
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 36 - 42 of 81
Format: Toolkits
Data Meeting ToolkitThe Data Meeting Toolkit is a suite of tools that groups can use to guide conversation around data and support data-based decisionmaking. The toolkit provides resources to support success before, during, and after data meetings.
Format: Quick Reference
618 Data Collection and Submission TimelineA graphic illustrating how different IDEA data collections can span multiple years and how a state may be working simultaneously with data from multiple school years.
Format: Quick Reference
Due Dates for SY 2022-23 IDEA DataIDC updates this list of EDFacts Submission System (ESS) files and EMAPS submissions due dates for SY 2022-23 so you don't have to! Download it and pin it to your refrigerator where it'll help you stay cool.
Format: Quick Reference
Frequently Used Terms and AcronymsDo you confuse your OMB MAX for your EMAPS? Has your SLDS slid into your SSIP? If so, this list is for you. Keep the alphabet soup organized with our handy Frequently Used Acronyms and Terms resource, downloadable for your convenience.
Format: Quick Reference
Privacy Resources for IDEAThis tool provides a list of privacy resources for IDEA.
Format: Applications and Spreadsheets
Data Sources for Calculating Significant DisproportionalityData Sources for Calculating Significant Disproportionality provides a summary of the data needed to calculate significant disproportionality for identification, placement, and discipline. For each category of analysis, this resource provides a description of the data needed to calculate the risk numerator and risk denominator, and notes the relevant EDFacts file specifications, including which subtotals or category sets, as appropriate.
Format: Applications and Spreadsheets
IDEA Part B Data Manager CompetenciesThe IDEA Part B Data Manager Competencies tool outlines foundational knowledge and skills necessary for typical data manager roles and responsibilities. The competencies reflect principles for effective management, support, and use of high-quality IDEA Part B data and fall under one of three overarching categories: content knowledge and skills, technical knowledge and skills, and interpersonal skills.