[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-535352-105":59,"doc-detail-535352-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","root-cause-analysis-overview-data-center-for-addressing-significant-disproportionality-dcasd-in-brief","Root Cause Analysis Overview - Data Center for Addressing Significant Disproportionality (DCASD) In Brief","","Root Cause Analysis Overview explains how IDEA drives states to collect and review data on local education agencies (LEAs) and, when significant disproportionality is identified, to improve students with disabilities’ experiences and outcomes. The brief defines root cause analysis as a systemic investigation to uncover contributing factors and avoid decisions based on limited data. It outlines best practices, including team engagement, analysis of policies/procedures/practices, and evidence-supported RCA processes, plus the role of CCEIS strategies.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/root-cause-analysis-overview-data-center-for-addressing-significant-disproportionality-dcasd-in-brief/535352/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/root-cause-analysis-overview-data-center-for-addressing-significant-disproportionality-dcasd-in-brief/535352.png","ImageObject",300,407,{"name":92,"@type":93},"Riley West","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-16","2026-10-10",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does IDEA require states and LEAs to address using data?","Question",{"text":112,"@type":113},"IDEA requires state education agencies to collect and examine local data each year and determine whether significant disproportionality is occurring in each LEA.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What is root cause analysis in the context of significant disproportionality?",{"text":117,"@type":113},"Root cause analysis is a systemic investigation of contributing or root causes that helps LEAs identify true drivers and develop action plans to improve policies, practices, and procedures.",{"name":119,"@type":110,"acceptedAnswer":120},"What best practices should an LEA follow before starting an RCA?",{"text":121,"@type":113},"The brief recommends meaningful team engagement, careful analysis of data including policies/procedures/practices tied to the disproportionality areas, and a clearly defined RCA process supported by evidence.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},535352,1791688782,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":19,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":52},1099523885074,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","Root Cause Analysis Overview  \nIntroduction to Root Cause Analysis  \nThe Individuals with Disabilities Education Act (IDEA) requires state education agencies (SEAs) to collect and examine data from their local education agencies (LEAs) each year and to use that data to determine whether significant disproportionality is occurring within each LEA. If the state identifies an LEA as having significant disproportionality, that LEA must then take steps to focus on and improve the experiences and outcomes of students with disabilities by addressing and mitigating the cause(s) of significant disproportionality. Before any such steps can occur, however, the LEAs must identify the contributing causes of significant disproportionality. In this DCASD In Brief, the Data Center for Addressing Significant Disproportionality (DCASD) will provide an overview of one of the best practices LEAs can use in such cases: root cause analysis.  \nWhat Is Root Cause Analysis?  \nA root cause analysis (RCA) is a systemic investigation of the contributing, or root, causes of problems that organizations or institutions face. When it comes to addressing significant disproportionality, conducting an RCA can help LEAs unearth the true root causes and identify contributing factors of the significant disproportionality. LEAs can also create action plans based on RCA findings, which will have a higher likelihood of improving systemic structures, policies, practices, and procedures that led to the significant disproportionality. Alternatively, making assumptions or making decisions based on limited data can lead to costly changes that have little-to-no effect on the system or the students affected by the significant disproportionality.  \nBefore We Begin  \nThough IDEA does not identify a specific method for identifying the root causes of significant disproportionality, following best practices, including conducting an RCA, are recommended and should include  \ny the meaningful engagement of a team;  \ny the careful analysis of data, including policies, procedures, and practices (PPPs) used in the areas for which an LEA is identified with significant disproportionality; and  \ny engaging in a clearly defined RCA process that is supported by evidence.  \nDid You Know?  \nIDEA regulations require the identification of contributing factors and the subsequent targeting of improvement strategies to address these factors through a comprehensive coordinated early intervening services (CCEIS) approach that uses 15% of an LEA’s IDEA Part B (Sections 611 and 619) funds.1  \n(34 C. F. R. § 300. 646(d))  \n1 For more information, see U. S. Department of Education, Office of Special Education Programs. (2017) . IDEA Part B regulations: Significant disproportionality (Equity in IDEA). Washington, D.C.: Author. [https://sites.ed.gov/idea/fi](https://sites.ed.gov/idea/fi)les/significant-disproportionalityqa-03-08-17.pdf  \nDCASDIN BRIEF 1  \nWho Conducts an RCA?  \nOne key to a successful root cause analysis for significant disproportionality is assembling a varied team to engage in the process. It is important to have a team of partners who can help identify and understand local context2 and who have expertise and roles in various areas related to education, including students with disabilities (e.g., leadership, general education, special education, parents, community partners) .  \nWyhen rnseiderDingacatribmtingpfaorctoraofnsigtnifioantrdiRsprCopinality, it is important  \nthat the LEA team uses a variety of data to make informed decisions based on facts rather than assumptions. This wide range of data will provide a comprehensive approach to understanding root causes from a variety of sources.  \nWe use data to...  \n􀂙 test our assumptions.  \n􀂙 help direct our focus and know where to look deeper.  \n􀂙 develop the whole picture that influences our outcomes.  \n􀂙 make informed decisions.  \n􀂙 help us understand the implementation of policies, practices, and procedures.  \nWhat Will Guide Inquiry f","cbCaiakQ6710eoT2","https://ap.wps.com/l/cbCaiakQ6710eoT2","pdf",3260982,"English","# Introduction to Root Cause Analysis\n# What Is Root Cause Analysis?\n# Before We Begin\n# Who Conducts an RCA?\n# What Will Guide Inquiry for RCA?\n# What Types of Data Can Teams Use for RCA?","[{\"question\":\"What problem does IDEA require states and LEAs to address using data?\",\"answer\":\"IDEA requires state education agencies to collect and examine local data each year and determine whether significant disproportionality is occurring in each LEA.\"},{\"question\":\"What is root cause analysis in the context of significant disproportionality?\",\"answer\":\"Root cause analysis is a systemic investigation of contributing or root causes that helps LEAs identify true drivers and develop action plans to improve policies, practices, and procedures.\"},{\"question\":\"What best practices should an LEA follow before starting an RCA?\",\"answer\":\"The brief recommends meaningful team engagement, careful analysis of data including policies/procedures/practices tied to the disproportionality areas, and a clearly defined RCA process supported by evidence.\"}]","Root Cause Analysis Overview - Data Center for Addressing Significant Disproportionality (DCASD) In Brief | PDF",1791600225]