TIES Inclusive Education Roadmap

Step 1C: Review the Organization's LRE Data

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Least Restrictive Environment (LRE) data provide important information on the extent to which students with disabilities are educated in the general education classrooms with their peers. When teams review their state, district, or school LRE data over multiple years, they can see trends that show growth, no change, or a decline in students with disabilities being educated in general education.

Reviewing a large amount of data can be overwhelming. Organizations are flooded with data. However, it is very common not to understand how to use the data to affect student learning. The activities in Step 1D are designed to help support the EILT analyze their LRE data in manageable ways, making sense of it, and then using it as they create an action plan.

Estimated Time Commitment

The time to complete the LRE data analysis is usually 30-45 minutes. Depending on the organization and the data system, the challenge may lie more with accessing the LRE data than it is doing the group analysis once you have the data. As you gain an understanding about how to access data in your organization or you already know the process, you will be able to build in the lead time for accessing the data into the development plan.

Overview

Least Restrictive Environment (LRE) is an important indicator that describes the extent that all students with disabilities are educated in the general education classrooms with their peers. Federal law requires that:

(i) To the maximum extent appropriate, children with disabilities, including children in public or private institutions or other care facilities, are educated with children who are nondisabled; and

(ii) Special classes, separate schooling, or other removal of children with disabilities from the regular educational environment occurs only if the nature or severity of the disability is such that education in regular classes with the use of supplementary aids and services cannot be achieved satisfactorily (IDEA, Sec. 300.114 )

All districts report their LRE data to their State Department of Education annually as part of their Special Education Child Count data. Each state annually reports its data to the U.S. Department of Education.

Understanding the definition for each category is important for interpreting the data. There are several LRE categories, including different categories for students enrolled in Grades K-12 and in Early Childhood. The LRE categories typically assigned to students with disabilities in Grades K-12 are

  • LRE 1 = Students are taught in general education 80% or more of the school day.
  • LRE 2 = Students are taught in general education 40%-79% of the school day.
  • LRE 3 = Students are taught in the separate special education classrooms 39% or more of the school day.
  • LRE 4 = Students are taught in a separate special education public school for 50%-100% of the school day

It may also be important to review data on out-of-district placements (i.e., homebound, out-of-district and out-of-state) if these are common placement trends.

Data helps people understand what is happening in an organization in a very tangible way. While aggregated LRE data provides a “big picture” look at all students with disabilities in the system, it can hide patterns of uneven access to general education for subgroups of students. Reviewing LRE data disaggregated by disability category, race, English Learner designation, home language, and socio-economic status can identify inequities in access to general education.

The sub-groups of students that are very useful for identifying inequalities in access to general education for students with disabilities are:

  • Individual disability categories (such as Intellectual Disabilities, Autism, Multiple Disabilities)
  • Students with significant cognitive disabilities*
  • Race
  • Gender
  • Grade Level
  • English Learners
  • Free or Reduced Meal status
  • Individual schools (for districts)
  • Geographic areas

* Gathering data for students with significant cognitive disabilities can be challenging because state and federal data are not collected specifically for this group of students. A few strategies for approximating the LRE for this group are to analyze data for (1) students who take the alternate achievement assessment; (2) students who have the disability labels of autism, intellectual disability, multiple disabilities, and deaf-blindness; and (3) depending on the details of how state and district special education finances are determined, disaggregating the LRE data for students who generate additional funding because of high need costs.

The Special Education Department is responsible for ensuring that LRE data is collected for every child who has an Individual Education Program (IEP) (LRE is identified on each IEP).

If you are at the school level, it is important to find out who in your district is responsible for special education data so you can request the LRE data. Many districts have data dashboards that are used to integrate data from multiple sources. Sometimes, special education data are integrated into these dashboards; sometimes they are not. If LRE is not available on a dashboard, pursuing the question to understand why and problem solve how to include this data is an important discussion. In the interim, access the LRE data by requesting the district to share a spreadsheet (aggregated and disaggregated by the various subgroups). This will keep the planning process moving forward.

Some smaller districts are unable to disaggregate subgroup data. Public data from the State Department of Education (DOE) can be useful for gathering some pieces of information. You can also reach out to the DOE to request the data you need. It is important to remember that the DOE only has the data that the district submitted, but the DOE may be able to provide it back to you in a different format that is helpful to the team

What activities can the EILT use to analyze the LRE data?

Prepping for the activity

  • Identify what LRE data you want to review so that it can be requested or downloaded.
    • Request aggregated LRE data looks across all disability categories and grade levels.
    • Request disaggregated LRE data. (Aggregated LRE data often masks sub-groups of students who do not have equal access to general education as other groups of students.)
    • At a minimum, obtain the most recent year’s LRE data. It is preferable to have three years of LRE data in order to see placement trends. If available, you can compare your system’s LRE data to national, state or district data to frame the discussion within a larger perspective
    • If you are not able to download the LRE data from a data dashboard, identify who you need to contact to request the LRE data that the EILT wants to analyze. In smaller systems, you may be able to obtain all of the data that you need because the system does not have the data infrastructure. Sometimes these data can be obtained from your state department of education because they are able to disaggregate it. Request the data in sufficient time to meet your meeting schedule.
    • If you are able to obtain some comparison data, such as district or state LRE data, those pieces can also be useful for framing where the system is currently at in terms of all students accessing the general education curriculum in the least restrictive environment.

Reviewing the LRE data

  • Ensure that the team reviews all of the LRE data in advance.
    • It helps if the data is in electronic formats to be sorted and filtered. Printed copies are useful for teams to mark up during the discussion.
  • As a team, review the definition of Least Restrictive Environment, its connection to special education law, what the different LRE levels mean, and what can be learned from LRE data.
  • Review the aggregated LRE data for all students with disabilities.
    • Where is the organization at in terms of educating students with disabilities in general education with their peers without disabilities?
    • What areas of strengths are evident and in which levels of the system?
    • What areas for improvement are evidence and in which levels of the system?
    • What are the LRE trends over the last 2-3 years?
    • How does the data compare to the district, state, or national data?
    • How does the data compare to schools, districts, or states that you see as leaders in inclusive education?
  • Next look at disaggregated LRE data by key sub-groups of students, including students with significant cognitive disabilities.
    • What observations does the team have about LRE data for the subgroups of students with disabilities?
    • Do some groups of students have greater access to general education than other students?
    • How does the LRE data for the subgroups intersect with other important subgroup data (i.e. disability and race)?
    • To what extent are students with significant cognitive disabilities being placed in separate special education classrooms or schools?
    • What strengths are evident and for which groups of students?
    • What areas for improvement and for which groups of students?
  • Use the final part of the meeting to draw conclusions that will be useful for moving forward. Possible questions include:
    • What are our strengths? What areas or subgroups of students are moving in a positive direction that gets us closer to our mission/vision for all students?
    • What are our needs? What areas or subgroups of students are stagnant or not included in our mission/vision?
    • What 3 to 5 insights are apparent after reviewing the LRE data?

Real World Example

The EILT in an urban middle school was able to access two years of K-12 placement data disaggregated by disability and race/ethnicity. To differentiate between students with autism who were also identified as high-functioning and those with intellectual disabilities, the EILT looked at additional data that cross-referenced the placement data for students with autism who also qualified for the alternate assessment.

After discussing the LRE data, the team felt that the district was having mixed results. There was a slight improvement for students with disabilities being educated in general education greater than 80% of the school day when looking at the aggregated data. However, this was not true for students with intellectual disabilities, physical disabilities, blind/visually impaired, and autism. In fact, while overall the district was moving to educate more students with disabilities in the LRE 1, it was also placing more students with extensive support needs in separate schools. Almost all students with multiple disabilities were placed in separate schools. There were also inequities evident when looking at race/ethnicity and LRE. There was a gap between students with disabilities who were African American and Asian American being placed in LRE 1 at lower rates than students who were Hispanic, American Indian, and Caucasian. Additional data also showed that almost all students who qualified for the state alternate assessment were placed in self-contained classrooms or separate schools.

What's Next?

Move on to identifying initial strategies with key stakeholders for developing a commitment to an inclusive system of education.

  • After reviewing your disaggregated LRE data, complete Step 1C in the IER Inclusive Education Action Plan.
  • Consider these data when writing Goal 1 of the action plan where the EILT will address the change in placement to the general education classrooms for all students with disabilities, including students with extensive support needs.
  • Save the data that was analyzed in Step 1C so it can be used for comparison in the future.
  • Move to Step 1D: Building a Commitment to Inclusive Education.