Transcript Slide 1
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 • 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
High-Quality Data
• • Supports high-quality instructional decisions • • • • Characteristics Accurate Timely Useful Secure • Requires effective data governance
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
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
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
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
Data Quality Council Meetings
Goals • Create a networking environment • Share techniques for improving reporting accuracy • Share ways to maximize revenues
Data Quality Council Meetings
• Topics • Attendees/Invitations • Frequency • State Representation • Handouts/Resources • Obstacles/Solutions
Example of characteristics to identify at council meeting before each collection
Child Accounting
Child Accounting
• What is Collected?
• Average Daily Membership (ADM) • How is it reported?
• Student File • School Calendar • Student Calendar Fact
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
Child Accounting
• Why the data is collected • No Child Left Behind (NCLB) • Adequate Yearly Progress (AYP) • School Report Card • School Performance Profile • Federal ADA report
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
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?
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
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
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
Data Systems and Data Teams activity
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
Identify obstacles/roadblocks to creating data teams and quality data
Identify solutions to the obstacles/roadblocks identified by your neighbor
What is new for 13-14 School year?
• 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
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
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 1 st submission via the DQE
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
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!
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About the System Provide info on Intervention Services Identify Students at Risk of Dropping Out Educator Dashboard Offer Timely Data to Improve Student Performance
For Teachers Dashboard Uses For Administrators PA Educator Dashboard & Early Warning System
Support Effective Educators
Dashboard Features
Secure & FERPA Compliant Intuitive and Easy to Use Created with Input from 3,000 Educators Early Warning System metrics based on “ABC’s” – Attendance, Behavior, & Course Grades
Copyright © 2010, SAS Institute Inc. All rights reserved.
Provides Vital Info in a Single View
Teacher/student Data Linkage
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 Copyright © 2010, SAS Institute Inc. All rights reserved.
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. [email protected]
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
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