reporting

  11. Introduction to Growth

  12. Achievement, Growth and Value-Added • Achievement (NCLB) • a “point in time” measure of student proficiency • compares the measured proficiency rate with a predefined proficiency goal • Gain (MDAT) • measures average gain in student scores from one year to the next • Growth (SGPs) • measures average gain in student scores from one year to the next • accounts for the prior knowledge of students • Valued-Added (VARC) • measures contribution of teachers/schools/districts to gain in student scores • accounts for the prior knowledge of students • accounts for student demographic characteristics • accounts for test measurement error

  13. All these measures are based on student test data, but analyzed different ways

  14. Combining Measurers: Achievement, Growth or Value-Added • For the most complete picture of student and school performance, it is best to look at Achievement in combination with Growth or Value-Added. • This will tell you: • What students know at a point in time (Achievement) • How students at your school are growing (Growth) or how your school is affecting student academic growth (Value-Added)

  15. Advanced Analytics: SGP, WISEdash, and Guided Analysis

  16. Demonstration • Tutorial • WISEdash • SGP Visualization • Guided Analysis • Note: The tutorial shown in the presentation will soon be available here: http://dpi.wi.gov/lds/dashhome.html.

  17. Partnerships

  18. Evolution Timeline Value-Added Statewide Opt-In Year 1 (advisory group) Madison Metropolitan School District Milwaukee Public Schools Statewide Opt-In Year 2 Statewide Demonstration Statewide All Districts School Year 99-00 00-01 01-02 02-03 03-04 04-05 05-06 06-07 07-08 08-09 09-10 10-11 11-12 Edvantage DPI 1st Gen (WINSS) Other Districts (Green Bay, Racine) Madison Metropolitan Edvantage Milwaukee Public Schools 1st Gen Madison Metropolitan 1st Gen Milwaukee Public Schools Edvantage Milwaukee Finance & Staff DPI Edvantage

  19. Advanced Analytics: Value-Added and Edvantage

  20. Value-Added Partner Districts

  21. The Power of Two & Achievement Value-Added Compares students’ performance to a standard Measures students’ individual academic growth longitudinally A more complete picture of student learning Factors in students’ background characteristics outside of the school’s control Does not factor in students’ background characteristics Measures students’ performance at a single point in time Measures the impact of teachers and schools on academic growth Critical to students’ post-secondary opportunities Critical to ensuring students’ future academic success Adapted from materials created by Battelle for Kids

  22. The Oak Tree Analogy To view a narrated version of this analogy go to http://varc.wceruw.org/Projects/wisconsin_statewide_examples/ChapterOne/index.htm

  23. Value-Added Color Coding These colors are meant to categorize results at a glance, but making responsible decisions based on Value-Added estimates may require more careful use of the data. General guidelines: Green and Blue results are areas of relative strength. Student growth is above average. Gray results are on track. In these areas, there was not enough data available to differentiate this result from average. Yellow and Red results are areas of relative weakness. Student growth is below average.

  24. NUMBER OF STUDENTS (WEIGHTED) VALUE-ADDED ESTIMATES +10 +5 -10 -5 0 Numbers higher than 0 represent growth that is higher than average. Students are learning at a rate faster than the district/state average. Numbers lower than 0 represent growth that is lower than average. Students are still learning, but at a rate slower than the district/state average. 0 represents the district or state average growth for students. 30 Grade 4 MATH 47.1 Grade 3 -8.1 Grade 4 39.8 -2.5 Grade 5 43.0 +5.0

  25. Value-Added Scatter Plots 100 These scatter plots are a way to represent Achievement and Value-Added together Achievement 80 60 Percent Prof/Adv (2010) Value-Added 40 20 0 -15 -10 -5 0 +5 +10 +15 Value-Added (2010-2011)

  26. E Value-Added Scatter Plots C A. Students know a lot and are growing faster than predicted E. Students are about average in how much they know and how fast they are growing B. Students are behind, but are growing faster than predicted C. Students know a lot, but are growing slower than predicted D. Students are behind, and are growing slower than predicted 100 D A 80 B 60 Percent Prof/Adv (2010) 40 20 0 -15 -10 -5 0 +5 +10 +15 Schools in your district Value-Added (2010-2011)

  27. Value-Added Data Integration • Historically, VA data was collected at individual districts and integrated into local DWs. • Each deployment was unique. • A common data model, data set, and data visualization that could be used for all districts and the state were developed. • VARC produces VA data sets periodically through the year. • A standard loader application was created to automatically integrate this into the DW.

  28. Demonstration • Value-Added Dashboard • http://dashboard.demo.versifit.com/Dashboard/

  29. Next Steps

  30. Next Steps • Value-added implemented statewide through WISEdash by the end of 2012 • Integration of the following datasets into the Edvantage DW for analysis: • Statewide SIS starting 2013 • Additional assessment data into the data warehouse including ACCESS for ELL, NWEA MAP, and the new SMARTER assessment • Graduation cohort and Rate data • Postsecondary data (NSC + coursework) • Program Participation • Special Education • Staff Data • Early Childhood Data • Additional Documentation and Guided Analysis Workbooks • Implement Dashboard Cohorting Feature • Reporting • Enhancements to value-added models (differential effects, expanded grades and subjects)

  31. DPI Information • Additional Information • DPI LDS Project – www.dpi.wi.gov/lds • SDPR – https://apps2.dpi.wi.gov/sdpr/spr.action • WISEmaps - https://wisemaps.dpi.wi.gov/ • WISEdash - http://dpi.wi.gov/lds/dashhome.html • OEA Growth page - http://dpi.wi.gov/oea/growth.html • Contact • Melissa Straw (melissa.straw@dpi.wi.gov)

  32. VersiFit Information • Additional Information • VersiFit – www.versifit.com • Contact • Brian Pritzl (pritzlb@versifit.com)

  33. VARC Information • Additional Information • VARC – varc.wceruw.org • Contacts • Michael Christian (mchristian2@wisc.edu) • Ernie Morgan (ernestmorgan@wisc.edu)

  34. Questions?

  35. Additional Screenshots

  36. WISEdash Everything is Completely Customizable Content Area for metrics, reports or other content Tabbed Navigation with Dropdown Menus Cascading Filters with complete control of order, sorts, filters, grouping, execution, etc. Navigation (links) to related content internal or external to the Dashboard

  37. Guided Analytics • Metrics focused on a specific analysis are collected and ordered • Probative questions on the data are linked to each • Formatted to print but on-line version in the works • Used as a PD tool

  38. Student Growth • Layered Presentations • Student past performance on state assessment for a selected subject is plotted over proficiency levels • Year over year growth is highlighted • Statistical projections for growth is presented

  39. Value-Added Dashboard Prompts are Cascading & Red in the Label calls user to a prompt requiring a selection Prompts with Yellow in the Label prompts the user to Press the Go button Font Color of Prompts Tie to Guidance below

  40. Value-Added Dashboard

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