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Building Data Quality within LEAs. Welcome/Introductions Data Quality and Data Governance Building Quality Councils Data governance activity Identifying.

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Presentation on theme: "Building Data Quality within LEAs. Welcome/Introductions Data Quality and Data Governance Building Quality Councils Data governance activity Identifying."— Presentation transcript:

1 Building Data Quality within LEAs

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

3 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 Data Has Become High- Stakes

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

5 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 Elements of Data Governance

6 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 Actions Improving Data Quality

7 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 IU Support for Data Quality

8 From the National Forum on Education Statistics Building a Culture of Quality Data Curriculum for Improving Education Data Resources on Data Quality & Governance

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

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

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

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

13 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 Why the data is collected? Child Accounting

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

15 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 What are the areas of concern? Child Accounting

16 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? Data Governance Exercise

17 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 Data Quality Council Meetings

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

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

20 Data Systems and Data Teams activity

21 Source Systems for Student Used for: Graduates, Dropouts, and Cohort 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 What is new for School year?

25 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 New – tools to help

26 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 New – tools to help

27 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 1 st submission via the DQE New – tools to help

28 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 New – Data check

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

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31 Copyright © 2010, SAS Institute Inc. All rights reserved.. About the System Identify Students at Risk of Dropping Out PA Educator Dashboard & Early Warning System Offer Timely Data to Improve Student Performance Provide info on Intervention Services Support Effective Educators Dashboard Uses Dashboard Features For Administrators For Teachers Provides Vital Info in a Single View Intuitive and Easy to Use Early Warning System metrics based on “ABC’s” – Attendance, Behavior, & Course Grades Created with Input from 3,000 Educators Secure & FERPA Compliant Educator Dashboard

32 Copyright © 2010, SAS Institute Inc. All rights reserved. What is PVAAS Roster Verification? 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 PIMS Course/HQT is the key file to prepopulate the PVAAS Roster System Teacher/student Data Linkage

33 When will the manual be ready for initial public comment? The approved draft PIMS changes are posted at _pennsylvania_information_management_system/8959/p/ How do you respond? There is an RA account setup so all PIMS proposed change- related comments can be submitted. Timeline 2013/14 PIMS Manual

34 When is deadline to respond? The comment period lasts for roughly 30 calendar days. An 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 Timeline 2013/14 PIMS Manual

35 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

36 Any Questions / Roundtable / Feedback form


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