Attachment B - Response to 60 Day Public Comments

This attachment contains the U.S. Department of Education (ED) Office for Civil Rights’ (OCR) responses to the 60-day public comment period on the Civil Rights Data Collection (CRDC) for school year 2021−22. OCR is responsible for administering the CRDC, a survey of local educational agencies (LEA).

On November 19, 2021, OCR published in the Federal Register (Vol 86, No. 221), a Notice of Proposed Information Collection Request (ICR) that proposed some changes to the 2021–22 CRDC, including the retirement of five data elements related to the outcomes of allegations of staff-on-student sexual offenses. Upon further reflection, OCR withdrew the ICR and replaced it with an ICR that was published in the Federal Register (Vol 86, No. 236) on December 13, 2021 that proposed to maintain the collection of these elements.

A total of 922 commenters submitted 3005 individual comments to OCR in response to the two ICRs. The comments for the 2021–22 CRDC included feedback on the four directed questions, specific areas of data collection that were shown in the attachments, and the information clearance process. A variety of stakeholders provided comments, including: state educational agencies (SEA), LEAs, administrators, educators, non-profit organizations, coalitions, professional organizations, advocates, parents, and other members of the public. The majority of the individual comments were from individuals and advocacy groups, together making up 88 percent of the comments.

Overall, only 1 commenter opposed the collection while 151 commenters expressed appreciation for OCR’s efforts to gather data on the variety of elements related to equal educational opportunity. Nineteen commenters noted general support for the CRDC’s continued collection of student civil rights data, while 132 commenters expressed specific support for the changes proposed for the 2021–22 CRDC. Of the 132 commenters, 127 also noted appreciation for OCR’s proposal to reinstate data elements that had been previously removed. Commenters pointed out the importance of collecting student civil rights data to inform OCR’s enforcement of federal civil rights laws that prohibit recipients of federal financial assistance from discriminating based on race, color, national origin, sex and disability. For example, one commenter noted “[a]ny change to limit the scope, frequency, or public accessibility of the CRDC would hamper the ability of the Department to fulfill its legal obligations and undermine the public’s shared interest in creating the best school environments so that all people can thrive and reach their full potential.”

Other commenters noted the importance of CRDC data for the greater civil rights legal and professional community in identifying student civil rights trends and issues. For example, 12 commenters stated that CRDC data “continues to be a critical source of information on educational equity, racial discrimination in school climate and discipline, and the use of fundamentally flawed practices such as corporal punishment, seclusion and restraint, and police in schools,” and noted that CRDC data “is essential for identifying schools and districts that are not in compliance with civil rights laws that prohibit discrimination in our nation’s schools, and to show where interventions must occur to ensure equal opportunity for all students to reach their full potential.” Additionally, one commenter noted the importance of the CRDC as the sole source of “viable, reliable, and consistent” disaggregated data on student civil rights. Another commenter noted that CRDC data helps illuminate “students’ experiences in schools and whether all students have equal access to education.” Commenters further pointed out the importance of CRDC data in identifying civil rights issues for students of color, students with disabilities, and other underrepresented students.

OCR appreciates each commenter’s time and effort in providing thoughtful commentary in response to this proposed data collection. OCR reviewed, summarized, and documented each comment prior to offering the responses below. OCR’s summary and responses reflect careful consideration of each commenter’s contribution to this process.

Addition of 2023–24 CRDC

OCR is proposing to make numerous changes for the 2021–22 CRDC that will further the core civil rights mission of the CRDC. OCR recognizes the increased reporting burden on LEAs and SEAs associated with these changes. Accordingly, OCR has decided to seek approval of the proposed changes that will apply to both the 2021–22 CRDC and the 2023–24 CRDC. OCR has made this decision for numerous reasons that benefit reporting LEAs and SEAs. These reasons include the following:

LEAs and SEAs will know what data will be collected for the next two CRDC cycles.
Consistency between the 2021–22 and 2023–24 CRDCs will allow LEAs and SEAs to become more familiar with the data collection and will foster the collection of more accurate and reliable data.
LEAs and SEAs will have the opportunity to prepare their data submission systems for two CRDCs, instead of just one CRDC.
After consecutive data collection cycles for the 2020–21 and 2021–22 CRDCs, LEAs and SEAs will now have ample time to prepare for the 2023–24 CRDC.
LEAs and SEAs will be able to apply experience gained from collecting and reporting data for the 2021–22 CRDC, specifically as it relates to new or unfamiliar data elements, to developing and implementing best practices for collecting and reporting these data for the 2023–24 CRDC.
Training and other resources developed and provided by OCR to assist LEAs and SEAs in collecting and reporting data specifically for the 2021–22 CRDC will generally also apply to the 2023–24 CRDC.

Response to COVID-19 Pandemic

COVID-19 Pandemic – Impact

Public Comments

Two commenters wrote about the impacts of the Coronavirus (COVID-19) pandemic on CRDC data. One commentor noted that the COVID-19 pandemic shut down schools, which will impact the data reported. Another commenter noted that, because of COVID-19, CRDC data are even more critical.

OCR’s Response

Discussion: OCR appreciates commenters recognizing the significant impacts of the COVID-19 pandemic and the need for data to better understand those impacts. For these reasons, OCR continues to propose adding new COVID-19 related data elements about the amount of virtual instruction provided by teachers, and percentage of students who received virtual instruction to the survey.

Changes: None.

Virtual Instruction

Public Comments

One hundred thirty-six commenters explicitly supported the proposed data elements about the amount of virtual instruction provided by teachers, and the percentage of students who received virtual instruction. One commenter explained, “[t]his COVID-19-related data will help us understand the effects of the pandemic on access and help determine how resources should be directed”, while another commenter expressed concern about the quality of virtual instruction. One commenter noted that emerging research during the pandemic revealed a relationship between students’ achievement and the instruction method provided, with students receiving full-time in-person instruction showing less significant declines in achievement. According to the commenter, researchers also found that LEAs serving lower-achieving students and more Black students were less likely to provide in-person instruction, and that a decline in achievement associated with virtual instruction was greater in areas serving mostly non-white students. The commenter wrote: “Collecting data on districts’ reliance on virtual instruction will help confirm these gaps in access to in-person learning and strengthen the case for additional support and resources, where necessary, for students of color to make up for lost instructional time.”

For the percentage of students who received virtual instruction data element, 122 commenters suggested that OCR collect data, disaggregated by student characteristics [i.e., race/ethnicity, sex, nonbinary, disability-Individuals with Disabilities Education Act (IDEA), disability-Section 504 of the Rehabilitation Act only (Section 504 only), and English learner status]. One commenter also suggested that the data be collected by reduced price lunch status. One hundred twenty commenters further proposed the collection of disaggregated data for a new percentage of time students spent receiving virtual instruction data element. Two commenters recommended that OCR collect the number of students who received virtual instruction, disaggregated by student characteristics.

Three commenters suggested that OCR collect information about instructional time and methods of instruction, with one commenter also suggesting that the information be disaggregated by student characteristics. Two commenters further suggested that OCR collect data about LEA/school support for remote learning. One of these commenters stressed the importance of collecting these data “as far too many students, especially those who are from low-income families, families of color, and immigrant families, had little or no access to technology [during the pandemic] resulting in learning loss.” One commenter expressed support for OCR collecting data on virtual and in-person instruction.

Some commenters proposed that OCR collect a variety of new virtual instruction-related data using the CRDC. Proposed new data elements included: number of students who were instructed on-line or in-person; whether students “were under a staggered or hybrid school plan;” the length of time (measured in weeks or school days) students were instructed on-line or in-person;” rate of attendance for students who were instructed on-line or in-person; whether students received virtual instruction by synchronous or asynchronous means; number of English learners who received specialized supports via virtual instruction; number of students who were suspended or expelled from virtual instruction; number of students who were excluded from in-person learning and relegated to virtual learning due to behavior; and whether schools were designed to offer full-time virtual instruction.

One commenter suggested that OCR provide more clarity about virtual instruction data (e.g., whether students in quarantine are counted as receiving virtual instruction and whether students who participated in a single day of virtual instruction count toward the percentage of students who received virtual instruction). Another commenter suggested that OCR clarify what counts as “instructional time” and not count educator-provided instructions on assignments as instructional time. A different commenter recommended that OCR collect data on the amount of virtual instruction provided by teachers, and the percentage of students who received virtual instruction only from schools that indicate they offered a hybrid of in-person and virtual instruction, and not from schools that offered virtual instruction only. This commenter was concerned that the outcomes of the data could vary between the two modes of instruction.

Two commenters encouraged OCR to make the two new proposed data elements mandatory for the 2021–22 CRDC, while one commenter suggested that OCR engage in additional consultation with educators and advocates regarding civil rights lessons learned during the COVID-19 emergency to further refine or alter elements related to virtual instruction for future CRDCs.

One commenter stated that the elements would have “little perceived benefit” and “would cause undue burden” for the commenter’s SEA “due to the fluid nature of these practices within districts” and because “current data collection practices do not allow [the SEA] to easily report these data elements.”

OCR’s Response

Discussion: OCR appreciates the overwhelming support from commenters for its proposed two new COVID-related virtual instruction data elements for the 2021–22 CRDC. OCR also appreciates the recommendations to: disaggregate the new data elements by student characteristics; introduce additional data elements; differentiate among types of instruction; and differentiate among reasons students received virtual instruction. However, at this time, OCR believes that the proposed data elements are sufficient to inform its civil rights enforcement obligations. OCR may consider the recommendations for expanding COVID-related virtual instruction data elements for future civil rights data collections.

In response to a few commenters’ suggestions, OCR will consider whether to include instructions in the 2021–22 CRDC that address: whether students in quarantine and whether students who received a single day of virtual instruction should be included in the percentage of students who received virtual instruction; and what is considered instructional time. OCR also originally proposed and continues to propose a new Instruction Type Directional Indicator (see Attachment A-4) to determine whether a school offered a hybrid of in-person and virtual instruction, or virtual instruction only. Therefore, OCR will be able to track data variations between the two modes of instruction. OCR is committed to continuing its engagement with educators and advocates regarding civil rights lessons learned during the COVID-19 pandemic, and to using what is learned in that engagement to further refine elements related to virtual instruction for future CRDCs.

OCR carefully considers, on an ongoing basis, each data collection element and endeavors to balance its civil rights law enforcement obligations with the data collection and reporting burdens imposed on LEAs. Ultimately, OCR found that the benefits of the additional virtual instruction data outweigh the burden of their collection. OCR proposed the virtual instruction data elements because additional data are needed to inform both civil rights enforcement and the provision of technical assistance. The COVID-19-related data are essential to understanding how the ongoing pandemic has affected students’ access to education and the efforts by educators nationwide to meet the needs of students in public schools. To minimize the potential burden on LEAs, OCR proposed limiting the 2021–2022 CRDC to only two virtual instruction data elements. These data elements continue to be proposed as required for the 2021–22 CRDC.

Changes: None.

Burden and Data Collection Process and Timeline

Reporting Burden

Public Comments

Nineteen commenters wrote regarding the burden of reporting data for the CRDC. Commenters raised concerns about the increased reporting burden expected for the 2021–22 CRDC and offered solutions for lessening this burden. Nine commenters said that the expanded data collection places too much burden on reporters, noting that the CRDC is already a large task for districts and that there is an increased workload with adding in reintroduced data elements that have previously been removed. Several commenters noted that the increased burden of the new data items is made worse by staffing shortages and the strain that the COVID-19 pandemic has put on districts. One commenter noted the importance of balancing the value of the data collected and the burden imposed by the requirement to collect and submit that information.

Another commenter recommended that OCR partner with software vendors to integrate the CRDC with widely used School Information Management Systems to minimize the burden of reporting data schools already have. One commenter simply asked OCR to reduce the number of data groups.

Seven commenters expressed concerns about the timing of the collection. These commenters noted that because the school year is already half over, it is too difficult for schools to go back and collect the data, especially for new data elements. Five commenters noted that the proposed CRDC package could pose additional burden on schools that have not updated their School Information Systems for the additional items. One commenter noted that the proposed collection would rush revised data from LEAs when their capabilities are already stressed. Another commenter argued that the back-to-back collection proposed by OCR is only “nice-to-know,” rather than “need-to-know,” for OCR to succeed in protecting students’ civil rights.

OCR’s Response

Discussion: OCR recognizes the burden of collecting and reporting CRDC data and that LEAs are facing a challenging workforce environment. OCR has given significant consideration to all of the proposed data elements and the burden they may impose on LEAs. OCR has proposed revising or retiring data elements to balance the benefits of the data to OCR’s civil rights law enforcement obligations with the reporting burden on LEAs. OCR is also taking other steps to reduce the reporting burden on LEAs, while also maintaining a rigorous standard to ensure the quality of information submitted. For example, for the 2021−22 CRDC, OCR consulted with other program offices within OCR to identify and eliminate any duplication of data items and, where possible, ensure the CRDC uses definitions consistent with those used by other program offices. This inter-office coordination is a part of the operational processes for each collection, including the 2021−22 collection. In addition, to aid LEAs in reporting data for the CRDC, OCR has developed a set of pre-collection tools to allow all LEAs to collect and store their CRDC data in a format that can be easily uploaded into the CRDC data submission system. With these tools, LEAs can store their CRDC data in ready-to-use flat files that can be uploaded once the survey data submission system is available to LEAs. These pre-collection tools are widely used. Furthermore, the data submission system includes “skip-logic” questions so that LEAs need only respond to applicable questions.

OCR provides training opportunities to help LEAs and SEAs understand the data elements collected in the CRDC and the survey submission process. Webinars, frequently asked questions and answers, short tip sheets, videos, and other resources are available on the CRDC Resource Center website (https://crdc.communities.ed.gov). The CRDC Partner Support Center (PSC) is also available to LEAs and SEAs to call or email questions regarding the content of the data to be collected. Additionally, the PSC provides frequent communications and reminders to all participating LEAs on common issues and trending topics spotted within the volume of directed questions coming in. OCR is committed to working with LEAs and SEAs to ensure accurate reporting of CRDC data and to improve the quality of this information for use by LEAs and SEAs to improve educational access and opportunity.

In response to the commenters’ concerns about the timing of the collection, OCR plans to give LEAs sufficient time to prepare for the 2021–22 CRDC by making the reporting of data for most new items optional, which is a practice OCR has used for previous CRDCs. OCR expects LEAs to submit optional data elements but recognizes that the data may not be available. Therefore, OCR plans to delay the mandatory collection of most of the new items until the 2023–24 CRDC. In general, OCR mandates new items that yield time-sensitive and high priority data (e.g., COVID-related items) and new items that are based on data that LEAs already collect (e.g., nonbinary student enrollment data, which would be mandatory for those LEAs that collect it). By making most of the new data elements optional for the 2021–22 school year, LEAs will have more than sufficient notice to change their data collection systems to report complete and accurate data for the subsequent CRDC.

Changes: None.

Data Reporting, Data Use, and Public Availability of Data

Public Comments

Twenty-nine commenters expressed concerns over the reporting of CRDC data. Twenty-five of those commenters urged OCR to address inaccuracies, inconsistencies, and fraudulent data reporting by reporting institutions. Some commenters raised specific concerns related to the reporting process for SEAs, LEAs, and schools. One commenter complained about the slow submission system and how this may hinder an institution’s ability to submit data in a timely manner. Two commenters requested that OCR provide more support to SEAs and suggested that these agencies may have technical difficulties in using the data submission system compared to LEAs and schools. Another commenter suggested that OCR collect data using duplicated counts by incidents instead of by number of students to conform with how most education data are kept and to reveal whether certain groups of students are more likely to experience a certain outcome.

Some commenters noted concerns about how inaccurate, inconsistent, or untimely data might affect how the data are used. Five commenters expressed concern about the overall quality of the data, with one of these commenters expressing concern about CRDC data being inconsistent over time, making year-to-year comparisons difficult.

Nineteen commenters urged OCR to carry out more analysis of the data, including cross-tabulations of the collected data. Three commenters suggested that OCR improve the timeliness of releasing CRDC data by publishing collected data as soon as possible to provide recipients, students, families, and other stakeholders with more contemporary civil rights data. Fourteen commenters suggested that OCR improve the CRDC data website, including the available tools, user ability to analyze data, and the integration of other OCR datasets.

OCR’s Response

Discussion: OCR strives to ensure CRDC data are an accurate and comprehensive depiction of student access to educational opportunities in the nation’s public schools. The data submission system uses a series of embedded data quality checks to ensure: (1) potential data errors are flagged with warning messages, which may or may not require an LEA to address, depending on the severity level of the error, prior to the LEA proceeding to submit its data; and (2) significant data errors are flagged with error messages, which require an LEA to address by making a change to the data, before the LEA may proceed to submit its data. Additionally, each district is required to certify the accuracy of its data submission. Only a district superintendent, or the superintendent’s designee, may certify the CRDC submission. Following the close of the survey submission window, OCR reviews the data to identify possible reporting anomalies and gives some districts the opportunity to amend their CRDC submission, as necessary. Following the data quality review, OCR releases the data to the public.

Although the LEAs are ultimately responsible for the certification of their data, OCR encourages SEAs to support LEAs in reporting CRDC data. Additionally, OCR provides frequent training opportunities for all LEAs and SEAs to understand the data elements collected in the CRDC and the survey data submission process. Webinars, frequently asked questions, short tip sheets, videos, and other resources are available on the CRDC Resource Center website (https://crdc.communities.ed.gov). A Partner Support Center (PSC) is also available to LEAs and SEAs to call or email questions regarding the content of the data to be collected. OCR is committed to working with LEAs and SEAs to ensure accurate reporting of CRDC data and to improve the quality of this information.

OCR appreciates the commenter’s recommendation that OCR switch to duplicated counts by incidents instead of by the number of students. OCR has considered all the recommendations it has received for the collection of specific data elements by incident and has decided to propose only the new collection of the numbers of instances of referrals to law enforcement and school-related arrests. For additional information about these three new proposed data elements, please see the Referrals and Arrests section of this document.

OCR has a longstanding commitment to transparency and recognizes the importance of making the CRDC data available to the public in a timely manner. OCR is also committed to ensuring that the CRDC data are made available to the public consistent with OCR’s privacy policies. After the data files are finalized from the CRDC, OCR engages in a rigorous process to ensure that the data publicly reported protects against the disclosure of individual student information. This process takes several months to ensure that both the data files and the data provided through the website adhere to the highest standards for privacy protection. OCR continually looks for ways to improve the efficiency of this process to ensure timelier access to the data without compromising the protection of individual student data.

OCR appreciates the commenters’ suggestions on further analysis of CRDC data and making this data more accessible and user-friendly. OCR’s current CRDC data website provides the public with visually intuitive displays of the CRDC data (http://ocrdata.ed.gov). Displays include a “summary of selected facts” and “detailed data tables.” The “summary of selected facts” for a district or school displays data about key issues through tables and charts. Users have the option to access additional data for the district or school for the current CRDC or prior CRDCs. The “detailed data tables” have a flexible interface, which allows users to select data from more than one district or school, for the current CRDC and/or prior CRDCs. The website also includes data analysis tools that generate school, district, and state data comparison reports, and English learner, discipline, and educational equity reports. OCR is committed to improving its CRDC data analyses and website.

Changes: None.

SEAs Reporting for LEAs

Public Comments

Fourteen commenters provided feedback on SEAs reporting data for LEAs. Commenters were concerned with the increased burden for the 2021–22 CRDC and expressed frustration at duplicate reporting at the state and federal levels. Twelve commenters noted that most CRDC data are already reported at a state-level for funding and accountability purposes, including most of the proposed new CRDC data elements, creating a duplication in reporting. Five commenters complained that OCR’s CRDC is time-consuming and overwhelming to complete, and that OCR’s proposed additional data elements only further increase the reporting burden on LEAs. One commenter was particularly concerned about the burden imposed on smaller or less-resourced schools. Six commenters inquired why the information already reported to the state cannot be used to complete the CRDC.

Some commenters had suggestions on how OCR might streamline the CRDC reporting process and eliminate duplicate data reporting. Nine commenters requested that OCR develop a way to retrieve the necessary data via a technology system from the SEA that would decrease the burden and duplication in reporting for LEAs. In addition, one commenter added that it would be less costly for LEAs to have each SEA submit CRDC data to OCR on behalf of the LEAs. Finally, four commenters felt that eliminating duplication in data reporting would decrease technical issues in the CRDC submission system and improve data quality.

OCR’s Response

Discussion: OCR appreciates the commenters’ concerns about the reporting burden and their suggestions regarding ways SEAs and OCR can support the data reporting work of LEAs. OCR is continually exploring ways to reduce the reporting burden on LEAs, while also maintaining a rigorous standard to ensure the quality of information submitted.

OCR has been contacted by several SEAs looking for ways to support their LEAs in meeting the CRDC’s reporting requirements. OCR worked with the National Center for Education Statistics (NCES) to develop a collection tool for the 2013–14 CRDC and subsequent collections that allows SEAs to voluntarily provide data to pre-populate LEA-level CRDC surveys with relevant data available in the SEAs’ student information systems. OCR provides training opportunities to help LEAs and SEAs understand the data elements collected in the CRDC and the survey submission process. Webinars, frequently asked questions and answers, short tip sheets, videos, and other resources are available on the CRDC Resource Center website (https://crdc.communities.ed.gov). The CRDC Partner Support Center (PSC) is also available to LEAs and SEAs to call or email questions regarding the content of the data to be collected.

Additionally, the PSC provides frequent communications and reminders to all participating LEAs and SEAs on common issues and trending topics spotted within the volume of directed questions coming in. OCR is committed to working with LEAs and SEAs to ensure accurate reporting of CRDC data and to improve the quality of this information for use by LEAs and SEAs to improve educational access and opportunity.

For the past four CRDC collections, several states have submitted all or some of the civil rights data for their LEAs, although the LEAs are still required to review the accuracy of the data and certify the data for the purposes of CRDC reporting. For the prior four CRDC cycles, OCR has been improving the process of obtaining data from SEAs and will continue to do so for future collections.

Changes: None.

Annual and Universal Collection

Public Comments

Thirty-seven commenters suggested that OCR permanently change the CRDC from a biennial collection to an annual collection. Thirteen of these commenters noted that not collecting the data annually could lead to data that are “often years out-of-date and [that do] not allow for urgent action or clear demonstration of the current problems faced by students and their families.”

Ten commenters provided feedback on OCR’s plan to administer consecutive CRDCs for the 2020–21 and the 2021–22 school years. Six commenters supported the consecutive collections, whereas four commenters expressed opposition to consecutive collections due to the burden on reporting institutions.

Eighteen commenters supported OCR continuing to conduct a universal CRDC because it maximizes children’s experiences to be reflected in the data.

OCR’s Response

Discussion: OCR has collected civil rights data since 1968. Beginning with the 2011–12 collection, the CRDC has been administered every two years to all public-school districts and schools in the 50 states and Washington, DC. OCR has proposed administering annual collections for the 2020–21 and 2021–22 CRDCs. In response to the COVID-19 pandemic, OCR cancelled the 2019–20 CRDC, and instead collected data for the 2020–21 school year. OCR is proposing to conduct the survey again for the 2021–22 school year, to allow OCR to collect and analyze data related to the effects of the pandemic and identify areas of continuing need for students that will further the core civil rights mission of the collection. OCR believes it is important for OCR to collect data to help gauge the impact the pandemic has had on students access to education. This is the first time that OCR has conducted a universal CRDC annually and OCR will learn many lessons from the process, including the reporting burden on LEAs. OCR will consider in future collections whether to continue annual or biennial collection.

OCR concurs that the public benefits from a universal CRDC data collection. For that reason, OCR proposes the 2021–22 CRDC as a universal collection.

Changes: None.

Time Period

Public Comments

One commenter wrote regarding the time period for reporting CRDC data. This commenter recommended changing the CRDC reporting schedule, stating that the current data collection timeline is built on an assumption that schools will utilize a fall-to-spring school year. The commenter noted this may produce incorrect reported results for year-round schools; contributes to maintaining the problematic Fall-to-Spring school calendar; and may leave a gap in monitoring civil rights during winter and summer breaks.

OCR’s Response

Discussion: OCR appreciates the feedback on the timing of the CRDC. The timing of CRDC reporting obligations is intended to maximize the data collection and minimize the reporting burden on institutions’ limited resources. The CRDC includes both non-year round and year-round schools, with year-round schools instructed to report cumulative data to reflect their entire school year. In addition, OCR does not consider it appropriate to have non-year round schools monitor students when students are not in school—during intersession or summer.

OCR disagrees that the current reporting timeline leaves a gap in monitoring student civil rights, as the CRDC definition of a “regular school year” may include the summer for year-long schools, and OCR is always available to receive complaints of civil rights violations, including alleged violations during school breaks.

Changes: None.

Collection of Data with Additional Disaggregation

Data Disaggregation

Public Comments  

Five commenters provided suggestions for data disaggregation. Two commenters suggested that OCR standardize the disaggregation of data by race/ethnicity and sex, while another commenter suggested standardization by race/ethnicity, sex, and disability. One commenter urged OCR to disaggregate data at a micro subgroup level to collect information on intersecting identities, including by race and gender, race and disability, gender and disability, race and income level, gender and income level, and disability and income level. This commenter noted that by examining intersecting identities, decisionmakers would be better equipped to make targeted, data-driven decisions, and enhance understanding among parents, school staff, and the community about student experiences. Two commenters suggested that OCR collect data disaggregated by socioeconomic status (SES) to help understand the effects of poverty on student achievement.

OCR’s Response

Discussion: OCR appreciates the commenters’ suggestions and understands how further disaggregation of data might provide useful information. Regarding the commenters’ suggestion for data disaggregated by SES, OCR already collects some socioeconomic data. OCR’s National Center for Education Statistics collects and reports data on percent of students eligible for free or reduced priced lunch. This information is published on OCR’s website (https://ocrdata.ed.gov). Additionally, OCR publishes information regarding each school’s Title I status on its OCR website (https://ocrdata.ed.gov), where it can be viewed alongside the educational access and equity data collected by the CRDC.

While the recommendation to further disaggregate the CRDC’s data may be useful, OCR must balance the usefulness of the data with the reporting burden. OCR believes that the proposed disaggregation of data for the 2021–22 and 2023–24 CRDCs is sufficient to inform OCR’s civil rights enforcement obligations. OCR may consider the recommendations for further disaggregation for future civil rights data collections.

Changes: None.

Disaggregation by Additional Racial/Ethnic Categories

Public Comments

Five commenters raised concerns regarding the existing racial and ethnic categories of the CRDC’s data collection. Three of these commenters suggested that OCR disaggregate race/ethnicity data using the categories found in the American Community Survey, with one commenter noting that doing this would help address specific communities’ concerns about specific students’ outcomes. Three commenters also stated that the categorization of data by existing race and ethnicity did not adequately capture the diversity present in the Asian American, Native Hawaiian, and Pacific Islander (AANHPI) communities. They believe this obscures disparities in student outcomes. One commenter stated that there are cultural and linguistic differences, war, and genocide that cause displacement and relocation which affect student outcomes, and that the current category “Asian” is too broad and obscures the diversity and educational inequities in these communities. Three commenters suggested the disaggregation of data by specific AANHPI ethnic subgroups to collect and highlight information on educational disparities among AANHPI communities.

OCR’s Response

Discussion: OCR appreciates the commenters’ suggestions to disaggregate data using the categories found in the American Community Survey. OCR further appreciates the commenters’ suggestions to disaggregate data by specific AANHPI ethnic subgroups. OCR understands that disaggregating data by categories reflecting a greater level of racial and ethnic diversity would provide valuable information about students’ access to educational opportunities and is committed to collecting further disaggregated data as soon as feasible. However, OCR must first work to address student privacy concerns that the further disaggregation of data to racial and ethnic subgroups may present. For the reasons stated below, OCR has decided not to further disaggregate race and ethnicity data for the 2021–22 CRDC, but OCR anticipates doing so for future CRDCs, including the 2023–24 CRDC.

Standards for reporting federal data on race and ethnicity are governed by the Office of Management and Budget’s (OMB) Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity, last revised in October 1997 (62 Fed. Reg. 58,782). The OMB standards set the minimum number of categories for data on race at five, including American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White, with an additional ethnic indication for Hispanic or Latino. These standards give federal agencies the option to collect a greater level of detail at their own discretion, but with the caveat that the number of standard categories be kept to a manageable size, determined by statistical concerns and data needs.

For CRDC reporting purposes, LEAs are required to follow ED’s “Final Guidance on Maintaining, Collecting, and Reporting Racial and Ethnic Data to the U.S. Department of Education” from October 2007 (72 Fed. Reg. 59,266), which requires recipients to report race data by seven major racial/ethnic categories (i.e., American Indian or Alaska Native, Asian, Black or African American, Hispanic/Latino, Native Hawaiian or Other Pacific Islander, two or more races, and White). Under current ED guidance, LEAs may choose to disaggregate these categories further to address their own needs at the state level but must categorize race data according to these seven categories for the purposes of the CRDC.

President Biden’s Executive Order on Advancing Racial Equity and Support for Underserved Communities Through the Federal Government (Exec. Order 13985, 86 Fed. Reg. 7009 (January 25, 2021)), created an Interagency Working Group on Equitable Data, which has released a list of recommendations for achieving data equity. The recommendations include making disaggregated data the norm while protecting privacy by revising the OMB standards for data collection to promote improved understanding of disaggregation by additional racial and ethnic subcategories. Also, in June 2022, the OMB U.S. Chief Statistician announced the creation of an Interagency Technical Working Group, which is tasked with reviewing and revising OMB’s Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity, by considering, among other things, further disaggregation of race and ethnicity data. The recommendations of this working group will inform OCR’s plans to expand race and ethnicity data in the CRDC.

OCR acknowledges that currently several federal surveys have adopted disaggregation of AANHPI data by additional racial and ethnic subcategories. For example, the Centers for Disease Control and Prevention’s National Vital Statistics System disaggregates AANHPI data by the following nine subcategories: Asian Indian, Chinese, Filipino, Guamanian or Chamorro, Japanese, Korean, Vietnamese, Native Hawaiian, and Samoan. The U.S. Census Bureau’s American Community Survey disaggregates AANHPI data even further by collecting racial/ethnic data on 105 racial/ethnic subcategories (see https://nces.ed.gov/fCSM/acs.asp). Both of these surveys also disaggregate Hispanic/Latino by additional ethnic subcategories (e.g., Mexican, Puerto Rican, Cuban), while the American Community Survey further disaggregates American Indian by four ethnic tribal groupings (Cherokee, Chippewa, Navajo, and Sioux). However, for CRDC purposes, disaggregation by racial/ethnic subcategories may present student privacy concerns because this disaggregation might result in individual students being identified if the students belong to racial/ethnic communities with a particularly small population at a specific LEA or school.

For these reasons, OCR has decided not to further disaggregate AANHPI and other racial/ethnic data for the 2021–22 CRDC. Instead, OCR will continue to consider the recommendation from commenters, address student privacy concerns, and will endeavor to further disaggregate race data for future CRDCs.

Changes: None.

Disaggregation by Age

Public Comments

One commenter stated that collection of information on the ages of students assigned to each grade level would facilitate OCR’s enforcement of the Age Discrimination Act of 1975. The commenter noted that age discrimination is “ubiquitous and insidious” and causes students emotional and developmental harm, while also limiting some students’ educational opportunities. Collection of these data, the commenter pointed out, would address these harms; reveal the prevalence of age discrimination; and allow for the identification of disparities in age-related discriminatory practices against students in other classes protected by the civil rights statutes.

OCR’s Response

Discussion: OCR appreciates the commenter’s recommendation that OCR collect age data for students assigned to each grade level to help address age discrimination in schools. OCR also appreciates the commenter’s feedback on the importance of collecting age data. While further disaggregating the CRDC data by age for each grade level would be useful, OCR must balance the usefulness of the data with the reporting burden. For this reason, at this time, OCR has decided not to disaggregate CRDC data as recommended. However, OCR will consider options for including this data for future collections.

Changes: None.

Disaggregation by Grade Level

Public Comments

One commenter recommended that OCR include grade level as a disaggregated category for the ability to explore important research questions (e.g., algebra participation rates at different grade levels and retention rates at each grade level). The commenter also noted that the data would allow for comparisons across schools and districts.

OCR’s Response

Discussion: OCR appreciates the commenter’s recommendation that OCR collect grade level data for research purposes. OCR also appreciates the commenters’ feedback on the importance of collecting grade level data. While further disaggregating the CRDC data by grade level might be useful, OCR must balance the usefulness of the data with the reporting burden. OCR has decided not to disaggregate CRDC data by grade level at this time.

Changes: None.

School and District Characteristics

Public Comments

Four commenters provided feedback on the proposed School and District Characteristics module of the CRDC. One commenter expressed several concerns with alternative schools. The commenter mentioned that OCR only collects data on the specific group of students whom the alternative school serves, such as whether the alternative school is for students with academic difficulties, discipline problems, or students with both academic difficulties and discipline problems. This commenter also highlighted that students of color, students with disabilities, and pregnant students are disproportionately removed from their regular classroom and referred to alternative schools. Consequently, the commenter requested a new data element to collect demographic information on student enrollment at alternative schools.

One commenter noted that most school districts assign children to schools based on address, and changes in school assignment zones are a major contributing factor to increased school segregation within districts. Therefore, the commenter suggested that for the CRDC, districts be required to report and specify any schools with changed attendance zone boundaries that occurred since the prior CRDC, and to report the resulting change in racial enrollment in the affected schools. In addition, the commenter recommended that OCR require districts to report any choice-based student assignment policies in effect. Furthermore, the commenter discussed school desegregation and integration plans, noting that OCR and the Department of Justice maintain information on districts subject to desegregation plans. To “further data transparency,” the commenter suggested that OCR include a hyperlink to each district’s desegregation program in the district’s public-facing report.

One commenter recommended that OCR collect data on open-enrollment statistics. This commenter emphasized that many states have open-enrollment policies that allow nonresident students to enroll, but, due to the nature of open-enrollment, determining whether a school is truly “at-capacity” is difficult. It can be difficult to ascertain whether schools are denying enrollment to a “certain type of student.” Therefore, the commenter suggested that the CRDC include information on the number of students in open enrollment and the number of students denied open enrollment, with that data disaggregated based on race, gender, and disability.

One commenter suggested that OCR collect data on students’ involvement in afterschool and out-of-school activities (including participation in comprehensive afterschool and summer programs). The commenter proposed the following data element: “The unduplicated number of students who participate regularly in an after-school program, either on-site or off-site, that provides a combination of academics and enrichment after the traditional school-day ends.” The commenter highlighted that these activities support students’ educational trajectory throughout school, noting that research shows these programs can support on-time grade promotion, increased academic performance, scientific interest and career pathways, and graduation rates. In addition, the commenter stated that these programs offer important social and emotional supports and the opportunity to develop positive relationships with caring adults. Finally, the commenter remarked that 25 million children face barriers to accessing afterschool programs, including no available programs, no affordable programs, or issues with transportation.

OCR’s Response

Discussion: OCR appreciates the commenters’ recommendations related to student placements in alternative schools, student school assignments, desegregation programs, open enrollment, and student involvement in afterschool programs. OCR also appreciates the commenters concerns about: certain marginalized student populations being removed to alternative schools; school segregation; whether open enrollment decisions are discriminatory; and barriers to accessing afterschool activities.

OCR proposes the continued collection of counts of students who were transferred for disciplinary reasons to an alternative school, disaggregated by sex, race/ethnicity, disability, and English learner status, and the new nonbinary disaggregation category for the data element. OCR also proposes the continued collection of data on whether an LEA is covered by a desegregation order or plan. At this time, OCR believes that the proposed data elements are sufficient to inform its civil rights enforcement obligations.

Changes: None.

Public Schools

Public Comments

One commenter recommended that OCR remove Data Group 958, the total count of public schools, arguing that the information collected by this data group was duplicative of data collected by three other data groups. The three data groups included: Data Group 977, classification of schools based on the curriculum concentration; Data Group 915, charter status; and Data Group 932, grades offered.

OCR’s Response

Discussion: OCR appreciates recommendations of how to make the CRDC a more efficient collection. The CRDC currently collects information on the number of public schools under the governance of each LEA (Data Group 958); the classification of schools based on the curriculum offered (Data Group 977); whether public schools operate under a specific charter school law (Data Group 915); and grade levels offered by the school (Data Group 932). OCR disagrees that the collection of the LEA’s data about the schools under its governance is inherently duplicative to the data collected by the other three data groups. In addition, the total count of public schools data can be useful to verify that the total count of public schools matches the total number of schools that the LEA has reported data to OCR for the CRDC.

Changes: None.

Enrollment in Non-LEA Facilities

Public Comments

Two commenters provided suggestions regarding the collection of data on enrollment in non-LEA facilities. One commenter suggested that OCR disaggregate the unduplicated number of students enrolled in the LEA but served in non-LEA facilities by sex, disability (IDEA/504), English learner status, and race/ethnicity. Another commenter encouraged OCR to collect qualitative data on out-of-district placements and outcomes.

OCR’s Response

Discussion: OCR appreciates the comments received regarding data collection on enrollment in non-LEA facilities. OCR currently collects data on the count of students served in non-LEA facilities. Also, the outcome data for the students enrolled in public non-LEA facilities are incorporated into the CRDC data. At this time, OCR believes that the proposed data elements are sufficient to inform its civil rights enforcement obligations and has decided not to expand data collection on student enrollment in non-LEA facilities as recommended by commenters.

Changes: None.

Juvenile Justice Facilities

Public Comments

Three commenters requested that OCR expand the data collection related to juvenile justice facilities. Two of the commenters suggested that OCR collect the number of students in juvenile justice facilities disaggregated and cross-tabulated by race, sex, disability (IDEA/504), and English learner status. Another commenter recommended that OCR collect information related to juvenile justice facilities during the COVID-19 pandemic, including: whether students were quarantined in solitary confinement; and whether students had access to self-study packets, virtual learning, or support related to IDEA. This same commenter also recommended data collection on solitary confinement in juvenile justice facilities, including: the number of students placed in solitary confinement; the race/ethnicity and gender of students placed in solitary confinement; and how long students were placed in solitary confinement.

OCR’s Response

Discussion: OCR appreciates the commenters’ suggestions that the CRDC expand the data collection on juvenile justice facilities for the 2021–22 CRDC and acknowledges that the data would provide useful information. In response to the commenter’s recommendations that OCR collect information related to the juvenile justice facilities during the COVID-19 pandemic, OCR’s proposed new COVID-19 related data elements about the amount of virtual instruction provided by teachers, and percentage of students who received virtual instruction will apply to juvenile justice facilities. OCR will consider the recommendations to expand the data elements related to juvenile justice facilities for future CRDCs.

Changes: None.

Civil Rights Coordinators

Public Comments

Seven commenters wrote regarding OCR’s collection of information on civil rights coordinators and its proposed changes for the 2021–22 CRDC. Some commenters were opposed to limiting OCR’s collection of information on civil rights coordinators. In particular, four commenters opposed OCR’s proposal to not collect coordinators’ names and phone numbers in favor of collecting only the coordinators’ email addresses. These commenters noted that collecting only email addresses may be inadequate because responses often include generic email addresses that are not unique to the individual coordinator, and thus do not necessarily reveal whether anyone has been designated as a civil rights coordinator as required by law. Four commenters also requested that, rather than limiting the data collection, OCR create a database of all civil rights coordinators and their information and to make that information available to the public. One commenter argued that the burden associated with this data collection is small, as the civil rights coordinators themselves may be the individuals completing the CRDC collection forms. Finally, another commenter recommended adding “religion” to the list of types of discrimination found in the civil rights coordinator description.

OCR’s Response

Discussion: OCR appreciates the responses received to the proposed changes in data collection of contact information for civil rights coordinators. Based on the commenters’ feedback, OCR acknowledges that generic email addresses that are not unique to a civil rights coordinator would likely not provide sufficient information to determine whether an LEA has a designated civil rights coordinator. OCR also recognizes that having more contact information would offer more options to individuals who need to contact their civil rights coordinator and would likely make it easier for individuals to successfully reach and communicate with their coordinator. To address the commenters’ feedback, OCR proposes a new Civil Rights Coordinators Directional Indicator to determine whether the LEA has designated one or more employees to act as a civil rights coordinator for: sex (Title IX); race, color, or national origin (Title VI); and disability (Section 504 and/or Title II). OCR also proposes to continue the collection of the civil rights coordinators’ names and email addresses only and retire the collection of phone numbers, both in an effort to address the commenters’ feedback and to reduce the data entry burden on CRDC respondents. OCR believes the proposed amended collection will continue to enable OCR to protect civil rights without unduly burdening LEAs. OCR also plans to continue to make the civil rights coordinators information available to the public on the following website: https://ocrcas.ed.gov/civ-rts-coordinators.

OCR appreciates the suggestion to add “religion” to the list of types of discrimination found in the civil rights coordinator description. However, OCR believes that the inclusion of “race, color, or national origin” in the description adequately encompasses the types of discrimination that Title VI prohibits, including discrimination against individuals based on actual or perceived shared ancestry or ethnic characteristics or citizenship or residence in a country with a dominant religion or distinct religious identity.

Changes: Please see the proposed changes in the OMB Supporting Statement, Part A document, the revised Civil Rights Coordinators Contact Information Data Group 916 found in Attachment A-2, page 23, and the new Civil Rights Coordinators Directional Indicator 30 found in Attachment A-4, page 30.

Interscholastic Athletics

Public Comments

Thirteen commenters responded to OCR’s proposal to retire certain data groups related to single-sex interscholastic athletics and to collect more accurate data on all students participating in interscholastic athletics, regardless of gender identity. Specifically, OCR proposed to retire the collection of the following data groups: (1) number of high school-level interscholastic athletics sports in which only male or only female students participate (Data Group 937); (2) number of high school-level interscholastic athletics teams in which only male or only female students participate (Data Group 938); and (3) number of participants on high school-level interscholastic athletics sports teams in which only male or only female students participate (Data Group 939). OCR also proposed to introduce a new data group to collect the number of all students (including male, female, and non-binary students) in grades 9-12 who participated on interscholastic athletic sports teams (Data Group 1036).

Of the thirteen commenters, eight expressed concerns pertaining to the proposed retirement of Data Groups 937, 938, and 939. Four commenters stated that it is helpful to have longitudinal data from these data groups to address the history part of the three-part test for Title IX athletics compliance and/or to retain comparisons with past collections. Two commenters noted that these data groups are a key way to assess sex disparities in high school athletics, while two commenters pointed out that the data groups are necessary for Title IX enforcement.

Six commenters advocated for the inclusion of all four data groups in the CRDC. Six of these commenters expressed support for OCR’s proposed Data Group 1036, to collect and disaggregate the data on the number of students who participated on interscholastic athletics sports teams by female, male, and nonbinary students. One commenter noted that the disaggregation allowed OCR to identify the type of guidance and technical assistance schools may need to support nonbinary students’ participation in athletics. Three commenters urged OCR to retain Data Groups 937, 938, and 939 because these data groups provide data points related to athletic opportunities by sex, and the proposed addition of Data Group 1036 is insufficient as a substitute. The commenters supported the addition of Data Group 1036 but asserted that the data elements proposed to be retired are essential to understand whether LEAs are making available sufficient opportunities to meet the student population and athletic interests in an equitable manner. Another commenter noted that although Data Group 937 (unduplicated number of high school-level athletic sports) and Data Group 938 (unduplicated athletics teams) may not be direct measures of Title IX compliance, they still yield relevant and useful information that relates to the assessment of gender equity in sports.

One commenter explained that the new proposed Data Group 1036 cannot be used as a substitute for Data Groups 937, 938, and 939 because knowing the number of students who participate in athletics is, in and of itself, inadequate information for purposes of Title IX enforcement. The commenter stated that, for example, if a school reports an equal number of girl and boy student athletes, then it may be the case that all of the girls play on a few sports teams whereas the boys participate in a dozen different sports. Without data on the number of sports and teams (disaggregated by female, male, and non-binary identity) the CRDC cannot be used to identify schools that are denying students equal opportunity for athletic participation because of their sex/gender identity. In addition, the commenter asserted that even if Data Group 1036 shows that a school fails prong 1 of the three-part test (e.g., it does not provide substantially equal athletics participation opportunities for girls and boys), Data Groups 937, 938, and 939 are still necessary to determine whether the school fails prong 2 and prong 3 as well (e.g., it has not continually expanded girls’ athletics opportunities or it has not fully and effectively accommodated girls’ athletic interests and abilities).

Another commenter objected to the retirement of Data Groups 937, 938, and 939 because, in the absence of a high school equivalent to the Equity in Athletics Disclosure Act, this information in the CRDC is often used by researchers and advocates to assess sports participation in schools. Four commenters recommended that OCR amend Data Groups 937 and 938 to capture the number of “boys’ sports” and “girls’ sports” and “boys’ teams” and “girls’ teams,” respectively, that schools offer. In this case, OCR should define boys’ sports and boys’ teams and girls’ sports and girls’ teams as inclusive of students who participate in sports or teams that primarily serve boys and girls, respectively, and replace prior CRDC references to “male-only” and “female-only” sports and teams. The commenters also asserted that Data Group 939 should be revised to capture student participation counts in “boys’,” “girls’,” and “all other” athletic programs by sex (membership), including nonbinary where available, and race/ethnicity.

One of the commenters suggested that OCR have schools report how many girls, boys, and nonbinary students play on girls’ and boys’ teams. The commenter stated that, for example, a school may report 50 boys, 40 girls, and 10 nonbinary students playing sports, but under the current proposal, OCR would not know that the boys’ teams have 50 boys, 3 girls, and 2 nonbinary students, whereas the girls’ teams have 37 girls and 8 nonbinary students.

Two commenters raised a concern that the current structure of proposed Data Group 1036, which is limited to students in grades 9-12, does not include 7th or 8th graders participating on high school teams. Two other commenters raised concerns about OCR not requiring submission of CRDC data from middle schools and requested that OCR begin to collect these data. One commenter asserted that there is nothing in the law or CRDC guidance that would exempt recipient middle schools that offer interscholastic athletics from being required to submit data to OCR about their interscholastic athletics programs. This commenter noted that the nondiscrimination requirements of 34 C.F.R.§ 106.41(a) apply to “any interscholastic, intercollegiate, club or intramural athletics offered by a recipient.” The commenter asserted that there are “rampant” athletic participation disparities for middle school girls in addition to disparities identified at high schools.

Three commenters suggested that OCR collect data on opportunities to participate in interscholastic athletics that vary across students’ genders. These commenters noted that there are gender disparities in students’ participation in school sports, and that availability, access, and students’ experiences of comfort and safety contribute to these disparities. These commenters further noted that, for transgender students, these disparities increasingly take the form of discriminatory bans or invasive barriers to participating in the athletic programs that align with their gender identities. Given the benefits of participating in sports, these commenters suggested that the CRDC include measures that enable the analysis of how students’ genders impact their opportunities to participate in school athletic programs.

One commenter recommended that OCR collect data on the number of transgender and nonbinary youth who participate in school sports. This commenter also urged OCR to collect data on the number of mixed-gender interscholastic high school sports, including sports or events that do not separate athletes into gender divisions (e.g., mixed doubles in tennis). The commenter noted that evaluating only single-gender sports leaves out an important subset of school sports.

Three commenters recommended that OCR add a data group to the CRDC that would provide insight into the breakdown of student-athletes’ race/ethnicity. These commenters asserted that adding this data group would allow researchers to understand the intersection of race and gender as it relates to sports participation. One of these commenters also suggested that the interscholastic athletics data categories include counts of additional student groups, including: disability (IDEA) by sex (membership); disability (Section 504 only) by sex (membership); English learner status by sex (membership); and reduced lunch status.

Two commenters suggested OCR begin collecting data on athletic expenditures for boys’ and girls’ teams. One commenter noted that the CRDC does not provide any information on how girls’ teams are treated in terms of the benefits and services they receive. The commenter suggested that the OCR collect data on expenditures, from school and non-school sources, for travel; equipment; uniforms; practice and competitive facilities; locker rooms; training and medical facilities; and publicity, including press materials and personnel. Another commenter stated that adding a data group to collect information on athletic expenditures on boys’ and girls’ teams would help provide transparency and allow students, parents, coaches, advocates, and others understand how schools are investing in their sports teams and could provide insight into Title IX compliance at a school.

One commenter recommended that OCR collect data on the incidence of harassment or bullying that occurs while the targeted students are participating in sports or are in sports-related spaces such as locker rooms.

OCR’s Response

Discussion: OCR appreciates the comments pertaining to the proposed retirement of Data Groups 937, 938, and 939, and the proposed addition of Data Group 1036. Upon further consideration, OCR now proposes retaining and expanding Data Groups 937 and 938 to include data on the number of male-only, female-only, and all students sports and teams instead of just data on male-only and female-only sports and teams. This revision is needed because the current “male-only” and “female-only” paradigm in Data Groups 937 and 938 does not capture interscholastic athletic sports or teams that include all students (males, females, and nonbinary students). As one commenter noted, evaluating only single-sex sports leaves out an important subset of school sports. OCR agrees. OCR also acknowledges that the Equity in Athletics Disclosure Act survey includes data collection for men’s, women’s, and coed teams (https://surveys.ope.ed.gov/athletics2k20/wwwroot/documents/2019_EADA_Users_Guide.pdf).

Also, OCR’s proposed retention of the male-only and female-only sports and teams categories allows for the continuation of comparisons with past collections. Ultimately, OCR believes that the benefits of the proposed retention and expansion of Data Groups 937 and 938 outweigh the burden of the collection of the data.

OCR has considered all the comments about retiring Data Group 939 and adding Data Group 1036. OCR recognizes the value of collecting comparable data in each collection to allow the public to analyze changes in data over time and appreciates concerns that commenters raised on this issue. OCR also recognizes the value of collecting data that are accurate, comprehensive, and relevant to civil rights. OCR has decided to continue to propose to retire Data Group 939 because Data Group 1036 is comparable to Data Group 939, while collecting more accurate and comprehensive data that are better indicators of civil rights compliance. Data Group 939’s focus on the number of participants on male-only or female-only teams does not capture opportunities on all students teams. Additionally, even if OCR were to expand Data Group 939 to collect data on the total number of participants on all students teams, it would not accurately reflect all the athletic opportunities available to male, female, and nonbinary students on those teams. In evaluating whether an LEA offers equitable access to its athletic program, OCR considers all athletic participation opportunities, regardless of whether they are on male-only, female-only, or all students teams. Therefore, OCR continues to propose adding Data Group 1036 to collect more accurate and comprehensive data on the number of participants on interscholastic athletics teams disaggregated by male, female, and nonbinary sex categories.

Data Group 1036 is defined as “the number of students who participated on interscholastic athletic sports teams, disaggregated by sex (female, male, or nonbinary).” To clarify that a single student should be counted multiple times for different sports, OCR proposes adding a note in the Comment section of Data Group 1036.

OCR also appreciates the suggestions for potential additions to the CRDC and will consider these suggestions when developing future CRDC surveys. At this time, OCR declines to add additional data groups given the reporting burden on LEAs to respond to additional questions.

Changes: OCR proposes to retain Data Groups 937 and 938 but expand them to include counts of coed sports and teams. Please see OMB Supporting Statement, Part A, Attachment A-2, pages 53-54 (Data Groups 937 and 938), and Attachment A-3, page 21 (Data Category: Interscholastic Athletics). OCR also has added a note in the Comments section of Data Group 1036 found in Attachment A-2, page 53.

Single-Sex Classes

Public Comments

Two commenters provided feedback on data elements relating to single-sex classes. One commenter expressed support in response to OCR’s proposal to combine, for the count of single-sex academic classes in courses/subject areas, data elements, “Algebra I, Geometry, and/or Algebra II” and “Other mathematics” into one course/subject area, “Mathematics.” The commenter noted that the change would alleviate confusion. A second commenter urged OCR to collect additional data related to single-sex classes. Specifically, the commenter suggested that OCR: (1) collect data on race/ethnicity and disability for students in single-sex classes to ensure that Title IX, Title VI, and Section 504 are enforced in single-sex classes; (2) collect data, including data disaggregated by race/ethnicity and disability, on coeducational sections of classes that are also offered with single-sex sections to provide context and determine whether students of color and students with disabilities are disproportionately channeled into either single-sex or coeducational classrooms; and (3) further disaggregate single-sex class data by sex to include transgender and nonbinary students.

OCR’s Response

Discussion: OCR appreciates the recommendation to expand data collection for single-sex classes. OCR understands that collecting more detailed data may be informative. However, OCR has decided that collecting single-sex class data disaggregated by male and female is sufficient to support OCR’s mission of civil rights enforcement.

Changes: None.

School Expenditures

Public Comments

Sixteen commenters responded to OCR’s proposal to maintain the retirement of school expenditures data elements and continue its collaboration with ED’s National Center for Education Statistics (NCES) to explore options for how to require SEAs to complete NCES’ School-Level Finance Survey (SLFS). Ten commenters supported the move of school finance data from CRDC to SLFS once the SLFS is mandatory for all states and two of these commenters requested that the data be made publicly available. The 10 commenters requested that OCR continue to collect the data using the CRDC until the SLFS becomes a universe collection. The other six commenters suggested that the CRDC maintain the collection of this data.

Eight of the commenters noted that it is important to collect school finance data to identify funding inequities that result in disparities in educational opportunities and outcomes. One commenter pointed out that data about funding for personnel are critical because of ongoing staffing shortages and disproportionate impact on special education.

One commenter encouraged OCR to “carry over certain elements of the CRDC expenditures data collection requirements to the mandatory SLFS data collection,” including staff salaries. In contrast, a different commenter noted advantages of school expenditures data being part of the SLFS instead of the CRDC—namely that SEAs will be reporting for their schools and not their individual LEAs, and that the SLFS can have a more narrow and detailed focus on school finance. Another commenter suggested that SLFS data be published on the CRDC website.

OCR’s Response

Discussion: OCR appreciates the commenters’ recommendations to reinstate the school expenditures data elements for the CRDC—either temporarily, until the SLFS becomes mandatory for all SEAs, or permanently. The SLFS expenditures data items are analogous to the former school-level finance data that were collected for the 2009–10, 2011–21, 2013–14, 2015–16, and 2017–18 CRDCs. Currently, about 33 states either report or are committed to reporting data to the SLFS, which is a voluntary collection. OCR continues to collaborate with NCES to make data items for the 2021–22 SLFS collection mandatory so that OCR may utilize the SLFS expenditures data for civil rights enforcement purposes. This change will reduce the reporting burden on LEAs, and remove reporting redundancies between the CRDC and the SLFS.

OCR continues to propose that the school expenditures data elements remain retired from the CRDC, as OCR continues to collaborate with NCES on the mandatory collection of school finance data through the SLFS. OCR plans to provide technical assistance for SEAs in fulfilling the SLFS data collection and reporting requirements and provide a link to SLFS data on the CRDC website.

Changes: None.

Class Size

Public Comments

Forty-four commenters urged OCR to collect and report class size data. Thirty-two of the commenters noted that there is no other source for this information. Reasons for adding class size to the CRDC included: many classes are too large; smaller class sizes contribute to better teaching, learning, and climate; and class size contributes to education equity. One commenter also noted that class size is important for educator recruitment and retention.

One commenter stated that “students who receive the greatest benefit from smaller classes are those from disadvantaged groups, including low-income families, students of color, English language learners, and students with disabilities.” The commenter recommended that class size data be disaggregated by race/ethnicity, gender, free lunch status, disability, and English learner status. In addition, the commenter suggested that the data include average sizes of general education, inclusion, and self-contained special education classes.

OCR’s Response

Discussion: OCR appreciates the recommendation to expand the CRDC to include class size data. Additionally, OCR understands the impact class size has on academic achievement, school climate, and other outcomes and that collecting class size data would provide useful information. However, OCR must balance the usefulness of data with reporting burden. The CRDC already collects student school enrollment count data and full-time equivalent teacher count data, which can be used to estimate student-to-teacher ratios for schools and as proxies for class size. Therefore, OCR has decided not to propose the collection of additional data on class size.

Changes: None.

Health and Wellness

Public Comments

One commenter recommended that OCR include additional measures related to school health and wellness. To enhance the quality and utility of the data collected, this commenter specifically recommended adding questions related to health and wellness that address school food and fitness environments, and access to school health services. The commenter noted that the data are necessary because research has found, for example, that: there is a link between health and learning as healthy, well-nourished, and active students are more likely to be engaged in learning; low-income and minority students are more likely to attend schools with unhealthy environments; and low-income and minority students are more likely to have health problems like obesity and asthma that hinder learning. The commenter also noted that by collecting these data, OCR would be better able to identify health-related inequities and target resources accordingly.

OCR’s Response

Discussion: OCR appreciates the commenter’s recommendations that OCR collect data involving school food and fitness environments, and access to school health services. OCR must balance the usefulness of data with reporting burden and has decided not to propose additional data elements surrounding health and wellness in schools at this time.

Changes: None.

Facilities

Public Comments

Seven commenters provided comments on data collection related to facilities. Commenters generally suggested that OCR expand the collection of data on facilities. Three commenters requested OCR collect data on outdated or dilapidated facilities at schools with higher concentrations of minority students and potential civil rights violations or incorporate questions regarding facilities into other data elements. Another commenter suggested that OCR collect specific data about facility construction, renovations, heating and air conditioning, lead levels, ventilation, asbestos, and athletic facilities/equipment.

Additional commenters urged OCR to collect facilities data to document environmental changes, with two commenters stating that OCR should frame climate change as a civil rights issue, and collect data on related issues, including lost classroom instruction due to weather-related facility issues and opportunities for students, especially underserved students, to participate in green learning. One commenter said that OCR should collect facility-related data because many states fail to track this information.

OCR’s Response

Discussion: OCR appreciates the commenters’ proposals to collect more data regarding facilities. OCR understands that collecting such data might provide useful information about conditions that students face while physically present in school facilities (e.g., poorly functioning heating and cooling systems; exposure to environmental hazards like lead or asbestos), and the loss of learning time related to the school facilities’ conditions. However, OCR must balance the usefulness of the data with the reporting burden.

Based on the commenters’ recommendations, OCR has decided to add to the Attachment A-5: Directed Questions document, a new topic related to whether OCR should collect CRDC data on school closures due to extreme heat or cold weather conditions, to obtain input from data submitters and stakeholders. OCR will consider the input it receives from the public to help inform the development of future collections.

Changes: None.

School Climate Surveys

Public Comments

One commenter recommended that OCR require schools to report the percentage of students, teachers, and staff taking school climate surveys. The commenter noted that some school climate surveys gauge how safe students feel at school, whether students believe they are valued and supported, how confident students are as learners, and other social and emotional markers of school success. The commenter also mentioned that in schools where students feel safe and welcome, they are more likely to attend class, earn good grades, and graduate from high school. The commenter stated that this additional data element would not be overly burdensome because states already provide a range of surveys, and many require annual reporting.

OCR’s Response

Discussion: OCR appreciates the commenter’s recommendation for OCR to collect data on those who participate in school climate surveys. OCR believes that the data it has proposed to collect for the 2021–22 and 2023–24 school years are sufficient to inform OCR’s civil rights enforcement activities and has decided not to propose the collection of additional data on school climate surveys.

Changes: None.

Student Demographics

English Learners

Public Comments

Eleven commenters wrote regarding the collection of data on English learners. Six commenters supported restoring the data element related to the number of English learner (EL) students enrolled in EL programs, disaggregated by IDEA. One of the commenters wrote that the data are necessary “to ensure schools are providing instruction to these students as required by law and help to address problems with over- and under-identification of children who need special education services.”

Commenters provided suggestions for revising or improving the collection of EL data. One commenter suggested that OCR disaggregate these data by “English learners and ability” to account for intersectional identities. Two commenters recommended that OCR collect data on the number of EL students disaggregated by Section 504, in addition to IDEA. Another commenter requested that OCR clarify “EL program” and what would qualify as an EL program.

Commenters provided recommendations for expanding this data collection even further. One commenter, stressing the benefits of bilingual education, recommended that OCR: (a) collect information about “English learners’ access to bilingual programming,” language instruction education programs, “segregated learning of English learners,” and “the number of English learners who only received English instruction;” (b) explore data on the number of schools offering “native language preservation and maintenance of revitalization programs;” and (c) launch a task force to understand how to identify and support students who “speak other varieties of English, such as African American English or Appalachian English.” Another commenter recommended that OCR expand the data collection to include “emergent bilingual students,” including “their access to courses, how they are disciplined, graduation and attrition rates, the language programs to which they have access, and how their achievement during and after those programs is measured.” An additional commenter suggested that OCR collect detailed data on dual language programs.

One commenter noted that the proposed data collection on EL students would not create a negative impact or an additional reporting burden for the commenter’s state educational agency.

OCR’s Response

Discussion: OCR appreciates the support for OCR’s proposal to restore the collection of enrollment data for EL students in English language instruction educational programs, disaggregated by IDEA.

OCR also appreciates the recommendations to expand data collection in various ways, including the collection of data regarding bilingual programming, dual language programming, and emergent bilingual students, as well as further disaggregation. OCR understands that collecting these data would offer useful information about EL students. However, OCR must balance the usefulness of data with the reporting burden and has decided not to propose expanding the data collection on EL students at this time.

Launching a task force is outside of the scope of OCR’s CRDC program. Notably, other OCR offices have used the CRDC for purposes such as monitoring compliance with requirements for federal professional development funding, monitoring states under Elementary and Secondary Education Act flexibility waivers and evaluating the Office of English Language Acquisition’s programs and activities. Other federal agencies and researchers and policymakers also use CRDC data.

Lastly, the CRDC defines EL programs as “English language instruction educational programs designed for EL students.” (See Data Groups 947 and 1033).

Changes: None.

Students with Disabilities

Public Comments

One hundred and fifty-three commenters wrote regarding the collection of data on students with disabilities.

Commenters provided recommendations for the collection of data on students with disabilities who receive Section 504 services. One hundred thirty-two commenters recommended that OCR disaggregate all relevant and applicable data elements by 504 only, separate from IDEA. Eight commenters suggested that OCR collect 504 only data for specific data elements, including: the number of students enrolled in gifted and talented programs; the number of students enrolled in distance education courses; and the number of students who participated in a high school equivalency exam preparation program.

Some commenters offered suggestions for expanding this data collection. Thirteen commenters suggested that OCR further disaggregate data to include the type of disability, such as emotional disturbance or intellectual disabilities, while one commenter recommended that OCR further disaggregate data to capture specific language impairments that some LEAs are no longer providing services to accommodate. Another commenter urged OCR to collect data on students with hearing, vision, and speech disabilities, so that the data could be used to reveal communication-based civil rights violations for students with these types of disabilities.

One commenter recommended the collection of data on compensatory education services provided to students with disabilities for learning loss due to COVID-19, while another commenter suggested that OCR collect data on post-disciplinary measures for students with or without disabilities and the outcome of those measures. A different commenter urged OCR to collect data on manifestation determination hearings conducted under Section 504, including how many times a student received such a hearing and their outcomes. One commenter recommended that OCR monitor submissions with 504 only data and rely on these data to ensure compliance with Section 504.

OCR’s Response

Discussion: OCR appreciates the commenters’ recommendations regarding the collection of data for students with disabilities. Most of the proposed CRDC data elements that collect disaggregated student subgroups data already include IDEA status and Section 504 only status.

Over the past four collections of CRDC data, OCR has seen an increase in the number and percentage of students with disabilities served under Section 504 of the Rehabilitation Act of 1973. In the 2017−18 CRDC, about 1.4 million students were served under Section 504. Given the increase of students served under Section 504, and OCR’s interest in ensuring equal educational opportunity for all students, OCR believes it important to collect more data on students served under this section.

OCR always weighs whether an element’s expansion will improve efficiency in data collection; whether an element is necessary to inform current civil rights enforcement; whether an element represents a pressing civil rights concern; and whether the data can be obtained from other sources. Based on these considerations, OCR continues to propose: (1) the collection of disaggregated data by Section 504 only participation and IDEA participation for most student data items; and (2) expanding the collection of preschool student program enrollment and preschool student discipline data to include disaggregated Section 504 only data. For future CRDCs, OCR may consider the commenters’ specific data elements recommended for Section 504 only disaggregation.

OCR acknowledges that expanding the CRDC to collect data on students with specific types of disabilities, and data on post-disciplinary measures and manifestation determination hearings may yield useful information. However, OCR believes the benefit of such an expansion would be outweighed by the increased burden of collecting and reporting that information.

As for the recommendation that OCR collect data on COVID-related compensatory education services, OCR believes that the variability of relevant data collection practices among LEAs and schools for these data would impede the quality and utility of data at this time.

Changes: None.

Students with Disabilities in Non-Public Schools

Public Comments

A total of 129 commenters requested that OCR collect data via the CRDC on students with disabilities who are placed in non-public schools by school districts. All 129 commenters urged OCR to collect data that measure all experiences of these students. In addition, 118 commenters stressed the importance of the collection of data on all disciplinary actions and use of restraint, while 5 commenters stressed disciplinary actions, and 3 commenters stressed restraint and seclusion. One commenter recommended that OCR collaborate with the U.S. Department of Health and Human Services to develop parallel data collections that would provide a more complete picture of the experiences of young children in private community-based early care and learning programs, with particular regard to eligibility under Section 504 and discipline practices.

OCR’s Response

Discussion: OCR appreciates the numerous comments received regarding the collection of data on experiences for students with disabilities placed by school districts in non-public schools. OCR will consider preparing a CRDC technical assistance document with instructions and guidance on how LEAs and schools should report on students with disabilities who are placed in non-public schools by school districts.

Changes: None.

DACA Students and Youth in Foster Care

Public Comments

One commenter recommended the inclusion of Deferred Action for Childhood Arrivals (DACA) students as a subgroup in the CRDC. The commenter noted that this historically neglected subgroup was similar in many respects to other subgroups that have been underrepresented and marginalized in education achievement and economic opportunities. The commenter encouraged OCR to collect and publish data on these students’ achievements and experiences.

Another commenter recommended the collection of data on preschool and grades K-12 foster youth, disaggregated by race, sex, disability, and EL status. This commenter further noted that while the U.S. Department of Health and Human Services tracks the placement of foster youth, there is no federal data pertaining to foster youth and their involvement in school discipline; restraint and seclusion; or pathways to college and career. The result, the commenter concluded, is an under-identification of the unique needs among foster youth which, among other things, hinders services to them in school and in planning for their transition out of foster care.

OCR’s Response

Discussion: OCR appreciates the commenters’ recommendations for OCR to collect CRDC data on DACA students and youth in foster care. While the collection of these data would be informative, OCR must balance the benefits of data with the reporting burden. Additionally, the data could raise privacy concerns regarding the LEA’s identification of and record-keeping about DACA students. OCR has decided not to propose expanding the data to DACA students and youth in foster care.

Changes: None.

Pregnant or Parenting Students

Public Comments

Four commenters wrote regarding the collection of data about pregnant or parenting students. Commenters generally had suggestions for expanding the collection of data on pregnant or parenting students. Two commenters urged OCR to collect data on accommodations offered by LEAs and schools to pregnant or parenting students, including data on alternative education programs, lactation and other medical accommodations, and childcare programs. One commenter urged OCR to collect data on the educational experiences of pregnant or parenting students, including data on the type of education received by pregnant or parenting students (e.g., AP and IB courses; SAT or ACT test preparation; high school equivalency exam preparation), and data on the number of pregnant or parenting students who are chronically absent, who graduate, and who are not promoted to the subsequent grade. Two commenters urged OCR to collect more data on discrimination faced by pregnant or parenting students, including discipline data, and whether LEAs have written policies on discrimination against pregnant or parenting students. Two additional commenters requested that OCR disaggregate data by pregnancy or parental status. Finally, one commenter noted that data on pregnant or parenting students will help OCR’s Title IX enforcement activities, consistent with the guidance that it issued in 2013 regarding Title IX and pregnant or parenting students.

OCR’s Response

Discussion: While several of the data collection items proposed by the commenters may provide useful additional information, the data could raise privacy concerns regarding the LEA’s identification of and record-keeping about pregnant and parenting students. In addition, OCR must balance the usefulness of the data with the reporting burden. Thus, OCR has decided not to include data on pregnant and parenting students in the 2021–22 CRDC.

Changes: None.

Nonbinary Category

Public Comments

One hundred fifty-two commenters wrote regarding OCR’s proposed new collection of data on nonbinary students, with 136 commenters expressing support of OCR’s proposed addition of a nonbinary sex category. Four commenters noted that the addition of a nonbinary sex category would shine a light on the experiences of nonbinary students and support OCR’s mission to enforce Title IX’s prohibition on discrimination on the basis of sex, including discrimination based on sexual orientation and gender identity. Two commenters stated that the proposal is an important change toward inclusivity. Three commenters mentioned that some LEAs are already collecting data using a third nonbinary sex category.

Some commenters highlighted a few benefits to the new collection of nonbinary student data. Four commenters stated that the absence of a nonbinary category in the past has led to problematic data collection practices, including misgendering of students and inaccurate data. Two of these commenters also stated that the lack of a nonbinary category in past CRDCs has created a discrepancy that increases the reporting burden for institutions that have already adopted nonbinary-inclusive record policies. These commenters noted that the new nonbinary category would resolve these issues. In addition, another commenter noted that the collection of nonbinary student data would benefit nonbinary students with disabilities because the data would begin revealing the intersectionality of these students’ unique experiences.

One hundred eighteen commenters expressed support for OCR’s proposed definition of the “nonbinary” category for the 2021–22 CRDC. Two commenters suggested that OCR revise the proposed nonbinary definition to clarify that nonbinary may be indicated by an “X” gender marker. These commenters noted that some state agencies, including departments of motor vehicles and vital records, have adopted an “X” for those who do not identify as exclusively male or female. Another commenter urged OCR to consult with students, families, and advocates to further refine the definitions related to this data collection and to ensure that “sex” and “gender” are being used accurately.

Some commenters provided feedback on whether this collection should be mandatory or optional. One commenter urged OCR to make the nonbinary field mandatory for the 2021–22 collection. In contrast, six commenters noted that they agreed with OCR’s proposal to make the collection of nonbinary student data optional for the 2021–22 collection, and mandatory for future collections.

Commenters wrote in support of this data collection and urged OCR to provide some clarifying points. One commenter urged OCR to clarify whether the proposed inclusion would apply only to institutions that already collect data on nonbinary students or to all reporting institutions. Four commenters urged OCR to clearly communicate limitations that will result in the underreporting of nonbinary students. Three commenters recommended that OCR clarify that a student’s self-identified sex is appropriate and recommended that LEAs use this information when reporting these data.

One commenter urged OCR to clarify that transgender students may be male, female, or nonbinary. The commenters proposed that OCR include certain clarifying instructions, including statements that: a transgender person who identifies as exclusively male should be indicated as a male; a transgender person who identifies as exclusively female should be indicated as a female; and, if there are any nonbinary individuals, then the LEA must use the Sex (Membership)—Expanded Data Category for reporting sex. This commenter also recommended that the comments for Sex (Membership)–Expanded be revised to make it clear that: individuals who identify as male are reported as male; individuals who identify as female are reported as female; nonbinary refers to an individual who does not identify exclusively as male or female; nonbinary does not refer to a transgender individual who identifies exclusively as either male or female; and transgender individuals are reported by affirmed sex.

Some commenters recommended further expansion of this data collection to capture more information about unique student experiences. Three commenters requested that OCR include the nonbinary category in all data collections where sex data are collected via student enrollment records, including in the EDFacts Submission System, to further disaggregate and collect data on disparities for nonbinary students, such as chronic absenteeism and rates of graduation. Two additional commenters suggested expanding the sex category even further to capture the range of identities in the lesbian, gay, bisexual, transgender, queer or questioning, intersex, or other (LGBTQI+) community, including transgender students, and to do so with an eye towards nuance and sensitivity. One commenter encouraged OCR to collect disaggregated and cross-tabulated data on the nonbinary sex category.

Four commenters wrote neither in support nor opposition to OCR’s proposal to collect nonbinary student data, and instead provided general suggestions for improvement. These commenters requested that OCR correct a typographical error in the definition of the Sex (Membership)–Expanded Data Category. The definition includes the male and female categories, but is missing the nonbinary category.

Two commenters that already collect data on nonbinary students noted that they have not experienced a significantly higher reporting burden associated with collecting these data. In contrast, 20 commenters expressed general concern with the burden LEAs would encounter when collecting data pertaining to nonbinary students.

Three commenters stated that, even among LEAs that use a nonbinary sex category for enrollment records, nonbinary students may be unaware that they can amend their records, and this process may be unnecessarily arduous. These commenters noted that students may not feel safe amending their records, particularly in cases where they are not out to their family, their family is unsupportive, or they experience a hostile school climate. Two commenters stated that OCR must communicate clearly about these and other barriers that will result in underreporting of nonbinary students. Two other commenters recommended that OCR share best practices that SEAs and LEAs are using to communicate that students may update their enrollment records to ensure the process is not unnecessarily arduous, and to maintain separate, confidential records of sensitive information, where required.

Nineteen commenters noted potential obstacles that reporting institutions might face in collecting and reporting nonbinary student data. Five commenters noted that policy changes at the state and local levels may need to occur for schools to collect these data accurately. For example, three commenters noted that some states require schools to report the sex of a student as it appears on the student’s birth certificate, and that this might create a conflict with reporting a student as nonbinary. Five commenters similarly noted that changes in student information systems may be required, as some information technology programs do not allow for a third sex category.

Two commenters urged OCR to make changes to the proposed collection of nonbinary student data to address potential concerns. One commenter noted that “nonbinary” is a “gender” identifier and not a value for “sex.” The commenter also stated that the definition of “sex” is related to the genetic identification that is generally used on the birth certificate, and in many states, additional values are not accepted. The commenter asserted that OCR could create an additional value for “gender” (which would include “nonbinary” as a gender identity) while also capturing an individual’s sex assigned at birth. The other commenter encouraged OCR to align its CRDC nonbinary student data collection and related definitions with the EDFacts data collection and definitions, to reduce the reporting burden on institutions.

Some commenters questioned the impact these data might have on OCR’s civil rights enforcement work. One commenter noted that this collection appears political and stated that it would have only a small impact on a minute percentage of the student population. Similarly, three commenters noted that any counts of nonbinary students would be insignificant and underreported. Another commenter questioned the utility of the data if not reported by all institutions, citing the impossibility of comparing between participating and non-participating institutions. Two additional commenters raised concern that the collection of these data would undermine OCR’s efforts to protect women and girls from sex discrimination under Title IX.

Five commenters noted concern with student safety and privacy associated with collecting these data and urged OCR and reporting institutions to use caution in collecting and disclosing students’ sex. One of these commenters encouraged OCR to practice disclosure avoidance techniques to avoid student safety and privacy concerns. Some commenters voiced privacy concerns for students or administrative concerns for school officials when it comes to changing the sex value of a student in the school’s student information systems. For example, two commenters noted that in some states, parents may need to be asked to confirm their child’s sex before the district changes it in its records, and in other states, a parent may be the only person who can officially request to change the sex of their child in school records. Two commenters stated that SEAs and LEAs would need to be trained on how to appropriately collect this information without harming students.

One commenter was concerned that nonbinary students and transgender students may be treated differently for purposes of formal data collection, and that categorizing transgender students according to their affirmed gender identity would result in transgender students not being separately represented in the data.

Three commenters strongly opposed the addition of nonbinary to the sex category in the CRDC. One commenter stated that the proposed changes to the CRDC would encourage schools to not only collect data on student sex identification but would also empower schools to actively question and engage with children on gender identity and sexual identification issues that fall outside of the purview of public schools and are matters to be dealt with exclusively by parents. Another commenter noted that collecting information beyond biological sex of the student is asking LEAs to probe the minds and developing perceptions of pre-adolescent and adolescent students. The commenter felt that such changes to the CRDC are an intrusion upon student privacy and family life. The commenter stated that it is not the role of OCR or LEAs to force students across a wide spectrum of age and physiological and psychological development to form such self-assessments.

Three commenters expressed concern that the collection of these data intrudes on the rights of parents and allows schools to inappropriately engage with students on matters of gender identity and sexual identification. One commenter urged OCR to clarify who gets to make the decision about reporting a student’s sex when there are conflicts between students, families, and schools. Two commenters expressed concern that the new sex category might require schools to violate the Protection of Pupil Rights Amendment (PPRA), which affords parents of minor students the right to consent before a child is subject to a mandatory survey, analysis, or evaluation, if it is funded in whole or in part as part of a program administered by OCR and reveals certain private information. These commenters argued that, under the PPRA, schools are prohibited from inquiring about a student’s “sex behavior or attitudes,” which could include sexual orientation and gender identity, without complying with the parental consent provisions in the law.

One commenter expressed concern that that OCR’s collection of these data exceeds OCR’s statutory authority because federal civil rights laws do not expressly protect nonbinary students. Another commenter noted that the proposal is a move towards increasing accountability, especially in light of the U.S. Supreme Court’s decision in Bostock v. Clayton County, 140 S. Ct. 1731, 590 U.S. __ (2020), and OCR’s June 22, 2021, Notice of Interpretation clarifying that Title IX prohibits discrimination based on sexual orientation and gender identity.

Commenters urged OCR to conduct more research and obtain stakeholder feedback before implementing the proposed collection of nonbinary student data. Specifically, three commenters urged OCR to consult with experts to better understand the diversity of identities that exist within the LGBTQI+ community and to develop best practices based on this feedback for the collection of these data and the protection of LGBTQI+ students.

Seven commenters expressed concerns about the resources, costs, and time needed to implement this data collection, and urged OCR to provide guidance, technical assistance, and funding. For example, one commenter noted the need for staff training on how to collect these data sensitively without harming students. Six other commenters noted the need for further guidance, technical assistance, and training to assist schools in their collection of nonbinary student data and to inform students and families of their rights. In addition, two commenters recommended that OCR provide technical assistance related to the use of the “X” gender marker, including a list of all known ways by which schools code nonbinary in their student information systems.

OCR’s Response

Discussion: OCR appreciates the commenters’ feedback and overwhelming support regarding OCR’s proposed collection of nonbinary student data.

While OCR acknowledges that some state agencies and local agencies have adopted an “X” gender marker for those individuals who do not identify exclusively as male or female, OCR believes that its proposed “nonbinary” value is more precise and better aligns with the “male” and “female” values that are also used in the CRDC.  For an LEA that uses the X marker to indicate nonbinary status in their data collections, the LEA would include those individuals in the nonbinary counts for the CRDC. However, because some entities use that X marker when sex is unknown or unspecified, OCR cannot assume as a general rule that an LEA’s use of the X marker will always align with the CRDC’s proposed definition of nonbinary.  For these reasons, OCR continues to propose male, female, and nonbinary as the possible values for the Sex (Membership)–Expanded Data Category. 

OCR acknowledges the recommendation to revise the proposed nonbinary definition to include an “X” gender marker. OCR’s originally proposed definition reads as follows: “Nonbinary refers to a student who does not identify exclusively as male or female. Nonbinary does not refer to a transgender student who identifies exclusively as either male or female.” OCR has decided not to revise the definition as the commenters suggested because OCR does not believe it is necessary to include examples of gender markers in the definition and some LEAs may use the X gender marker in a manner that is inconsistent with the CRDC’s proposed definition of nonbinary. OCR also appreciates the commenters’ suggestion to consult various groups to further refine relevant definitions and to ensure the terminology used is accurate. OCR meets with and receives correspondence from stakeholders on a regular basis on a range of relevant issues, and we carefully review all comments we receive from the public.

OCR appreciates commenters’ feedback on whether the collection of nonbinary student data should be mandatory or optional. For the 2021–22 CRDC, OCR originally proposed that only LEAs that indicate, via their response to the Nonbinary Student Indicator (see Attachment A-4, page 23), that they collect nonbinary information from students would be required to report student enrollment data for nonbinary students.  For these LEAs, the reporting of other data for nonbinary students would be optional for the 2021–22 CRDC. Other LEAs that indicate they do not collect nonbinary student information would not be required to report nonbinary student data for the 2021–22 CRDC. In an effort to ensure the collection of quality data, OCR continues to support its original proposal for the 2021–22 CRDC, and for the 2023–24 CRDC, OCR now proposes that only LEAs that indicate that they collect nonbinary student information will be required to report all nonbinary student data.

Commenters urged OCR to expand the collection of nonbinary data. OCR must consider the benefits of expanding data collections with the reporting burden on LEAs. OCR believes that the collection of nonbinary student data as proposed will increase the quality and accuracy of the data from LEAs that currently collect this data. OCR may consider the commenters’ suggestions for expanding the collection of these data for future CRDCs.

OCR appreciates commenters noting that the definition of Sex (Membership)–Expanded has not been updated to reflect “nonbinary” as a potential response.  This was an inadvertent omission and has been corrected.   

OCR understands that many LEAs and SEAs may not currently collect nonbinary gender information during student enrollment. As some commenters noted, there will need to be a transition period for LEAs and SEAs to adapt their systems to collecting these data. There may be a need to update software associated with student information systems. OCR understands this concern and proposes that only LEAs and schools that collect nonbinary student data will be required to report these data for the 2021-22 and 2023-24 CRDCs.

OCR appreciates commenters raising privacy concerns related to recording or disclosing the sex of a student in the school’s student information systems. OCR’s proposal does not contemplate that an LEA would need to change the sex recorded in a student’s records as part of its obligation to respond to the CRDC. Rather, OCR proposes that an LEA with recordkeeping systems that identify students as nonbinary would be allowed to report those students as nonbinary in response to the CRDC. In addition, federal law protects the privacy of information in student records. For example, the Family Educational Rights and Privacy Act generally prevents the nonconsensual disclosure of personally identifiable information from a student’s education records; one exception is that records may be disclosed to individual school personnel who have been determined to have a legitimate educational interest in the information. 20 U.S.C. § 1232g(b)(1)(A); 34 C.F.R. § 99.31(a)(1). This exception includes school employees designated to respond to the CRDC for the purpose of ensuring schools’ compliance with federal civil rights laws. Further, OCR makes CRDC data available to the public in a privacy protected format.

One commenter considered the proposed addition of the nonbinary category “political.” The addition of the nonbinary data point in the CRDC is an acknowledgement that some LEAs classify students as male, female, or nonbinary, that prior data collections may not have accurately captured data on students who are classified as nonbinary in those LEAs, and that the CRDC should reflect the experiences of all students.

OCR understands the potential increased burden on LEAs that have not previously reported data they collect on nonbinary students in their responses to the CRDC. OCR also acknowledges that addition of the nonbinary category will reduce the burden for LEAs that maintain data on nonbinary students and have struggled to accurately complete the CRDC when it allowed for only two values for student sex. OCR disagrees that this proposal will increase burden on LEAs that do not collect nonbinary student data as the proposal does not require those LEAs to make changes to the way they report student sex for the 2021–22 CRDC and 2023-24 CRDC. OCR agrees with the commenters who noted that the data are valuable and would help shed light on the experiences of nonbinary students.

In response to the commenter who expressed concern that adding nonbinary as a new sex category to the CRDC would impair efforts to enforce anti-discrimination law and erase females as a distinct legal category, OCR disagrees. OCR vigorously enforces the civil rights of all students.

OCR disagrees with the commenter who said collection of these data exceeds OCR’s statutory authority because federal civil rights laws do not expressly protect nonbinary students. By expanding the CRDC data collection to include data on nonbinary students, OCR is aligning the CRDC collection with the scope of Title IX’s prohibition on sex discrimination.

OCR recognizes that some LEAs already use three values for recording students’ sex. In analyzing CRDC submissions from prior years, OCR realized that some students were likely not being reported in data groups because the CRDC had limited “permitted values” of male or female in the Sex (Membership) Data Category. By implementing the new Sex (Membership) – Expanded Data Category, OCR proposes capturing these students in the data collection and relieving LEAs of the burden of trying to classify a student as a male or female when their records do not identify them as such. For the CRDC, LEAs may report a student’s sex based on a student’s sex as represented in student records.

OCR acknowledges that some commenters believe that “nonbinary” is a gender identifier and not a value for sex. OCR believes that the nonbinary value for sex in the CRDC is appropriate because some students’ sex is not listed as male or female in their school records and a third category is needed to capture data pertaining to these students.

In response to the commenters who expressed concern that the proposed changes to the CRDC would empower schools to actively question and engage with children on gender identity and sexual identification issues that fall outside of the purview of public schools and are matters to be dealt with exclusively by parents, OCR disagrees. The CRDC requires LEAs to report data from their schools’ administrative records. The CRDC is not a survey for students to complete. The sex of a student is required for student enrollment purposes and OCR is merely collecting the data that are included in student enrollment records. Nevertheless, in response to the commenters’ concern, OCR proposes to provide instructions in the survey and revise the nonbinary definition to clarify that OCR expects schools to report information that is in a student’s administrative records. In particular, OCR proposes to revise the nonbinary definition to read as follows: “Nonbinary ~~refers to a student who does~~ means not ~~identify~~ exclusively as male or female. ~~Nonbinary does not refer to a transgender student who identifies exclusively as either male or female.~~”

OCR acknowledges the opinions of commenters who wish for OCR to not proceed with this collection based on fears related to parental rights, student privacy, and other potential issues.  However, the inclusion of a nonbinary sex category will allow LEAs to report complete and accurate data consistent with their own recordkeeping practices and requirements. It would also allow OCR to capture data that could provide some insight into the experiences of nonbinary students.  Recognizing a broader definition of sex in data collection is also consistent with the scope of Title IX’s protection of all students, including nonbinary students, from all forms of sex discrimination. 

While OCR understands that some commenters want OCR to seek additional input from experts before implementing the changes to the data collection, OCR notes that it has received a variety of comments from experts, advocacy organizations, associations, academics, and the public on the proposed nonbinary student data collection. OCR does not believe that additional input from stakeholders (outside the ICR public comment process) is necessary before implementing its proposal for this CRDC.

Finally, OCR appreciates the commenters’ recommendations for OCR to provide additional guidance, technical assistance, and training to CRDC participants on the collection and reporting of nonbinary student data. OCR will continue to consider and provide needed technical assistance to SEAs and LEAs for the CRDC. OCR also may explore possible options for developing new resources that may help support SEAs and LEAs who have questions pertaining to nonbinary students in student information systems.

Changes: Please see the revised nonbinary definition found in the OMB Supporting Statement, Part A document. Also, please see the revised nonbinary definition and the corrected sex description for the Sex (Membership)–Expanded Data Category found in Attachment A-3, page 37.

Transgender, Gender Identity, and Sexuality

Public Comments

Three commenters recommended the creation of a data element to assess the welfare of transgender students. Another commenter suggested that OCR disaggregate data by gender identity and sexuality.

OCR’s Response

Discussion: OCR appreciates the commenters’ suggestions to include data elements concerning transgender students, and to disaggregate data by gender identity and sexuality. Although OCR understands that expanding the data collection as the commenters’ suggested might provide useful information, OCR must balance the usefulness of the data with the reporting burden on LEAs. OCR continues to propose new gender identity data elements on: the number of harassment or bullying allegations reported by students on the basis of gender identity; whether an LEA has a written policy or policies prohibiting harassment or bullying of students on the basis of gender identity; and the web link to the written policy or policies. OCR has decided not to further disaggregate data by gender identity and sexuality at this time.

Changes: None.

Student Family Data

Public Comments

One commenter recommended that OCR broaden its data collection on participation in pre-kindergarten by including information such as family structure, and the education level of parents. This commenter noted that more information on this topic would increase advocates’ abilities to gauge and support student access to programs and services.

Another commenter requested a Military Student Identifier (MSI) data element. The commenter noted that districts are not reporting MSI data.

OCR’s Response

Discussion: OCR appreciates the recommendation for OCR to collect student family data to help advocates gauge and support equitable student access to pre-kindergarten programs and services. OCR also appreciates the recommendation for OCR to collect MSI data. OCR recognizes the importance of understanding the unique issues that students of military families may encounter in school. OCR believes that the proposed data elements are sufficient to inform its civil rights enforcement obligations and has decided not to collect student family and MSI data.

Changes: None.

Early Childhood Education, Preschool, and Kindergarten Characteristics

Public Comments

One hundred forty-five commenters responded to OCR’s proposal to re-introduce as optional for the 2021–21 CRDC, 6 data elements related to early childhood education, preschool, and kindergarten characteristics. Of these commenters, 137 supported OCR’s proposal to restore the 4 data elements involving the collection of LEA data on: whether the LEA provided early childhood services or programs, in either LEA- or non-LEA facilities, to non-IDEA children age birth to 2 years; whether early childhood education or preschool services serve non-IDEA children; whether preschool is provided to all students, IDEA students, Title I school students, and students from low income families; and preschool and kindergarten length (full-day, part-day) offered and cost (free, partial/full charge). One commenter recommended further disaggregation of data for full- and half-day preschool programs by race, sex, disability, and English learner status, to determine whether there is an impact on duration of preschool on dual language learners.

Eight of the commenters also expressed support for OCR’s proposal to restore and revise two data elements and revise one data element involving: whether the LEA was providing preschool services or programs, in either LEA- or non-LEA facilities, to non-IDEA children, by age 3, 4-5; whether the school was providing preschool services or programs to non-IDEA children, by age 3, 4-5; and number of students served by the LEA in preschool programs, by age 3, 4, 5. One commenter questioned why OCR decided to combine ages 4-5 (originally ages 3, 4, and 5), for the data elements that collect data on whether schools and LEAs serve non-IDEA children, but not for the data element that collects LEA-level counts of children served in preschool (originally ages 2, 3, 4, and 5). The commenter also questioned why OCR decided to combine children ages 2 and 3, to just be classified as 3-year-olds, for the LEA-level children served in preschool data element, but not make similar changes to the non-IDEA children data elements. Twelve commenters noted their support for OCR’s proposed expansion of preschool student enrollment counts to include disaggregated data by sex and students with disabilities served under Section 504 only.

One hundred twenty commenters recommended making the proposed restored data elements mandatory, rather than optional. In particular, 13 commenters noted that restoring the data elements to the CRDC would not pose a problem for schools, as the data were previously mandatory, while 11 commenters expressed their concern that allowing the data elements to be optional would compromise the integrity of the dataset.

Three commenters raised a concern that the proposed data elements would not paint a complete picture of the landscape of early childhood education and preschool, where children may attend programs in their communities outside of LEAs that respond to the CRDC. These commenters recommended that OCR collaborate with the U.S. Department of Health and Human Services (HHS) to ensure a comprehensive account of early childhood education and preschool experiences. Another commenter noted that the proposed data elements were not currently collected by its SEA, and that reinstating them would pose an undue burden on the SEA.

One commenter requested clarification regarding the difference between the Preschool Grade Data Group (913) and the Preschool Program Directional Indicator (24).

OCR’s Response

Discussion: OCR appreciates the overwhelming support for OCR’s proposals to restore, restore and revise, revise, and expand various data elements related to early childhood education, preschool, and kindergarten for the 2021–22 CRDC. OCR also appreciates the recommendation to collect preschool length of day and cost data by disaggregated student demographics. While more information would be helpful, OCR believes that the proposed data collection is sufficient to inform its civil rights enforcement obligations.

OCR acknowledges the commenters who urged OCR to make the proposed restored data elements required, instead of optional for the 2021–22 CRDC. OCR has determined that these data elements should remain optional for the 2021–22 CRDC to give LEAs and schools sufficient time to restore these data elements and prepare for their reporting obligations. For the 2023–24 CRDC, OCR proposes these data elements to be required. While the 2021–22 CRDC, with the restored optional data elements, will not be as comprehensive as the 2023–24 CRDC that will include those data elements as required, OCR does not believe making those data elements optional for the 2021–22 collection will compromise the integrity of the data, as it will still reveal significant amounts of information about early childhood education, preschool, and kindergarten availability and length.

OCR recognizes that there are other community-based providers of early childhood education and preschool that will not be captured by the CRDC. OCR will consider collaborating with HHS to ensure comprehensive data collection about early childhood and preschool experiences.

OCR believes the proposed restored data elements are central to the enforcement of the civil rights laws OCR enforces and other purposes for which OCR collects data. Therefore, the burden these data elements impose on SEA and LEA respondents does not outweigh the benefit it confers.

OCR appreciates the commenter’s questions involving why for certain data elements, certain age groups are combined, while others are not, and the other commenter’s request for an explanation on how Data Group 913 and Directional Indicator 24 differ. For the data elements involving whether schools or LEAs were providing preschool services or programs to non-IDEA children, by age 3 years, and 4-5 years, OCR continues to propose to combine ages 4 and 5 into one group because compared to 3-year-old children, 4- and 5-year-old children tend to engage in kindergarten readiness activities. Also, since these data elements are indicators and do not collect counts, OCR considers it sufficient to collect data on whether 4- and 5-year-old non-IDEA children were provided preschool services or programs. However, for the data element involving the number of students served by the LEA in preschool programs, in either LEA or non-LEA facilities (disaggregated by age 3 years; 4 years; 5 years), OCR considers it important to collect data for students of a specific age.

For the data element involving the number of students served by the LEA in preschool programs, in either LEA or non-LEA facilities, OCR continues to propose to combine the 2-year-old and the 3-year-old categories. The 2-year-old category collects data for children who are 2 years of age and will turn 3 years of age during the school year. OCR considers it sufficient to collect one count of 3-year-olds that includes 2-year-olds who will turn 3 years of age during the school year and 3-year-olds who are 3 years of age at the time of the October 1 reporting snapshot date.

For the data elements involving whether schools or LEAs were providing preschool services or programs to non-IDEA children, by age 3 years, and 4-5 years, OCR decided not to expand the non-IDEA children age 3 years category to include non-IDEA children who are 2 years of age and will turn 3 years of age during the school year, because OCR does not want to change the construct of the 3 years of age category. OCR would like to continue to compare CRDC data collected over time, and therefore, makes an effort to minimize changes to data constructs.

As for Data Group 913 and Directional Indicator 24, the former represents the preschool grade level offered by a school, whereas the latter represents a guiding item that determines whether the LEA provides one or more preschool programs that serve children ages 3 through 5.

Changes: None.

Preschool Enrollment for Students Served Under Section 504 Only

Public Comments

One hundred thirty commenters addressed OCR’s proposal to collect preschool enrollment data for students with disabilities served under Section 504 only, disaggregated by sex, race, and English learner status. One hundred twenty-three commenters urged OCR to include this data element in the 2021–22 CRDC. Two commenters noted that the data collected could be used to better understand the enrollment and experiences of young students with disabilities, while another commenter noted that the data could be used to understand the differences in experiences between students eligible under Section 504 only and students eligible under IDEA.

Four commenters opposed the collection of these data. Two commenters expressed concern that the data would paint an incomplete picture because students with disabilities may be receiving services in private settings that do not report CRDC data. Similarly, two other commenters noted that preschool programs may be contracted out to private providers, making it especially difficult to collect and report these data. In the event OCR decided to proceed with the collection, one of the commenters recommended that OCR collect these data from state agencies, due to the wide variations in how preschool programs are managed on a district-to-district basis. This commenter also noted potential difficulties with this data collection and suggested that OCR collaborate with the U.S. Department of Health and Human Services (HHS) to receive a more complete data collection on preschool experiences.

In response to OCR’s directed question on whether LEAs have enrolled preschool students served only under Section 504 in preschool programs (see Attachment A-5: Directed Questions document), one commenter stated that these data are collected by their LEA, while two commenters noted that the data are currently not collected by their LEAs.

OCR’s Response

Discussion: OCR appreciates the commenters’ feedback and overwhelming support for OCR’s proposed collection of data on preschool enrollment of students with disabilities served under Section 504 only. OCR also appreciates the commenters’ expressed concerns and acknowledges that the proposed data collection could result in potentially incomplete results. Nevertheless, OCR believes this information is important to help OCR better protect preschool students’ civil rights and monitor how LEAs are meeting their responsibilities to provide equal educational opportunities to these students.

OCR thanks the commenter for their recommendations that OCR collect the data from state agencies and collaborate with HHS. OCR is open to continuing to work with SEAs that assist LEAs with submitting CRDC data and will consider collaborating with HHS to ensure comprehensive data collection about preschool experiences.

Changes: None.

Preschool English Learners

Public Comments

Five commenters provided feedback on data collection relating to preschool English learners. Four commenters supported OCR’s proposal to expand its collection of preschool English learner data to include: preschool English learner (EL) students disaggregated by race/ethnicity and sex; preschool EL students enrolled in EL programs, disaggregated by race/ethnicity, sex, and disability-IDEA; preschool EL students served under IDEA, disaggregated by sex; and preschool EL students served under Section 504 only, disaggregated by sex. Commenters highlighted the importance of collecting preschool EL data. Two commenters noted that EL students are one of the fastest-growing student populations. Another commenter described the benefits of bilingualism on the long-term success of EL students and stated that this data collection would capture important information on the types of programs offered to EL and bilingual students.

Commenters provided suggestions for improving this data collection. One commenter suggested that the data be disaggregated by race, disability, and language level. Another commenter recommended changing OCR’s terminology to refer to EL preschool students as “dual language learners” since preschool students may not have developed their first language at the preschool age. This commenter also suggested disaggregating the data collection to account for different types of preschool EL programs.

One commenter stated that this data collection is an undue burden for institutions in states where EL enrollment data are not collected until kindergarten.

OCR’s Response

Discussion: OCR appreciates the responses to OCR’s proposal to expand its collection of data on EL preschool enrollment. OCR also appreciates the recommendations to expand the data collection in various ways. While the expanded data collection would offer useful information about preschool EL students and programs, OCR must balance the expansion of helpful data with the reporting burden on LEAs. OCR has decided to not collect these data at this time but may consider these suggestions for future collections.

Additionally, OCR has decided not to replace “English learners” with the term, “dual language learners” to remain consistent with the term used by offices throughout OCR.

OCR believes the proposed new preschool data elements are central to the enforcement of the civil rights laws. Therefore, the burden these data elements impose on SEA and LEA respondents does not outweigh the benefit it confers.

Changes: None.

Preschool Gifted and Talented

Public Comments

Seven commenters responded to OCR’s directed question on whether LEAs enrolled preschool students in gifted and talented programs. Three commenters recommended that OCR continue to collect counts of students (preschool-grade 12) enrolled in gifted and talented programs, whereas one commenter urged OCR to remove preschool students from the data element. Five commenters noted that they were unaware of any gifted and talented programs for preschool-aged students. A different commenter indicated no preference on whether preschool gifted and talented data should be collected.

A few commenters provided specific feedback to express their support for this collection. One commenter noted the importance of these data in measuring historical inequities in the availability of gifted and talented programs, especially for students of color, students from low-income families, and English learner students. Another commenter mentioned that despite being prevalent in LEAs with socioeconomic privilege, gifted and talented students are still dramatically underserved. An additional commenter noted their support of OCR’s description of gifted and talented programs, encouraged OCR to collect these data to account for the demographic makeup of these programs, and suggested that academically advanced preschool students are victims of age discrimination due to unfair age-sorting in schools.

OCR’s Response

Discussion: OCR appreciates the responses to the directed question on preschool students enrolled in gifted and talented programs. Given that only five commenters noted that they are largely unaware of the existence of such programs, while three commenters recommended that OCR continue to include preschool students in the students enrolled in gifted and talented programs data element, OCR has decided to keep the students enrolled in gifted and talented programs data element unchanged. OCR believes this information could prove useful in continuing OCR’s mission of protecting students’ civil rights. As commenters noted, there may be historic and ongoing inequities in access to gifted and talented programs, and OCR believes data about these inequities will be important to OCR’s enforcement of civil rights laws.

Changes: None.

Pathways to College and Career

Courses and Classes

Public Comments

Fifteen commenters addressed the collection of data on courses and classes.

Eight commenters suggested disaggregating the data collected on the number of students enrolled in math, science, and computer science courses by students with disabilities served under Section 504 only. These commenters also recommended making this collection mandatory. Another commenter commended OCR’s proposed continued collection of data on computer science courses but suggested a revision to the definition of computer science courses to focus particularly on programming and coding. Specifically, the commenter suggested the following definition and inclusion of the sample course list:

Computer science courses include computer programming or coding as a tool to create things like software, applications, games, and websites. They involve the study of computers and algorithmic processes, including their principles, hardware and software designs, applications, and their impact on society. They often include managing large databases of information, legal and ethical issues involved in computer technology use, and network security. Computer science does not include using a computer to do everyday things, such as browsing the internet, use of tools like word processing, spreadsheets or presentation software, or using computers in the study and exploration of other subjects. Web page design, networking systems, information technology, computer literacy, or computer education are NOT counted as computer science. Computer science courses include: Computer Science Principles, Exploring Computer Science, Coding, Computer Science Essentials, Computer Science A, Business Programming, Computer Programming, Computer Gaming and Design, Mobile Applications, and Robotics.

This commenter also suggested collecting specific data on computer science opportunities for K-12 students to measure what opportunities are available and when they become available for this student population.

Some commenters provided feedback on OCR’s proposed retirement of data elements counting the number of middle school Algebra I classes and numbers of high school math, science, and computer science classes taught by certified teachers. One commenter commended OCR’s proposed retirement of these data elements, noting that the data were burdensome for LEAs to collect. In contrast, two commenters expressed disappointment in OCR’s proposal to retire these data elements. These commenters emphasized that this retirement would impact the collection of data on the experiences of students of color. Three other commenters urged OCR to specifically retain the high school classes taught by certified teachers data elements.

Finally, one commenter expressed concern over the burden associated with OCR’s proposed expansion of the counts of grade 8 Algebra I course student enrollment and student passage disaggregated by sex, race/ethnicity, disability, and English learner status data elements, to include grade 7 and nonbinary status. The commenter noted that the proposed changes would present a burden for reporting institutions in their state.

OCR’s Response

Discussion: OCR appreciates the responses received regarding the collection of data on courses and classes. OCR appreciates the recommendations to disaggregate students enrolled in math, science, and computer science courses, by disability-Section 504 only, and to make the new disability category required for the 2021–22 CRDC. OCR also appreciates the recommendation that OCR collect specific data on K-12 computer science opportunities. While these recommended additional data may be useful, OCR must balance the utility of the data with reporting burden. OCR has decided not to further disaggregate or add new categories of data at this time.

OCR has considered the one commenter’s recommendation to amend the computer science definition and has decided not to revise the definition. OCR’s current computer science courses definition reads as follows:

Computer science courses involve the study of computers and algorithmic processes, including their principles, hardware and software designs, applications, and their impact on society. They often include computer programming or coding as a tool to create things like software, applications, games, websites and electronics, managing large databases of information, legal and ethical issues involved in computer technology use, and network security. Computer science does not include using a computer to do everyday things, such as browsing the internet, use of tools like word processing, spreadsheets or presentation software, or using computers in the study and exploration of other subjects.

OCR, however, may consider including the commenter’s proposed list of topics that are not considered computer science, and the commenter’s proposed list of sample courses as instructions in the survey.

OCR appreciates the feedback on OCR’s proposed retirement of the middle school and high school classes taught by certified teachers data elements. OCR continues to propose these data elements’ retirement and instead, to collect a full-time equivalent count of teachers certified to teach in specific areas (i.e., mathematics; science; special education; and English as a second language). OCR believes this change will allow OCR and others to assess student access to teachers certified to teach the subjects they are assigned to teach as well as reduce the reporting burden on LEAs.

OCR acknowledges comments raising concerns about the burden associated with OCR’s proposed expansion of the counts of grade 8 Algebra I course student enrollment and student passage disaggregated by subgroups data elements, to include grade 7 and nonbinary status. LEAs are already required to collect total counts only for grade 7 Algebra I course enrollment and passage, and total counts for grade 8 Algebra I course enrollment and passage disaggregated by sex, race/ethnicity, English learner status, and disability. Therefore, OCR’s proposal to retire grade 7 Algebra I data elements and combine grades 7 and 8 for the Algebra I course enrollment and passage data elements to capture important disaggregated data for Algebra I course enrollment and passage for both grades 7 and 8 should result in little to no additional burden. In addition, the new proposed nonbinary disaggregation for the courses data elements is proposed as optional for the 2021–22 CRDC, and required for the 2023–24 CRDC, giving LEAs ample time to prepare for the collection.

Changes: None.

Data Science

Public Comments

Fifteen commenters provided feedback on OCR’s proposed new collection of counts of data science classes and students enrolled in data science courses. Eleven of the commenters expressed support for OCR’s proposed new data elements. Two of these commenters noted the importance of data science courses in today’s world. The other two commenters noted that the addition would help eliminate opportunity gaps by shedding light on whether certain student groups (e.g., “historically marginalized students,” students of color, students with disabilities, and students from low-income households) have equitable access to courses and early postsecondary opportunities. A different commenter pointed out that a definition of data science course was needed. Seven commenters urged OCR to add disability-Section 504 only as a disaggregation category to the students enrolled in data science courses data element, and to make the data element mandatory, instead of optional, for the 2021–22 CRDC. One commenter also suggested that OCR disaggregate the data element by grade level.

Two commenters pointed out the increased burden that the addition would create for LEAs. Specifically, one commenter noted LEAs would have to: establish “course identifiers” for courses that are considered “data science” courses; and regularly review the curriculum and assign the identifiers to relevant courses. Another commenter expressed general frustration with shifting CRDC requirements and expectations and questioned whether information regarding data science courses would be probative of civil rights issues rather than a reflection of staffing for such classes.

OCR’s Response

Discussion: OCR has proposed to add the following data elements to the 2021−22 CRDC: the number of data science classes taught to students in grades 9-12; and the number of students in grades 9-12 enrolled in data science courses, disaggregated by race/ethnicity, sex, nonbinary, disability-IDEA, and EL. OCR has also proposed a definition for “data science courses” in Attachment A-2, page 30 (Data Group 1030) and page 31 (Data Group 1031). The definition reads as follows:

Data science courses focus on learning and gathering meaning from datasets, using methods from mathematics, statistics, computing, and other fields. Students in data science courses learn data-related skills, such as data cleaning, merging, analysis, modelling, and visualization; exposure to a wide variety of data types; and may study societal, ethical, and civic implications of data usage and analysis. Many data science courses also include coverage of the “data cycle,” akin to the scientific method: 1) formulating data-related questions; 2) gathering and collecting data; 3) exploring the data; 4) analyzing the data; and 5) interpreting and communicating the results, which then leads to additional inquiry.

OCR consistently reviews and seeks to refine and improve the CRDC, including by making necessary updates to reflect shifts in public education and to adequately monitor trends. OCR also carefully considers, on an ongoing basis, each data collection element and endeavors to minimize the burdens imposed on LEAs, all while continuing to collect important civil rights data. Ultimately, OCR found that the benefits of the additional data science course enrollment data outweigh the burden of their collection. While any new data collection increases the burden on LEAs to a certain extent, this burden should be relatively small with respect to data science courses. LEAs are already required to collect data on a variety of course offerings and enrollment. Moreover, data science courses are increasing in prevalence.

Regarding the comment about the impact of staffing changes on data science course data, the CRDC data are primarily used to compare subgroups of participating students for civil rights monitoring and enforcement purposes. If course offerings are reduced generally, student course enrollment would likely be reduced but disparities among subgroups of enrolled students could still be analyzed.

OCR appreciates the recommendations to disaggregate data science course enrollment by disability-Section 504 only and by grade level. The proposed element, with grades 9-12 combined, for data science courses is consistent with other course enrollment elements (e.g., dual enrollment, computer science, distance education, etc.). While further disaggregation of the data may provide useful information, OCR must balance the data’s usefulness with the reporting burden. OCR has decided not to further disaggregate the data at this time.

OCR also appreciates the recommendation that the data element be required and not optional, for the 2021–22 CRDC. Typically, when OCR introduces new or restored data elements, OCR makes the data elements optional the first year to give LEAs and schools an opportunity to prepare for their reporting obligations. OCR has determined that the proposed students enrolled in data science courses data element should remain optional for the 2021–22 CRDC and should be required for the 2023–24 CRDC.

Changes: None.

Advanced Placement, International Baccalaureate, SAT, and ACT

Public Comments

Nineteen commenters provided feedback on the Advanced Placement (AP) & International Baccalaureate Diploma Programme (IB) Enrollment module of the CRDC. Nine commenters supported the restoration of the number of students enrolled in at least one AP course in other AP subjects. Six requested that the data element be required and not optional for the 2021–22 CRDC. One of the commenters noted the importance of AP courses in helping students gain skills needed to be successful in college, current opportunity gaps in enrollment, and the need for data to help identify barriers to access.

Eight commenters recommended that the students enrolled in an AP course in a specific subject area data element be disaggregated by disability-Section 504 only. Seven of these commenters made the same disaggregation recommendation for the students who took the SAT, the ACT, or both data elements. The commenters noted that “…the CRDC is the only federal-level data collection that yields information on Section 504-only students. Therefore, disaggregating data elements to include 504-only students provides critical information.” A different commenter recommended that OCR collect socioeconomic status data for AP course and IB participants.

Six commenters suggested reinstating data elements involving the number of students who took one or more AP exams. Reasons provided included: research that shows that students who take at least one AP exam are more likely than their peers to complete a bachelor’s degree on time and to earn higher grades in college in the subject area of their AP exam; public use of data to assess whether certain students are being denied the benefits of AP exams because taking the exam seems to solidify the benefits of an AP course, even if the student fails the exam; a large differential between the number of students taking an AP course and the number taking an AP exam at a school that may suggest barriers, like cost, that may impede students from taking an exam and obtaining the benefit of college credit.

One commenter suggested that reinstating the data element about students enrolled in other AP subjects, and disaggregating the data element by nonbinary status would be burdensome. The commenter also indicated that their state is not currently collecting data about nonbinary students, and therefore, would need “ample time” to add the field to its student information system. Another commenter suggested that AP data are no longer of interest because students are now choosing to take course work (dual enrollment) for college credit over AP courses.

One commenter recommended retiring the data element on whether students are allowed to self-select for participation in AP courses because the commenter considered the data element “almost meaningless.” Another commenter commended OCR for proposing to continue to include this data element in the CRDC. This commenter noted that is it important to understand where students are allowed to self-select AP courses because a study found that some students, particularly Black and Latino students, attend schools with AP courses but are often denied access to those courses.

OCR’s Response

Discussion: OCR appreciates the broad support for the proposal to restore the data element for number of students enrolled in at least one AP course in other subject areas, and the recommendation that the data element be required and not optional, for the 2021–22 CRDC. Typically, when OCR introduces “new” or “restored” data elements, OCR makes the data elements optional the first year to give LEAs and schools an opportunity to prepare for their reporting obligations. OCR has determined that the students enrolled in an AP course in other subject areas data element should remain optional for the 2021–22 CRDC.

While any new data collection increases the burden on LEAs to a certain extent, the burden from the restored data element and new nonbinary disaggregation for the AP, IB, and SAT/ACT data elements (both optional for the 2021–22 CRDC) should be relatively small. LEAs are already required to collect data on a variety of course offerings and enrollment.

OCR appreciates the recommendations to disaggregate students enrolled in an AP course in a specific subject area, and students who took the SAT, ACT, or both, by disability-Section 504 only, and the recommendation to disaggregate students enrolled in an AP course in a specific subject area, and students enrolled in IB, by socioeconomic status. OCR must balance the usefulness of any new data element with the reporting burden on LEAs. OCR believes that the proposed data collection is adequate to inform OCR’s civil rights enforcement obligations and has decided not to further disaggregate the data at this time.

OCR also appreciates the recommendation to reinstate the data elements involving student participation in AP exams. OCR consistently reviews and seeks to refine and improve the CRDC. OCR recognizes that AP exam student participation data can be used to help gauge inequities in educational outcomes. OCR must also consider the reporting burden and has decided not to reinstate the student participation in AP exams data element. OCR believes that AP data are important for tracking college or career readiness and agrees with the commenter that it is important to understand where students have the opportunity to enroll into AP courses via self-selection. Accordingly, OCR will continue to collect data on whether students are allowed to self-select for participation in AP courses.

Changes: None.

Credit Recovery

Public Comments

Thirty-three commenters provided feedback on OCR’s proposal to restore credit recovery participation. Of these commenters, 22 supported restoring the data element to collect the number of students (grades 9-12) who participate in at least 1 credit recovery program that allows them to earn missed credit to graduate from high school. Another eight commenters requested that the data element be mandatory for school year 2021–22 reporting.

Six commenters remarked on the importance of this data, noting that this data can show which student populations are more likely to participate in credit recovery. One commenter explained, “Collecting data about credit recovery programs can inform policies and other practices that help students stay in school and graduate. Excluding data on the number of students participating in credit recovery programs will limit information about the experiences of marginalized students and prevent school districts from ensuring the success of all students.”

Fifteen commenters suggested expanding the data element to include the number of students in juvenile justice facilities who participate in credit recovery programs and the number of calendar days that they participate. Two of these commenters noted the importance of credit recovery for youth reentering communities from justice systems and expressed concerns about reentry planning and access to high-quality educational opportunities and supportive programming for such youth.

Two commenters recommended that the credit recovery data element be disaggregated by student demographics, such as race/ethnicity, disability, English learner status, and free or reduced-price lunch status. One commenter expressed concerns about the quality of credit recovery programs and whether they are provided in a manner that is consistent with participating students’ Individualized Education Plans. The commenter urged OCR to collect information about what credit recovery “programs are actually providing.”

OCR’s Response

Discussion: OCR appreciates the broad support for the proposal to restore the data element for number of students (grades 9-12) who participate in at least one credit recovery program that allows them to earn missed credit to graduate from high school, and the recommendation that the data element be required and not optional, for the 2021–22 CRDC. Typically, when OCR introduces new or restored data elements, OCR makes the data elements optional the first year to give LEAs and schools an opportunity to prepare for their reporting obligations. OCR has determined that the credit recovery data element should remain optional for the 2021–22 CRDC.

OCR also appreciates the recommendations to expand the data collection to include: students in juvenile justice facilities who participate in credit recovery programs; the length of time these students participate; disaggregated data by student subgroups; and a program quality measure. The proposed credit recovery data element would apply to schools and justice facilities with any grade 9 through 12, and/or with ungraded high school age students.

As for the other recommendations, at this time, OCR believes that the proposed restored credit recovery data element is sufficient to inform its civil rights enforcement obligations. OCR may consider the recommendations for expanding the credit recovery data collection for future civil rights data collections.

Changes: None.

Dual Enrollment

Public Comments

Eleven commenters expressed support for OCR’s proposed continued collection of data on students enrolled in a dual enrollment/dual credit program. One commenter noted that participation in dual enrollment is an indicator of equity that relates to opportunities extending beyond the school building or school day. Another commenter recommended disaggregating dual enrollment by race/ethnicity and English learner (EL) status. The third commenter suggested making dual enrollment data at least as detailed as the data elements for Advanced Placement (AP) “to ensure equitable access to college pathways.” The commenter noted that dual enrollment is increasingly used to improve competitiveness for college admissions and that disparities persist in the types of courses made available to students (e.g., transferrable vs. non-transferrable and academic vs. career technical).

Seven commenters urged OCR to add disability-Section 504 only as a disaggregation category to the students enrolled in data science courses data element, and to make the data element mandatory, instead of optional, for the 2021–22 CRDC. One commenter suggested that OCR collect socioeconomic status data for dual enrollment.

OCR’s Response

Discussion: OCR has proposed to continue collecting dual enrollment/dual credit program data disaggregated by race/ethnicity, sex, disability-IDEA, and EL status. The only proposed change for the 2021−22 CRDC is to add nonbinary as an optional expansion.

OCR appreciates the recommendations to expand the dual enrollment/dual credit program data collection to match the more extensive AP data collection, and to collect socioeconomic status data for the dual enrollment data element. OCR also appreciates the recommendations to disaggregate dual enrollment student enrollment by disability-Section 504 only, and to make the data element required, instead of optional, for the 2021–22 CRDC.

OCR understands that collecting more detailed dual enrollment/dual credit program data may be informative, but, at this time, OCR believes that collecting dual enrollment/dual credit program data disaggregated by the demographic groups specified in OCR’s proposed 2021–22 CRDC is sufficient to support OCR’s mission of civil rights enforcement. In addition, typically, when OCR introduces new or restored data elements, OCR makes the data elements optional the first year to give LEAs and schools an opportunity to prepare for their reporting obligations. OCR has determined that the nonbinary students enrolled in dual enrollment/dual credit data element should remain optional for the 2021–22 CRDC and should be required for the next CRDC.

Changes: None.

Devices and Wi-Fi

Public Comments

Sixteen commenters provided feedback on OCR’s proposal to add 4 new data elements on Wi-Fi enabled devices and hotspots concerning the number of students who needed and received Wi-Fi enabled devices or hotspots for student learning use. Thirteen commenters expressed support for OCR’s proposed data elements. One commenter was not supportive of the new items, stating that the elements have not been “thoroughly vetted,” are too broad or too narrow, are subjective, and will result in unreliable data. Responses from two commenters were neither expressly supportive nor unsupportive; rather, they suggested response options.

Specifically, commenters in support of these data elements noted that student access to necessary devices and Internet connectivity are indicators of equity and the proposed elements would help identify barriers to equitable access to education and whether there is a tech divide. Three of the commenters noted that the COVID-19 pandemic has illuminated and exacerbated existing inequities and that the proposed elements would be helpful for analyzing disparities. One commenter wrote that the information included in the elements “will provide policymakers, advocates, and families with information to determine how well districts addressed students’ home broadband needs and to identify communities where the digital divide is widest.” An additional commenter wrote that “high-speed home Internet and a connected device are essential tools for learning in today’s world, even when districts provide in-person instruction.”

Commenters noted that these data would be particularly helpful in identifying inequities for students of color, EL students, and other underserved students. One commenter stated that, as more students return to school from remote learning, schools are providing less technology to students, thereby “leaving ELs and their families disconnected once again.” According to one commenter, Black, Latino, and economically disadvantaged students disproportionately lack access to a reliable devices and Internet access. Another commenter pointed out that American Indian/Alaska Native households are also more likely to lack high-speed home Internet and Wi-Fi enabled devices necessary for virtual learning. Finally, one commenter noted the large numbers and percentages of students who transitioned to distance learning during the pandemic but who remained “disconnected or under-connected.” That same commenter further observed that, while all students experienced “diminished opportunities to learn,” the loss was disproportionally greater among Black and Latino students. Eight commenters suggested that the elements be disaggregated by student sub-groups such as race/ethnicity, disability, socioeconomic, and EL status.

Commenters had suggestions on additional data collection and how this data should be collected. Two commenters suggested adding how schools identified barriers and strategies to identify these barriers. One commenter recommended that OCR collect data regarding teachers’ qualifications to “offer technology-powered opportunities.” Two commenters suggested that, to avoid duplication, OCR should align CRDC and Elementary and Secondary School Emergency Relief (ESSER) data reporting requirements. A different commenter suggested that the elements also be provided as percentages of students.

OCR’s Response

Discussion: For the 2021–22 CRDC, OCR proposes retaining the following data elements: (1) whether the school allows students to take home school-issued devices that can be used to access the Internet for student learning; (2) whether the school allows students to bring to school student-owned devices that can be used to access the Internet for student learning; and (3) number of Wi-Fi enabled devices provided by the school to students (preschool-grade 12) for student learning use. Additionally, OCR proposed adding data elements, for preschool-grade 12, about the number of students who: (1) needed Wi-Fi enabled devices from the school for student learning use; (2) needed a Wi-Fi hotspot from the school for student learning use; (3) received Wi-Fi enabled devices from the school for student learning use; and (4) received a Wi-Fi hotspot from the school for student learning use. OCR appreciates the broad support for these proposals.

OCR also appreciates the recommendations to disaggregate the data by student subgroups; to add data regarding teachers’ qualifications to “offer technology-powered opportunities;” and to add data about “what schools did to identify barriers to connectivity and to provide students with the connections and devices they needed to ensure continuity of learning.” OCR understands that this data would be informative, but, at this time, OCR will limit the data elements to those proposed and may consider disaggregating the data in future collections.

OCR has, and continues to, carefully vet the elements, including through this information collection request. For example, OCR considers the proposed CRDC elements in light of other data reporting requirements to OCR, including those associated with ESSER, and takes steps to avoid duplication, where feasible. The commenter who suggested that the requirements would be either too broad or too narrow did not explain why this would be the case; thus, it is difficult for OCR to formulate a detailed response. OCR’s general response is the elements are about specific devices for specific grade levels, and key terms are defined for the CRDC.

Changes: None.

Career and Technical Education

Public Comments

Two commenters provided recommendations concerning career and technical education (CTE). One commenter recommended that OCR collect the number of students enrolled in CTE, disaggregated by race, sex, nonbinary, disability, and English learner (EL) status. This commenter highlighted that because the Methods of Administration for Civil Rights is the responsibility of state departments and these same departments are tasked with implementing the Strengthening Career and Technical Education Act for the 21^st Century, it would “be prudent for their data collection elements to include the data additions proposed for elementary and secondary education.”

Another commenter also proposed data elements related to CTE, highlighting that access to CTE courses is an important civil rights indicator because evidence demonstrates that CTE concentrators graduate high school at higher rates than their peers. Specifically, this commenter recommended that OCR collect: the number of students enrolled in at least one CTE course, disaggregated by race, sex, nonbinary, disability-IDEA, disability-Section 504 only, and EL status; the number of different CTE courses provided by career cluster; and the number of students who have earned two or more credits within a single CTE career cluster, disaggregated by race, sex, nonbinary, disability-IDEA, disability-Section 504 only, and EL status.

OCR’s Response

Discussion: OCR appreciates the commenters’ suggestions to include data elements related to CTE. OCR recognizes that CTE courses can help prepare students with academic, technical, and career skills to assist with workplace competence and introduce students to work-based learning opportunities. OCR also understands that equitable access to CTE courses is an important educational and civil rights issue. OCR has decided not to collect CTE data at this time but may consider the commenters’ suggestions for future civil rights data collections. OCR will continue to utilize its Methods of Administration Program to monitor states’ compliance with federal civil rights laws in their administration of CTE programs.

Changes: None.

Holocaust Education

Public Comments

Five hundred eighty-seven commenters urged OCR to collect data on whether Holocaust education is part of the school curriculum. All 587 commenters cited a rise in anti-Semitic harassment, intimidation, and violence in schools and noted that data on Holocaust education might help OCR better understand schools’ responses to anti-Semitism and other forms of hate on campus. One commenter specifically requested that OCR include data elements on “the number of Holocaust education courses provided” and “the number of courses that include Holocaust education in the curriculum” in the “Pathways to College and Career” section of the CRDC survey.

OCR’s Response

Discussion: OCR appreciates the commenters’ proposal for collection of data regarding Holocaust education and shares the commenters’ concern about anti-Semitic harassment on school campuses. For the 2021–22 and 2023–24 CRDCs, OCR is proposing the continued data collection of the number of allegations, received by a school, of harassment or bullying on the basis of perceived religion, regardless of whether the targeted student actually identifies with that religion, for each of 14 religion categories, including Jewish students and students of other religious groups. OCR believes that continuing to collect data on instances of harassment or bullying on the basis of perceived religion is both responsive to the commenters’ concern, which OCR shares, regarding rates of anti-Semitic harassment and essential to aid in OCR’s mission of civil rights enforcement.

Changes: None.

Instruction and Outcomes

Instruction

Public Comments

Fourteen commenters requested that OCR collect data on the number of days of lost instruction disaggregated by race with disability.

OCR’s Response

Discussion: While the collection of the data proposed by the commenters could provide useful additional information, OCR must balance the usefulness of the data element with the reporting burden. OCR proposes to continue to collect the number of school days missed due to K-12 students who received out-of-school suspensions disaggregated by race, sex, disability, and English learner status. OCR proposes expanding the sex category to include students who identify as nonbinary and has decided not to collect additional data related to days of lost instruction at this time.

Changes: None.

Educational Interventions

Public Comments

One commenter recommended adding data on the number of students receiving “intensive interventions” in math and reading, who are not served under the IDEA or Section 504. The commenter noted there are no data collected on students who test significantly below grade level but are not found eligible for services under IDEA or Section 504. The commenter also argued that these data may reveal instances of civil rights violations since many of these students are students of color.

OCR’s Response

Discussion: OCR appreciates the recommendation to expand the CRDC to include data on students without disabilities receiving additional educational interventions. OCR believes the currently proposed collection is sufficient to inform OCR’s civil rights law enforcement obligations, and therefore will not expand the data to include educational interventions.

Changes: None.

Post-School Outcomes

Public Comments

One commenter recommended that OCR add elements to the CRDC to determine where students matriculate after graduation from high school or go to when they exit schools without graduating. The commenter noted that students may be “pushed out” or “counseled out” of traditional educational experiences, for example, through encouragement to enroll in GED programs. The commenter also noted that information about student outcomes from a particular school would help parents and students find schools that fit their needs and help policymakers draft policies to promote desired educational outcomes.

OCR’s Response

Discussion: OCR appreciates the recommendations to collect data on where students go after graduating high school or after exiting school without graduating. Although OCR understands that collecting these data may be informative, OCR must balance the benefits of informative data with the reporting burden on LEAs. The CRDC is an early childhood through grade 12 data collection, and OCR already collects student post-secondary data via the NCES’ Integrated Postsecondary Education Data System. Therefore, OCR has decided not to add data elements to the CRDC on post-graduation or exiting school information.

Changes: None.

Student Deaths by Suicide

Public Comments

One commenter recommended that OCR add a new CRDC data element related to student deaths by suicide, disaggregated by sex. The commenter noted that deaths by suicide are becoming more common for young people, and especially female students.

OCR’s Response

Discussion: OCR appreciates the recommendation to add a new student deaths by suicide data element to the CRDC. However, the proposed data collection would place LEAs in the position of reporting data that are not necessarily available to them. Therefore, OCR has decided not to add a student deaths by suicide data element to the CRDC.

Changes: None.

Harassment or Bullying

Public Comments

Fifty-three commenters provided feedback on the CRDC’s Harassment or Bullying module. Fourteen commenters specifically addressed OCR’s proposed collection of data on harassment or bullying on the basis of religion. Five commenters noted their specific support of OCR’s proposed data collection on harassment or bullying on the basis of religion, with two commenters expressly noting their support for OCR’s proposal to collect data on LEA policies addressing harassment or bullying on the basis of religion. One commenter supported disaggregating the allegations data to capture the religion or perceived religion of each victim of religious-based harassment.

A few of these commenters also provided suggestions for improving or expanding this collection. One commenter recommended that OCR collect data on harassment or bullying on the basis of religion in a manner that mirrors how OCR collects data on harassment or bullying on other bases, including collecting religious harassment or bullying data by the number of students who report or are disciplined for such behavior. Another commenter suggested that OCR incorporate data from other supplemental sources that may better represent students’ experiences of religious-based harassment or bullying. One commenter recommended that OCR expand this collection to include harassment or bullying against atheist students. A different commenter suggested that OCR add a data element on whether LEAs train staff on cultural sensitivity related to religious-based harassment or bullying, and urged OCR work with religious communities to provide guidance and training to schools to ensure accurate reporting and collection of these data.

Some commenters expressed concerns with OCR’s proposed collection of data on harassment or bullying on the basis of religion. Six commenters noted that OCR’s proposed collection of this information might raise privacy concerns for students and families. Four commenters recommended making the religious harassment data collection optional, with three of these commenters also recommending that OCR evaluate the quality of the religious harassment data prior to making the collection mandatory. An additional commenter noted that OCR should make clear that affirming the identities of LGBTQI+ and pregnant or parenting students is not religious harassment or bullying.

Twenty-one commenters wrote regarding OCR’s proposed collection of data on harassment or bullying on the bases of sexual orientation and gender identity. Twenty commenters expressed support for OCR’s proposed collection of data on harassment or bullying on the basis of sexual orientation or gender identity. Nine of these commenters specifically supported OCR’s proposed collection of data on LEA policies that address harassment or bullying on the basis of sexual orientation and gender identity, with one commenter noting that these data elements would not present an additional reporting burden.

Commenters further provided suggestions on what additional data related to harassment or bullying on the basis of sexual orientation and gender identity should be collected, and how these data should be collected. Six commenters urged OCR to begin to collect data on the counts of students subjected to or disciplined for harassment or bullying on the basis of sexual orientation and gender identity. Three commenters recommended that OCR disaggregate data on sexual orientation and gender identity harassment or bullying to include more identities falling under the LGBTQI+ spectrum. Two commenters suggested adding a data element to measure the outcome of allegations of sexual orientation and gender identity harassment or bullying. Another commenter suggested tracking allegations of harassment or bullying on the basis of sexual orientation and gender identity by grade level, and collecting unduplicated counts of allegations of harassment or bullying to account for incidents in which students are harassed or bullied based on their intersectional identities. This same commenter also suggested combining the separate data groups regarding anti-discrimination policies into a single data group and noted that these data groups overlap in their treatment of sexual orientation and gender identity. The commenter further requested that, for the anti-discrimination policy data elements, OCR clarify which civil rights categories are and are not covered.

Some commenters noted support and suggestions for the definitions proposed by OCR regarding harassment or bullying on the basis of sex. Four commenters supported OCR’s inclusion of gender identity and sexual orientation in the proposed definition of sex. These commenters also noted their support of OCR’s interpretation of the Supreme Court’s decision in Bostock v. Clayton County to recognize discrimination on the basis of sex to include sexual orientation and gender identity. Seven commenters supported OCR’s inclusion of sex characteristics in the proposed definition of harassment or bullying on the basis of sex, noting the importance of this inclusion for the collection of data on the experiences of intersex students, and suggested that OCR additionally collect data on whether LEA policies address sex characteristics. Six commenters recommended that OCR revise the definition of “on the basis of sex” to explicitly encompass harassment or bullying based on transgender status and gender expression. Three commenters suggested that OCR amend the definition to include associational discrimination, to capture instances where students are discriminated against because of their relationship with an LGBTQI+ parent, relative, or friend. Two additional commenters recommended further revisions to align with OCR’s definitions of rape and sexual assault under the Clery Act.

Two commenters raised concerns about OCR’s proposed collection of data on harassment or bullying on the basis of sexual orientation and gender identity. One commenter noted the increased burden associated with requiring LEAs to collect data on harassment based on sexual orientation and gender identity. Another commenter expressed concern with requiring institutions to submit a weblink to non-discrimination policies, as these links could be misused.

Several commenters recommended additional data elements on harassment or bullying on a variety of bases and contexts, including on basis of spoken language; on the basis of pregnancy; occurring online; among early learners; and occurring by staff against students.

OCR’s Response

Discussion: OCR appreciates the responses to OCR’s proposals related to the collection of harassment or bullying data.

OCR proposes to continue to collect data on the number of harassment or bullying allegations on the basis of perceived religion, for 14 religion categories. OCR recognizes the concerns raised by commenters worried about a potential breach of privacy, but the proposed harassment or bullying allegations for 14 religion categories data element does not elicit private information about students, just as existing data elements on harassment or bullying for all specific categories do not collect data that are sensitive in nature. The instructions that accompany the CRDC harassment or bullying on the basis of religion data element make clear that the CRDC does not give respondents the authority to inquire about the religion of students. OCR will continue to provide training opportunities for school districts to properly understand all the data elements, including this particular data element that requires LEAs to include religious affiliation of students as part of their administrative records. OCR understands that technical assistance would be helpful to LEAs to promote accurate data collection and will provide assistance in the survey itself and through the technical assistance channels that already exist for the CRDC. Such technical assistance will also be clear that student privacy should not be impacted, and OCR will continue to clarify what conduct falls under each category of harassment or bullying.

In addition, a CRDC Partner Support Center is available to school districts to call or email questions regarding the content of the data to be collected. For this data, in classifying the allegations of harassment or bullying, respondents will be directed to look to the likely motives of the alleged harasser/bully, and not the actual status of the alleged victim. For the allegations of harassment or bullying on the basis of perceived religion for each of 14 religion categories data element, this direction also applies.

In response to one commenter’s request, OCR will ensure that for the anti-discrimination policy data elements, it is clear in the survey form which civil rights categories are and are not covered.

While any new data collection increases the burden on LEAs to a certain extent, OCR considers the increased burden to collect new data on harassment based on sexual orientation and gender identity reasonable, including because the data elements do not include disaggregated student groups (e.g., race/ethnicity, sex). In addition, OCR considers the new data elements necessary to ensure compliance with the civil rights laws and that, individually and in total, the burden is justified by the need for the data.

OCR has considered all the commenters’ feedback and has decided to proceed with the originally proposed data elements and definitions for the CRDC. OCR will keep the commenters’ recommendations in mind for future collections. For the currently proposed CRDC collection, OCR believes the proposed collection effectively balances the data reporting burden with the data’s value and usefulness to OCR’s ongoing work to enforce the laws within its jurisdiction. At this time, OCR believes that the data elements and definitions as proposed are sufficient to inform our civil rights enforcement obligations and has decided not to expand the collection of harassment or bullying data beyond what is currently proposed.

Changes: None.

Harassment or Bullying Policy Web Links

Public Comments

Five commenters responded to OCR’s proposal to request that LEAs provide web links to written policies prohibiting discriminatory harassment or bullying of students on the basis of sexual orientation, gender identity, or religion. Three commenters supported OCR’s proposed new collection of these web links. Additionally, three commenters recommended that OCR publish the collected web links, noting that failure to publish the web links would harm the CRDC’s value to researchers.

OCR’s Response

Discussion: OCR appreciates the support received for the proposed new collection of LEAs’ web links to policies prohibiting discriminatory harassment or bullying of students on the basis of sexual orientation, gender identity, or religion. OCR also appreciates the recommendation to release the LEAs’ web links information to the public. The new data elements are proposed as optional for the 2021–22 CRDC, with the intent to make them required for future CRDCs. As OCR has done in the past, OCR proposes to release optional 2021–22 CRDC data in a restricted-use data file that is available to researchers who obtain a license to access the file from the National Center for Education Statistics. For subsequent CRDCs, OCR proposes to release the required CRDC web links information to the public via the CRDCs’ public-use data files.

Changes: None.

Discipline

Preschool Discipline

Public Comments

Nine commenters wrote regarding the collection of preschool discipline data, with seven commenters expressing general support for OCR’s continued collection of this data. One commenter urged OCR to collect the number of preschoolers subjected to additional forms of discipline beyond suspension and expulsion, such as transfers to alternative schools. Other commenters provided additional recommendations and feedback.

Commenters provided feedback on OCR’s proposal to collect preschool discipline data disaggregated by disability-Section 504 only. Two commenters specifically expressed support for the collection of data on the number of preschoolers who received services under Section 504 subjected to expulsion, in addition to the other disaggregation categories. In contrast, two commenters opposed this collection. One of these commenters stated that their SEA does not already require the collection of preschool discipline Section 504 only data and that such a collection would be unduly burdensome. The other commenter noted the difficulty of obtaining the data due to the wide variations in preschool programs from district to district and the use of private contractors. This same commenter recommended that, if the data are required, the information should be collected through the SEA, rather than the LEA.

Two commenters commended OCR’s proposal to continue to collect preschool discipline data disaggregated by race/ethnicity, with one of these commenters suggesting that OCR collect race/ethnicity preschool discipline data for students with disabilities.

Finally, commenters emphasized the importance of preschool discipline CRDC data. One commenter noted that the CRDC has served as the primary source of national data on the extent to which students with disabilities, students of color, and other historically underserved students are expelled in preschool settings, and that this collection of preschool discipline data will show where disparities in the use of exclusionary discipline exist. Another commenter highlighted the importance of this data, noting that the “school to prison pipeline,” starts in preschool and disproportionally impacts students of color and students with disabilities.

OCR’s Response

Discussion: OCR appreciates the support from commenters for the proposal to continue to collect preschool discipline data, and to expand the preschool discipline data elements to include preschool students with disabilities served under Section 504 only. OCR also appreciates the commenters’ recommendations for expanding this data collection and acknowledges that the recommended changes may yield valuable information. OCR must balance the benefits of informative data with the reporting burden on LEAs. At this time, OCR believes that the proposed data elements are sufficient to inform its civil rights enforcement obligations.

In response to the commenters’ concerns about the collection of preschool discipline Section 504-only data, OCR continues to propose making the reporting of preschool discipline Section 504-only data optional for the 2021–22 CRDC. LEAs will then have more than sufficient notice to change their data collection systems to report complete and accurate data for the 2023–24 CRDC.

Changes: None.

Preschool Suspensions

Public Comments

Thirty commenters provided feedback on the collection of data on preschool suspensions. Eleven commenters specifically supported OCR’s proposal to revert to collecting separately data on the number of preschool students who received one out-of-school suspension, and the number of preschool students who received more than one out-of-school suspension. Five commenters noted their support for the continued disaggregation of this data by race/ethnicity, sex, English learner (EL) status, and disability-IDEA. One commenter commended OCR for specifically collecting data for preschool students with disabilities served under IDEA, while three commenters commended OCR for proposing to expand the collection to include preschool students with disabilities served under Section 504 only.

Commenters offered suggestions for improving OCR’s collection of this data. One commenter suggested collecting data on the specific number of suspensions, rather than simply “one” or “more than one” suspension. Another commenter noted that OCR should specifically disaggregate the number of suspended preschoolers receiving Section 504 services by race/ethnicity and sex.

Commenters provided suggestions for expanding OCR’s collection of this data. Sixteen commenters requested the addition of a mandatory data element detailing the reason for a preschool suspension. Four commenters suggested collecting the number of school days missed by preschool students due to out-of-school suspensions, and to disaggregate this data by race/ethnicity, sex, and disability. Four other commenters suggested the collection of data on preschool students who received in-school suspensions, disaggregated by race/ethnicity, sex, disability, and EL status. Two additional commenters suggested collecting disaggregated data on how many preschool students had access to their Individualized Family Service Plan while suspended.

One commenter noted that the proposed data collection on preschool suspensions would not create a negative impact or an additional reporting burden for the commenter’s SEA.

OCR’s Response

Discussion: OCR appreciates the support from commenters for the proposal to reinstate the separate data elements on the number of preschool students who received one out-of-school suspension, and the number of preschool students who received more than one out-of-school suspension, and to expand the data elements to include preschool students with disabilities served under Section 504 only. OCR also appreciates the commenters’ recommendations for revising or expanding this data collection and acknowledges that the recommended changes may yield valuable information. At this time, OCR believes that the proposed data elements are sufficient to inform its civil rights enforcement obligations.

Changes: None.

Discipline – Corporal Punishment

Public Comments

Thirty commenters provided feedback on the collection of data on the use of corporal punishment. One commenter expressed general support for OCR’s proposed continued collection of preschool corporal punishment data, while five commenters specifically supported the collection of these data as it relates to students of color, who have historically been subjected to corporal punishment at disproportionate rates. Two commenters noted support for OCR’s proposed continued collection of the number of instances of corporal punishment received by preschool students with disabilities served under IDEA, and OCR’s new proposed collection of the number of instances of corporal punishment received by preschool students with disabilities served under Section 504 only. Three commenters commended OCR for its proposed new disability-Section 504 only disaggregation category for the number of preschool students who received corporal punishment data element.

Commenters provided suggestions for how the corporal punishment data should be disaggregated. One commenter suggested all corporal punishment data be disaggregated by grade level. Another commenter recommended that the number of K-12 corporal punishment instances data element and the number of preschool corporal punishment instances data element be disaggregated by English learner status. Three commenters urged OCR to disaggregate the K-12 instances data by race, gender, and disability, while 22 commenters urged OCR to disaggregate the preschool instances data by those subgroups. One commenter suggested that OCR disaggregate the number of preschool students who received corporal punishment data by a cross-section of disability-IDEA by sex and race/ethnicity, to mirror the collection of corporal punishment data for K-12 students.

A few commenters provided recommendations for expanding the corporal punishment data collection. One commenter recommended the collection of additional data, including: the reason for the use of corporal punishment; the type of corporal punishment used; the number of teachers or school officials involved in corporal punishment incidents; and the race of teachers or school officials involved in corporal punishment incidents. This same commenter suggested that OCR practice greater transparency in the collection process for data on corporal punishment, by informing the public of: how schools report corporal punishment incidents; and OCR’s verification process for ensuring that school districts are giving truthful and transparent information. Another commenter recommended the collection of new data on whether corporal punishment was imposed by a law enforcement officer or another school staff person. An additional commenter suggested that OCR collect data on the frequency in which preschoolers receive corporal punishment.

Finally, one commenter noted that, while collecting data on the use of corporal punishment would not generally be a burden on institutions in their state, the collection of these data as it relates to preschoolers receiving services under Section 504 would be a burden, as that data are not currently collected.

OCR’s Response

Discussion: OCR appreciates the support from commenters for its proposed continued collection of preschool and K-12 data on corporal punishment, and for its proposed collection of additional preschool corporal punishment data. OCR also appreciates the commenters’ numerous suggestions on how to further disaggregate the data, and how to expand the data collection. However, at this time, OCR believes that the proposed data elements are sufficient to inform its civil rights enforcement obligations. OCR may consider the recommendations for expanding the collection of data on corporal punishment for future CRDCs.

LEAs who participate in the CRDC are required to certify the accuracy of their data submissions. Nevertheless, OCR checks some CRDC data, including corporal punishment data, for accuracy. OCR does this checking by including data quality checks for some CRDC data in the CRDC data submission system that flag potentially erroneous data, and after the close of the survey submission window, reviewing the data to identify possible reporting anomalies. LEAs are then given the opportunity to amend their CRDC submission, as necessary.

In response to the commenter’s concerns about the collection of preschool corporal punishment Section 504-only data, OCR continues to propose making the reporting of preschool discipline Section 504-only data optional for the 2021–22 CRDC. LEAs will then have more than sufficient notice to change their data collection systems to report complete and accurate data for the 2023–24 CRDC.

Changes: None.

K-12 Discipline

Public Comments

Seventeen commenters wrote regarding the collection of K-12 discipline data. All commenters supported the collection of this data. Two commenters noted their support for OCR’s proposed continued collection of K-12 discipline data, and OCR’s proposed new nonbinary disaggregation category, citing disparate discipline practices against nonbinary and LGBTQI+ students.

Commenters offered suggestions for how these data should be disaggregated. Two commenters suggested the collection of all discipline data disaggregated by a cross-section of race with Section 504 only to collect more information on students of color with disabilities receiving Section 504 services. One commenter urged OCR to disaggregate all discipline data on Section 504 only students by sex and race, while another by sex, race, and English learner status. One commenter suggested the disaggregation of K-12 out-of-school suspension instances data by race, citing the frequent occurrence of discriminatory discipline against students of color and the “school-to-prison pipeline.”

Commenters also had suggestions for expanding the collection of discipline data. Two commenters suggested that OCR change the collection of K-12 data from one or more in-school suspensions to one in-school suspension and more than one in-school suspension. One of these commenters also suggested the new collection of data on school days missed due to in-school suspensions to mirror the current collection of school days missed due to out-of-school suspensions. Two commenters urged OCR to collect data on how many K-12 students had access to their Individualized Education Programs while suspended, disaggregated by race/ethnicity, sex, and disability. Two other commenters suggested that OCR collect data on whether discipline was received during in-person or virtual instruction. Three commenters suggested that OCR collect data on the reason for disciplinary measures taken against K-12 students.

OCR’s Response

Discussion: OCR appreciates the commenters’ support for the proposed continued collection of K-12 discipline data, and the new proposed nonbinary category. OCR also appreciates the commenters’ suggestions for additional data disaggregation and additional new discipline data elements and acknowledges that these data might provide valuable information. However, OCR must balance the utility of the data with the reporting burden. At this time, OCR believes that the proposed discipline data elements are sufficient to inform its civil rights enforcement obligations.

Changes: None.

ESEA Report Cards

Public Comments

One commenter indicated that not all school districts comply with the requirements in the Elementary and Secondary Education Act (ESEA) regarding the inclusion of discipline and safety data in report cards. The commenter urged OCR to require that ESEA report cards include discipline data for individual schools and to expand ESEA reporting to include data on restraints, seclusions, teachers with special education training, and related service providers.

OCR’s Response

Discussion: OCR, which administers the CRDC, is not responsible for enforcing ESEA. Any questions or concerns relating to school districts’ fulfillment of ESEA requirements may be directed to OCR’s Office of Elementary and Secondary Education. Additionally, OCR cannot change statutory data reporting requirements established by Congress, and therefore, cannot add data elements to ESEA.

As background, Congress required in ESEA, as amended in 2015 by the Every Student Succeeds Act (ESSA), that school districts and states include certain data reported to the CRDC on their publicly available state and local report cards. Specifically, Sections 1111(h)(1)(C)(viii) and 1111(h)(2)(C) of ESEA, as amended by ESSA, requires that state and local report cards include CRDC information on measures of school quality, climate, and safety, such as suspensions, expulsions, referrals to law enforcement, school-related arrests, and harassment or bullying. ESSA does not require that report cards include CRDC data on restraints, seclusion, teachers, or related services providers.

Changes: None.

Informal Removals

Public Comments

Thirty-one commenters wrote regarding informal removals. All commenters requested the addition of data elements on informal removals or non-suspension classroom removals with no instruction. Twenty-three commenters noted the importance of collecting these data for monitoring and documenting the amount of lost instructional time experienced by students.

Numerous commenters advocated for the collection of data on informal removals based on how long students are removed from the classroom setting. Three commenters urged OCR to collect data on informal removals lasting less than half a day, including students missing multiple class periods. Fourteen commenters recommended that OCR collect data on informal removals with no instruction, lasting less than, more than, or half a day. Other commenters highlighted the importance of data on longer-term informal removals. Two commenters expressed concern about longer-term “off the books” removals, defined as removals for periods longer than 10 days and lasting weeks or months, where often already underserved children are forced to learn at home with limited instructional assistance.

Some commenters noted the importance of capturing the different types of informal removals that students experience. Five commenters noted that OCR should collect data on instances when a student is “sent to sit in the principal’s office for an extended amount of time or having a parent called to pick them up.” One commenter offered examples of short-term informal removals like “detention,” “tardy sweep,” or “hallway time.” Another commenter requested that OCR collect data on students removed from school through “school-initiated referral to the juvenile legal system, transfers to either no school program or an inappropriate program,” or “psychiatric commitment.” Two commentors cited students being locked out of remote programming as an example of an informal removal. One commenter urged OCR to collect data on students who are sent home early during the class day or placed on shortened schedules. Two additional commenters noted that OCR should collect data on informal disciplinary removals not designated as formal suspensions or expulsions.

Numerous commenters noted the particular civil rights concerns associated with informal removals. Fifteen commenters expressed concern about informal removals resulting in violations of students’ civil rights protections and protections under IDEA and Section 504. Eight other commenters noted their concern with the lack of due process protections students subjected to informal removals receive, as compared to students subjected to formal suspensions and expulsions. One commenter mentioned that informal removals can particularly impact students with disabilities, as they may be provided shortened school days or removed on a continual or repeated basis.

Commenters noted the disproportionate use of informal removals against students of color. Two commenters stressed the importance of collecting these data to better understand the overwhelming impact of informal removals on Black students. One commenter noted that Black girls are often unfairly informally removed for violations of student dress or grooming policies, while another commenter noted that Black students are disciplined more than their counterparts, including by being informally removed.

One commenter expressed concern on how “soft suspensions” impact younger children when schooling is not mandatory, such as prekindergarten. One example of these removals involves parents being asked to pick up their child.

OCR’s Response

Discussion: OCR appreciates the commenters’ recommendations for the collection of data on informal removals. OCR acknowledges that expanding the CRDC to collect data on students who receive informal removals would yield useful information and we would like to consider further what data to collect and how to define informal removals. OCR has added informal removals as a topic in the Attachment A-5: Directed Questions document to encourage specific input from the public.

Changes: None.

Referrals and Arrests

Public Comments

Thirty-three commenters provided feedback on OCR’s proposed collection of data on referrals to law enforcement and arrests.

Six commenters provided suggestions on refining or revising the definitions associated with this data collection. Four commenters suggested revising the definition of referral to account for all scenarios where incidents may occur and the various ways that students are referred to law enforcement, including incidents occurring on school transportation/vehicles or on sidewalks or paths used to get to and from school property. One commenter suggested adding referrals and arrests by non-sworn law enforcement officers to the definitions of referral and arrests. Another commenter suggested revising the definition of referrals to include a list of specific law enforcement agencies or officials to which students can be referred.

Commenters suggested collecting more information about referrals and arrests. One commenter suggested disaggregating the counts of students referred to law enforcement and the counts of students arrested by grade level. Five commenters suggested collecting new data on the number of instances of referrals and arrests to provide greater clarity regarding the frequency of these forms of actions. Three commenters recommended collecting the basis or reason (i.e., a mental health crisis, threat assessment, and/or violations of school codes of conduct) for a referral or arrest. One commenter suggested capturing whether a law enforcement referral resulted in an arrest. This commenter also suggested disaggregating the basis and results data by sex, race/ethnicity, English learner (EL) status, native language, socioeconomic status, disability, pregnancy or parenting status, foster care status, homeless status, and national origin. An additional commenter recommended collecting data to capture where arrests occurred (i.e., on school grounds, during an off-campus event, or while taking school transportation). Another commenter suggested collecting data on referrals or arrests that involve other circumstances, including those stemming from electronic surveillance of students, and those resulting in involuntary commitment of students to psychiatric institutions. One commenter suggested that OCR provide “clear definitions that allow states to categorize the type of referral to law enforcement made to accurately gather specific data about the use of citations or complaints, arrests, referrals to juvenile probation, referrals to adult criminal court, or the involvement of law enforcement officers in routine discipline matters.”

Some commenters had specific suggestions for collecting data on who initiated a law enforcement referral. One commenter suggested collecting data on which school official made a referral, and to make clear who qualifies as a school official for these purposes. Two commenters suggested disaggregating the data to differentiate referrals initiated by school-based police as opposed to other school staff. Four commenters suggested collecting data on referrals to law enforcement by persons other than school staff, including parents, in part to account for referrals occurring in virtual learning settings.

Some commenters urged OCR to expand the referrals and arrests data collection to capture more data on particular groups of students. Six commenters recommended that OCR collect data on preschool students referred to law enforcement or subjected to arrest. Two other commenters suggested disaggregating referral and arrest data for Section 504-only students by race, sex, and EL status.

Many commenters were particularly concerned with the use of threat assessments in schools as they relate to law enforcement referrals and arrests. According to one commenter, threat assessments involve convening a team that includes law enforcement alongside school personnel to assess a student’s risk for school-based violence. Twenty-six commenters urged the collection of the number of students referred to receive threat assessments, disaggregating this data by student demographics, and including threat assessments in the definition of a law enforcement referral. Twenty-two commenters recommended that OCR collect data on the outcomes of referrals and arrests, particularly those incidents stemming from threat assessments. In particular, two commenters noted that “there exists no real data on the efficacy of student threat assessments, yet there is a rapid spread to implement student threat assessment nationwide, without sufficient attention to the severe negative unintended consequences, especially for children of color and children with disabilities.

Commenters requested that OCR make clarifications related to the referrals and arrests data collection. One commenter urged OCR to clarify what actions specifically entail a referral. One commenter suggested that OCR clarify whether every interaction with law enforcement should count as a referral, or whether only interactions resulting in investigation and/or arrest should count. Another commenter suggested clarifying the distinction between “reporting” and “referring” a student to law enforcement, noting that law enforcement involvement based on a referral should be distinct from a report to law enforcement. A different commenter urged OCR to reinforce guidance to LEAs that “referrals to law enforcement” include citations, tickets, and court referrals. One commenter suggested that OCR clarify that LEAs should be reporting unduplicated counts of students referred or arrested. Three commenters suggested additional OCR guidance, training, technical assistance, and follow-up to assist institutions in collecting and reporting this data, with one commenter suggesting that OCR consult with experts in creating this guidance.

OCR’s Response

Discussion: OCR appreciates the commenters’ suggestions for OCR to amend the referrals and arrests definitions, expand and further disaggregate the collection of data on referrals and arrests, and to provide additional guidance to LEAs on the referrals and arrest data collection.

OCR currently defines referral to law enforcement and school-related arrest as follows:

Referral to law enforcement – An action by which a student is reported to any law enforcement agency or official, including a school police unit, for an incident that occurs on school grounds, during school-related events, or while taking school transportation, regardless of whether official action is taken. Citations, tickets, court referrals, and school-related arrests are considered referrals to law enforcement.
School-related arrest – occurs when a sworn law enforcement officer takes a student into custody, and intends to or appears to intend to seek charges against the student for a specific offense or offenses for any school-related activity. School-related activities include any activity conducted on school grounds, during off-campus school activities (in-person or virtual), while taking school transportation, or due to a referral by any school official. All school-related arrests are considered referrals to law enforcement.

Based on the commenters’ feedback, OCR proposes to amend the definitions. Specifically, OCR proposes to revise the referral and arrest definitions to clarify and expand on who may refer a student to law enforcement. OCR also proposes to revise the arrest definition to include all law enforcement, sworn and unsworn. The proposed revised definitions read as follows:

Referral to law enforcement – An action by which a student is reported by a school official or that official’s designee to any law enforcement agency or official, ~~including~~ such as a school police unit, for an incident that occurs on school grounds, during school-related events, or while taking school transportation, regardless of whether official action is taken. Citations, tickets, court referrals, and school-related arrests are considered referrals to law enforcement.
School-related arrest – occurs when a ~~sworn~~ law enforcement officer takes a student into custody, and intends to or appears to intend to seek charges against the student for a specific offense or offenses for any school-related activity. School-related activities include any activity conducted on school grounds, during off-campus school activities (in-person or virtual), while taking school transportation, or due to a referral by any school official or that official’s designee. All school-related arrests are considered referrals to law enforcement.

OCR also proposes to include instructions in the CRDC survey that clarify that referrals to law enforcement may include referrals made to sworn or unsworn law enforcement officers and that school-related arrests are typically made by sworn law enforcement officers. For OCR’s proposed new law enforcement officer definition, please see the Security Staff section of this document.

Based on commenters’ recommendations for OCR to clarify what actions entail a referral, OCR proposes providing guidance to LEAs that clarifies that a student referred to law enforcement includes a student sent to meet with a law enforcement agency or official because of a school-related incident, a student reported to law enforcement because of a school-related incident, and a student who has direct interactions with law enforcement because of a school-related incident. OCR also proposes to clarify that referrals include formal referrals and informal referrals that are not part of an official report.

In response to one commenter’s suggestion that OCR clarify that counts of students referred or arrested should be unduplicated counts, both the Discipline of Students with Disabilities Data Group (922) and the Discipline of Students without Disabilities Data Group (923) already contain a note that for each discipline method, the data should be unduplicated.

OCR appreciates the commenters’ suggestions to collect the numbers of instances of referrals to law enforcement and arrests and understands that this collection would provide valuable information. OCR agrees with the commenters’ suggestions and proposes to add the following new data elements to the CRDC: (1) the number of instances of referrals for K-12 students without disabilities, students served under IDEA, and students served under Section 504 only; and (2) the number of instances of arrests for K-12 students without disabilities, students served under IDEA, and students served under Section 504 only. These proposed data elements, which are consistent with the way the CRDC collects instances of out-of-school suspensions that K-12 students received, are proposed as optional for the 2021–22 CRDC and required for the next CRDC.

OCR appreciates the commenters’ other various suggestions to expand and further disaggregate the referrals and arrests data collection. While these additional data elements and further disaggregation of the data may provide useful information, OCR believes that the proposed CRDC K-12 referrals and arrests data elements are sufficient to inform its civil rights enforcement obligations at this time.

OCR also appreciates the commenters’ recommendations for OCR to provide additional guidance, training, and technical assistance to CRDC participants on the collection and reporting of referrals and arrests data, and to consult with experts in the field. OCR has provided training and technical assistance to SEAs and LEAs since the initial collection of referrals and arrests data, and plans to continue providing them this type of support.

Additionally, OCR appreciates the commenters’ recommendations for the collection of data on the use of student threat assessments in schools, as they relate to law enforcement referrals and arrests. While OCR is concerned about the possible discriminatory use of threat assessments in schools, given the large number of new data elements OCR proposes to add to the 2021–22 and 2023–24 CRDCs, OCR has decided not to expand the data as recommended. Instead, OCR will rely on the threat assessment data collected by NCES’ School Survey on Crime and Safety (SSOCS). SSOCS collects data from schools to determine whether they have a threat assessment team to identify students who might be a potential risk for violent or harmful behavior. These data can help OCR gauge use of threat assessments in schools, and also help OCR decide whether additional threat assessment data should be collected in the future via the CRDC.

Changes: See proposed revised referrals to law enforcement and school-related arrests definitions in Attachment A-3, page 15 (Data Category: Discipline Method). Also, see proposed new Referrals or Arrests Instances Data Group 1047 in Attachment A-1, page 76.

Offenses

Public Comments

Thirty commenters wrote regarding the proposed data elements on offenses, with most commenters noting their support for the collection of offenses data.

One commenter recommended making the new proposed incidents of school shootings and incidents of school homicides data elements mandatory, instead of optional, for the 2021–22 CRDC. Two commenters objected to OCR’s proposed removal of two data elements involving whether a school shooting occurred and whether a school homicide occurred.

Some commenters proposed recommendations on revising the proposed definitions of certain types of offenses. Three commenters recommended revising and expanding the definitions of certain offenses like “rape” and “sexual assault” to align with the definitions found in the Clery Act. These commenters recommended these changes to ensure that the definitions emphasize lack of consent and capture accurately the broad range of sexual and gender-based offenses that can occur. One commenter recommended that OCR align the definitions to match definitions schools use when reporting data to their respective states. Another commenter urged OCR to expand the definitions of “rape” and “sexual assault” to better capture the unique experiences of LGBTQI+ students.

Commenters provided suggestions for expanding the collection of offenses data. Thirteen commenters suggested collecting data on the incident type and location, such as whether an offense occurred in the classroom, in the hallway, on the bus, on social media, or on the playground. Two other commenters suggested the collection of data on offenses occurring off-campus, particularly in instances of sexual or gender-based violence. Another six commenters recommended collecting more data on assaults on students and the use of firearms/less-lethal weapons on students by law enforcement and school security staff. One commenter suggested that OCR collect data specifically on dating violence and stalking. Three commenters recommended that OCR add data elements to the CRDC on student-on-student sexual offenses and their outcomes that are analogous to the staff-on-student sexual offenses and their outcomes data elements.

One commenter recommended removing the staff-on-student sexual offenses data elements. Three commenters argued that none of the offenses data should be collected by the CRDC. Two of these commenters believed that the offenses data could not be used to address civil rights issues, while the other commenter believed that the data could lead to the criminalization of students.

One commenter wrote neither in support nor opposition of this collection. This commenter noted that this data collection would not pose an additional reporting burden for districts in their state.

OCR’s Response

Discussion: OCR appreciates the commenters’ feedback regarding the CRDC offenses data collection proposal. OCR also appreciates the commenters’ suggestions on how to revise definitions for certain offenses, and how to expand the data collection.

Most of the school-based offenses definitions proposed for the CRDC were adopted or adapted from the School Survey on Crime and Safety (SSOCS) for the 2021–22 school year. SSOCS is a survey of a nationally representative sample of public schools in the U.S., sponsored by the National Center for Education Statistics (NCES). As indicated in the Attachment A-3 document, OCR originally proposed to revise the rape and sexual assault definitions as follows:

Rape – Rape refers to forced sexual ~~intercourse~~ penetration (vaginal, anal, or oral ~~penetration~~). This includes sodomy and penetration with a foreign object. ~~Both male and female students~~ All students, regardless of sex, sexual orientation, or gender identity, can be victims of rape. Rape is not defined as a physical attack or fight.
Sexual assault – Sexual assault is an incident that includes threatened rape, fondling, indecent liberties, or child molestation. ~~Both male and female students~~ All students, regardless, of sex, sexual orientation, or gender identity, can be victims of sexual assault. Classification of these incidents should take into consideration the age and developmentally appropriate behavior of the offender(s).

OCR has considered the commenters’ recommendations on how to further revise the CRDC definitions for “rape” and “sexual assault,” and has decided not to revise them as the commenters’ recommended at this time. However, in an effort to align the CRDC rape and sexual assault definitions with the definitions used for NCES’ SSOCS for the 2021–22 school year, OCR proposes to retain the original first sentence of the rape definition and continues to propose the other revisions for the rape definition and the sexual assault definition. The retained original first sentence for the rape definition reads, “Rape refers to forced sexual intercourse (vaginal, anal, or oral penetration).”

OCR proposed retiring two data elements asking whether a shooting or homicide occurred at a school and replacing it with two new data elements soliciting the number of shootings and homicides at a school. After further consideration, OCR will maintain the original data elements and supplement them with the new data elements.

OCR believes that OCR’s proposed data elements on offenses are sufficient to inform OCR’s civil rights enforcement obligations, and the proposed data elements on offenses, strike a fair balance between serving OCR’s mission and limiting the CRDC’s burden on LEAs. Therefore, OCR has decided not to collect additional offenses data at this time. OCR may consider the recommendations for expanding the collection of offenses data for future CRDCs.

Finally, OCR acknowledges the opinions of commenters who urge OCR to discontinue this collection. However, OCR will continue to collect the data as proposed, as it continues to be important to OCR’s civil rights enforcement.

Changes: Please see the revised rape definition found in Attachment A-3, pages 22, 26, and 28 (Data Category: Offense Type; Data Category: Offense Type (Students and School Staff)). Also, please see the now continuing homicide and shooting data elements found in Attachment A-2, pages 32 and 40 (Data Group 919: Deaths due to Homicide and Data Group 927: Firearm Use).

Offenses – Allegations Made Against School Staff

Public Comments

Eighteen commenters responded to OCR’s initial proposal to retire five data elements related to allegations made against a school staff member of certain sexual offenses.

Commenters overwhelmingly opposed removing these data elements, with 17 commenters urging OCR to continue to collect these data in the face of rising sexual assault on campus. Commenters provided reasons for why they opposed the removal of these data elements. Seven commenters noted that discontinuing this data collection could impact school safety, and particularly the safety of already underserved students. Four commenters stated that teachers could evade responsibility if these data are not collected and could continue to teach in other schools or districts. Five commenters noted that the removal of these data elements would allow for schools to be less transparent in their handling of incidents of sexual assault. One commenter also noted that their removal would allow for the number of allegations against staff to go unreported, as opposed to incidents. Four commenters suggested that OCR was motivated to remove the data elements in an attempt to appease teachers’ unions.

One commenter, in support of maintaining these data elements, had suggestions for improving and expanding them, including by disaggregating the data based on the alleged victim’s: race/ethnicity; sex; eligibility under IDEA and Section 504; eligibility for free or reduced price lunch; foster care status; and school placement.

One commenter did not express support or opposition to OCR’s proposal, and instead noted that sexual contact between teachers and students should be reported to the police.

OCR’s Response

Discussion: On November 19, 2021, OCR published in the Federal Register, a CRDC information collection request (ICR) that proposed the retirement of five data elements related to the outcomes of allegations of staff-on-student sexual offenses. Upon further reflection, OCR withdrew the ICR, and replaced it with an ICR that was published in the Federal Register on December 13, 2021 that proposed to maintain the collection of the five data elements.

OCR continues to propose maintaining the collection of the data elements related to allegations made against a school staff member of certain sexual offenses. OCR appreciates the commenters’ feedback supporting the retention of these data elements and agrees with the commenters that they should not be retired. OCR may consider the recommendations for revising and expanding these data elements for future civil rights data collections.

Changes: None.

Restraint and Seclusion

Chemical or Irritant Restraints

Public Comments

One hundred fifty-three commenters responded to OCR’s directed questions on the possibility of OCR collecting new student restraint data involving the use of chemicals or irritants in public schools, for future CRDCs (after the 2021–22 CRDC) (see Attachment A-5: Directed Questions document). Of these commenters, 150 wrote in support of OCR’s proposed future collection of data related to the use of chemical or irritant restraints by sworn law enforcement officers. In addition to supporting OCR’s proposed collection of chemical restraint and irritant restraint data, 123 commenters explicitly urged OCR to collect data on “the use of chemical restraint and irritant restraint by a sworn law enforcement officer and/or school staff assigned to/employed by a school.”

Some commenters proposed certain definitions for chemical or irritant restraints. Thirteen commenters suggested that the definition of chemical or irritant restraints include “chemical agents, fixed restraints, and psychotropic medications for the purposes of coercion, punishment or otherwise used to control student behavior instead of an appropriate intervention.” Sixteen commenters suggested the use of the definition of chemical restraint from the U.S. Congressional bill Keeping All Students Safe Act (KASSA), S. 1858, H.R. 3474 defined as:

a drug or medication used on a student to control behavior or restrict freedom of movement that is not prescribed by a licensed physician, or other qualified health professional acting under the scope of the professional’s authority under State law, for the standard treatment of a student’s medical or psychiatric condition and administered as prescribed by the licensed physician or other qualified health professional acting under the scope of the professional’s authority under State law.

Three commenters explicitly supported including “irritant restraint” in any future definition of “chemical restraint.” Another commenter expressed concern about the use of forced injections and other involuntary medications and urged OCR to adopt “chemical restraints in schools, including the involuntary use of medication outside of a prescribed use and for the purposes of sedating a student, and the use of pepper spray, tear gas, or other chemical or irritant restraints” as the definition of chemical or irritant restraint.

Commenters expressed thoughts on which type of incidents should be collected. Two commenters specifically noted that OCR should collect data on instances when “law enforcement officer(s) assigned to a school used chemicals to restrain students,” because the presence of law enforcement on campus escalates and increases instances of confrontation on campus, particularly against students of color.

Five commenters specifically stressed the importance of collecting data on the wide range of school personnel who may use chemical or irritant restraints, in addition to law enforcement or security officers as defined in KASSA. One commenter urged OCR to collect specific data on the types of chemical or irritant restraints used, including the use of pepper spray.

In response to OCR’s directed question on potential obstacles LEAs might face in collecting these data, one commenter noted there is a risk that some incidents may go unreported, and that all incidents of chemical or irritant restraint by any individual person, regardless of whether these incidents are proven or reported, should be counted. Two commenters urged OCR to thoroughly investigate and hold schools accountable for all instances of the use of chemical or irritant restraints by law enforcement on campus, highlighting the particular harm these restraints may have on students.

Many commenters made suggestions on how these data should be collected. Fourteen commenters suggested the inclusion of specific new data elements, including: (1) the number of non-IDEA students subjected to chemical restraint and/or irritants, disaggregated by race, sex, nonbinary status, disability (IDEA/504), and English learner (EL) status; and (2) the number of IDEA students subjected to chemical restraint and/or irritants, disaggregated by race, sex, nonbinary status, and EL status. Three other commenters recommended that OCR include separate data elements for “chemical restraint” and “irritant restraint,” with chemical restraint defined as the use of drugs and medication. One commenter expressed that data should be disaggregated by race, sex, grade, and IDEA/504 disability and should include unduplicated counts of students affected.

Another commenter expressed concern about whether the intent of OCR’s directed questions was to determine the behavior of law enforcement, rather than school staff, and suggested that OCR be more direct in asking specific questions about chemical or irritant restraints and law enforcement behavior.

Some commenters stressed the importance of these data for various reasons and for various groups. Six commenters noted that OCR should consider the unique circumstances of students with disabilities subjected to chemical or irritant restraint, including students with disabilities in nonpublic schools. Another commenter recommended the collection of data on the primary method of communication used by students subjected to restraint, including natural speech, symbolic or language-based augmentative and alternative communication, or a combination of these language strategies. Five commenters noted that OCR should collect data to capture the unique circumstances of students of color and students who identify as LGBTQI+ subjected to chemical or irritant restraints.

One commenter spoke in opposition to OCR’s proposed future collection of incident data related to the use of chemical or irritant restraints. Specifically, the commenter noted that these types of incidents are exceedingly rare and occur without consultation with school personnel. Therefore, the commenter believed that the collection of these data was not warranted.

Two commenters spoke neither in support of nor opposition to OCR’s proposed future collection of data related to the use of chemical or irritant restraints because these types of restraints are not utilized in their districts.

OCR’s Response

Discussion: OCR appreciates the commenters’ responses to its directed questions on the collection of data on the use of chemical or irritant restraints for future CRDCs. OCR understands that the vast majority of commenters expressed support for the future collection of data on the use of chemical or irritant restraints by sworn law enforcement officers and school staff.

OCR also appreciates the commenters’ suggestions on the proposed definitions of chemical or irritant restraints, the types of incidents that should be included in future collections, and how the data should be collected. OCR will consider the suggestions if it decides to propose chemical or irritant restraints data elements for future collections.

OCR acknowledges the commenter who expressed that data on the use of chemical or irritant restraints is unnecessary due to the infrequent and unique nature of its use in schools. However, due to the overwhelmingly positive response to OCR’s directed questions on whether to collect these data, OCR will consider including data elements on the use of chemical or irritant restraints for future collections.

Changes: None.

Restraints and Seclusion

Public Comments

One hundred sixty-one commenters responded regarding the collection of data on mechanical restraint, physical restraint, and seclusion for the 2021–22 CRDC.

Fourteen commenters expressed thoughts on mechanical restraint. Eleven commenters supported OCR’s proposed revised definition of mechanical restraint. Two commenters urged OCR to adopt the definition of mechanical restraint found in draft legislation known as the Keeping All Students Safe Act (KASSA). Mechanical restraint is defined in KASSA as “the use of devices as a means of restricting a student’s freedom of movement.” One commenter suggested that the definition of mechanical restraint clarify that restraint includes restraint by sworn or unsworn law enforcement. Another commenter noted that handcuffs are used exclusively by law enforcement and that law enforcement should have the right to use handcuffs on students when the law enforcement officer feels that it is needed. One commenter urged OCR to add tasers and batons to the proposed definition of mechanical restraint. Two commenters stated that some states have definitions of restraint that differ from federal definitions or do not legally allow for the use of mechanical restraints in schools.

One commenter recommended that OCR collect data on all instances of mechanical restraint by handcuffing, including by sworn and unsworn law enforcement and other school staff. Another commenter urged OCR to expand its collection of instances of mechanical restraint by collecting data that reflects mechanical restraint when initiated by: school-based law enforcement staff; and other school staff.

Twenty-four commenters wrote regarding physical restraint. Five commenters explicitly wrote in support of OCR’s proposed revised definition of physical restraint. Other commenters provided suggestions on revising the proposed definition.

One commenter supported amending the definition of physical restraint to include the phrase “imposed by school staff member or other individual” in the first sentence of the proposed definition. Another commenter appreciated that OCR distinguished “physical escort” from physical restraint and urged OCR to provide examples of “physical escort” to highlight that distinction. One commenter expressed support for OCR’s proposed added statement “Physical escorting that involves methods utilized to maintain control of a student should be considered a physical restraint” to the definition. In contrast, two commenters urged OCR to not include the statement in the definition because, according to the commenters, the statement adds confusion to the earlier statement in the definition that defines “physical escort.” One commenter noted that the proposed definition of physical restraint was too “tight” and should focus more generally on restricting movement. Another commenter noted that in OCR’s proposed revised definition, “physical escort” is described as a “temporary” touching or holding of the student but there is no time-based indication for physical restraint. Given that physical restraint is never a permanent action, it is unclear to the commenter how a [temporary] restriction that “immobilizes or restricts the ability of a student to move freely” is different from a “temporary touching or holding of a student” for transportation purposes. Fifteen commenters supported a definition of physical restraint that includes the role of police. One commenter urged OCR to adopt the KASSA definition of physical restraint, which reads as “a personal restriction that immobilizes or reduces the ability of an individual to move the individual’s arms, legs, torso, or head freely, except that such term does not include a physical escort, mechanical restraint, or chemical restraint.”

Twenty-nine commenters discussed seclusion. One of these commenters suggested maintaining the current definition of seclusion, while five of the commenters supported OCR’s proposed revised definition of seclusion. One commenter appreciated OCR’s removal of the term “time-out” from the definition of seclusion and for clarifying that seclusion should not include the use of a separate area of a classroom. Three commenters explicitly wrote in support of the inclusion of the phrase “students who believe or are told by a school staff member that they are not able to leave a room or area, should be considered secluded.” Three other commenters recommended that OCR not include the following statement in the definition: “Seclusion does not include placing a student in a separate location within a classroom with others or with an instructor where that student continues to receive instruction, is free to leave the location, and believes they can leave the location.” The commenters considered the statement too broad because students “generally do not believe they have the right to just leave a classroom, or any location they are put in.” The commenters urged OCR to remove the student perception component from the proposed definition. Two additional commenters recommended revising the definition of seclusion to include “pseudoseclusion,” or “confinement in a space from which [students] cannot leave even if they are not alone” and removing the requirement that “the [student] be physically prevented from leaving a space.” One commenter urged OCR to adopt KASSA’s definition of seclusion, which reads, “the involuntary confinement of a student alone in a room or area from which the student is physically prevented from leaving, except that such term does not include a time out.”

Seventeen commenters recommended an expanded definition of seclusion that includes the role of police. Fifteen of these commenters noted the police’s ability to isolate or confine students in police cars, empty classrooms, or other locations students cannot leave, as a reason. One commenter suggested that OCR expand the proposed definition of seclusion to include “detention by a law enforcement officer or security in a patrol car or elsewhere,” while two other commenters suggested the inclusion of the phrase “detention by law enforcement or other school security where the student is not allowed to leave, including detention in a patrol car.”

Some commenters raised how restraint and seclusion data are or should be collected. Two commenters appreciated that OCR disaggregated restraint and seclusion data for non-IDEA students by sex, including nonbinary, race/ethnicity, disability (Section 504 only), and English learner (EL) status. Eleven commenters supported the continued collection of the number of instances of mechanical restraint, physical restraint, and seclusion, disaggregated by students without disabilities, students with disabilities-IDEA, and students with disabilities-Section 504 only, but urged OCR to also collect the data by sex, including nonbinary, and EL status.

A few commenters provided thoughts on the use of law enforcement concerning restraint and seclusion. Two commenters specifically urged OCR to collect data on instances where seclusion is imposed by sworn and unsworn law enforcement and other school staff. One commenter urged for separate data collections for instances of mechanical and physical restraint and seclusion when initiated by school-based law enforcement and instances of mechanical restraint initiated by other school staff.

One hundred twenty-nine commenters recommended that OCR include “additional data elements centered on restraint and seclusion that highlight instances where parent contact has not been confirmed (attempted but not confirmed or no meeting held).”

Several commenters suggested that OCR consider the unique circumstances of certain school populations and student groups. Five commenters noted that OCR should consider the unique circumstances of students with disabilities. One commenter highlighted the importance of collecting data when “students with disabilities who are also receiving or may be receiving restraint, seclusion, or other potentially harmful therapies are removed from regular classes based merely on classroom behaviors or natural behaviors.” Another commenter recommended the collection of data on the primary method of communication used by students subjected to restraint and seclusion, including natural speech, symbolic or language-based augmentative and alternative communication, or a combination of these language strategies. Four commenters noted the disproportionate use of restraint and seclusion against Black and Brown students, while four other commenters recommended that OCR collect data on the use of restraint and seclusion in nonpublic schools to capture data on students with disabilities in nonpublic schools. Two commenters suggested collecting restraint and seclusion data from the preschool setting. A different commenter urged OCR collect data on injuries sustained by students due to restraint and seclusion.

A few commenters provided suggestions on training and staff concerns. One commenter urged OCR to collect data on whether districts employ policies or funds to train staff on the use of restraint and seclusion. Another commenter recommended that OCR collect data on training and whether instances of restraint and seclusion were performed by trained personnel. An additional commenter urged OCR to collect data on instances where staff received injuries in instances where restraint and seclusion were used.

OCR’s Response

Discussion: OCR appreciates the commenters’ support for the continued collection of restraint and seclusion data by the CRDC. OCR also appreciates the commenters’ feedback on the proposed definitions of mechanical and physical restraint and seclusion, and their suggestions for amendments to the proposed definitions. OCR proposed the following revised definitions for mechanical restraint, physical restraint, and seclusion:

Mechanical restraint refers to the use of any device or equipment to restrict a student’s freedom of movement. The term includes the use of handcuffs or similar devices by sworn law enforcement or other school security to prevent a student from moving the student’s arms. The term does not include devices used by trained school personnel or a student that have been prescribed by an appropriate medical or related services professional and are used for the specific and approved purposes for which such devices were designed, such as:

Adaptive devices or mechanical supports used to achieve proper body position, balance, or alignment to allow greater freedom of mobility than would be possible without the use of such devices or mechanical supports;
Vehicle safety restraints when used as intended during the transport of a student in a moving vehicle;
Restraints for medical immobilization; or
Orthopedically prescribed devices that permit a student to participate in activities without risk of harm.

Physical restraint refers to a personal restriction, imposed by a school staff member or other individual, that immobilizes or reduces the ability of a student to move his or her torso, arms, legs, or head freely. The term physical restraint does not include a physical escort. Physical escort includes a temporary touching or holding of the hand, wrist, arm, shoulder, or back of a student for the purpose of inducing a student to walk to a safe location, where the contact does not continue after arriving at the safe location. Physical escorting that involves methods utilized to maintain control of a student should be considered a physical restraint.

Seclusion refers to the involuntary confinement of a student in a room or area, with or without adult supervision, from which the student is not permitted to leave. Students who believe or are told by a school staff member that they are not able to leave a room or area, should be considered secluded. The term does not include a behavior management technique that is part of an approved program, which involves the monitored separation of a student in an unlocked setting, from which the student is allowed to leave. Seclusion does not include placing a student in a separate location within a classroom with others or with an instructor where that student continues to receive instruction, is free to leave the location, and believes they can leave the location.

OCR appreciates the recommendations that OCR adopt the KASSA mechanical restraint, physical restraint, and seclusion definitions for the CRDC. OCR has compared the KASSA definitions to those for the CRDC. The definitions are similar, and OCR believes the proposed CRDC definitions are appropriate for data collection purposes.

For the mechanical restraint definition, OCR agrees with the recommendation to expand the definition to include unsworn law enforcement officers. Therefore, OCR has decided to remove the term, “sworn” and add the term, “officers” to the definition. In addition, to address the use of mechanical devices that prevent students from moving their legs (e.g., ankle shackles), OCR has decided to add the term, “legs” to the definition. The impacted sentence from the proposed definition now reads: “The term includes the use of handcuffs or similar devices by ~~sworn~~ law enforcement officers or other school security to prevent a student from moving the student’s arms or legs.” OCR continues to consider the recommendation to include the use of tasers and batons as a mechanical restraint and looks forward to receiving and reviewing any additional comments—including on whether the use of tasers and batons should be considered a physical restraint or a mechanical restraint— received during the 30-day public comment period, to help inform OCR’s decision.

OCR considers “physical restraint” and “physical escort” distinct terms. OCR defines “physical restraint” as a restriction that immobilizes or restricts the ability of a student to move freely, and “physical escort” as a temporary touching or holding of the hand, wrist, arm, shoulder, or back of a student for the purpose of transporting a student to a safe location. Given that both “physical restraint” and “physical escort” are temporary actions, OCR has decided to remove the term “temporary” from the definition. Also, to address the concern that the statement “Physical escorting that involves methods utilized to maintain control of a student should be considered a physical restraint” in the definition suggests that physical escorting is a form of physical restraint, OCR has revised the statement. The proposed sentence now reads, “~~Physical escorting~~ Encouraging, inducing or forcing a student to walk to a safe location in a way that involves methods utilized to maintain physical control of a student should be considered a physical restraint.” In response to a commenter’s recommendation, OCR will consider preparing a technical assistance document for the 2021–22 CRDC that includes examples of “physical restraint” and “physical escort” to help distinguish the terms.

Based on the commenters’ feedback that OCR received regarding OCR’s proposed revised seclusion definition, OCR has decided to amend the definition to clarify further what OCR does not consider “seclusion.” In particular, OCR proposes to revise the definition as follows: “…The term does not include: a classroom or school environment where, as a general rule, all students need permission to leave the room or area such as to use the restroom; a behavior management technique that is part of an approved program, which involves the monitored separation of a student in an unlocked setting, from which the student is allowed to leave; ~~Seclusion does not include~~ or placing a student in a separate location within a classroom with others or with an instructor, ~~where that~~ so long as the student ~~continues~~ has the same opportunity to receive and engage in instruction~~, is free to leave the location, and believes they can leave the location~~.”

OCR appreciates the commenters’ recommendations on the collection of new restraint and seclusion data elements for the CRDC, such as incidents involving law enforcement, incidents when parental contact was attempted, and incidents involving trained personnel, and on collecting data on the use of restraint and seclusion against students with disabilities, students of color, and preschool students. OCR understands the commenters’ desire for OCR to expand its collection of restraint and seclusion data. However, OCR believes that the existing CRDC K-12 restraint and seclusion data elements are sufficient to inform its civil rights enforcement obligations. For these reasons, OCR has decided not to collect the additional data requested at this time.

Changes: See proposed revised mechanical restraint, physical restraint, and seclusion definitions found in OMB Supporting Statement, Part A and Attachment A-3, page 5-6 (Data Category: Action (Restraint or Seclusion)).

School Staff

Teachers

Public Comments  

One hundred forty-three commenters provided feedback on OCR’s data collection proposal regarding teachers. OCR is proposing to restore the following data elements: number of full-time equivalency (FTE) first-year teachers; number of FTE second-year teachers; number of FTE teachers absent more than 10 school days; number of teachers employed at the school during the 2021–22 regular school year; and number of teachers employed at the school during both the 2020–21 regular school year and the 2021–22 regular school year. One hundred twenty-eight commenters supported restoring all these data elements. Of these commenters, 117 urged OCR to make all of them mandatory, instead of optional, for the 2021–22 CRDC. In addition, five other commenters specifically noted the importance of counting the number of first- and second-year teachers, while seven commenters specifically mentioned their support for the collection of data on chronically absent teachers. Five commenters expressed their specific support for the restoration of the data element on the number of teachers employed at a school both during the current school year and the previous school year, citing the importance of teacher retention for student outcomes.

Some commenters provided suggestions on how teacher data should be disaggregated, citing that disaggregation would provide more valuable information on student experiences and outcomes. For the number of teachers employed at the school during the 2021–22 regular school year data element, 15 commenters supported OCR’s proposal to begin to collect disaggregated data by race/ethnicity and sex. One of the commenters suggested that OCR collect race data by ethnic group (e.g., Pacific Islander, Middle Eastern, South Asian, East Asian, and Southeast Asian, etc.). In addition, seven of the commenters suggested that sex be expanded to include a nonbinary gender category.

Two commenters expressed concerns that collecting data on the number of teachers absent more than ten days would provide inaccurate information on teacher attendance, given the COVID-19 pandemic. One of the commenters recommended that the data not be collected until the 2022–23 school year.

One hundred twenty-two commenters supported OCR’s proposed new collection of FTE counts of teachers certified to teach in mathematics, science, special education, and English as a second language. One commenter noted that teachers should be counted based on the specific subjects they are certified to teach, like Biology or Chemistry as opposed to general science. Two other commenters did not support OCR’s proposal to replace the collection of the number of certain classes (Algebra I; Geometry; Algebra II; advanced mathematics; Calculus; Computer Science; Biology; Chemistry; Physics) taught by certified teachers, with the new collection of FTE counts of teachers certified to teach in specific areas. These commenters urged OCR to retain the classes taught by certified teachers data elements and add the new teachers certified in specific areas data element to the CRDC. Two commenters recommended that OCR collect race/ethnicity data for the new certified teachers data element. Another commenter suggested that OCR collect data on teacher race and ethnicity in a nuanced fashion, noting the importance of capturing the complexities of racial and ethnic identities.

Some commenters provided suggestions on collecting data for teachers based on certain areas of expertise. Two commenters suggested that OCR collect data on special education teachers and any specific endorsements they might have, while one commenter recommended the collection of comprehensive data on early childhood education teachers. Two other commenters suggested collecting data on the languages teachers use in school and the number of bilingual programs in the school. One commenter noted the importance of collecting data on the number of teachers qualified to offer technology-powered opportunities and the impact of teacher training on digital equity.

One commenter noted the difficulties that may arise in their state regarding certain data collections, including the count of first- and second-year teachers, teacher certification, and teacher absenteeism.

OCR’s Response

Discussion: OCR appreciates the overwhelming support from commenters on the proposed restoration of the teacher data elements that OCR previously retired from the CRDC, the proposed disaggregation of the number of teachers employed at the school during the 2021–22 regular school year data element, by race/ethnicity and sex, and the proposed addition of the new teachers certified in specific areas data element. OCR also appreciates the commenters’ recommendations to collect more data regarding teachers, and understands that collecting such data might provide useful information about teacher experience, diversity, retention, and certification. OCR must balance the benefit of adding useful data and their reporting burden on LEAs. OCR believes that the proposed teacher data elements are sufficient to meet OCR’s civil rights law enforcement obligations and has decided not to add more data elements at this time.

OCR acknowledges the commenters’ suggestions to make the restored data elements mandatory for this collection. However, to give LEAs ample time to prepare for mandatory reporting of the data, OCR has decided to make these data elements optional for the 2021–21 CRDC and required for the 2023–24 CRDC.

OCR acknowledges the commenters’ concern with the increased reporting burden, especially during the COVID-19 pandemic. OCR proposes to make the reintroduction of these data elements optional for the 2021–21 CRDC, to lessen the reporting burden on reporting institutions for this collection.

Changes: None.

School Staff

Public Comments

Six commenters supported the collection of data on school support staff and provided further suggestions on how this collection can be improved. One commenter suggested that OCR collect data on instructional assistants, and that these and all other data on school staff be disaggregated by race and sex. Two commenters noted the particular importance of collecting data on staff who support student mental health. Another commenter suggested expanding the collection of the number of school counselors, by collecting data on whether a certain number of school counselors are assigned to a specific grade level within a school. One commenter requested that OCR differentiate between psychologists and school psychologists and that OCR add an explicit data category for school psychologists. Two commenters suggested collecting data on school principals and assistant principals, disaggregated by race, ethnicity, and sex, and noted the importance of representative leadership and its effect on student outcomes.

OCR’s Response

Discussion: OCR acknowledges that collecting additional data on school support staff would provide useful information. However, OCR must balance the usefulness of the data with the reporting burden. For the 2021–22 CRDC, OCR proposes to continue to collect full-time equivalency count data on a wide range of school support staff, including school counselors, psychologists, social workers, and nurses. Therefore, OCR has decided to not collect the additional data on school staff proposed by the commenters at this time, but may consider these suggestions for future collections.

Changes: None.

Security Staff

Public Comments

Twenty-three commenters wrote regarding the collection of data on school security staff, and they unanimously supported the collection of these data. The data include the number of full-time equivalency (FTE) security guards, and the number of FTE sworn law enforcement officers. Sixteen commenters requested that OCR provide guidance on the collection of these data to ensure that it is recorded correctly.

One commenter suggested providing special instructions to clarify that security staff include “Any individual who is employed by, contracted to work in, or assigned to work with a local educational agency, system of vocational education, or other school system; in a program that serves children who receive federal funding; or in an elementary school or secondary school that is not a public school that enrolls a student who receives special education and related services under IDEA.” This same commenter suggested that these special instructions clarify that all security staff must have the full amount of their working hours in the LEA allocated across schools and reported to the CRDC in FTEs.

Most commenters provided suggestions for expanding the security staff data collection. Fifteen commenters suggested collecting various types of security staff employed in schools, including private security personnel, correctional officers, and law enforcement personnel. Six commenters recommended the collection of data on unsworn law enforcement officers, with one commenter noting that the term “sworn” has created confusion in certain states that have different reporting requirements for these data. Three commenters suggested collecting LEA-level data on security staff who work district-wide as opposed to one campus. Another commenter suggested collecting data on where security staff predominately work (e.g., stationed at one school, stationed at multiple schools, roaming the district, or stationed at a central office). This commenter also suggested the collection of data on where security staff come from (e.g., internal police department to the school district; local police department; local sheriff’s office; state police agency; private security).

OCR’s Response

Discussion: OCR appreciates the commenters’ suggestions for OCR to provide guidance to LEAs on the security staff collection, clarify security staff definitions, and expand the collection of data on security staff. OCR began to collect security guard and sworn law enforcement officer FTE data in the 2013–14 CRDC, and has provided LEAs instructions and technical assistance, which have been refined over the years based on the LEAs’ feedback. OCR anticipates continuing to provide this type of guidance to LEAs. Over the years, based on feedback received from LEAs, OCR believes that LEAs understand the security staff definitions and that all security staff must have the full amount of their working hours allocated across schools in the LEA and reported to the CRDC in FTEs.

To address the commenters’ recommendation to collect data on unsworn law enforcement officers and the commenter’s noted concern that the term “sworn” creates confusion in states that have different reporting requirements, OCR has decided to propose to expand its collection of the number of FTE sworn law enforcement officers to include unsworn law enforcement officers. The number of FTE law enforcement officers data element is proposed as required for the 2021–22 CRDC and the subsequent CRDC. OCR has also decided to amend the definition of “sworn law enforcement officer” to include an unsworn law enforcement officer. OCR’s proposed revisions to the original definition are presented below.

~~Sworn~~ law enforcement officer – A law enforcement officer includes a sworn or unsworn law enforcement officer. A sworn law enforcement officer is a person who is authorized to make arrests while acting within the scope of explicit legal authority. This officer is responsible for safety and crime prevention and may respond to calls for service and document incidents that occur within their jurisdiction. ~~A sworn law enforcement officer is a career law enforcement officer, with arrest authority.~~ ~~A sworn law enforcement~~ This officer may be a school resource officer, (who has specialized training and is assigned to work in collaboration with school organizations). An unsworn law enforcement officer typically does not have arrest authority, but otherwise holds limited law enforcement powers and responsibilities as part of their regular duties. This officer’s law enforcement powers and responsibilities may include investigative and enforcement activities. A ~~sworn~~ law enforcement officer may be employed by any entity (e.g., police department, school district or school).

OCR acknowledges that collecting data on the various types of security staff, where they work, their specific duties, and which agencies they are from may provide valuable information. However, because of the need to balance the utility of data with the reporting burden, OCR has decided not to collect these data at this time.

Changes: Please see the proposed law enforcement officer definition found in Attachment A-3, page 34 (Data Category: Security Staff Type).

Law Enforcement

Public Comments

Thirteen commenters provided feedback on the collection of data on law enforcement.

Commenters made suggestions for OCR to collect data on different forms of student interactions with law enforcement. Two commenters suggested collecting data on all incidents involving law enforcement or security, including the unduplicated student count, while three commenters suggested collecting data on assaults by school-based law enforcement. Four other commenters recommended the collection of disaggregated data on use of force instances involving law enforcement. One of these commenters also recommended the collection of data on use of electroshock weapons by law enforcement or other school personnel, and incidents of law enforcement involvement in discipline matters that do not result in arrest, citations, or other legal system involvement. Another commenter suggested collecting data on whether sworn law enforcement officers were involved in every recorded instance of discipline.

Some commenters also provided suggestions on collecting data on school resources and procedures related to law enforcement. One commenter suggested collecting data on whether LEAs have a complaint process for police, and the number of complaints against school police that were filed and resolved, disaggregated to include complaints of sexual harassment and assault. This commenter also suggested collecting data on the percentage of an LEA’s budget that is spent on policing and security. Three other commenters recommended the collection of data on funds spent on police/school resource officers vs. student support personnel.

OCR’s Response

Discussion: OCR acknowledges that the collection of additional data on law enforcement in schools may provide useful information. Because of the need to balance the utility of the data with the overall reporting burden, OCR has decided not to collect the commenters’ recommended data at this time.

Changes: None.

Security

Security and Surveillance

Public Comments

Eighteen commenters recommended that OCR collect data on the use of security and surveillance technologies in schools to better understand the impact on students’ privacy and civil rights. Four commenters expressed their support for this data collection because of concern about the use of security and surveillance of students and its disproportionate impact on historically underserved students. Three of these commenters noted that this topic is particularly important to study given the COVID-19 pandemic and schools’ increased reliance upon technology in digital distance learning. These commenters also noted that digital distance learning has heightened pre-existing concerns about student surveillance, such as privacy in the home and discipline and criminalization of students, specifically for students of color. These commenters additionally expressed specific concerns about facial recognition technologies being utilized by schools given their unreliability in identifying people of color. One commenter suggested that OCR add a data category on surveillance infrastructure, requiring schools to report the existence of metal detectors, video cameras, facial recognition technology, social media monitoring, ShotSpotter, and any other surveillance technological devices or software. This commenter noted that data about the prevalence of these structures would help civil rights advocates determine whether Black children are disproportionately surveilled and criminalized in their schools.

One commenter explained that student activity monitoring software permits schools unprecedented glimpses into students’ lives, including analyzing students’ browsing habits, scanning their messages and documents, and viewing or listening to activities in the home. Twelve commenters recommended that the data collection include computer or social media surveillance programs or applications that trigger school disciplinary actions or threat assessments. Another commenter urged OCR to collect student disaggregated data related to types and usage of electronic surveillance that result in discipline or referrals to law enforcement. A different commenter expressed concern about the use of predictive policing tools in school settings and noted that this occurs when schools or districts work with law enforcement officials to adopt tools that predict risk for future involvement with the criminal justice system based on overly broad and potentially discriminatory identifying characteristics, such as race, age, or poverty level.

OCR’s Response

Discussion: OCR appreciates the comments about emerging and evolving surveillance technologies being utilized by LEAs, and the recommendations that OCR collect data on the use of security and surveillance technologies in schools to understand their impact on students’ privacy and civil rights. While the data collection items proposed by the commenters may provide useful additional information, OCR must balance the usefulness of the data with the reporting burden. OCR has decided not to include new data on the use of security and surveillance technologies in the 2021–22 or the 2023–24 CRDC, which already includes a number of proposed new and reinstated data elements that LEAs would report.

Changes: None.

File Type	application/vnd.openxmlformats-officedocument.wordprocessingml.document
File Title	Attachment B
Author	Rosa Olmeda
File Modified	0000-00-00
File Created	2022-09-29