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Resource Library

Guides. Briefs. Toolkits. Quick reference information. IDC and its partners created these data quality resources to help states better prepare to address their existing or emerging IDEA data quality needs. Use our search and filtering tools to navigate the library.

Resources 1 - 7 of 16

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    An IDC Resource

    Format: Trainings

    The Importance of High-Quality Data and the Role of Business Rules

    The Importance of High-Quality Data and the Role of Business Rules instructional video provides a brief introduction to the concept of using business rules to promote and support the collection of high-quality data within state and local systems for IDEA Part B and C.

    An IDC Resource

    Format: Toolkits

    Success Gaps Toolkit: Addressing Equity, Inclusion, and Opportunity

    The Success Gaps Toolkit presents a process for using data and the Success Gap Rubric to identify root causes of gaps between groups of children in districts or schools. These success gaps occur when the education system is not meeting the needs of all groups of children and outcomes for some groups are different than outcomes for most groups. The toolkit, with its process and materials, provides a manageable and defined way for districts or schools to identify success gaps that are present and their root causes and then make a plan for addressing the gaps. The success gaps may be the graduation rate of students who are English learners compared to the rate of all other children, the out-of-school suspension rate of children who are Black compared to the rate of all other children, the identification of children who are Hispanic as children with specific learning disabilities compared to the identification of all other children, and other gaps.

    An IDC Resource

    Format: Quick Reference

    Significant Disproportionality Resources

    The Equity in IDEA regulations require states to determine annually if local education agencies (LEAs) are identified with significant disproportionality. The regulations outline specific requirements related to methods for identifying LEAs and activities the LEAs must complete after they are identified. These significant disproportionality resources can assist states with implementing these requirements and supporting LEAs through the process of meeting the requirements.

    An IDC Resource

    Format: Toolkits

    SEA Data Processes Toolkit

    Using the SEA Data Processes Toolkit to document data processes for all 616 and 618 data collections will establish a well-managed process for data collection, validation, and submission. In collaboration with IDC State Liaisons, states can use the toolkit to create and maintain a culture of high-quality data and establish and support consistent practices that produce valid and reliable data, while building the capacity of state staff. 

    An IDC Resource

    Format: Guides and Briefs

    Measuring Significant Discrepancy: An Indicator B4 Technical Assistance Guide

    The TA guide describes the methods a state might use to appropriately determine which of its districts has a significant discrepancy (including a significant discrepancy by race or ethnicity) in the rates of out-of-school suspensions and expulsions totaling greater than 10 days for children with disabilities.

    An IDC Resource

    Format: Toolkits

    Making the Most of Parent Involvement Data: Improving Quality and Enhancing Understanding

    This toolkit is designed to assist states as they plan for and carry out their efforts to collect, report, analyze, and use high-quality parent and family involvement data. It defines key concepts; offers guidance on ways to improve the quality of the collection, analysis, and use of parent and family involvement data; and provides resources and tools to help states in their efforts parent involvement data efforts.

    An IDC Resource

    Format: Applications and Spreadsheets

    LEA EDFacts Edit Check and Data Display Tools

    The LEA EDFacts Edit Check and Data Display Tools allow states to identify potential business rule errors or errors in category sets, subtotals, or totals prior to submitting the data to OSEP via the EDFacts Submission System. The tool also provides states with user-friendly data summaries.