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West Virginia's IDEA Data: Developmental Disability in Time and Space



Director Sam Workman
Institute for Policy Research and Public Affairs
Rockefeller School of Policy and Politics
West Virginia University
1515 University Ave.
Woodburn Hall, 221D PO Box 6286
Morgantown, WV 26506

Executive Summary

This report examines temporal trends and spatial variation in independent educational plans (IEPs) documented in IDEA data in West Virginia. The West Virginia Department of Education (WVDE) delivers the IDEA data as a set of cross-tabulations (i.e., “pivot tables”). From these tables, it was necessary to manually compile a data set addressing the demographics, geography, and trends in the state’s children on IEPs. Below, the reader will first find the key takeaways from this analysis. Afterward, the report presents temporal trends in the IDEA data relating to IEPs and standard demographic information. Finally, we present an atlas for IDEA data in West Virginia that addresses spatial variation in the prevalence of IEPs and support staff at the county level.

Key Findings

  • The data hint at an uptick in IEPs statewide during the global pandemic associated with COVID-19. More research is warranted here.

  • A near two-thirds majority of students on IEPs are male, while roughly one-third are female.

  • Autism, Developmental Delay, Other Health Impairments, and Specific Learning Disabilities have witnessed sharp increases, especially in recent years. Categorization in historical categories for developmental disabilities is on the decline.

  • While all racial demographics have witnessed increases in IEPs, Asians, Latinos, and African Americans have risen more sharply.

  • The special needs staffing in counties is highly variable in the numbers of certified teachers, service personnel, and para-professionals and the ratio of students to teachers and support staff.

  • Staffing levels for students with IEPs are more strained in rural counties than those with urban centers.

Data Organization and Curation

For background information on the necessity of compiling the IDEA data manually from WVDE’s set of cross-tabulations, please see our previous report, “IDEA Data Reporting in West Virginia: Challenges and Opportunities.” The following analysis is compiled from multiple years of IDEA data and standardized to assess trends and geospatial variation. This report utilizes the available data from academic years 2017-2018 through 2022-2023. Data categorization is not consistent across years. This is not an error in WVDE’s recording but reflects changes in categorization schemes and trends in the fields of education and medicine. Where data is inconsistent, this report leaves those categories for future analysis.

The work here highlights the need for continued data delivery and recording refinement. In particular, irregularity in data recording below certain thresholds is problematic in furthering research in the area. Likely, this results from a need to protect the identities of vulnerable populations of students and parents. Standardization along the upper bound for these cases would preserve anonymity and allow systematic compilation of the set of spreadsheets. Also, it's necessary to pay attention to where data is missing or not applicable. The global pandemic caused by COVID-19 presents challenges in understanding temporal trends in the data. These trends should be considered preliminary and warrant further investigation as the data delivery and recording system stabilizes after the pandemic. Finally, recording NAs or missing data would benefit from adopting more modern practices facilitating ease of computation in modern statistical programs.

The data underlying the following analyses were organized in a “long” format to facilitate the following descriptive analyses. The analyses use graphical methods as much as possible. The reader should exercise caution in causal reasoning from the analyses to follow. The report is an exercise in descriptive inference from which causal analyses can reasonably be developed. The report addresses the state of IDEA data. It offers some comparisons across time and space to provide a better understanding of the dynamics of developmental disabilities in young people in West Virginia. Proper causal reasoning will proceed from researchers working more deeply in the fields of public policy, public administration, education, and healthcare, integrating public health data with that presented here. In addition to these limitations, the WVDE lists numerous cautions in several footnotes attached to the Section 618 data largely owed to the unique educational environment around COVID-19.

In the analyses to follow, we primarily use data on the "student count" spreadsheets. The data for performance and exits are particularly sparse, heavily limiting the options for analysis. The WVDE makes this data available in detail and we encourage the reader to visit their website for this information.

An IDEA Data Atlas

Figure 9 maps IEPs by county for reading in the left column and math in the right column for 4th, 8th, and 11th grade. Darker shades for the county indicate greater numbers of students with IEPs. The first broad thing to notice is that the maps for reading and math at each grade level are similar. Students needing accommodation and assistance in reading are likely to need it in math and vice versa.

Figure 9: Three sets of chloropleth county maps for reading and math in fourth, eighth, and eleventh grades.

Figure 9: IDEA Plans by County and Grade

The maps also have a great deal of similarity from grade to grade. As mentioned above, students on an IEP in fourth grade will likely remain on an IEP as they progress through school. The exception here is the leap from 8th to 11th grade, with vastly reduced numbers of students. The same is true across age groupings above as students progress, age out, graduate, or leave public education for other reasons. The data for participation and achievement in reading and math are plagued by sparsity and highly variable benchmarks for protecting identity in spreadsheets. This makes it more difficult to hypothesize the differences across grades.

Figure 9 also shows that the highest concentrations of students with IEPs are found in counties with urban-like population centers (e.g., Monongalia, Kanawha, Raleigh, Harrison). Of course, these population centers contain higher numbers of students. In addition, where support professionals and resources for identifying students with developmental disabilities are higher, we would predict greater densities of IEPs, all else equal.

Figure 10 maps the total number of special education teachers, service personnel, and para-professionals by county as raw counts in the left column and student-staff ratios in the right column. In the figure below, we include certified and non-certified professionals from each group of staff.

The top row of Figure 10 speaks to the sparsity and unevenness in special education teachers and support staff. Counties that are home to population centers have more students on IEPs and more staff to teach and support those students. Leaving the counties with population centers, many rural counties have high student-staff ratios. Clay and Logan counties, for example, have student-staff ratios exceeding four. Remember, these students are on IEPs, and many have specific disability and accommodation requirements. A teacher-to-student ratio common in general education is especially pernicious in a special education setting.

Figure 10: County chloropleth maps for the rates of students to teachers, service professionals, and para-professionals.

Figure 10: Student - Staff Ratios, 2022-2023

A similar story appears for service professionals and para-professionals. Para-professionals and teachers’ aides are especially scarce in more rural counties in West Virginia. Taking the maps altogether means that rural counties have higher student-staff ratios, and in these instances, teachers or service personnel also lack the assistance of teachers’ aides.

This report has described a number of temporal and spatial approaches to understanding children with developmental disabilities on IEPs. The analysis demonstrates the data's importance for integration with other public policy, educational, and public health measures.

Institute for Policy Research and Public Affairs Partnerships

The Rockefeller Institute for Policy Research and Public Affairs (IPRPA) in Eberly College at WVU is a non-partisan source of research, data, and analysis for state and local officials in West Virginia and the broader Appalachian region. IPRPA conducts basic and applied research on various problems important to the region and related to public policy and broader social, political, and economic transitions.

We employ the full range of qualitative and quantitative research methodologies to societal problems to help public, non-profit, and private sector partners plan, strategize, and adapt to changes and challenges in the region, be they physical or biological, economic, governmental, or societal. We have extensive expertise in developing and maintaining large-scale data infrastructures to answer fundamental questions about public policy and its effects on communities. Our partnerships span the public, nonprofit, and private sectors and develop research co-designed with our stakeholders, clients, and communities, improving the use of research and data-driven decision-making in tackling important policy problems. The Institute aims to spur evidence-based policymaking and uptake of research in the state and region.

Please contact the Institute for Policy Research and Public Affairs (IPRPA) for questions and technical assistance in pursuing any recommendations outlined here.

How to Cite this Report

Workman, Samuel. 2024. “West Virginia’s IDEA Data: Developmental Disability in Time and Space.” Institute for Policy Research and Public Affairs (IPRPA), West Virginia University (WVU). IPRPA-2024-006-PO.

Using Our Visualizations - Media

All tables and data visualizations in this report are available for use. Please get in touch with us here:

Ack nowledgements & Disclaimers

This project is made possible by funding from the WV Developmental Disabilities Council (WVDDC) and partly supported by a grant from the U.S. Administration for Community Living (ACL), Department of Health and Human Services, Washington D.C. 20201.

While we acknowledge the support provided by WVDDC and Think Kids, errors in content, style, or judgment in the report remain with the Institute for Policy Research and Public Affairs (IPRPA) at West Virginia University.


  1. See the US Department of Education’s definition here: ↩︎

  2. See the WVDE’s IDEA data dashboard for information on caution necessary and the types of tests administered for each year. WVDE’s dashboard can be found here: ↩︎

  3. The US Census “Quick Facts” for the state of West Virginia can be found at: ↩︎