State Population
This data is from the U.S. Census Bureau American Community Survey (ACS) 1-Year Estimates Demographic and Housing Table. This data includes the count and percent of state’s population by age and race/ethnicity. The race and ethnicity subgroups are reported as race alone, not Hispanic.
Education Relief Funding
This data is from the office of Elementary and Secondary Education and the National Association of State Budget Officers. This shows the total amount states received from relief funds for education and what percent that amount is compared to the state’s 2020 elementary and secondary education expenditures. This includes funds from Governor’s Emergency Education Relief Fund (GEER), GEER II, Emergency Assistance to Non-Public Schools (EANS), Elementary and Secondary School Emergency Relief Fund (ESSER), and ESSER II. See Appendix G for a breakdown of these relief funds and education expenditures.
Young Adult Metrics
25-to-34-year-olds in school, in the military, in the workforce, or disengaged
This data is from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. This data includes the percent of 25-to-34-year-olds that are in school, in the military, in the workforce, or disengaged. These are defined as follows:
- Individuals were considered in school if they were enrolled in a public or private school or college.
- Individuals were considered in the military if they had not attended school in the prior three months and were in the armed forces, at work; or armed forces, with a job but not at work.
- Individuals were considered in the workforce if they had not attended school in the prior three months and were employed, at work; employed with a job but not at work; or unemployed.
- Individuals are counted as employed with a job but not at work if they have a job they will return to but were absent during the survey week because they were on vacation, ill, experiencing child care problems, on maternity or paternity leave, taking care of family or personal obligations, involved in a labor dispute or prevented from working by bad weather.
- Individuals were considered disengaged if they had not attended school in the prior three months, were not in the labor force, and were not in the military.
- Each group (military, school, workforce, disengaged) is mutually exclusive – if an individual is in one group, they are not in another.
- The survey respondents self-report whether they are in school, employed, or in the military in the last three months.
This metric was calculated with a ratio of the count of 25-to-34-year-olds in one group by state, subgroup, and year to the total number of 25-to-34-year-olds in that state, subgroup, and year.
For example:
(count of 25-to-34-year-old females in school (Wyoming, 2018)) /
(total count of 25-to-34-year-old females (Wyoming, 2018))
This data was collected using the Census public microdata explorer. Both the total and group counts used are the unweighted ACS 5-year estimates. Additionally, to ensure representative sample sizes, any states subgroup that had less than 100 total number of 25-to-34-year-olds was reported as not available for that year.
The race and ethnicity subgroups are reported as race alone, not Hispanic.
25-to-34-year-olds in the workforce earning above the median wage
This data is from the U.S. Census Bureau American Community Survey (ACS). The data includes the percent of 25-to-34-year-olds that are in the workforce and earning at or above the state median income.
Individuals were considered in the workforce if they had not attended school in the prior three months and were employed, at work; employed with a job but not at work; or unemployed.
The median income is defined as the nonfamily household median income, not restricted to any age, from the ACS Median Income in the Past 12 Months 1-Year Subject Table. The median income was identified for each state for each year. See appendix A for a complete list of the median incomes.
This metric was calculated with a ratio of the count of 25-to-34-year-olds in the workforce earning above a state’s median income by state, subgroup, and year to the total number 25-to-34-year-olds in that state, subgroup, and year.
For example:
(count of 25-to-34-year-old males in the workforce earning above Ohio’s 2018 median wage (Ohio, 2018) /
(total count of 25-to-34-year-old males (Ohio, 2018))
This data was collected using the Census public microdata explorer. Both the total and group counts used are the unweighted ACS 5-year estimates. Additionally, to ensure representative sample sizes, any states subgroup that had less than 100 total number of 25-to-34-year-olds was reported as not available for that year.
The race and ethnicity subgroups are reported as race alone, not Hispanic.
25-to-34-year-olds with a high school degree, some college, an associate’s degree, or a bachelor’s degree
This data is from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. This data includes the percent of 25-to34-year-olds that have a high school degree or higher, have attended some college with or without a degree, have an associate’s or higher degree, or have a bachelor’s or higher degree. High school includes individuals that have a high school degree equivalent, such as a GED or alternative credential. ACS respondents self report their highest level of education.
This metric was calculated with a ratio of the count of 34-year-olds at each attainment level by state, subgroup, and year to the total number of 34-year-olds in that state, subgroup, and year.
For example:
(count of 25-to-34-year-olds that are Hispanic with a Bachelor’s or higher degree (Arizona, 2018)) /
(total count 25-to-34-year-olds that are Hispanic (Arizona, 2018))
This data was collected using the Census public microdata explorer. Both the total and group counts used are the unweighted ACS 5-year estimates. Additionally, to ensure representative sample sizes, any states subgroup that had less than 100 total number of 25-34-year-olds was reported as not available for that year.
The race and ethnicity subgroups are reported as race alone, not Hispanic.
25 to 34-year-olds volunteer rates
This data is from the Corporation for National and Community Service. The data includes the volunteer rates for 25 to 34-year-olds by state from 2013 to 2015.
Subgroup data is not available by age at the state level.
25 to 34-year-olds voter turnout rates
This data is from the U.S. Census Bureau Current Population Survey (CPS) Voting and Registration Supplement. The data includes the voter turnout of eligible voters that are 25-to-34-years-olds in 2014, 2016, and 2018.
The Voting and Registration Supplement is collected biennially in the November Current Population Survey. The statistics presented are based on replies to survey inquiries about whether individuals were registered and/or voted in specific national elections. For the purpose of these estimates, election types are considered to be either Congressional (e.g., 2002, 2006, etc.) or Presidential (e.g., 2004, 2008, etc.).
Subgroup data is not available by age at the state level.
Post-Secondary Metrics
18 to 24-year-olds in school, in the military, in the workforce, or disengaged
This data is from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. This data includes the percent of 18-to-24-year-olds that are in school, in the military, in the workforce, or disengaged. These are defined as follows:
- Individuals were considered in school if they were enrolled in a public or private school or college.
- Individuals were considered in the military if they had not attended school in the prior three months and were in the armed forces, at work; or armed forces, with a job but not at work.
- Individuals were considered in the workforce if they had not attended school in the prior three months and were employed, at work; employed with a job but not at work; or unemployed.
- Individuals are counted as employed with a job but not at work if they have a job they will return to but were absent during the survey week because they were on vacation, ill, experiencing child care problems, on maternity or paternity leave, taking care of family or personal obligations, involved in a labor dispute or prevented from working by bad weather.
- Individuals were considered disengaged if they had not attended school in the prior three months, were not in the labor force, and were not in the military.
- Each group (military, school, workforce, disengaged) is mutually exclusive – if an individual is in one group, they are not in another.
- The survey respondents self-report whether they are in school, employed, or in the military in the last three months.
This metric was calculated with a ratio of the count of 18-to-24-year-olds in one group by state, subgroup, and year to the total number of 18-to-24-year-olds in that state, subgroup, and year.
For example:
(count of 18-to-24-year-old females in school (Wyoming, 2018)) /
(total count of 18-to-24-year-old females (Wyoming, 2018))
This data was collected using the Census public microdata explorer. Both the total and group counts used are the unweighted ACS 5-year estimates. Additionally, to ensure representative sample sizes, any states subgroup that had less than 100 total number of 18-to-24-year-olds was reported as not available for that year.
The race and ethnicity subgroups are reported as race alone, not Hispanic.
18-to-24-year-olds in the workforce earning above the median wage
This data is from the U.S. Census Bureau American Community Survey (ACS). The data includes the percent of 18-to-24-year-olds that are in the workforce and earning at or above the state’s median income.
Individuals were considered in the workforce if they had not attended school in the prior three months and were employed, at work; employed with a job but not at work; or unemployed.
The median income is defined as the nonfamily household median income, not restricted to any age, from the ACS Median Income in the Past 12 Months 1-Year Subject Table. The median income was identified for each state for each year. See appendix A for a complete list of the median incomes.
This metric was calculated with a ratio of the count of 18-to-24-year-olds in the workforce earning above a state’s median income by state, subgroup, and year to the total number 18-to-24-year-olds in that state, subgroup, and year.
For example:
(count of 18-to-24-year-old males in the workforce earning above Ohio’s 2018 median wage (Ohio, 2018) /
(total count of 18-to-24-year-old males (Ohio, 2018))
This data was collected using the Census public microdata explorer. Both the total and group counts used are the unweighted ACS 5-year estimates. Additionally, to ensure representative sample sizes, any states subgroup that had less than 100 total number of 18-to-24-year-olds was reported as not available for that year.
The race and ethnicity subgroups are reported as race alone, not Hispanic.
18-to-24-year-olds with a high school degree or equivalent, some college – no degree, an associate’s degree, or a bachelor’s degree
This data is from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. This data includes the percent of 18-to24-year-olds that have a high school degree or higher, have attended some college with or without a degree, have an associate’s or higher degree, or have a bachelor’s or higher degree. High school includes individuals that have a high school degree equivalent, such as a GED or alternative credential. ACS respondents self report their highest level of education.
This metric was calculated with a ratio of the count of 24-year-olds at each attainment level by state, subgroup, and year to the total number of 24-year-olds in that state, subgroup, and year.
For example:
(count of 18-to-24-year-olds that are Hispanic with a Bachelor’s or higher degree (Arizona, 2018)) /
(total count 18-to-24-year-olds that are Hispanic (Arizona, 2018)).
This data was collected using the Census public microdata explorer. Both the total and group counts used are the unweighted ACS 5-year estimates. Additionally, to ensure representative sample sizes, any states subgroup that had less than 100 total number of 18-to-24-year-olds was reported as not available for that year.
The race and ethnicity subgroups are reported as race alone, not Hispanic.
16 to 24-year-olds volunteer rates
This data is from the Corporation for National and Community Service. The data includes the volunteer rates for 16 to 24-year-olds by state from 2013 to 2015.
Subgroup data is not available by age at the state level.
18 to 24-year-olds voter turnout rates
This data is from the U.S. Census Bureau Current Population Survey (CPS) Voting and Registration Supplement. The data includes the voter turnout of eligible voters that are 18-to-24-years-olds in 2014, 2016, and 2018.
The Voting and Registration Supplement is collected biennially in the November Current Population Survey. The statistics presented are based on replies to survey inquiries about whether individuals were registered and/or voted in specific national elections. For the purpose of these estimates, election types are considered to be either Congressional (e.g., 2002, 2006, etc.) or Presidential (e.g., 2004, 2008, etc.).
Subgroup data is not available by age at the state level.
Secondary Metrics
ACT benchmarks in English, Reading, and Math
This data is from ACT US High School Graduating Class Data. The data includes the percent of students meeting ACT English, Reading, and Math benchmarks.
Benchmarks rates from different states may not be comparable due to differences in testing populations. For example, a state testing 100% of its graduating class would be expected to have a lower average Composite score and benchmark rate than a state where only 50% of students (presumably those more likely to be going to college) have taken the ACT. In addition, states’ Composite score and benchmark rate may change from year to year as states begin or end comprehensive testing, and so many not be comparable between years. See appendix B for ACT participation rates.
To be consistent across all data metrics included in this stool, socioeconomic status (SES) eligibility is reported as low SES. ACT defines low-income status as income at or below $36,000 per year.
All subgroup data is not available for every state. Subgroups that are not reported appear as Not Available.
High school graduation rate
This data is from the National Center for Educational Statistics (NCES). The data includes the
4-year ACGR, which is the number of students who graduate in 4 years with a regular high school diploma divided by the number of students who form the adjusted cohort for the graduating class. From the beginning of 9th grade (or the earliest high school grade), students who are entering that grade for the first time form a cohort that is “adjusted” by adding any students who subsequently transfer into the cohort and subtracting any students who subsequently transfer out, emigrate to another country, or die.
As an example, the ACGR formula for 2017-18 was calculated like this:
(number of cohort members who earned a regular high school diploma by the end of the 2017-18 school year) /
(number of first time 9th graders in fall 2014 [starting cohort] plus students who transferred in, minus students who transferred out, emigrated, or died during school years 2014-15, 2015-16, 2016-17, 2017-18)
Graduation rates from different states may not be comparable due to differences in state graduation requirements. In addition, states’ graduation requirements may change from year to year, and so many not be comparable between years.
ACGR metric values are listed under the school year’s spring year. For example, the ACGR for 2017-2018 is shown under 2018, the ACGR for 2016-2017 is shown under 2017, etc.
Data for Asian, Hawaiian Native/Pacific Islander, and Two or more races students were published by NCES for the third time in the school year 2017–18. Before the 2015–16 school year, Asian/Pacific Islander was reported as one category. To be consistent across all years included in this tool, the Asian/Pacific Islander was reported as one category under the Asian subgroup for all years. Therefore the Hawaiian/Pacific Islander subgroup is reported as Not Available for all years and states. Additionally, not all states report all subgroup data. Subgroups that are not reported by a state appear as Not Available.
NCES reports estimate values of ≥ (greater than or equal to) to protect the confidentiality of individual student data. To be consistent across all data metrics included in this tool these values were reported as Not Available.
To be consistent across all data metrics included in this tool, socioeconomic status (SES) is reported as low SES. NCES uses eligibility for the Department of Agriculture’s National School Lunch Program (NSLP) as a measure of socioeconomic status.
AP exams taken, score of 3 or better
This data is from The College Board. The data includes the percent of all AP exams taken receiving a score of 3 or better in the given year. Individual reports can be found by updating the state and year in the following link: https://secure-media.collegeboard.org/digitalServices/misc/ap/STATE-summary-YEAR.xlsx For example, Massachusetts 2017 data can be found here: https://secure-media.collegeboard.org/digitalServices/misc/ap/massachusetts-summary-2017.xlsx
Rates from different states may not be comparable due to differences in testing populations. For example, a state testing 100% of its graduating class would be expected to have a lower average score and rate than a state where only 50% of students (presumably those more likely to be going to college) have taken AP exams.
Subgroup data is not available for every state. Subgroups that are not reported appear as Not Available.
This data includes all AP exams taken in a year, not just exam taken by the graduation class. As a result, the data includes students from any grade in school (e.g., Sophomore, Junior, or Senior Year). We wanted to include the percent of high school graduates that scored a 3 or higher on at least one AP exam, but this data was not available for all states. Select states self report this information.
Idleness rate
This data is from the U.S. Census Bureau American Community Survey (ACS) Characteristics of Teenagers 15 to 19 Years Old subject table. The data includes the percent of 16-to-19-year-olds that are not enrolled in school and not in the labor force.
Data is from the ACS 1-Year estimates, except for states that were missing subgroup data for a given year. If a state was missing data between 2014 and 2018, all data for that state came from the ACS 5-Year estimate. The following states’ data is from the ACS 5-Year estimates.
- Alaska
- Delaware
- District of Columbia
- Hawaii
- Idaho
- Kentucky
- Maine
- Montana
- Nebraska
- New Hampshire
- New Mexico
- North Dakota
- Oregon
- Rhode Island
- Utah
- Vermont
- West Virginia
- Wyoming
Idleness rate data is only reported for the following subgroups: Black, Hispanic, and White. The remaining subgroups that are not reported were excluded from the idleness rate indicators page.
SAT benchmarks in ELA and Math
This data is from The College Board. The data includes the percent of students meeting Evidence-Based Reading and Writing (ERW) and Math benchmarks.
Benchmarks rates from different states may not be comparable due to differences in testing populations. For example, a state testing 100% of its graduating class would be expected to have a lower average Composite score and benchmark rate than a state where only 50% of students (presumably those more likely to be going to college) have taken the SAT. In addition, states’ Composite score and benchmark rate may change from year to year as states begin or end comprehensive testing, and so many not be comparable between years. See appendix C for SAT participation rates.
SAT metric values are listed under the school year’s spring year. For example, the data for test-takers in the class of 2018 is shown under 2018; the data for test-takers in the class of 2017 is shown under 2017, etc.
To be consistent across all data metrics included in this tool, socioeconomic status (SES) is reported as low SES, and English language learner is reported as ELL. The College Board reports socioeconomic status as fee waiver and English language learner as English not first language.
Subgroup data is not available for every state. Subgroups that are not reported appear as Not Available.
FAFSA Completion Rate
This data is calculated using public high school data files. This data includes the percentage of students that have completed the Free Application for Federal Student Aid (FAFSA) form to apply for financial aid for college. This metric was calculated through the following steps:
- Download public high school data files from National Center for Education Statistics (NCES) elementary/secondary information system.
- Include all schools that offer 12th grade.
- Calculate whether a school serves majority students of color (we defined a school as serving majority students of color if 40% or more of the students were not white).
- Classify if a school is Title I (based on the Title I eligibility variable in CCD. If a school had no data, assume not Title I)
- Download five most recent years of FAFSA completion as of August 31.
- For each year, match the CCD files and FAFSA files based on state, city, and school name.
- Drop all cases that do not meet the following criteria:
- Five or more FAFSA completions
- At least one enrollment
- At least one 12th grade enrollment
- Summarize individual school data by state and year; summarize state to US. This done for each subgroup category.
- Calculate percent completion based on summarized data. The rate were calculated as follows
- 2021 rate = ((August 2021-2022 completed applications) / (11th grade enrollment for 2019-20 year*(1+change in enrollment from grade 11 in 2019-20 to grade 12 in 2020-21))
- 2020 rate = (August 2020-2021 completed applications) / (12th grade enrollment for 2019-20 year)
- 2019 rate = (August 2019-2020 completed applications) / (12th grade enrollment for 2018-19 year)
- 2018 rate = (August 2018-2019 completed applications) / (12th grade enrollment for 2019-2019 year)
- 2017 rate = (August 2017-2018 completed applications) / (12th grade enrollment for 2016-2017 year)
- Additional data notes:
- The FAFSA completion data was pulled in November 2021, a different date may affect the 2021 rate
- The numerator includes the number of first-time completed applications (reported by high school). This includes all individuals up to 19 who will have graduated from high school by the beginning of the school year.
Low SES is defined as Title 1 eligible
School serving majority students of color is defined as schools where 40% or more of the students were not white. If a school did not meet that criteria, it was defined as serving majority students of color.
Elementary Metrics
Nation’s Report Card reading and math proficiency for 4th and 8th grade
This data is from the Nation’s Report Card NAEP Data Explorer. The data includes the percent of students with achievement levels at or above proficient in 4th and 8th-grade math and reading.
To be consistent across all data metrics included in this stool, socioeconomic status (SES) is reported as low SES. NAEP uses eligibility for the Department of Agriculture’s National School Lunch Program (NSLP) as a measure of socioeconomic status.
Some subgroup data appears as not available based on the NAEP participation rate criteria. NAEP results are reported for subpopulations only when sufficient numbers of students and adequate school representation are present. The minimum requirement is 62 students in a particular group from at least five primary sampling units (PSUs). However, the data for all students, regardless of whether their group was reported separately, were included in computing overall results.
State assessment reading and math proficiency for 4th and 8th grade
This data is from Ed Data Express. The data includes the percent of students at state-level mathematics and state-level reading/language arts proficiency rates for 4th and 8th grade.
Scores and proficiency rates from different states may not be comparable due to differences in state assessments and proficiency rate cutoff. In addition, states’ assessments and proficiency rate cutoffs may change from year to year, and so many not be comparable between years. See appendix D for state assessment notes regarding changes to assessments, cut scores, etc. The notes included in appendix D are from Ed Data Express and may not be inclusive of all changes to state assessments.
State assessment metric values are listed under the school year’s spring year. For example, the state assessment given in 2017-2018 is shown under 2018, the state assessment given in 2016-2017 is shown under 2017, etc.
To be consistent across all data metrics included in this stool, socioeconomic status (SES) is reported as low SES. Ed Data Express reports socioeconomic status as Economically Disadvantaged.
Subgroup data is not available for every state. Subgroups that are not reported appear as Not Available. Ed Data Express also reports estimate values of ≥ (greater than or equal to) to protect the confidentiality of individual student data. To be consistent across all data metrics included in this tool these values were reported as Not Available.
Early Childhood Metrics
Change in Public School Enrollment
This data is calculated using the NCES Common Core of Data (CCD) school enrollment files. This data shows the change in total school enrollment from one school year to the next for all grades PK-12 and students with no grade reported. DC, Nevada, and Vermont include a small percentage of adult education (not at the postsecondary level).
Changes in enrollment metric values are listed under the school year’s spring year. For example, the data for 2020-2021 is shown under 2021, for 2019-2020 is shown under 2020, etc.
Illinois did not report CCD data for fall 2020; therefore, Illinois data is unavailable in the reported 2021 data field, and Illinois is excluded from the 2021 U.S. total.
Kindergarten readiness assessment
This data is from a study examining states’ kindergarten entry assessment (KEA) policies between 2011 and 2018 by Georgenne G. Weisenfeld, Karin Garver & Katherine Hodges. Tables two and three detail which states implemented a KEA between the 2011 and 2019 school years. The study collected publicly available or self-reported data, however, KEA statuses change during the school year.
While most KEAs are given in the fall, we chose to list the metric values under the spring year to be consistent with the other data included in this tool. For example, the KEA given in 2018-2019 is shown under 2019, the KEA given in 2017-2018 is shown under 2018, etc.
The metric values include yes or no. A value of yes means the state implemented a KEA in that school year, and a value of no means they did not. See appendix E for notes on states KEA requirements.
Georgenne G. Weisenfeld, Karin Garver & Katherine Hodges (2020): Federal and State Efforts in the Implementation of Kindergarten Entry Assessments (2011-2018), Early Education and Development, DOI: 10.1080/10409289.2020.1720481
Bright Spots
To identify our Bright Spots, we first ranked all 50 states in each data bucket and then reviewed the top quartile of states, within and across buckets. We then further analyzed those that showed improvement across several data points, with a focus on understanding the policy behind improvements. Metric rates referenced in the bright spots are from the Education and Workforce Pipeline data set. See appendix F for equivalent population calculations.
State Longitudinal Data Systems (SLDS)
This evaluation is based upon a July 2020 review of publicly-available information and sources related to states’ longitudinal data systems. Evidence gathered from those sources, including passed legislation, state-approved budgets, materials from states’ LDS website, federal SLEDS grant information, Time to Act: Making Data Work for Students (Data Quality Campaign, 2016), and third party (e.g., ECS, SHEEO, NCES, DQC) reports, were used to rate each component. A complete list and link to sources are available in the SLDS downloadable data file.
While the evaluation indicates whether states have certain conditions in place to support a strong SLDS, it does not intend to imply that any state has a perfect SLDS system, as it does not assess the quality of implementation or state practices regarding those conditions. As such, any differences in practice and implementation among states that earn the same rating in this evaluation would not be reflected here.
Appendix A: Median Income by State for Nonfamily Households
| State | 2014 | 2015 | 2016 | 2017 | 2018 |
| Alabama | $ 24,240 | $ 25,214 | $ 25,741 | $ 26,647 | $ 26,208 |
| Alaska | $ 48,029 | $ 46,933 | $ 51,252 | $ 48,441 | $ 49,061 |
| Arizona | $ 31,889 | $ 33,452 | $ 34,776 | $ 36,607 | $ 38,032 |
| Arkansas | $ 24,142 | $ 24,282 | $ 25,339 | $ 25,188 | $ 26,682 |
| California | $ 40,842 | $ 42,068 | $ 44,115 | $ 46,599 | $ 48,563 |
| Colorado | $ 38,560 | $ 40,487 | $ 40,936 | $ 44,139 | $ 45,323 |
| Connecticut | $ 39,839 | $ 41,201 | $ 41,608 | $ 44,532 | $ 43,412 |
| Delaware | $ 36,973 | $ 37,810 | $ 37,052 | $ 37,458 | $ 37,581 |
| District of Columbia | $ 61,126 | $ 62,840 | $ 61,948 | $ 68,067 | $ 71,189 |
| Florida | $ 30,563 | $ 31,445 | $ 32,389 | $ 33,962 | $ 34,769 |
| Georgia | $ 31,104 | $ 31,834 | $ 3,209 | $ 34,224 | $ 36,155 |
| Hawaii | $ 41,669 | $ 42,331 | $ 42,111 | $ 41,972 | $ 43,432 |
| Idaho | $ 26,708 | $ 27,252 | $ 29,627 | $ 30,706 | $ 32,123 |
| Illinois | $ 34,681 | $ 35,818 | $ 35,953 | $ 38,105 | $ 38,274 |
| Indiana | $ 29,469 | $ 30,326 | $ 30,752 | $ 31,574 | $ 32,682 |
| Iowa | $ 30,280 | $ 31,029 | $ 31,576 | $ 34,335 | $ 35,085 |
| Kansas | $ 30,376 | $ 31,273 | $ 31,227 | $ 32,327 | $ 32,386 |
| Kentucky | $ 24,612 | $ 26,768 | $ 27,220 | $ 27,249 | $ 29,703 |
| Louisiana | $ 26,239 | $ 26,111 | $ 26,826 | $ 26,106 | $ 27,411 |
| Maine | $ 28,732 | $ 28,663 | $ 31,024 | $ 31,688 | $ 32,671 |
| Maryland | $ 46,684 | $ 46,963 | $ 47,868 | $ 50,457 | $ 50,776 |
| Massachusetts | $ 40,329 | $ 41,510 | $ 42,343 | $ 43,824 | $ 45,392 |
| Michigan | $ 29,855 | $ 30,716 | $ 31,305 | $ 32,401 | $ 33,270 |
| Minnesota | $ 36,076 | $ 36,721 | $ 37,804 | $ 40,222 | $ 40,642 |
| Mississippi | $ 22,407 | $ 22,494 | $ 22,552 | $ 23,654 | $ 24,987 |
| Missouri | $ 28,375 | $ 30,092 | $ 31,409 | $ 31,917 | $ 32,471 |
| Montana | $ 27,970 | $ 28,714 | $ 30,181 | $ 31,186 | $ 32,388 |
| Nebraska | $ 30,980 | $ 31,940 | $ 31,765 | $ 35,607 | $ 34,755 |
| Nevada | $ 33,861 | $ 34,734 | $ 35,412 | $ 38,579 | $ 38,643 |
| New Hampshire | $ 37,522 | $ 40,044 | $ 38,603 | $ 41,469 | $ 40,095 |
| New Jersey | $ 40,828 | $ 40,142 | $ 41,163 | $ 44,186 | $ 45,866 |
| New Mexico | $ 27,160 | $ 26,838 | $ 28,883 | $ 29,887 | $ 29,476 |
| New York | $ 37,063 | $ 38,111 | $ 39,313 | $ 40,350 | $ 41,092 |
| North Carolina | $ 28,820 | $ 29,387 | $ 30,977 | $ 31,627 | $ 33,347 |
| North Dakota | $ 33,528 | $ 35,427 | $ 37,158 | $ 35,233 | $ 39,289 |
| Ohio | $ 28,786 | $ 30,647 | $ 31,164 | $ 32,007 | $ 33,107 |
| Oklahoma | $ 27,680 | $ 28,036 | $ 28,564 | $ 28,870 | $ 31,278 |
| Oregon | $ 31,361 | $ 33,646 | $ 35,305 | $ 36,665 | $ 39,377 |
| Pennsylvania | $ 30,685 | $ 31,721 | $ 32,488 | $ 32,044 | $ 33,975 |
| Rhode Island | $ 31,674 | $ 34,566 | $ 35,174 | $ 34,234 | $ 38,201 |
| South Carolina | $ 26,822 | $ 27,811 | $ 29,193 | $ 29,644 | $ 30,962 |
| South Dakota | $ 30,059 | $ 30,775 | $ 32,296 | $ 32,347 | $ 33,808 |
| Tennessee | $ 26,400 | $ 27,858 | $ 29,670 | $ 30,490 | $ 31,481 |
| Texas | $ 33,210 | $ 35,525 | $ 36,060 | $ 36,529 | $ 37,848 |
| Utah | $ 33,380 | $ 36,781 | $ 37,404 | $ 38,344 | $ 41,265 |
| Vermont | $ 32,301 | $ 33,787 | $ 32,445 | $ 34,754 | $ 36,364 |
| Virginia | $ 40,107 | $ 40,730 | $ 41,568 | $ 43,210 | $ 43,252 |
| Washington | $ 38,127 | $ 40,194 | $ 41,513 | $ 44,213 | $ 46,792 |
| West Virginia | $ 23,272 | $ 24,425 | $ 24,364 | $ 24,084 | $ 25,447 |
| Wisconsin | $ 31,547 | $ 32,786 | $ 34,008 | $ 35,115 | $ 35,999 |
| Wyoming | $ 33,690 | $ 35,441 | $ 32,285 | $ 33,472 | $ 35,631 |
Appendix B: ACT Participation Rates
| State | 2015 | 2016 | 2017 | 2018 | 2019 |
| Alabama | 100% | 100% | 100% | 100% | 100% |
| Alaska | 39% | 53% | 65% | 33% | 38% |
| Arizona | 56% | 58% | 62% | 66% | 73% |
| Arkansas | 93% | 96% | 100% | 100% | 100% |
| California | 30% | 33% | 31% | 27% | 23% |
| Colorado | 100% | 100% | 100% | 30% | 27% |
| Connecticut | 32% | 34% | 31% | 26% | 22% |
| Delaware | 21% | 21% | 18% | 17% | 13% |
| District of Columbia | 42% | 44% | 32% | 32% | 32% |
| Florida | 79% | 81% | 73% | 66% | 54% |
| Georgia | 58% | 60% | 55% | 53% | 49% |
| Hawaii | 93% | 94% | 90% | 89% | 80% |
| Idaho | 42% | 39% | 38% | 36% | 31% |
| Illinois | 100% | 100% | 93% | 43% | 35% |
| Indiana | 41% | 41% | 35% | 32% | 29% |
| Iowa | 67% | 68% | 67% | 68% | 66% |
| Kansas | 74% | 74% | 73% | 71% | 72% |
| Kentucky | 100% | 100% | 100% | 100% | 100% |
| Louisiana | 100% | 100% | 100% | 100% | 100% |
| Maine | 10% | 10% | 8% | 7% | 6% |
| Maryland | 25% | 27% | 28% | 31% | 28% |
| Massachusetts | 28% | 28% | 29% | 25% | 21% |
| Michigan | 100% | 100% | 29% | 22% | 19% |
| Minnesota | 78% | 100% | 100% | 99% | 95% |
| Mississippi | 100% | 100% | 100% | 100% | 100% |
| Missouri | 77% | 100% | 100% | 100% | 82% |
| Montana | 100% | 100% | 100% | 100% | 100% |
| Nebraska | 88% | 88% | 84% | 100% | 100% |
| Nevada | 40% | 100% | 100% | 100% | 100% |
| New Hampshire | 23% | 23% | 18% | 16% | 14% |
| New Jersey | 29% | 32% | 34% | 31% | 25% |
| New Mexico | 71% | 70% | 66% | 67% | 63% |
| New York | 28% | 29% | 31% | 27% | 22% |
| North Carolina | 100% | 100% | 100% | 100% | 100% |
| North Dakota | 100% | 100% | 98% | 98% | 96% |
| Ohio | 73% | 73% | 75% | 100% | 100% |
| Oklahoma | 80% | 82% | 100% | 100% | 100% |
| Oregon | 38% | 39% | 40% | 42% | 42% |
| Pennsylvania | 22% | 23% | 23% | 20% | 17% |
| Rhode Island | 19% | 20% | 21% | 15% | 12% |
| South Carolina | 62% | 100% | 100% | 100% | 78% |
| South Dakota | 76% | 76% | 80% | 77% | 75% |
| Tennessee | 100% | 100% | 100% | 100% | 100% |
| Texas | 41% | 46% | 45% | 41% | 39% |
| Utah | 100% | 100% | 100% | 100% | 100% |
| Vermont | 29% | 29% | 29% | 24% | 20% |
| Virginia | 30% | 31% | 29% | 24% | 21% |
| Washington | 25% | 25% | 29% | 24% | 24% |
| West Virginia | 66% | 67% | 69% | 65% | 49% |
| Wisconsin | 73% | 100% | 100% | 100% | 100% |
| Wyoming | 100% | 100% | 100% | 100% | 100% |
Appendix C: SAT Participation Rates
| State | 2017 | 2018 | 2019 |
| Alabama | 5% | 6% | 7% |
| Alaska | 38% | 43% | 41% |
| Arizona | 30% | 29% | 31% |
| Arkansas | 3% | 5% | 6% |
| California | 53% | 60% | 63% |
| Colorado | 11% | 100% | 100% |
| Connecticut | 100% | 100% | 100% |
| Delaware | 100% | 100% | 100% |
| District of Columbia | 90% | 92% | 94% |
| Florida | 83% | 97% | 100% |
| Georgia | 61% | 70% | 71% |
| Hawaii | 55% | 56% | 54% |
| Idaho | 93% | 100% | 100% |
| Illinois | 9% | 99% | 100% |
| Indiana | 63% | 67% | 66% |
| Iowa | 2% | 3% | 3% |
| Kansas | 4% | 4% | 4% |
| Kentucky | 4% | 4% | 4% |
| Louisiana | 4% | 4% | 5% |
| Maine | 95% | 99% | 99% |
| Maryland | 69% | 76% | 82% |
| Massachusetts | 76% | 80% | 81% |
| Michigan | 100% | 100% | 100% |
| Minnesota | 3% | 4% | 4% |
| Mississippi | 2% | 3% | 3% |
| Missouri | 3% | 4% | 4% |
| Montana | 10% | 10% | 9% |
| Nebraska | 3% | 3% | 3% |
| Nevada | 26% | 23% | 20% |
| New Hampshire | 96% | 96% | 95% |
| New Jersey | 70% | 82% | 82% |
| New Mexico | 11% | 16% | 18% |
| New York | 67% | 79% | 79% |
| North Carolina | 49% | 52% | 51% |
| North Dakota | 2% | 2% | 2% |
| Ohio | 12% | 18% | 19% |
| Oklahoma | 7% | 8% | 22% |
| Oregon | 43% | 48% | 51% |
| Pennsylvania | 65% | 70% | 70% |
| Rhode Island | 71% | 97% | 100% |
| South Carolina | 50% | 55% | 68% |
| South Dakota | 3% | 3% | 3% |
| Tennessee | 5% | 6% | 7% |
| Texas | 62% | 66% | 68% |
| Utah | 3% | 4% | 4% |
| Vermont | 60% | 64% | 66% |
| Virginia | 65% | 68% | 68% |
| Washington | 64% | 69% | 70% |
| West Virginia | 14% | 28% | 99% |
| Wisconsin | 3% | 3% | 3% |
| Wyoming | 3% | 3% | 3% |
Appendix D: State Assessment Notes
| State | Notes |
| Alabama | Between the 2012-13 and 2013-14 school year, Alabama made the following changes to regular assessment with and without accommodations: (1) Changed cut scores, (2) Changed proficiency standards, (3) Changed assessment items, (4) Used new assessment, and (5) Discontinued Alabama High School Graduation Exam. As a result, the 2013-14 results are not comparable to prior years. |
| Alaska | In the 2015-16 school year, Alaska canceled state assessments. As a result, there is no data for the 2015-16 school year. Between the 2013-14 and 2014-15 school year, Alaska made the following changes to regular and alternate assessments for all grades: (1) Changed cut scores, (2) Significantly changed assessment items, and (3) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. |
| Arizona | Between the 2013-14 and 2014-15 school year, Arizona made the following changes to regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, (5) Realigned assessment to new content standards, (6) Changed from End-of-Grade 10 to End-of-Grade 11 test for alternate assessment, and (7) Changed from End-of-Grade to End-of-Course testing for High School regular assessments. As a result, the 2014-15 results are not comparable to prior years. |
| Arkansas | Between the 2014-15 and 2015-16 school year, Arkansas made the following changes to regular assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, and (4) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. Between the 2013-14 and 2014-15 school year, Arkansas made the following changes to regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, and (4) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. |
| California | Between the 2013-14 and 2014-15 school year, California made the following changes to its regular assessments for all grades: (1) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, California was a census field test state. As a result, their data is not comparable to prior years. |
| Colorado | |
| Connecticut | Between the 2014-15 and 2015-16 school year, Connecticut made the following changes to its regular assessments for grades 3 through 8: (1) Realigned assessment to new content standards. As a result, the State’s SY2015-16 results are not comparable to prior years. Between the 2013-14 and 2014-15 school year, Connecticut made the following changes to regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Connecticut was a census field test state. As a result, their data is not comparable to prior years. |
| Delaware | Between the 2013-14 and 2014-15 school year, Delaware made the following changes to its regular assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. |
| District of Columbia | Between the 2013-14 and 2014-15 school year, District of Columbia made the following changes to its regular assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, and (4) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. |
| Florida | Between the 2013-14 and 2014-15 school year, Florida made the following changes to its regular assessments for grades 3 through 8: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. |
| Georgia | Between the 2013-14 and 2014-15 school year, Georgia made the following changes to its regular assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, and (3) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. |
| Hawaii | Between the 2013-14 and 2014-15 school year, Hawaii made the following changes to its regular assessment for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, and (4) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. |
| Idaho | Between the 2013-14 and 2014-15 school year, Idaho made the following changes to its regular assessments for grades 3 through 8: 1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, and (4) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Idaho was a census field test state. As a result, their data is not comparable to prior years. |
| Illinois | Between the 2013-14 and 2014-15 school year, Illinois made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. Between the 2012-13 and 2013-14 school year, Illinois made the following changes to its regular assessments with and without accommodations for grades 3 through 8: (1) Realigned to new content standards. Illinois made the following changes to its alternate assessment based on alternate achievement standards for all grades: (1) Changed cut scores, and (2) Realigned to new content standards. As a result, the 2013-14 results are not comparable to prior years. In the 2013-14 school year, Illinois was a sample field test state. As a result, their data may not be comparable to prior years. |
| Indiana | Between the 2013-14 and 2014-15 school year, Indiana made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. |
| Iowa | In the 2013-14 school year, Iowa was a sample field test state. As a result, their data may not be comparable to prior years. |
| Kansas | Between the 2013-14 and 2014-15 school year, Kansas made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Kansas did not submit data due to a cyber-attack. As a result, there is no data for the 2013-14 school year. |
| Kentucky | |
| Louisiana | |
| Maine | Maine administers its mathematics and reading/language arts assessments for grades 3 through 8 in the fall. Thus, the students are assessed on content from the prior academic year. Between the 2014-15 and 2015-16 school year, Maine made the following changes to its regular assessments for all grades: (1) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. Between the 2013-14 and 2014-15 school year, Maine made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. |
| Maryland | Between the 2013-14 and 2014-15 school year, Maryland made the following changes to its regular assessments (1) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Maryland was a sample field test state. As a result, their data may not be comparable to prior years. |
| Massachusetts | Between the 2013-14 and 2014-15 school year, Massachusetts made the following changes to its regular assessments for grades 3 through 8: (1) SEA reported that MCAS and the PARCC test were administered as a regular assessment with and without accommodations. Approximately half of the state took PARCC and half of the state took MCAS. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Massachusetts was a sample field test state. As a result, their data may not be comparable to prior years. |
| Michigan | Michigan administers its mathematics and reading/language arts assessments for grades 3 through 8 in the fall. Thus, the students are assessed on content from the prior academic year. |
| Minnesota | |
| Mississippi | Between the 2014-15 and 2015-16 school year, Mississippi made the following changes to its regular assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, and (4) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. Between the 2013-14 and 2014-15 school year, Mississippi made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, (5) Realigned assessment to new content standards, and (6) Used PARCC for reading/language arts assessments. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Mississippi was a sample field test state. As a result, their data may not be comparable to prior years. |
| Missouri | Between the 2014-15 and 2015-16 school year, Missouri made the following changes to its regular assessments for grades 3 through 8: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, and (4) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. |
| Montana | Between the 2014-15 and 2015-16 school year, Montana made the following changes to its regular assessments (1) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. In the 2014-15 school year, due to computer issues with Measured Progress, the testing vendor, the number of students who took an assessment and received a valid score does not equal the number of students who participated in an assessment. This is a discrepancy of approximately 16 percent (7,733 students). These counts are expected to equal. In the 2013-14 school year, Montana was a census field test state. As a result, their data is not comparable to prior years. |
| Nebraska | |
| Nevada | In the 2014-15 school year, Nevada’s data was suppressed at the state (SEA) and local (LEA) levels due to data quality issues. In the 2013-14 school year, Massachusetts was a sample field test state. As a result, their data may not be comparable to prior years. |
| New Hampshire | New Hampshire administers its mathematics and reading/language arts assessments for all grades in the fall. Thus, the students are assessed on content from the prior academic year. Between the 2013-14 and 2014-15 school year, New Hampshire made the following changes to its regular assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Used entirely new assessment, and (4) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. |
| New Jersey | Between the 2013-14 and 2014-15 school year, New Jersey made the following changes to its regular and alternate assessments for all grades: (1) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. |
| New Mexico | Between the 2013-14 and 2014-15 school year, New Mexico made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, (5) Realigned assessment to new content standards, (6) Used PARCC for English, and (7) Used legacy SBA assessment for Spanish speakers in all grades. As a result, the 2014-15 results are not comparable to prior years. |
| New York | |
| North Carolina | |
| North Dakota | North Dakota administers its mathematics and reading/language arts assessments for all grades in the fall. Thus, the students are assessed on content from the prior academic year. Between the 2013-14 and 2014-15 school year, North Dakota made the following changes to its regular and alternate assessments for all grades: (1) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. In the 2014-15 school year, the number of students at the state (SEA) level who participated in an assessment is greater than the School number of students who took an assessment and received a valid score for Grades 6, 7, and 8. The discrepancy is approximately 8-9%. These counts are expected to equal. |
| Ohio | Between the 2014-15 and 2015-16 school year Ohio made the following changes to its regular assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standard, and (3) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. Between the 2013-14 and 2014-15 school year, Ohio made the following changes to its regular assessments for grades 3 through 8: (1) Changed cut scores, (2) Significantly changed assessment items, (3) Used entirely new assessment, (4) Realigned assessment to new content standards, and (5) Used the Ohio Achievement test for Grade 3; all other tests moved to the Ohio State Test. As a result, the 2014-15 results are not comparable to prior years. |
| Oklahoma | |
| Oregon | Between the 2013-14 and 2014-15 school year Oregon made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Oregon was a sample field test state. As a result, their data may not be comparable to prior years. |
| Pennsylvania | Between the 2013-14 and 2014-15 school year, Pennsylvania made the following changes to its regular assessments for grades 3 through 8: (1) Changed cut scores, (2) Significantly changed assessment items, (3) Used entirely new assessment, and (4) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. |
| Rhode Island | Rhode Island administers its mathematics and reading/language arts assessments for all grades in the fall. Thus, the students are assessed on content from the prior academic year. Between the 2013-14 and 2014-15 school year, Rhode Island made the following changes to its regular and alternate assessments for all grades: (1) Used entirely new assessment and (2) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. |
| South Carolina | Between the 2014-15 and 2015-16 school year, South Carolina made the following changes to its regular assessments for grades 3 through 8: (1) Changed cut scores, (2) Changed proficiency standard, (3) Significantly changed assessment items, and (4) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. In the 2014-15 school year, South Carolina did not report data for the regular assessment with accommodations. |
| South Dakota | Between the 2013-14 and 2014-15 school year, South Dakota made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, and (5) Realigned assessment to new content standards. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, South Dakota was a census field test state. As a result, their data may not be comparable to prior years. |
| Tennessee | Between the 2014-15 and 2015-16 school year, Tennessee made the following changes to its regular assessments and alternate assessments for all grades: (1) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. In the 2015-16 school year, Tennessee did not report data at the state (SEA), local (LEA), or school levels for the following student groups in grades 3-8: migratory students, English learners, and economically disadvantaged. |
| Texas | Texas phased in performance standards, changing cut scores year-to-year. As a result, results are not comparable each year.* *According to Texas Education Agency |
| Utah | In the 2015-16 school year, Utah did not report data at the state (SEA), local (LEA), or school levels for migratory students. Between the 2012-13 and 2013-14 school year, Utah made the following changes to its regular assessments with and without accommodations for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Changed assessment items, (4) Used new assessment, and (5) Realigned to new content standards. As a result, the 2013-14 results are not comparable to prior years. |
| Vermont | Vermont administers its mathematics and reading/language arts assessments for all grades in the fall. Thus, the students are assessed on content from the prior academic year. In the 2015-16 school year, Vermont did not report data at the state (SEA), local (LEA), or school levels for the regular assessment with accommodations. Between the 2013-14 and 2014-15 school year, Vermont made the following changes to its regular and alternate assessments for all grades: (1) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Vermont was a sample field test state. As a result, their data may not be comparable to prior years. |
| Virginia | |
| Washington | Between the 2013-14 and 2014-15 school year, Washington made the following changes to its regular and alternate assessments for all grades: (1) Used entirely new assessment. As a result, the 2014-15 results are not comparable to prior years. In the 2013-14 school year, Washington was a sample field test state. As a result, their data may not be comparable to prior years. |
| West Virginia | Between the 2013-14 and 2014-15 school year, West Virginia made the following changes to its regular and alternate assessments for all grades: (1) Changed cut scores, (2) Changed proficiency standards, (3) Significantly changed assessment items, (4) Used entirely new assessment, (5) Realigned assessment to new content standards, (6) Transitioned to the Dynamic Learning Maps Assessment for English language arts/literacy for alternate assessments, and (7) The West Virginia General Summative Assessment includes the Smarter Balanced Assessment for English language arts/literacy for regular assessments. As a result, the 2014-15 results are not comparable to prior years. |
| Wisconsin | Wisconsin administers its mathematics and reading/language arts assessments for all grades in the fall. Thus, the students are assessed on content from the prior academic year. Between the 2014-15 and 2015-16 school year, Wisconsin made the following changes to its regular assessments for grades 3 through 8: (1) Used entirely new assessment. As a result, the 2015-16 results are not comparable to prior years. Between the 2013-14 and 2014-15 school year, Wisconsin made the following changes to its regular and alternate assessments for all grades: (1) Used entirely new assessment, (2) Joined Dynamic Learning Maps consortium for alternate assessments, (3) Joined the Smarter Balanced Consortium for regular assessments, and (4) Administered the ACT college entrance exam for Grade 11 for the first time for High School regular assessments. As a result, the 2014-15 results are not comparable to prior years. |
| Wyoming | Between the 2012-13 and 2013-14 school year, Wyoming made the following changes to its regular assessments with and without accommodations for all grades: (1) Changed cut scores, (2) Changed proficiency standards, and (3) Realigned to new content standards (grades 3-8 only). As a result, the 2013-14 results are not comparable to prior years. In the 2013-14 school year, Wyoming was a sample field test state. As a result, their data may not be comparable to prior years. |
Appendix E: Kindergarten Readiness Assessment Notes
The table below identifies the states and for what years that are tracking kindergarten readiness by using a kindergarten entry assessment (KEA)
| State | 2012 | 2014 | 2017 | 2018 | 2019 | Notes |
| Alabama | Yes | No | No | No | No | |
| Alaska | Yes | Yes | Yes | Yes | Yes | |
| Arizona | No | No | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) available for statewide use, but it is not required for all students |
| Arkansas | Yes | Yes | Yes | Yes | Yes | |
| California | No | No | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) available for statewide use, but it is not required for all students |
| Colorado | No | Yes | Yes | Yes | Yes | |
| Connecticut | Yes | Yes | Yes | Yes | Yes | |
| Delaware | No | Yes | Yes | Yes | Yes | |
| District of Columbia | No | Yes | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) required for all public-school students, but the KEA is voluntary for charter schools |
| Florida | Yes | Yes | Yes | Yes | Yes | |
| Georgia | Yes | Yes | Yes | Yes | Yes | |
| Hawaii | Yes | Yes | No | No | No | |
| Idaho | Yes | Yes | Yes | Yes | Yes | |
| Illinois | No | No | Yes | Yes | Yes | |
| Indiana | No | No | No | No | No | |
| Iowa | Yes | Yes | Yes | Yes | Yes | |
| Kansas | No | No | No | Yes | Yes | |
| Kentucky | Yes | Yes | Yes | Yes | Yes | |
| Louisiana | Yes | Yes | Yes | Yes | Yes | |
| Maine | Yes | Yes | No | No | No | |
| Maryland | Yes | Yes | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) available for statewide use, but it is not required for all students |
| Massachusetts | No | Yes | No | No | No | |
| Michigan | No | Yes | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) available for statewide use, but it is not required for all students |
| Minnesota | No | Yes | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) available for statewide use, but it is not required for all students |
| Mississippi | No | No | Yes | Yes | Yes | |
| Missouri | No | No | No | No | No | |
| Montana | No | No | No | No | No | |
| Nebraska | No | No | No | No | No | |
| Nevada | No | No | No | Yes | Yes | |
| New Hampshire | No | No | No | No | No | |
| New Jersey | No | Yes | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) available for statewide use, but it is not required for all students |
| New Mexico | Yes | Yes | Yes | Yes | Yes | |
| New York | Yes | Yes | Yes | Yes | Yes | |
| North Carolina | No | Yes | Yes | Yes | Yes | |
| North Dakota | No | No | No | No | No | |
| Ohio | Yes | Yes | Yes | Yes | Yes | |
| Oklahoma | No | No | Yes | No | No | |
| Oregon | No | Yes | Yes | Yes | Yes | |
| Pennsylvania | Yes | Yes | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) available for statewide use, but it is only required for Title 1 and priority schools |
| Rhode Island | No | No | No | No | No | |
| South Carolina | No | No | Yes | Yes | Yes | |
| South Dakota | No | No | No | No | No | |
| Tennessee | No | No | Yes | Yes | Yes | Has a Kindergarten Readiness Assessment (KEA) available for statewide use, but it is only required for schools with PDG funding |
| Texas | Yes | Yes | Yes | Yes | Yes | |
| Utah | No | No | No | Yes | Yes | |
| Vermont | Yes | Yes | Yes | Yes | Yes | |
| Virginia | No | No | No | Yes | Yes | |
| Washington | No | Yes | Yes | Yes | Yes | |
| West Virginia | Yes | Yes | Yes | No | No | |
| Wisconsin | No | Yes | Yes | No | No | |
| Wyoming | No | No | No | No | No |
Appendix F: Bright Spot Calculations
| State | Data Point | Percentage Point Gain | Population | Population Subgroup | Subgroup Weight | Equivalent Population | Population Source |
| California | Fourth-grade NAEP reading proficiency | 7.5% | 456,361 | Overall | 100% | 34,399 | California DOE |
| California | Fourth-grade NAEP Hispanic reading proficiency | 9.5% | 456,361 | Hispanic | 55% | 23,699 | California DOE |
| California | 18-to-24-year-olds with an associate degree or higher | 1.9% | 3,731,187 | Overall | 100% | 70,793 | ACS 1-Year Estimates |
| California | College participation rates | 4.0% | 418,205 | Overall | 100% | 16,728 | CA Department of Education |
| Colorado | Potential FAFSA completion rate | 26% | 55,842 | Overall | 100% | 14,519 | Colorado Department of Education Education Strategy Group |
| Florida | Fourth-grade NAEP math proficiency | 10.2% | 214,720 | Overall | 100% | 21,901 | Florida DOE 2018-19 School Membership by Grade |
| Florida | High school graduation rates | 10.2% | 221,507 | Overall | 100% | 22,594 | Florida DOE 2014-15 School Membership by Grade |
| Mississippi | Fourth-grade NAEP math proficiency | 13.7% | 37,266 | Overall | 100% | 5,124 | Mississippi 2018-19 DOE |
| Mississippi | Fourth-grade NAEP math proficiency | 11.6% | 37,266 | Black | 48% | 2,072 | Mississippi 2018-19 DOE |
| North Carolina | Potential college degree completion | 61% | 50,000 | Overall | 100% | 30,500 | Tennessee Reconnect |
| Oregon | High school graduation rates | 6.7% | 46,081 | Overall | 100% | 3,087 | Oregon DOE 2017-18 Four-year Cohort Rates for Students entering High School in 2014-15 |
| Oregon | 25-to-34-year-olds with a bachelor’s degree or higher | 3.9% | 596,863 | Overall | 100% | 23,373 | ACS 1-Year Estimates |
| Oregon | 25-to-34-year-olds with a bachelor’s degree or higher | 8.7% | 14,456 | Black | 100% | 1,252 | ACS 1-Year Estimates |
| Oregon | 25-to-34-year-olds with a bachelor’s degree or higher | 5.1% | 92,487 | Hispanic | 100% | 4,733 | ACS 1-Year Estimates |
| Tennessee | Potential college degree completion | NA | 13,977 – 4,872 | Overall | 100% | 9,105 | Tennessee Higher Education Commission |
| Virginia | 25-to-34-year-olds with a bachelor’s degree or higher | 3.6% | 1186126 | Overall | 100% | 42,302 | ACS 1-Year Estimates |
| Virginia | 25-to-34-year-olds with a bachelor’s degree or higher | 4.1% | 246515 | Black | 100% | 10,069 | ACS 1-Year Estimates |
Appendix G: Education Relief Funding
| State | GEER (Revised) | GEER II (Revised) | EANS (subset of GEER CRRSA award) | ESSER | ESSER II | Total K-12 education relief funding | Elementary and Secondary Education Exp Total 2019 | Total relief funding equivalent to K-12 education expenditures in 2019 |
| Alabama | $ 48,853,203 | $ 21,356,788 | $ 45,502,043 | $ 1,084,738 | $ 899,464,932 | $ 1,016,261,704 | $ 6,043,000,000 | 17% |
| Alaska | $ 6,503,700 | $ 2,824,465 | $ 5,367,703 | $ 192,040 | $ 159,719,422 | $ 174,607,330 | $ 1,664,900,000 | 10% |
| Arizona | $ 69,198,549 | $ 30,909,075 | $ 54,413,531 | $ 1,387,115 | $ 1,149,715,947 | $ 1,305,624,217 | $ 6,510,000,000 | 20% |
| Arkansas | $ 30,664,782 | $ 13,380,894 | $ 22,872,412 | $ 643,793 | $ 558,017,409 | $ 625,579,290 | $ 3,550,065,000 | 18% |
| California | $ 355,237,757 | $ 153,992,950 | $ 187,475,843 | $ 8,236,531 | $ 6,709,633,866 | $ 7,414,576,947 | $ 61,170,000,000 | 12% |
| Colorado | $ 44,006,017 | $ 19,434,248 | $ 28,433,931 | $ 604,969 | $ 519,324,311 | $ 611,803,476 | $ 5,879,000,000 | 10% |
| Connecticut | $ 27,882,366 | $ 12,450,941 | $ 15,831,765 | $ 555,340 | $ 492,426,458 | $ 549,146,870 | $ 4,053,000,000 | 14% |
| Delaware | $ 7,917,051 | $ 3,459,188 | $ 4,965,788 | $ 217,464 | $ 182,885,104 | $ 199,444,595 | $ 2,725,400,000 | 7% |
| District of Columbia | $ 5,807,869 | $ 2,416,005 | $ 5,312,618 | $ 210,032 | $ 172,013,174 | $ 185,759,698 | $ 2,819,000,000 | 7% |
| Florida | $ 173,591,320 | $ 75,812,848 | $ 212,978,041 | $ 3,851,239 | $ 3,133,878,723 | $ 3,600,112,171 | $ 15,072,000,000 | 24% |
| Georgia | $ 105,724,181 | $ 47,083,508 | $ 79,175,146 | $ 2,285,849 | $ 1,892,092,618 | $ 2,126,361,302 | $ 13,306,462,212 | 16% |
| Hawaii | $ 9,993,609 | $ 4,456,306 | $ 9,815,286 | $ 216,926 | $ 183,595,211 | $ 208,077,338 | $ 2,181,000,000 | 10% |
| Idaho | $ 15,676,743 | $ 6,858,052 | $ 19,581,608 | $ 239,273 | $ 195,890,413 | $ 238,246,089 | $ 2,154,000,000 | 11% |
| Illinois | $ 108,500,769 | $ 47,912,306 | $ 84,489,804 | $ 2,847,336 | $ 2,250,804,891 | $ 2,494,555,106 | $ 10,675,000,000 | 23% |
| Indiana | $ 61,592,746 | $ 26,534,087 | $ 81,656,000 | $ 1,072,364 | $ 888,183,537 | $ 1,059,038,734 | $ 9,598,000,000 | 11% |
| Iowa | $ 26,217,740 | $ 11,567,957 | $ 26,271,345 | $ 358,128 | $ 344,864,294 | $ 409,279,464 | $ 3,867,000,000 | 11% |
| Kansas | $ 26,274,863 | $ 11,678,709 | $ 26,667,139 | $ 422,645 | $ 369,829,794 | $ 434,873,150 | $ 5,074,800,000 | 9% |
| Kentucky | $ 43,711,994 | $ 19,100,248 | $ 40,817,799 | $ 965,934 | $ 928,274,720 | $ 1,032,870,695 | $ 5,987,660,000 | 17% |
| Louisiana | $ 50,278,669 | $ 22,990,617 | $ 55,566,230 | $ 1,434,901 | $ 1,160,119,378 | $ 1,290,389,795 | $ 5,336,943,173 | 24% |
| Maine | $ 9,273,788 | $ 4,082,962 | $ 12,751,099 | $ 218,967 | $ 183,138,601 | $ 209,465,417 | $ 1,559,000,000 | 13% |
| Maryland | $ 45,659,054 | $ 20,735,518 | $ 35,878,533 | $ 1,039,170 | $ 868,771,243 | $ 972,083,518 | $ 8,312,000,000 | 12% |
| Massachusetts | $ 50,844,840 | $ 22,628,475 | $ 24,225,048 | $ 1,074,472 | $ 814,890,396 | $ 913,663,231 | $ 8,182,000,000 | 11% |
| Michigan | $ 89,435,381 | $ 38,888,950 | $ 86,776,841 | $ 1,948,985 | $ 1,656,308,286 | $ 1,873,358,443 | $ 14,657,000,000 | 13% |
| Minnesota | $ 43,428,236 | $ 19,486,311 | $ 41,907,253 | $ 700,686 | $ 588,036,257 | $ 693,558,743 | $ 10,428,726,004 | 7% |
| Mississippi | $ 34,664,200 | $ 15,581,517 | $ 31,353,423 | $ 849,415 | $ 724,532,847 | $ 806,981,402 | $ 3,230,200,000 | 25% |
| Missouri | $ 54,644,754 | $ 24,145,405 | $ 67,550,224 | $ 1,042,217 | $ 871,172,291 | $ 1,018,554,891 | $ 5,970,000,000 | 17% |
| Montana | $ 8,764,737 | $ 3,925,618 | $ 12,816,385 | $ 206,476 | $ 170,099,465 | $ 195,812,681 | $ 1,047,203,321 | 19% |
| Nebraska | $ 16,358,075 | $ 7,162,159 | $ 17,272,129 | $ 325,425 | $ 243,073,530 | $ 284,191,318 | $ 1,653,000,000 | 17% |
| Nevada | $ 26,478,157 | $ 12,012,231 | $ 19,375,550 | $ 585,925 | $ 477,322,438 | $ 535,774,301 | $ 2,164,000,000 | 25% |
| New Hampshire | $ 8,891,635 | $ 3,800,242 | $ 7,069,209 | $ 188,207 | $ 156,065,807 | $ 176,015,100 | $ 1,257,000,000 | 14% |
| New Jersey | $ 68,866,711 | $ 29,930,743 | $ 68,749,847 | $ 1,551,856 | $ 1,230,971,757 | $ 1,400,070,914 | $ 15,218,000,000 | 9% |
| New Mexico | $ 22,263,463 | $ 9,849,995 | $ 17,282,330 | $ 542,874 | $ 435,938,638 | $ 485,877,300 | $ 3,389,000,000 | 14% |
| New York | $ 164,291,001 | $ 72,773,972 | $ 250,113,323 | $ 5,185,228 | $ 4,002,381,738 | $ 4,494,745,262 | $ 32,794,000,000 | 14% |
| North Carolina | $ 95,641,854 | $ 42,928,649 | $ 84,824,393 | $ 1,981,558 | $ 1,602,590,987 | $ 1,827,967,441 | $ 11,738,000,000 | 16% |
| North Dakota | $ 5,932,825 | $ 2,732,697 | $ 3,998,745 | $ 166,489 | $ 135,924,393 | $ 148,755,149 | $ 1,202,000,000 | 12% |
| Ohio | $ 104,920,249 | $ 46,303,196 | $ 154,896,274 | $ 2,446,026 | $ 1,991,251,095 | $ 2,299,816,840 | $ 11,856,000,000 | 19% |
| Oklahoma | $ 39,920,664 | $ 17,712,950 | $ 30,986,191 | $ 804,752 | $ 665,038,753 | $ 754,463,310 | $ 4,032,000,000 | 19% |
| Oregon | $ 32,508,822 | $ 14,174,308 | $ 27,595,419 | $ 605,495 | $ 499,153,891 | $ 574,037,935 | $ 5,467,594,000 | 10% |
| Pennsylvania | $ 104,421,207 | $ 47,083,088 | $ 150,022,294 | $ 2,619,036 | $ 2,224,964,030 | $ 2,529,109,655 | $ 15,415,000,000 | 16% |
| Rhode Island | $ 8,704,488 | $ 3,804,963 | $ 7,148,776 | $ 231,752 | $ 184,791,567 | $ 204,681,546 | $ 1,445,538,017 | 14% |
| South Carolina | $ 48,469,552 | $ 21,093,241 | $ 39,981,327 | $ 1,081,556 | $ 940,420,782 | $ 1,051,046,458 | $ 5,044,000,000 | 21% |
| South Dakota | $ 7,944,235 | $ 3,503,867 | $ 7,773,070 | $ 206,476 | $ 170,099,465 | $ 189,527,113 | $ 733,000,000 | 26% |
| Tennessee | $ 63,584,117 | $ 27,807,507 | $ 72,838,359 | $ 1,299,456 | $ 1,107,656,022 | $ 1,273,185,461 | $ 6,380,000,000 | 20% |
| Texas | $ 307,036,242 | $ 134,357,266 | $ 153,168,245 | $ 6,429,430 | $ 5,529,552,209 | $ 6,130,543,392 | $ 31,057,000,000 | 20% |
| Utah | $ 29,190,230 | $ 13,201,742 | $ 23,978,187 | $ 339,109 | $ 274,071,684 | $ 340,780,952 | $ 4,080,000,000 | 8% |
| Vermont | $ 4,488,898 | $ 1,931,057 | $ 4,284,369 | $ 155,742 | $ 126,973,363 | $ 137,833,429 | $ 1,913,000,000 | 7% |
| Virginia | $ 66,776,941 | $ 29,971,079 | $ 46,618,019 | $ 1,192,996 | $ 939,280,578 | $ 1,083,839,613 | $ 8,140,000,000 | 13% |
| Washington | $ 56,770,611 | $ 25,456,145 | $ 46,263,028 | $ 1,084,462 | $ 824,852,290 | $ 954,426,536 | $ 14,182,000,000 | 7% |
| West Virginia | $ 16,353,874 | $ 7,060,467 | $ 9,052,260 | $ 433,202 | $ 339,032,096 | $ 371,931,899 | $ 2,382,000,000 | 16% |
| Wisconsin | $ 46,551,563 | $ 20,836,198 | $ 77,492,001 | $ 873,889 | $ 686,056,238 | $ 831,809,889 | $ 8,262,081,000 | 10% |
| Wyoming | $ 4,701,053 | $ 2,042,041 | $ 4,602,637 | $ 162,813 | $ 135,230,900 | $ 146,739,444 | $ 879,000,000 | 17% |