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Published byDominic Sparks Modified over 9 years ago
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2011 OSEP Leadership Mega Conference Collaboration to Achieve Success from Cradle to Career 2.0 Maryland IDEA Scorecard Data Driven Decision Making Nancy Vorobey, Maryland State Department of Education Karla Marty, Maryland State Department of Education Dianne Tracey, Johns Hopkins University August 3, 2011 304/312
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Maryland IDEA Scorecard This document and application were developed and produced by the MSDE, Division of Special Education/Early Intervention Services, in collaboration with the Johns Hopkins University/Center for Technology in Education. IDEA Part B Grant #H0270900035A and IDEA Part C Grant #H181A090124 are funded by the U.S. Department of Education, Office of Special Education and Rehabilitative Services. The views expressed herein do not necessarily reflect the views of the U.S. Department of Education or any other federal agency and should not be regarded as such. The Division of Special Education/Early Intervention Services received funding from the Office of Special Education Programs, Office of Special Education and Rehabilitative Services, U.S. Department of Education.
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Maryland IDEA Scorecard It is imperative that we use a data-driven decision making process to guide program changes that will improve the quality of services for children and youth with disabilities and their families in Maryland, thus leading to improved results.
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Moving from Data to Interventions Process: Review pre-defined reports to identify children and youth in need of intervention(s) Make decisions about targeted interventions or programmatic decisions Allocate appropriate resources Monitor progress
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Early Childhood What does this tool do? – Allows us to compare child and program characteristics at State, local, and individual child levels to help inform programmatic decision-making Types of early intervention/early childhood special education data fed into Early Childhood Scorecard Individualized Family Service Plan/ Individualized Education Program (IFSP/IEP) Early Childhood Accountability System (ECAS) Work Sampling System (WSS) Child Outcomes Summary (COS) Present Level Of Development (PLOD) Present Level of Performance (PLOP)
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High Quality Decision-Making Individual Child and Family Local ProgramStatewide
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Informed Programmatic Decision-Making As a Program Director, you are interested in identifying children by progress at exit status (A, B, C, D, or E) and exploring the characteristics of those children (e.g., category of eligibility, age of referral) and/or services (e.g., type of service, location of service) to determine which, if any, of these characteristics could be contributing to differences in status.
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Children Closing the Gap in COS Outcomes Children Birth – Five Receiving Services Through an IFSP
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Progress at Exit - Did Not Show Improvement Children Three – Five Receiving Services Through an IEP
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Maryland IDEA Scorecard Types of data fed into MD IDEA Scorecard Attendance Enrollment Discipline Achievement Individualized Education Program Possible uses of MD IDEA Scorecard data Examine trend data available in a longitudinal data system Analyze data to identify areas of need for students or programs Drill down to student level data for the purpose of identifying children at risk
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Early Alert Report
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Maryland IDEA Scorecard - Next Steps Defining and refining policies regarding exchange of information for a birth through 21 comprehensive and coordinated system of services Linking to the Maryland Longitudinal Data System, currently included in Race To The Top initiative Continuing to create Professional Development opportunities in the form of online modules and webinars
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