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Building Data Quality within LEAs

Building Data Quality within LEAs. Agenda. Welcome/Introductions Data Quality and Data Governance Building Quality Councils Data governance activity Identifying data systems and data teams Obstacles / Solutions New 13-14 Q & A. Data Has Become High-Stakes. Educator Effectiveness

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Building Data Quality within LEAs

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  1. Building Data Quality within LEAs

  2. Agenda • Welcome/Introductions • Data Quality and Data Governance • Building Quality Councils • Data governance activity • Identifying data systems and data teams • Obstacles / Solutions • New 13-14 • Q & A

  3. Data Has Become High-Stakes • Educator Effectiveness • Teacher pay • Teacher grievances over data errors • School Performance Profile • Public perception of schools and districts • Funding • Dashboard • Curricular, instructional, and program decisions • Effective differentiated instruction

  4. High-Quality Data • Supports high-quality instructional decisions • Characteristics • Accurate • Timely • Useful • Secure • Requires effective data governance

  5. Elements of Data Governance • Team approach • Multiple players, including data owners • Regular communication, meetings • Everyone from board to administrative assistants has a role • Communication of impact of data quality • Training on why data important, each role • Documented policies and procedures • Data calendar and timelines

  6. Actions Improving Data Quality • Informing all staff about purpose, outcomes of data they touch • Posting data-entry standards and guidelines at workstations • Turning data-entry screens away from public view • Correcting data in source system, not PIMS files • Work on data year-round

  7. IU Support for Data Quality • Facilitate collaborative development, sharing of data standards, dictionary, calendar, manuals, other docs • Provide professional development regarding data-quality best practices for each role • Host vendor-specific SIS user groups to discuss data standards, issues (support existing user groups) • Facilitate communication with PDE

  8. Resources on Data Quality & Governance From the National Forum on Education Statistics • Building a Culture of Quality Data http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2005801 • Curriculum for Improving Education Data http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2007808

  9. Data Quality Council Meetings Goals • Create a networking environment • Share techniques for improving reporting accuracy • Share ways to maximize revenues

  10. Data Quality Council Meetings • Topics • Attendees/Invitations • Frequency • State Representation • Handouts/Resources • Obstacles/Solutions

  11. Example of characteristics to identify at council meeting before each collection Child Accounting

  12. Child Accounting What is Collected? • Average Daily Membership (ADM) • Student File • School Calendar • Student Calendar Fact How is it reported?

  13. Child Accounting Why the data is collected? • State Subsidies • Basic Education Funding • Special Education Funding • Tuition For Orphans Subsidy • Secondary Career and Technical Education Subsidy • Weighted Average Daily Membership (WADM) • Used in calculation of aid ratios for State subsidies

  14. Child Accounting Why the data is collected cont.? • Average Daily Attendance (ADA) • No Child Left Behind (NCLB) • Adequate Yearly Progress (AYP) • School Report Card • School Performance Profile • Federal ADA report

  15. Child Accounting What are the areas of concern? • Validate data • Verify calendar and enrollment information before uploading • Run validation reports after uploading • Correct errors, run validation reports again • Share information • Child accounting staff should communicate with • Business office • Technology • Special education

  16. Data Governance Exercise • What is the source of the data? • Who enters the data? • What system stores this data? • Who is responsible for the data? • Who reports the data? • Who certifies the data? • Who understands the impact to the LEA?

  17. Data Quality Council Meetings • Attendees/Invitations suggestions • Superintendent • Tech Director • HR Director • Business Manager • Special Education Director • Curriculum Coordinator • PIMS Administrator • Specific Data Administrator - Child Accounting, Penn Data etc. • Any one as appropriate - suggestions please? • There could be a different data team for each collection

  18. Data Quality Council Meetings Getting Started • Get together as a PIL region (IU PoCs) • Build a core district team within your IU region • Build inter-IU relationships

  19. Joint Data Quality Council Date • Ease of information sharing across the state • Third Wednesday of the month • 9:00 a.m. to Noon • Starting July 17th

  20. Data Systems and Data Teams activity

  21. Source Systems for Student Used for: • 2011-2012 Graduates, Dropouts, and Cohort • 2012-2013 Graduates, Dropouts, and Cohort • Accountability reporting; PSSA, Spring Keystone exams and CDT student uploads • Career and Technical Education • Child Accounting • Classroom Diagnostic Testing • Course/Highly Qualified Teacher • District and Student Enrollment • English Language Learners - End of Year Count/SES Provider • English Language Learners…ACCESS for ELL • Pre-code for Spring Keystone Exams and additional CDT student upload • Pre-code for Winter Keystone and Classroom Diagnostic Testing (CDT) student upload • Pre-code student upload for Summer Keystone Exams • PSSA Pre-code/ACCESS for ELLs Pre-code; updates Winter Keystone, CDT student uploads • Safe Schools • Special Education • Special Education Update

  22. Identify obstacles/roadblocks to creating data teams and quality data

  23. Identify solutions to the obstacles/roadblocks identified by your neighbor

  24. Whatis new for 13-14 School year?

  25. New 13-14 – tools to help • Data Quality Certification (DQC) • Pilots 1, 2 and 3 - starting over summer • Three main tracks • PIMS Admin / Entry Level PIMS Admin • LEA Administrator • Data Entry Track • Specialty Modules • Data Quality Engine • PA Secure ID • School Performance profile • Special Education • Child Accounting • Career and Technology Education • Teacher-Student Data Linkage/Educator Effectiveness

  26. New 13-14 – tools to help Data Quality Curriculum Goals • Reduce data related errors in state and federal reporting • Reduce data related errors that lead to reductions in funding • Increase quality of the data that will be used for evaluation purposes, such as the School Performance profiles • Increase understanding of critical issues such as FERPA, data relationships and best practices • Create an effective and enterprise-wide data culture

  27. New 13-14 – tools to help PIMS Data Quality Engine • Checks data against PDE business rules before it enters PIMS • Improved Data quality • Less deletes / Less overrides / Fewer cognos reports • Trainings available late summer / September • Uploading October 1st submission via the DQE

  28. New 13-14 – Data check PA Secure ID - New quality check The PA Secure ID and student last name in your system must match the PA secure ID and student last name in the PA Secure ID system! If there is a mis match the record will FAIL to upload No exceptions

  29. New 13-14 – Why you need quality data • School Performance Profile • Educator Dashboard • Teacher student Data Linkage / Educator effectiveness • Topic to address ASAP this summer!

  30. Educator Dashboard About the System Provide info on Intervention Services Offer Timely Data to Improve Student Performance . Identify Students at Risk of Dropping Out Support Effective Educators Dashboard Uses For Administrators For Teachers PA Educator Dashboard & Early Warning System Dashboard Features Secure& FERPA Compliant Intuitive and Easy to Use Created with Input from 3,000 Educators Provides Vital Info in a Single View Early Warning System metrics based on “ABC’s” – Attendance, Behavior, & Course Grades

  31. Teacher/student Data Linkage What is PVAAS Roster Verification? PIMS Course/HQT is the key file to prepopulate the PVAAS Roster System Roster Verification is a process for teachers to VERIFY their students rosters - are the right students linked to the right teachers for the right subject/grade/courses for the right proportion of instructional responsibility? School Admin and District Admin verify as well. Spring process

  32. Timeline 2013/14 PIMS Manual When will the manual be ready for initial public comment? The approved draft PIMS changes are posted at http://www.portal.state.pa.us/portal/server.pt/community/pims_-_pennsylvania_information_management_system/8959/p/1527314 How do you respond? There is an RA email account setup so all PIMS proposed change-related comments can be submitted. RA-PIMSComment@pa.gov

  33. Timeline 2013/14 PIMS Manual When is deadline to respond? The comment period lasts for roughly 30 calendar days. An email is sent to the Chief School Administrators informing them of the postings and the dates of the comment window. What is PDEs timeline to approve? Once the comment period ends, the responses are accumulated and presented to senior management. Final decision on each requested change is rendered and approved changes are added to the PIMS User Manual. Final adoption and release of final manual? Release of the new PIMS manual usually occurs in August

  34. Why we are doing this • Develop a consistent approach to data quality across the state • Facilitate communication between PDE and LEAs • Leverage training opportunities for all levels • Support networking opportunities for LEA’s across the state • Maximize funding for LEAs

  35. Any Questions / Roundtable / Feedback form

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