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Student Subgroup

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In education, student subgroup generally refers to any group of students who share similar characteristics, such as gender identification, racial or ethnic identification, socioeconomic status, physical or learning disabilities, language abilities, or school-assigned classifications (e.g., special-education students). While “student subgroup” may be applied informally to any number of locally defined groups of students, the term typically refers to specific categories of students defined in federal and state legislation (and related rules and regulations) or used in data-collection processes, public reporting, research studies, statistical analyses, and other formal governmental or academic mechanisms employed to track the educational performance and attainment of particular groups of students.

In the United States, however, the term student subgroup is predominantly associated with a specific set of federally defined student subgroups for which public-education data are collected and reported by schools, districts, and state education agencies in accordance with requirements outlined in the 2002 No Child Left Behind Act. The law requires states to publish annual public reports on the educational performance of students across several distinct subgroup classifications outlined in Section 1111 of the Elementary and Secondary Education Act: economically disadvantaged students, students from major racial and ethnic groups, students with disabilities, and students with limited English proficiency.

Because the student subgroups widely used in public education and related data reporting are typically determined by legislation and regulatory guidance, it should be noted that student subgroups are (1) subject to regular modification or redefinition when applicable laws, rules, or regulations change, and are (2) defined in complex technical documentation that may be difficult to parse and interpret, even for specialists in the field. For these reasons, it is important to determine precisely how a student subgroup is being used or defined—and why—when investigating or reporting on the topic.

The following section provides a brief overview of a few of the most common student subgroups used in public education:

  • Gender Subgroups: The two gender subgroups widely used in public education are male and female. While historically these student subgroups have not been controversial, growing awareness of and sensitivity to students identifying as transgender poses potential complications for this approach to subgroup classification.
  • Racial and Ethnic Subgroups: When the law was originally passed, the No Child Left Behind Act required states to report data for the following racial and ethnic subgroups: (1) African American or Black, (2) American Indian or Alaska Native, (3) Asian or Pacific Islander, (4) Hispanic, and (5) White. Following changes in federal reporting guidelines for racial and ethnic data in 2007, a new subgroup of “two or more races” was introduced, among other modifications. Students who identify themselves as being of more than one major racial or ethnic group are now reported as part of this subgroup by state education agencies (and cannot be counted as part of any other racial or ethnic subgroup). In addition to the racial and ethnic subgroups required by the No Child Left Behind Act and used for the purposes of official federal reporting, some states or school districts may choose to collect and report education data on other racial and ethnic subgroups for which they have statistically large student populations. For example, Filipino, Puerto Rican, or Hmong students may be reported separately by some districts or states, typically because they have large populations of these students and they want to track and monitor student achievement the groups.
  • Students with Disabilities Subgroup: Any student with an Individualized Education Program, as defined by the Individuals with Disabilities Education Act, is reported in the “students with disabilities” subgroup. Students are counted as part of this subgroup for the entire time they are receiving special-education services in a public school and for two years after exiting a special-education program.
  • Students with Limited English Proficiency Subgroup: Students who are classified by their school as “limited English proficient,” often abbreviated as LEP, are reported in this subgroup. In general, districts and schools will use English-language tests or other forms of assessment to determine whether students are proficient in the English language. Students who have been designated as limited English proficient may continue to be counted in this subgroup for two years after they are deemed proficient in English. For a more detailed discussions of this topic, see English-language learner, long-term English learner, and the U.S. Department of Education’s guidance on limited English proficient students.
  • Economically Disadvantaged Subgroup: Historically, schools, districts, and governmental agencies have defined students as “economically disadvantaged” based on their eligibility to receive free or reduced-price lunch under the National School Lunch Program. In light of recent changes to the administrative guidelines for the program, however, which may result in more schools providing all students with free lunches regardless of eligibility, schools, districts, and state education agencies may have to consider alternative mechanisms to monitor economically disadvantaged student populations in the future.
  • Migrant Subgroup: Students are assigned “migrant status” when a parent or guardian’s principal means of livelihood is migratory work, typically in the agricultural or fishing industries. Migrant students move frequently from one school district to another as their parent or guardian obtains temporary or seasonal employment. The U.S. Department of Education’s Migrant Education Program oversees the relevant regulations and definitions for this student subgroup.

Reform

Before the No Child Left Behind Act became law in 2002, most state education agencies and school districts only collected aggregate data on students enrolled in public schools—i.e., data on the overall performance of all students in a given school or district. Today, however, all 50 states in the United States have systems that collect and maintain student-level data, not just aggregate records, which allows state education agencies to produce both aggregate and disaggregated reports on school and student performance. Specifically, states can now report on the academic achievement and educational attainment across the major student subgroups described above.

While data such as high school graduation rates or average test scores can yield a variety of important insights, a significant number of school leaders, researchers, education reformers, and policy makers have advocated in recent years for the importance of collecting, tracking, and monitoring data on student subgroups for the purpose of exposing underlying trends and issues such as achievement gaps, opportunity gaps, learning gaps, and other inequities in the public-education system. If, for example, the only graduation information available are annual rates for schools, this data may hide significant disparities in graduation rates for students from low-income households, students of color, students with disabilities, or students who are not proficient in the English language. It’s possible for a school’s graduation rate to appear strong overall—say, 90 percent—but when the data are disaggregated for different student subgroups, the different graduation rates may reveal, for example, that more than 50 percent of the African American and Hispanic students in the school fail to graduate, or that only 25 percent of English-language learners earn a diploma.

When data are reported for different student subgroups, educators also have more detailed information about the educational performance and learning needs of specific groups of students, which allows them to design more appropriate or effective educational experiences and academic support. For example, student-subgroup data may help school leaders and educators to direct limited resources—such as funding, staff time, or social services—where they are needed most (i.e., to those groups of students who are the furthest behind, struggling the most academically, or at greatest risk of dropping out).

Generally speaking, the primary purpose of collecting and reporting data on different student subgroups is to provide useful information about the performance of public schools and students to those who are monitoring public schools or working to improve them. While both aggregate and subgroup data are essential to understanding how the public-education system is working, district-level or school-level reports (i.e., aggregate data) are generally limited to the identification of broader trends and patterns in education, while subgroup data is used to identify deeper underlying problems—specifically, disparities in educational performance and attainment across different student groups.

Debate

While the use of student subgroups is generally not the objective of significant debate in public education (most educators, school leaders, policy makers, and reformers typically support the practice), the act of classifying and sorting individuals into broad groups tends to give rise to some level of debate or controversy. For example, a student’s gender, racial, or ethnic identification may not easily fit into or be accurately described by existing student subgroups, and consequently discussion, debate, or dispute may arise when students identify as transgender or mixed race.

In addition, social stigma associated with poverty, disability, language ability, or citizenship status—and the broader political and societal debates about these issues—may also intersect in a variety of ways with the definition, classification, and public reporting of student subgroups in education. For example, given the culturally sensitive and often ideologically contentious nature of the peripheral issues raised by the participation of non-English-speaking students in the American public-education system—including politicized debates related to citizenship status, English primacy, immigration reform, and social-services eligibility for non-citizens—it is perhaps unsurprising that students who are not proficient in English, and the instructional methods used to educate them, can become a source of debate (e.g., a significant number of states have adopted “English as the official language” statutes, and citizen referendums have passed in other states prohibiting instruction in Spanish or other languages except in special cases—see dual-language education for a related discussion).

De-identified Data

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In education, de-identified data generally refers to data from which all personally identifiable information has been removed—i.e., data about individual students, teachers, or administrators that has been rendered anonymous by stripping out any information that would allow people to determine an individual’s identity. Common forms of personally identifiable information include first and last names, home addresses, social security numbers, and other types of information that may reveal—advertently or inadvertently—an individual’s identity in a given set of data. The primary reason for “de-identifying” data is to protect the privacy or identity of the individuals associated with the data.

De-identified data are commonly used for research purposes in education. For example, a state education agency might hire an organization or university to study the results or impact of educational policy such as a recent expansion of state-subsidized pre-kindergarten programs. The researchers would then request the data they need to conduct the study (e.g., records showing the number of students enrolled in pre-kindergarten programs over a ten-year period), and the education agency would then assemble the necessary datasets. Before releasing the data files to the researchers, however, the agency would use a “de-identification process” to prevent individual identities from being revealed in the information provided to the external researcher. In many cases, the education agency and the research organization will also sign a formal agreement specifying how the data can be used and how files need to be disposed of once the study has been completed.

Data may also be de-identified when an education agency, district, or school shares information with external organizations and individuals not authorized to access or view personal information—for example, consultants and companies under contract to provide specialized services to districts and schools.

It is important to note that some datasets may indirectly reveal the identities of specific students or individuals even when the data seemingly contains no personally identifiable information. For example, some small, rural schools have very small minority student populations—perhaps only one or two students of color in the entire school. If state or school records contain, say, test scores or graduation rates for various racial subgroups, the identity of individual African American, Hispanic, or Asian students could inadvertently be revealed even though the data are otherwise “anonymous.” For this reason, states and schools may not publicly report or share certain data when subgroups are small enough to potentially connect otherwise anonymous data to specific students.

The most common strategies for de-identifying data are deleting all personal information in a data file and either “suppressing” or “masking” a selection of data so that the remaining information cannot be used to identify individuals. For more detailed discussions, see data masking and data suppression.

In addition, some de-identified datasets may contain what are often called “re-identification codes”—or random numbers assigned to individual records that have otherwise been stripped of personally identifiable information. Re-identification codes, for example, might allow researchers to match two anonymous datasets when conducting a study. Say a state education agency provides a set of data files to researchers who are studying whether a specific program resulted in academic gains for students. While conducting the study, the researchers determine that an additional year of data is needed to complete their analysis. The education agency may then use re-identification codes to “identify” the students in the original dataset (while still masking their personal identities), and then link those student records to the same students in the new dataset.

Data Suppression

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In education, data suppression refers to the process of withholding or removing selected information—most commonly in public reports and datasets—to protect the identities, privacy, and personal information of individual students, teachers, or administrators. Data suppression is used whenever there is chance that the information contained in a publicly available report could be used to reveal or infer the identities of specific individuals.

Data Suppression vs. Data Masking
The terms “data suppression” and “data masking” refer to similar yet distinct processes—although in some cases the terms may be used interchangeably. When data are suppressed, the information is entirely removed or deleted, most commonly in files and reports that are publicly shared. When data are masked, the information is concealed from view or encrypted in a file, but the masked data remains encoded in the file or database and can be accessed (or “re-identified”) by those with the proper authorization codes or passwords. For a more detailed discussion, see data masking.

When sharing data publicly, or with third parties such as contractors or researchers, state education agencies and school districts are generally required to take steps to protect individual privacy. In addition to suppressing data that will directly reveal the identity of individuals, such as names and social-security numbers, education agencies will also modify datasets—e.g., by “suppressing” selected information—that may indirectly reveal the identities of specific students even when the data seemingly contains no personally identifiable information.

For example, some small, rural schools have very small minority student populations—perhaps only one or two students of color in the entire school. If state or school records contain, say, test scores or graduation rates for various racial subgroups, the identity of individual African American, Hispanic, or Asian students could be inadvertently revealed even though the data are otherwise “anonymous” (by looking at the data, those who are familiar with the school, or who know who the minority students are, may be able to deduce which students earned which test scores, for example). For this reason, states, districts, and schools may suppress—i.e., not publicly report or share—certain data when subgroups are small enough to potentially connect otherwise anonymous data to specific students.

Suppression may also be needed when reporting percentages. If a report shows that 100 percent, or zero percent, of students in a particular grade at a school scored at a certain level on a test, for example, any readers familiar with the school will have learned personal information about individual students.

State education agencies and districts will typically have policies on data suppression that outline what types of data need to be suppressed in specific situations. For example, a policy may require the suppression of data in public reports when any subgroups represent less than five students. Most public data reports will explain why certain data has been suppressed.

For related discussions, see de-identified data, personally identifiable information, student-level data, and unique student identifier.

Data Masking

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In education, data masking refers to the process of concealing or encrypting selected information—most commonly in school-performance reports and datasets prepared by state education agencies and school districts—to protect the identity and privacy of individual students, teachers, or administrators. Data masking is used when reports are shared with third parties who are not authorized to access secure or private information—such as academics, researchers, or consultants—that could potentially be used to infer or reveal the identities of specific individuals.

Data Masking vs. Data Suppression
The terms “data masking” and “data suppression” refer to similar yet distinct processes—although in some cases the terms may be used interchangeably. When data are masked, the information is concealed from view or encrypted in a file, but the masked data remains encoded in the file or database and can be accessed (or “re-identified”) by those with the proper authorization codes or passwords. When data are suppressed, the information is entirely removed or deleted, most commonly in files and reports that are publicly shared. For a more detailed discussion, see data suppression.

Data masking is frequently used in research scenarios. For example, a state education agency might hire an organization or university to study the results or impact of educational policy—say, a recent expansion of state-subsidized pre-kindergarten programs. The researchers would then request the data they need to conduct the study (e.g., records showing the number of students enrolled in pre-kindergarten programs over a ten-year period), and the education agency would then assemble the necessary datasets. Before releasing files to the researchers, however, the agency would “mask” selected information—such as the first and last names of students—to prevent individual identities from being revealed in the information provided to the external researcher. Data may also be masked when education agencies, districts, or schools share information with any other external organizations or individuals not authorized to access or view personal information—for example, consultants and companies under contract to provide specialized services.

While the specific methods of data masking can be highly technical, the basic technique will be familiar to most people: credit-card statements that present only partial account numbers combined with Xs or online passwords that are represented as small dots are both common examples of data masking. While the companies masking account numbers and passwords know what the Xs or dots represent, masking or encrypting the information provides a layer of security against identify theft, fraud, and other abuses of customer information.

For related discussions, see de-identified data, personally identifiable information, student-level data, and unique student identifier.

Disaggregated Data

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Disaggregated data refers to numerical or non-numerical information that has been (1) collected from multiple sources and/or on multiple measures, variables, or individuals; (2) compiled into aggregate data—i.e., summaries of data—typically for the purposes of public reporting or statistical analysis; and then (3) broken down in component parts or smaller units of data. For example, information about whether individual students graduated from high school can be compiled and summarized into a single graduation rate for a school or a graduating class, and annual graduation rates for individual schools can then be aggregated into graduation rates for districts, states, and countries. Graduation rates can then be disaggregated to show, for example, the percentage of male and female students, or white and non-white students, who graduated. Generally speaking, data is disaggregated for the purpose of revealing underlying trends, patterns, or insights that would not be observable in aggregated data sets, such as disparities in standardized-test scores or enrollment patterns across different categories of students, for example.

While most disaggregated education data is numerical, it’s both possible and common to disaggregate non-numeric information. For example, educators, students, and parents in a school district may be surveyed on a topic, and the information and comments from those surveys could then be aggregated into a report that shows what the three groups—educators, students, and parents—collectively think and feel about the issue. The compiled information could then be disaggregated and reported for each distinct group to compare differences in how educators, students, and parents perceive the issue. Information collected during polls, interviews, and focus groups can be aggregated and disaggregated in a similar fashion.

To further illustrate the concept of disaggregated data and how it may be used in public education, consider a school with an enrollment of 500 students, which means the school maintains 500 student records, each of which contains a wide variety of information about the enrolled students—for example, first and last name, home address, date of birth, racial or ethnic identification, date and period of enrollment, courses taken and completed, course-grades earned, test scores, etc. (the information collected and maintained on individual students is often called student-level data, among other terms). Once or twice a year, the school district may be required to submit student-enrollment reports to their state department of education. Each school in the district will then compile a report that documents the number of students currently enrolled in the school and in each grade level, which requires administrators to summarize data from all their individual student records to produce the enrollment reports. The district now has aggregate enrollment information about the students attending its schools. Over the next five years, the school district could use these annual reports to analyze increases or declines in district-wide enrollment, enrollment at each school, or enrollment at each grade level. The district could not, however, determine whether there have been increases or declines in the enrollment of white and non-white students based on the aggregate data it received from its schools. To produce a report showing distinct enrollment trends for different races and ethnicities, for example, the district schools would then need to disaggregate the enrollment information by racial and ethnic subgroups.

Aggregated vs. Disaggregated Data

To aggregate data is to compile and summarize data; to disaggregate data is to break down aggregated data into component parts or smaller units of data. While this distinction between aggregated and disaggregated data may appear straightforward, there is a nuance worth discussing here: a lot of “disaggregated” data in education is actually data that has been technically aggregated, at some level, from records maintained on individual students. For example, graduation rates are widely considered to be “aggregate data,” while graduation rates reported for different subgroups of students—say, for students of different races and ethnicities—is typically considered to be “disaggregated data.” Yet to produce reports that disaggregate graduation rates by race and ethnicity, data on individual students actually has to be “aggregated” to produce summary graduation rates for different racial subgroups. Most likely, this distinction between aggregated and disaggregated data arose because, historically, only aggregated data on school-wide, district-wide, or statewide educational performance was readily or publicly available. When investigating or reporting on topics such as aggregate data or disaggregated data, it is important to determine precisely how the terms are being used in a particular context.

Reform

Before the early 2000s, most state education agencies and districts only collected aggregate data on students enrolled in public schools. Today, however, all 50 states in the United States have state-level systems that collect and maintain student-level data, not just aggregate records, which allows state education agencies to produce both aggregate and disaggregated reports on school and student performance (public-school districts typically collect student-level data from schools, and states collect student-level data from districts).

While aggregate data such as high school graduation rates or average test scores can yield a variety of important insights, a significant number of school leaders, researchers, education reformers, and policy makers have advocated in recent years for the importance of disaggregating data to expose underlying trends and issues such achievement gaps, opportunity gaps, learning gaps, and other inequities in the public-education system. If, for example, the only graduation data available are annual rates for individual schools, this aggregate data may hide significant disparities in graduation rates for students from low-income households, students of color, students with disabilities, or students who are not proficient in the English language. It’s possible for a school’s aggregate graduation rate to appear strong overall—say, 90 percent—but when the data are disaggregated for different groups of students, the disaggregation may reveal, for example, that more than 50 percent of the African American and Hispanic students in the school fail to graduate.

When data are disaggregated, educators also have more detailed information about the educational performance and learning needs of certain groups of students, which allows them to design more appropriate or effective educational experiences and academic support. For example, disaggregated data may help school leaders and educators to direct limited resources—such as funding, staff time, or social services—where they are needed most (i.e., to those groups of students who are the furthest behind, struggling the most academically, or at greatest risk of dropping out).

Generally speaking, the main purpose of collecting and reporting both aggregated and disaggregated data is to provide useful information about the performance of public schools and students to those who are monitoring schools or working to improve them. While both forms of data are essential to understanding how the public-education system is working, aggregate-data reports are generally limited to the identification of broader trends and patterns in education, while disaggregated data are more useful for diagnosing deeper underlying problems such as disparities in educational performance among different student groups.

Debate

In public education, aggregate data have been widely collected and publicly reported for decades, and for the most part the use of aggregate data has not been as controversial a topic in public education, primarily because aggregate data present far fewer concerns about student privacy than the collection, sharing, and use of data and personal information about specific students.

Although student safety, privacy, and confidentiality are more serious concerns with student-level data and personal information, disaggregated data may, in some cases, indirectly reveal the identities of specific students even when the data seemingly contains no personally identifiable information—i.e., information that might, directly or indirectly, reveal the identity or personal information of specific students. In some rural schools, for example, the minority student population may be very small—perhaps only one or two students of color in the entire school. If state or district records contain, say, test scores or proficiency levels for various racial subgroups, the identity of individual African American, Hispanic, or Asian students could be inadvertently revealed even though the disaggregated data are otherwise “anonymous” (by looking at the data, those who are familiar with the school, or who know who the minority students are, may be able to deduce which students earned which test scores, for example). For this reason, states, districts, and schools may mask or suppress (i.e., not publicly report or share) certain data when subgroups are small enough to potentially connect otherwise anonymous data to specific students.

For a more detailed discussion of related debates, see personally identifiable information.

Unique Student Identifier

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A unique student identifier is typically a number or code assigned to students enrolled in public schools that allow state education agencies, districts, schools, collegiate institutions, researchers, and others to monitor, track, organize, and transfer student records more efficiently and reliably. In the United States, state education agencies assign a randomly generated series of numbers and/or letters to individual students, with each student assigned one unique identifier. One of the primary advantages of a unique student identifier is that it’s used in place of a student’s name or other personal information that may compromise the privacy or reveal the identity of the student. For privacy-related reasons, social security numbers are generally not used as unique student identifiers in the United States, and several states have even passed laws that explicitly forbid the use of social security numbers as unique student identifiers.

It should be noted that different terms may be used when referring to unique student identifiers in education, including statewide student identifier, student identification number, or student ID, among others. Because these terms may or may not be used synonymously in certain technical contexts, it is important to determine precisely how the term is being defined when investigating or reporting on student data.

In addition to protecting student privacy, unique student identifiers are used to improve the quality, accuracy, and reliability of student data. By assigning students unique identifiers, a wide variety of educational records maintained by different educational agencies, schools, or programs—from report cards and test scores to disciplinary records and school-attendance data to learning-disability assessments and special-education plans—can be reliably associated with individual students in the vast, complex data systems that track information related to tens or hundreds of thousands of students enrolled in a public school in a given state.

Once a unique student identifier has been assigned, it remains attached to the student as long as he or she is enrolled in public school. The same unique identifier is used if a student transfers from one school district to another in a state, and it will remain in use if a student moves out of state for a period of time and then returns to the state. Because unique student identifiers are generated for use in a specific state’s educational data system, students will be assigned a different identifier when they enroll in different state’s public-education system. The United States does not use unique student identifiers at the national or federal level.

In some states, young children enrolled in state-subsidized prekindergarten programs may be assigned unique student identifiers that will stay with the students when they enroll in public school, while other states may not yet assign unique student identifiers to preschool students for any number of reasons (e.g., they may not have data systems capable of assigning and tracking unique student identifiers for preschool students, or they may lack the necessary staffing or funding). Postsecondary institutions—both public and private colleges and universities—have historically used social security numbers as their unique student identifiers. Some state agencies of higher education, however, do use public-school student identifiers in collegiate records (a practice that facilitates the transfer of student data between public schools and postsecondary institutions), but unique student identifiers are only used for students who graduated from in-state public high schools.

Unique student identifiers are often considered essential for the effective management of student-level data in longitudinal data systems—i.e., data systems that are used to track information over long periods of time, such as years or even decades. Because data related to an individual student may be stored in multiple data systems across multiple districts, schools, and state agencies, unique student identifiers are seen as the most accurate way to link individual student records across all the different data systems tracking students over multiple years. The use of unique student identifiers can also, for example, improve the speed with which transcripts and other records are transferred among schools, in addition to other benefits.

When working with large sets of data from multiple schools or across multiple academic years, maintaining data quality, accuracy, and reliability is an enormous challenge. Unique student identifiers can improve data quality by ensuring that individual students are consistently identified in a wide variety of databases, files, or reports. For example, districts and schools may inadvertently record a student’s name differently—e.g., Tommy Smith may have previously been enrolled in his previous school as Thomas E. Smith. Or there may be multiple Tommy Smiths enrolled in the same school and same grade level at the same time.

Debate

Although unique student identifiers can improve the accuracy and reliability of student data, and facilitate the transfer of data reliably across different systems, unique student identifiers also raise concerns about student privacy. For a more detailed discussion of privacy concerns and related debates, see personally identifiable information.

Student-Level Data

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In education, student-level data refers to any information that educators, schools, districts, and state agencies collect on individual students, including data such as personal information (e.g., a student’s age, gender, race, place of residence), enrollment information (e.g., the school a student attends, a student’s current grade level and years of attendance, the number of days a student was absent), academic information (e.g., the courses a student completed, the test scores and grades a students earned, the academic requirements a student has fulfilled), and various other forms of data collected and used by educators and educational institutions (e.g., information related to disciplinary problems, learning disabilities, medical and health issues, etc.). It should be noted that an increasing number of organizations, institutions, or companies may also collect or have access to student-level data on public-school students, typically as a part of a contract for services or a research study conducted in collaboration with schools, districts, or state education agencies.

It should be noted that a wide variety of terms may be used when referring to student-level data in education, including individual-level data, individual student-level data, student unit-level data, unit-record data, student unit-record data, record-level data, and record-level student data, among others. Because these terms may or may be used synonymously in certain technical contexts, it is important to determine precisely how the term is being defined when investigating or reporting on student data.

Increasingly, new educational technologies are redefining the definition of “student-level data,” given that educational software and online learning programs, for example, can collect a huge amount of information and metadata about the students who use them—information that was formerly impossible to track before the advent of sophisticated technologies and analytical tools—which includes information such as the geographic location of the computer being used by a student or the amount of time it took a student to answer certain questions or solve certain problems. Many online learning programs routinely collect hundreds or even thousands of distinct data points while students are using the systems—data that may then be used for any number of educational or non-educational purposes (e.g., to improve the software, modify the questions or problems students see, study how children and youth learn, or market the product to potential buyers).

Reform

Student-level data is collected and used for a wide variety of purposes, and it intersects with efforts to improve schools and educational systems in a number of ways—too many to comprehensively describe here. To cite just a few representative examples, however, student-level data may be used to:

  • Maintain more robust, accurate, and comprehensive student records for educators, students, graduates, parents, collegiate institutions, employers, and others who may need or request the information.
  • Inform or improve the instructional process by giving teachers and other educators and specialists information about the distinct learning needs, academic progress, and educational achievements of specific students.
  • Inform or improve various student-support strategies or systems, which may include any number of academic, behavioral, mental, health, or social services that students may need or access.
  • Improve the accuracy and reliability of aggregate educational data—such as graduation, dropout, or enrollment rates reported for schools, districts, and states—that originates from individual data collected on a large number of students (for a related discussion, see unique student identifier).
  • Track trends in the educational performance of individual students or educational systems over time using information such as school-completion data or standardized-test scores, for example.
  • Identify problems or weaknesses in the educational performance of students, teachers, schools, or districts for the purpose of improving academic achievement, teaching effectiveness, or educational results.

Before the advent of technologies and software applications that allow schools, districts, and state agencies to collect an array of highly detailed data on individual students, student-level data was generally limited to teacher grade books, report cards, school transcripts, attendance files, and other administrative records maintained by schools and districts. Because this information was largely or entirely paper-based—and therefore difficult, time consuming, and costly to collect, organize, or analyze—it limited the ability of educators, researchers, and others to use student-level data to diagnose education problems, track trends in performance over time, or improve the effectiveness of schools or teaching, for example. Advances in educational software, computing technologies, internet access, and innovations such as cloud-based data storage and “big data” analytics have fueled a dramatic increase in the collection and use of student-level data in recent years.

Since at least the early 2000s, some districts and state education agencies have been using large-scale data systems capable of collecting, archiving, and generating reports on a vast array of student-level data originating from multiple sources, ranging from schools to standardized tests. As technological advances make the collection of data on individual students more efficient, inexpensive, and potentially valuable to the educational process, an increasingly large, diverse, and ever more complex body of student-level data is being collected, archived, analyzed, and used at all levels of the educational system and by a growing number of researchers, institutions, organizations, and companies.

It should be noted that if student-level data is being collected for reasons other than maintaining academic records for students and their families, it is almost certainly being used, in some form, to reform or improve schools and education systems—even if the purpose is merely to provide more accurate, useful, and detailed information about performance to those working to improve schools.

While much of the discussion about student-level data in public education is focused on the large-scale collection of personal data on individual students—and on the potential applications and possible abuses of that information—the term also encompasses any information that teachers and other educators or specialists may use during the process of educating individual students. For example, teachers may keep journals, logs, or other records detailing the distinct learning needs or progress of individual students—information that may or may not be shared with colleagues and administrators or formally reported to state education agencies and other entities outside of the school. Personal learning plans, for example, are one of the many possible methods that educators might use to collect data on individual students. Early warning systems—usually databases of academic, attendance, and disciplinary information that educators use to identify and monitor students who are struggling academically or in danger of dropping out of school or not graduating on time—are another example.

Debate

Teachers and schools have always collected and maintained records of student-level data, but the transition from paper-based systems to digital systems, and from small-scale data collection by schools to large-scale data collection by state agencies and private companies, has given rise to numerous debates about student-level data and student privacy. For this reason, most debates related to the collection, storage, and use of student-level data are connected to concerns about student privacy.

For a more in-depth discussion of debates related to student-level data, see personally identifiable information.

Aggregate Data

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Aggregate data refers to numerical or non-numerical information that is (1) collected from multiple sources and/or on multiple measures, variables, or individuals and (2) compiled into data summaries or summary reports, typically for the purposes of public reporting or statistical analysis—i.e., examining trends, making comparisons, or revealing information and insights that would not be observable when data elements are viewed in isolation. For example, information about whether individual students graduated from high school can be aggregated—that is, compiled and summarized—into a single graduation rate for a graduating class or school, and annual school graduation rates can then be aggregated into graduation rates for districts, states, and countries.

While most aggregate education data is numerical—e.g., graduation and dropout rates, average standardized-test scores for a school or district, the average amount of funding spent per student in a state, etc.—it’s both possible and common to aggregate non-numeric information. For example, educators, students, and parents in a school district may be surveyed on a topic, and the information and comments from those surveys could then be “aggregated” into a report that shows what the surveyed individuals generally think and feel about the issue. Information collected during polls, interviews, and focus groups can be aggregated in a similar fashion.

To further illustrate the concept of aggregate data and how it may be used in public education, consider a school with an enrollment of 500 students, which means the school maintains 500 student records, each of which contains a wide variety of information about the enrolled students—for example, first and last name, home address, date of birth, gender identification, race or ethnicity, date and period of enrollment, courses taken and completed, course-grades earned, test scores, etc. (the information collected and maintained on individual students is often called student-level data, among other terms). Once or twice a year, the school district may be required to submit student-enrollment reports to their state department of education. Each school in the district will then compile a report that documents the number of students currently enrolled in the school and in each grade level, which requires administrators to summarize data from all their individual student records to produce the enrollment reports. The district now has aggregate enrollment information about the students attending its schools. Over the next five years, the school district could use these annual reports to analyze increases or declines in district-wide enrollment, enrollment at each school, or enrollment at each grade level. The district could not, however, determine whether there have been increases or declines in the enrollment of white and non-white students based on the aggregate data it received from its schools. To produce a report showing distinct enrollment trends for different races and ethnicities, the district schools would then need to disaggregate the enrollment information by racial and ethnic subgroups.

Aggregated vs. Disaggregated Data

To aggregate data is to compile and summarize data; to disaggregate data is to break down aggregated data into component parts or smaller units of data. While this distinction between aggregated and disaggregated data may appear straightforward, there is a nuance worth discussing here: a lot of “disaggregated” data in education is actually data that has been technically aggregated, at some level, from records maintained on individual students. For example, graduation rates are widely considered to be “aggregate data,” while graduation rates reported for different subgroups of students—say, for students of different races and ethnicities—is typically considered to be “disaggregated data.” Yet to produce reports that disaggregate graduation rates by race and ethnicity, data on individual students actually has to be “aggregated” to produce summary graduation rates for different racial subgroups. Most likely, this distinction between aggregated and disaggregated data arose because, historically, only aggregated data on school-wide, district-wide, or statewide educational performance was readily or publicly available. When investigating or reporting on topics such as aggregate data or disaggregated data, it is important to determine precisely how the terms are being used in a particular context.

Reform

Before the early 2000s, most state education agencies and districts only collected aggregate data on students enrolled in public schools. Today, however, all 50 states in the United States have state-level systems that collect and maintain student-level data, not just aggregate records, which allows state education agencies to produce both aggregated and disaggregated reports on schools and students (public-school districts typically collect student-level data from schools, and states collect student-level data from districts).

While aggregate data such as high school graduation rates or average test scores can yield a variety of important insights, a significant number of school leaders, researchers, education reformers, and policy makers have advocated in recent years for the importance of disaggregating data to expose underlying trends and issues such achievement gaps, opportunity gaps, learning gaps, and other inequities in the public-education system. If, for example, the only graduation data available are annual rates for individual schools, this aggregate data may hide significant disparities in graduation rates for students from low-income households, students of color, students with disabilities, or students who are not proficient in the English language. It’s possible for a school’s aggregate graduation rate to appear strong overall—say, 90 percent—but when the data are disaggregated for different groups of students, the disaggregation may reveal, for example, that more than 50 percent of the African American and Hispanic students in the school fail to graduate.

Generally speaking, the main purpose of collecting and reporting aggregate data is to provide useful information about the performance of public schools and public-school students to those who are monitoring schools or working to improve them. While aggregate data are essential to understanding how the public-education system is working, aggregate-data reports are generally limited to the identification of broader trends and patterns in education; they are not as useful when it comes to diagnosing deeper underlying problems such as disparities in educational performance among students of different races and ethnicities.

Debate

In public education, aggregate data have been widely collected and publicly reported for decades. For the most part, the use of aggregate data has not been a controversial topic in public education, primarily because aggregate data present far fewer concerns about student safety and privacy than the collection, sharing, and use of data and personal information about specific students. That said, a variety of debates related to the use of aggregate data in education have emerged in recent years, typically in response to (1) the use of public reports, often called “school report cards,” intended to provide families and the public with summarized assessments of individual school performance, and (2) the use of average student test scores and other aggregate measures in the job-performance evaluations of educators.

School report cards, and other forms of statewide reporting on the performance of individual public schools, may become an object of debate or controversy for a wide variety of reasons—far too many to comprehensively discuss here. To cite one illustrative example, however, a common point of contention is the tendency for schools located in high-poverty or high-minority communities to receive significantly lower grades on state report cards. These schools tend to serve a higher-need student population with larger learning deficits, to be underfunded (compared to wealthier districts), to have less-experienced or less-skilled teachers, and to face an array of additional obstacles that contribute to lower performance—yet the aggregate data presented in state report cards may not provide this contextual information. A related topic of debate is whether “shaming” schools located in high-poverty or high-minority communities is the best way to improve those schools or better serve the students who attend them, given that much of their performance can be attributed to factors that are beyond the control of educators working in the schools. Those who advocate for the use of state report cards may argue that—regardless of the challenges schools face—parents, families, and the general public have a right to be informed about the performance of the public schools in their state and community, and that increasing transparency when it comes to school performance will lead to policies and reforms that will ultimately improve educational quality for students.

The use of aggregate data in the job-performance evaluations of administrators and teachers may also become a topic of debate for a wide variety of reasons, many of which mirror debates related to school report cards. For example, many educators and teachers unions argue that teachers should not have their job security or salaries based on student performance because many factors influencing academic achievement are beyond their control: for example, factors such as low parental education levels, unsupportive or dysfunctional home environments, or nutritional deficits and stress—not to mention starting a school year significantly behind academically—can all adversely affect educational achievement. Those who oppose the use of aggregate data in job-performance evaluations generally argue that using aggregate data to evaluate individual educators is often misrepresentative and unfair. For a related discussion, see value-added measures.

Student-Teacher Ratio

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A student-teacher ratio expresses the relationship between the number of students enrolled in a school, district, or education system and the number of “full-time equivalent” teachers employed by the school, district, or system. For example, a student-teacher ratio of 10:1 indicates that there are ten students for every full-time equivalent teaching position. In public schools, the term full-time equivalent (often abbreviated as “FTE”) is a standard measure of teaching capacity that represents both full-time teachers (each full-time teacher is counted as one FTE) and part-time teachers (two half-time teachers, for example, would count as one FTE).

It should be noted that most schools, districts, and states count all “instructional staff” as teachers when calculating student-teacher ratios and full-time equivalencies. For this reason, a school might have 52.5 full-time equivalent teachers, which may include only 40 staff members who might be considered “teachers” in the more narrow or traditional sense of the term. The instructional staff in a given school may include librarians, speech therapists, and other academic-support specialists or licensed teaching staff who may not have traditionally defined classroom-teaching roles. For this reason, a student-teacher ratio of 10:1 does not mean that the average class size in a school is ten students. To better illustrate this issue, for example, one study found that the average difference between student-teacher ratios and average class sizes in a selection of schools was between nine and ten students. In this case, a school with a student-teacher ratio of 20:1 would likely have an average class size closer to 30. For a related discussion, see class size.

Because student-teacher ratios are a general way to measure teacher workloads and resource allocations in public schools, as well as the amount of individual attention a child is likely to receive from teachers, student-teacher ratios are often used as broad indicators of the overall quality of a school, district, or education system. In addition, “ideal” student-teacher ratios will depend on a wide variety of complex factors, including the age and academic needs of the students represented in the ratio (younger children or higher-need student populations typically require more time, attention, and instructional support from teachers) or the experience, skill, and effectiveness of the teachers (highly skilled teachers may be able to achieve better academic results with larger classes than less skilled teachers with smaller classes).

Student-teacher ratios also directly affect per-pupil spending—or the average amount of money spent to educate students in a school, district, or education system. For example, the salaries and benefits paid to teachers and instructional staff can account for up to 75 percent of per-pupil expenditures, so higher student-teacher ratios will typically result in lower per-pupil expenditures.

Reform

In recent decades, a wide variety of school-reform strategies and initiatives—at the level of state and federal policy, as well as in individual schools and districts—have focused on decreasing student-teacher ratios as a strategy for improving the academic performance of students. The basic rationale is that teachers with fewer students will be able to devote more time and attention to each student, which will increase their chances of improving learning outcomes. Yet because reducing student-teacher ratios generally requires the hiring of additional teachers, possibly even a significant number of teachers (in the case of states and large school districts), some ratio-reduction policies can entail significant increases in educational expenditures.

One of the desired benefits of lower student-teacher ratios is the increased amount of individual attention that students are more likely to receive when schools have more instructional and support staff per student. In addition to hiring more instructional staff, schools may also use a wide variety of alternative instructional or school-configuration strategies—such as advisories, personalized learning, teaming, or “small learning communities,” to name just a few—that are intended to achieve the same academic results as schools with lower student-teacher ratios. In small learning communities, to use just one example, students are typically paired with teachers, counselors, and support specialists who, over time, get to know students and their specific learning needs well, enabling them to educate the students more effectively. Even though the average student-teacher ratio in a school may not change in small learning community settings, students will be grouped and supported in ways that can potentially reproduce the benefits of lower student-teacher ratios.

Lower student-teacher ratios may also become the target of or rationale for reforms and policies aimed at reducing educational expenditures. For example, reformers and policy makers may use comparisons of student-teacher ratios from place to place, and the results achieved by different systems, as a rationale for justifying higher student-teacher ratios as a mechanism for reducing costs.

Debate

Debates related to student-teacher ratios tend to be focused on either educational expenditures or the effects of class size, and on whether simply reducing student-teacher ratios will actually improve academic achievement in a school, district, or education system. Research studies on student-teacher ratios and academic achievement have found mixed results: some indicate that lower student-teacher ratios in schools produce educational benefits for students; others suggest that teaching skill and quality are the main factors, and that hiring more teachers—who may not necessarily be more experienced or skilled—will simply increase educational costs without producing the desired results for schools and students.

In some cases, educators may also disagree over the precise point at which students begin to benefit from lower student-teacher ratios. Some research evidence suggests, for example, that reducing ratios may not have a beneficial effect on student achievement until the average ratio drops below at least 20:1, or that educational benefits are only measurable when student-teacher ratios fall to 18:1 or lower.

Personally Identifiable Information

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Personally identifiable information—often abbreviated as PII—refers to any data or information about students collected by schools, districts, government agencies, or organizations and companies working with schools that might reveal the identity or personal information of specific students or that could allow someone to indirectly track down the identity or personal information of students.

Common forms of personally identifiable information include a student’s name, the names of parents or family members (including the maiden name of a student’s mother), a household address, a date or place of birth, social security numbers, student-identification numbers issued by schools or school systems, and digital files such as photographs, videos, or audio recordings, among other forms of information that may reveal a specific student’s identity. Given that both students and schools are increasingly using powerful technological devices that record and store personal data, personally identifiable information may also include biometric data (e.g., fingerprints or palm prints), geolocation data (e.g., real-time location data relayed by a smartphone), and metadata (i.e., “data about other data,” such as data about image size, resolution, color, or date of creation that are commonly embedded in digital photos).

In some cases, data may indirectly reveal the identities of specific students even when the data seemingly contains no personally identifiable information. For example, some small, rural schools have very small minority student populations—perhaps only one or two students of color in the entire school. If state or school records contain, say, test scores or proficiency levels for various racial subgroups, the identity of individual African American, Hispanic, or Asian students could be inadvertently revealed even though the data are otherwise “anonymous” (by looking at the data, those who are familiar with the school, or who know who the minority students are, may be able to deduce which students earned which test scores, for example). For this reason, states, districts, and schools may “mask” or suppress (i.e., not publicly report or share) certain data when subgroups are small enough to potentially connect otherwise anonymous data to specific students.

Personally identifiable information is also a legally defined concept used in federal and state regulations and reporting requirements. In the federal context, personally identifiable information is defined in three primary statutes: the Family Educational Rights and Privacy Act—commonly abbreviated as FERPA—a statute that was first passed in 1974 and updated several times since, the Children’s Online Privacy Protection Act—or COPPA—which applies to information collected online through websites and apps from kids under the age of 13, and the Protection of Pupil Rights Amendment of the Family Educational Rights and Privacy Act, which is intended to protect the privacy rights of students and parents.

Reform
In recent years, personally identifiable information has become a topic of discussion, as well as a school-reform tool, mainly due to the growing power of computers and data systems to collect, communicate, and potentially compromise personal information in ways that were formerly far more difficult or impossible. While a comprehensive overview of the topic is beyond the scope of this resource, the following examples illustrate two ways in which personally identifiable information intersects with efforts to improve education systems, schools, or teaching:

  • Data quality: When dealing with large sets of complex data—for example, state education agencies collecting, analyzing, and publicly reporting the graduation, dropout, or attendance rates of all students enrolled in a state’s public schools—it can be extremely challenging to manage and maintain data quality in a state or district. One way to increase the reliability and accuracy of a data set is to use personally identifiable information to connect specific students with specific sets of information. For example, if students are assigned a unique identification number in a data system, that “unique student identifier” can be a more effective way to organize information in a database than, say, a date of birth, given that birth dates will inevitably be shared by many students. When multiple forms of personally identifiable information are used—first and last names, unique student identifiers, dates of birth, etc.—the reliability and accuracy of data in system can be improved significantly.
  • Data-informed instruction: New learning technologies, online course platforms, and educational software systems have given educators access to an unprecedented amount of information about students that can be used to diagnose or monitor student learning needs and academic progress in ways that were formerly impossible. In some situations, educators can use this information to modify or personalize learning experiences and instructional strategies and potentially improve or accelerate learning progress. For example, online courses and learning systems are typically capable of collecting a large amount of information about users, ranging from student results on embedded assessments to data about keystrokes, clicking patterns, log-in and log-out times, or the amount of time that elapses between when a question is displayed and when it is answered. Educators may then analyze and use this information to improve instruction for students. In addition, online courses and other forms of educational software may use the data to provide adaptive learning experiences—i.e., the systems may automatically modify learning tasks or questions based on student answers and other information collected by the system.

Debate
While personally identifiable information can be recorded in both physical and digital documents, archives, and reports, the term as commonly used today is primarily associated with electronic and online information systems (particularly systems that share data among multiple organizations, government agencies, companies, or systems that may be accessed and used by for-profit businesses, marketers, and other entities for purposes unrelated to the education of students, including illegal purposes such as identity theft). Consequently, concerns about online security and student privacy frequently generate debate about personally identifiable information in education.

While debates about personally identifiable information are numerous, complex, and nuanced, most are focused on (1) what types of information should be collected for educational purposes and should be legal to collect, (2) how information is stored and secured, and (3) how information is being used by schools, government agencies, companies, and others. The following questions will help to illustrate the complexity of debates about personally identifiable information:

  • What types of personal information are necessary to collect for educational purposes, and what types of information are not essential to the educational process? For example, is it necessary to know a student’s home address or social security number to administer a standardized test? If the information is not essential, should it be collected?
  • Is the personal data collected about students adequately protected from unauthorized viewers? Has personal student information been sufficiently secured from hackers, theft, and potential misuse? And who has access to what types of student information—for example, can school administrators, teachers, and parents all access and view the same information?
  • Should outside companies have access to personal student information, and what types of legal protections and security measures are in place to safeguard student data and protect against identity theft and other forms of misuse?
  • Are parents and guardians aware of and informed about the types of personal information being collected about their children? Can parents or guardians view the information and verify whether it’s accurate? Have parents or guardians been given an opportunity to opt-out of data-sharing arrangements between schools and third parties? To what degree can parents and guardians determine how their child’s personal data are being used?
  • Can personally identifiable information violate student confidentially and privacy? Can the information be used to discriminate against or embarrass students and families? If connected to specific students, personal information related to psychological disorders, physical health or disability, special-education status, sexual orientation, disciplinary actions, family income, and immigration or migrant status—among other types of information—could potentially be misused or mishandled in any number of ways by districts, schools, or outside entities.

While many privacy-related issues are addressed in the Family Educational Rights and Privacy Act, the Protection of Pupil Rights Amendment, and other federal and state laws and regulations, most experts agree that the sophistication and speed of technological advancements are outpacing the laws intended to regulate and secure the use of personally identifiable information in education. In addition, school administrators and educators may not have the technical or legal background and expertise required to negotiate the complexities of data collection, sharing, and security. As a result, many states and education agencies are establishing and enforcing policies related to the software systems being used by schools and the related agreements made with third-party vendors and software developers that could inadvertently expose or compromise personally identifiable information.

Concerns about the accidental or inappropriate release of personally identifiable information have given rise to critical news stories; protests and lobbying campaigns by student-rights and privacy groups (and counter campaigns by proponents of new learning technologies); and state legislation that either bans the collection of certain types of student data (such as a student’s biometric information, political interests, and religious affiliation) or prohibits certain types of data arrangements (such as storing student data in cloud-based applications owned and managed by third parties).

As educational technologies and data systems become more embedded in public education, debates about personally identifiable information will likely continue to evolve.

Local-Control State

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In education, the term local-control state refers to states in which the governing and management of public schools is largely conducted by elected or appointed representatives serving on governing bodies, such as school boards or school committees, that are located in the communities served by the schools. For a related discussion, see autonomy.

The concept of local control is grounded in a philosophy of government premised on the belief that the individuals and institutions closest to the students and most knowledgeable about a school—and most invested in the welfare and success of its educators, students, and communities—are best suited to making important decisions related to its operation, leadership, staffing, academics, teaching, and improvement. This general philosophy of governance is often contrasted with state or federal policies intended to influence the structure, operation, or academic programs in public schools, given that level of control granted to local governing bodies is directly related to the level of prescription articulated in education laws, regulations, and related compliance rules and requirements.

While the United States Constitution does not explicitly mention education, the Tenth Amendment states that “the powers not delegated to the United States by the Constitution, nor prohibited by it to the States, are reserved to the States respectively, or to the people,” which has been widely interpreted to give states primary authority and control over the governance and operation of public schools (that said, many federal laws and regulations heavily influence the operation of public schools both directly and indirectly). The role that state governments and agencies play in school governance and management varies from state to state, with some states exerting more direct control over public schools and other states allowing local governing bodies to adopt policies and perform governance functions for the schools located in their district or community. States that assign more responsibility over the governance and management of public schools to local governing bodies are commonly called “local-control states.” Historically, these states have generally deferred to local school boards and committees on governance issues, even issues related to compliance with state statutes and regulations.

For a more detailed discussion, see local control.

Teacher Autonomy

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The concept of teacher autonomy refers to the professional independence of teachers in schools, especially the degree to which they can make autonomous decisions about what they teach to students and how they teach it.

In recent years, teacher autonomy has become a major point of discussion and debate in American public education, largely as a result of educational policies that, some argue, limit the professionalism, authority, responsiveness, creativity, or effectiveness of teachers.

While teacher autonomy is most frequently discussed in terms of what teachers teach to students and how they teach it, the issue may also manifest in other ways. For example, some schools are entirely led and managed by teachers—i.e., the schools do not have formal administrators; teachers assume administrative roles, usually on a revolving basis. In addition, the composition and negotiation of teacher contracts may also vary significantly from place to place. For example, local teachers unions will negotiate annual contracts with school districts in some states, while most states have statewide teacher contracts that are negotiated by state teachers unions. Depending on its provisions, teaching contracts can directly affect professional autonomy, given that contracts may, for example, determine the specific number of hours that teachers can work each week or limit the roles that teachers can play in a school or district.

For a related discussion, see autonomy.

Debate

While debates related to teacher autonomy vary from place to place, the professionalism of teachers is typically a central issue in the debates. Many educators, and groups such as teachers unions or membership-based professional organizations for teachers, may argue that infringing on teacher autonomy in the classroom undermines the professional status and expertise of teachers. In this view, attempts to micromanage teaching strategies or teacher performance through more prescriptive policies, greater administrative oversight, or strict curriculum requirements will undermine job satisfaction or the perception that teachers are skilled professionals who have earned a degree of public trust in their abilities.

Advocates of greater teacher autonomy may also argue that because teachers are in the best position to make informed decisions about a student’s education, they should be given as much autonomy as possible when it comes to choosing instructional strategies, designing lessons, and providing academic support. In this view, more stringent regulations, tougher job requirements, greater administrative oversight, or more burdensome teacher-evaluation procedures, for example, will inevitability stifle the instructional creativity and responsiveness of teachers, which could produce a variety of negative results, including lower student performance or higher job dissatisfaction and attrition rates among teachers. Given that no policy that is applied to all teachers can take into account the myriad abilities and needs of students, the reasoning goes, important decisions about educating students should be left to teachers. Similarly, local school leaders and administrators are better positioned to determine the performance of teachers, rather than blanket policies that are applied to all teachers in a district or state, such as valued-added measures—i.e., formulas used to estimate or quantify how much of a positive (or negative) effect individual teachers have on student learning during the course of a given school year.

Critics of teacher autonomy tend to cite evidence that teaching quality is uneven, and that problems such as achievement gaps or low graduation rates indicate that measures need to be taken to improve the effectiveness of teachers and public-school instruction. While the proposed solutions to ineffective teaching are numerous, proposals may include greater administrative oversight, increased educational and professional requirements for new teachers, prepackaged or “scripted” curriculum materials, more demanding evaluation systems for job performance, or penalties for poor-performing teachers, for example.

The following examples will help to illustrate a few of the primary issues giving rise to debates about teacher autonomy:

  • Testing policies: High-stakes tests—exams used to make important decisions about schools, educators, or students—are widely considered to cause a phenomenon known as “teaching to the test”—i.e., educators focusing their instruction on the topics that are most likely to be tested, or spending classroom time prepping students for tests rather than teaching them knowledge and skills that may be more important. If penalties are imposed on schools, educators, students, or teachers due to test results, critics argue, teachers will inevitably have less autonomy over the instructional process because they will be forced to “teach to the test.” As the use of standardized tests has grown in the United States in recent decades, educators have increasingly expressed concern about the consequences of such policies, including the consideration of student test scores in the job-performance evaluations of teachers—a highly controversial subject among educators and teachers unions.
  • Standards policies: All fifty states in the United States have developed and adopted learning standards—concise, written descriptions of what students are expected to know and be able to do at a specific stage of their education—that establish learning goals for students in kindergarten through high school. Consequently, when schools “align” their academic programs and curriculum with the learning goals described in standards, some argue that teachers will have less “autonomy” in determining the knowledge, skills, and content they teach to students. The extent to which learning standards limit the autonomy of teachers remains a subject of ongoing discussion and debate, but many educators argue that standards do not impose significant limitations on the professional autonomy of teachers. For example, some argue that standards only describe broad learning expectations, and that they do not tell teachers how to teach or even, to a great extent, what to teach. For example, a standard that requires students to demonstrate understanding how “checks and balances” and “separation of powers” work in American government does not require teachers to teach those ideas in any specific way—they can use any number of instructional approaches, learning materials, or historical examples to teach students the concepts described in the standards.
  • Curriculum policies: Some states, districts, and schools have policies related to curriculum that may affect teacher autonomy to a greater or lesser extent. For example, some districts and schools require teachers to use “scripted curriculum”—i.e., a prescriptive, standardized, prepackaged form of curriculum that may require teachers to follow a particular sequence of prepackaged lessons and, in some cases, read aloud from a teaching script in class. Though the term is now considered pejorative and rarely used, forms of scripted curriculum were called “teacher-proof curriculum” in past decades. Clearly, the professional autonomy of individual teachers will be significantly limited when such a curriculum system is mandated. In other districts or schools, teachers may be required to use certain texts or instructional approaches, or follow “pacing guides” that outline a specific sequence of lessons and content. For example, teachers may be required to have students reading a designated chapter in a particular textbook on a certain day of the school year. Depending on the level of prescription, and whether they are voluntary guidelines or mandates, curriculum policies can directly affect the instructional autonomy of teachers.
  • Promotion policies: Some states, districts, and schools have policies related to grade promotion or graduation that may limit the ability of teachers to play a role in the process of deciding how and when students will be promoted. For example, a district policy may require that students be automatically held back if they fail a course, which could, in some circumstances, supersede a teacher’s recommendation that the student be promoted due to certain extenuating factors. Some states may also require students to pass a standardized test before they are promoted to the next grade level or eligible to receive a high school diploma (for a related discussion, see high-stakes test). Other policies may require a particular course of corrective action when students fail a course, which could also have implications for teacher autonomy. For example, students who fail a course may be required to complete a credit-recovery program—such as an online course or summer-school program—that may not mirror the content taught in the course the student failed. In this case, the teacher may not have a say in how their students “recover” the credit they failed to earn in the teacher’s class.
  • Evaluation policies: Discussions and debates about “teacher evaluation” and “teacher accountability” have grown more prominent—and contentious—in recent years. Depending on the systems, methods, and criteria used in the job-performance evaluations of teachers, evaluation policies may affect teacher autonomy. If evaluation processes, expectations, and requirements are more stringent or burdensome, it could influence the way that teachers instruct students. For example, if standardized test scores are used in the evaluation process, and if compensation decisions (salaries, bonuses, or “merit-based” pay) are connected to test scores, teachers will be more likely to modify how and what they teach to improve student test results.

Local Control

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In education, local control refers to (1) the governing and management of public schools by elected or appointed representatives serving on governing bodies, such as school boards or school committees, that are located in the communities served by the schools, and (2) the degree to which local leaders, institutions, and governing bodies can make independent or autonomous decisions about the governance and operation of public schools. For a related discussion, see autonomy.

The concept of local control is grounded in a philosophy of government premised on the belief that the individuals and institutions closest to the students and most knowledgeable about a school—and most invested in the welfare and success of its educators, students, and communities—are best suited to making important decisions about its operation, leadership, staffing, academics, teaching, and improvement. This general philosophy of governance is often contrasted with state or federal policies intended to influence the structure, operation, or academic programs in public schools, given that level of control granted to local governing bodies is directly related to the level of prescription articulated in education laws, regulations, and related compliance rules and requirements.

While the United States Constitution does not explicitly mention education, the Tenth Amendment states that “the powers not delegated to the United States by the Constitution, nor prohibited by it to the States, are reserved to the States respectively, or to the people,” which has been widely interpreted as delegating primary authority and control over the regulation, governance, and operation of public schools to states (that said, many federal laws and regulations heavily influence the operation of public schools both directly and indirectly—see discussion below). The role that state governments and agencies play in school governance and management varies from state to state, with some states exerting more direct control over public schools and other states allowing local governing bodies to adopt policies and perform governance functions for the schools in their district or municipality. States that assign more responsibility over the governance and management of public schools to local governing bodies are often called “local-control states.” Historically, these states have generally deferred to local school boards and committees on governance issues, including many issues related to compliance with state statutes and regulations.

While local control takes a variety of forms from place to place—far too many to extensively catalog here—the following illustrative examples will serve to describe a few common forms of local control in the United States:

  • Regional school boards: Regional school boards and committees typically oversee the governance and operation of a school district that serves a variety of communities in a defined area. Membership is composed of locally elected representatives who sit on the board for a defined term of office, and membership is often apportioned in accordance with the population of the participating communities. Responsibilities can vary significantly from place to place, but common functions include the hiring and firing of superintendents, the development of school budgets, and the adoption of district policies. Some districts, it should be noted, may have multiple schools boards. For example, a district may have separate boards overseeing its elementary schools and its secondary schools, or a regional career and technical education center that serves students from one or more districts may have its own governing board.
  • Municipal school boards: Similar in structure and function to regional school boards, municipal school boards and committees oversee the governance and operations of public schools located in single town or city (given that larger cities have sizeable student populations, they are often defined as standalone school districts). In municipal school districts, governance responsibilities may be shared with other municipal bodies. For example, a school board may need to secure approval of its annual district budget from the city council, town council, or board of selectpersons.
  • Regional school unions: A regional school union is a confederation of multiple school boards representing specific towns and municipalities. Unlike a regional school board that is composed of elected representatives from the municipalities in a given district, school unions retain a distinct school board for each community. While responsibilities for governance and operations vary from place to place, school unions typically make collective decisions related to certain governance functions and independent decisions related to others. For example, schools unions may collectively hire the superintendent and district staff, approve an annual district budget, or set policy for a regional high school that serves students from all the participating communities, while also retaining individual autonomy and governance authority for the elementary and middle schools located in each participating town.
  • School-based governance: Local control also manifests in the form of school-based governance, which can take a wide variety of forms from school to school. For example, charter schools—privately operated schools funded partially or entirely by public money, often in the form of student tuition paid by states and communities—typically have their own distinct governance structure and board of directors. While charter schools are subject to state regulation, they may not need to comply with the policies governing public schools in the districts they are located in.

Reform

Local control can become the object of reform in a wide variety of ways. The following representative examples will serve to illustrate a few of the primary ways that local control may become targeted for reform:

  • Federal and state policies: Legislative bodies and governmental agencies at the federal and state levels may adopt new laws, regulations, and related compliance rules and requirements that influence the degree of control local bodies have over the governance and operation of public schools. While these policies are too numerous and complex to address here, federal and state policies can affect local control both directly and indirectly. For example, state governments may directly influence local control by taking steps to reduce the number of districts and school boards in a state, or they may adopt statewide graduation requirements for public-school students that directly affect the degree of control that school boards have to determine local graduation requirements for students. Other policies, such as high-stakes tests, have a more indirect influence on local control. In this case, schools may specifically prepare students to take a standardized test by teaching them the knowledge, skills, and test-taking strategies likely to increase their performance on a test (a phenomenon informally known as “teaching to the test”). While the schools are not required to teach the material that will be tested, the prospect of low scores and related consequences may nevertheless influence both how and what schools decide to teach.
  • Regionalization and consolidation: The consolidation of school districts and school boards is another common form of local-control reform. In many cases, elected officials, legislators, and policy makers attempt to consolidate or regionalize the governance of public schools in an effort to cut educational costs by reducing administrative staffing, closing offices or schools, and consolidating district operations such as accounting, transportation, maintenance, and purchasing. While lowering costs through the elimination of operational redundancies is the perhaps the most common rationale for consolidation, many other factors may influence the decision to regionalize school governance and operations, including the opportunity to improve, expand, or diversify school programming for students. In rural areas, for example, smaller schools, particularly high schools, with smaller budgets and student populations are financially unable to provide many of the programs, services, and learning opportunities available to students in larger schools, including a diversity of arts, world-language, athletics, and co-curricular programs. Consolidating with other towns and sending their students to a larger regional high school is one way that communities can offer their students a greater variety of educational programs and opportunities.
  • Assertion or reinstatement of local control: Local control may also be asserted by local governing bodies or reinstated after an unsuccessful attempt to consolidate districts, school boards, and public schools. In some states, efforts to consolidate school governance have been attempted, but have subsequently failed for any number of complex reasons, leading to the reinstatement of former district or school-board governance structures. In recent years, local actors have also attempted to assert greater control over public schools. One particularly high-profile example are so-called “parent trigger laws” that allow parents to intervene when the school their children attend is deemed “low performing” by the state. Although laws differ from state to state, they usually allow parent groups to create petitions that, with enough signatures, can “trigger” a variety of actions, such as converting a public school into a charter school, firing and replacing the school’s administration and faculty, or closing the school and sending its students to alternate schools. In addition, the proliferation and growing popularity of charter schools represents another way that local control is asserted, given that charter schools, though they are regulated by states, are often locally governed and managed (exceptions include virtual charter schools operated by out-of-state organizations and large corporations, and charter-school franchises that may be centrally managed from outside of the community in which a particular school is located).

Debate

Numerous historical, cultural, political, and legal factors can influence the structure and execution of local school governance, and the issue of local control can be extremely complicated, emotionally charged, and contentious in some communities, states, and regions. New England, for example, has a long history of local control over public schools that dates back to the colonial era, and local control is often a source of debate and conflict in the northeast, while state-directed control of public schools is less controversial or contentious in many southern states that do not have the same history of local control.

Local control also intersects with the legal concept of “state’s rights,” and feelings of skepticism or hostility directed at the federal government and federally administered programs. In recent years, local control of public schools has become a source of tensions and conflicts that are part of broader political and ideological schisms and debates in American society, such as disagreements related to role that state and federal governments should play in the lives of citizens.

While debates related to local control are both numerous and nuanced, the following examples are representative of a few major arguments for and against local control.

Reducing local control can:

  • Lower educational costs and improve efficiency of districts and schools. By eliminating administrative positions, closing offices, and consolidating district operations, and by centralizing many administrative and operational functions such as accounting, transportation, maintenance, and purchasing, the overall cost of public schooling will go down, taxpayers in states and communities will save money, and public schools can be run more efficiently and effectively.
  • Reduce bureaucracy. By eliminating and streamlining bureaucracy, school leaders will have more authority to make executive decisions related to academics, staffing, teaching, and school improvement.
  • Improve, expand, or diversify school programming. In rural areas with smaller schools, student populations, and district operating budgets, public schools do not have the resources to provide many of the programs, services, and learning opportunities that are available to students in larger schools.
  • Improve academic quality, educational consistency, and teaching effectiveness. Because new policies and requirements can enforce higher academic standards for students, and higher professional standards for administrators, teachers, and staff, reducing local control can improve school quality across a state or region.

Increasing local control can:

  • Improve academic quality and teaching effectiveness in a school. Because the school is being governed and managed by the individuals and institutions that are the most knowledgeable about and invested in the school and its educators, students, and communities, and because no one is more invested in the welfare and success of children than parents, teachers, and community members, locally controlled schools are more likely to act in the best interest of students.
  • Increase local pride, civic participation, and public and financial support for public schools. Because active participation in the governance process increase feelings of connectedness and ownership, locally controlled schools will benefit from greater community involvement and investment.
  • Improve teaching and student performance. Because school leaders and teachers in smaller schools with smaller classes know the backgrounds, learning needs, and aspirations of their students better than educators in larger schools with larger numbers of students, consolidating districts and schools could potentially lead to lower-quality teaching and lower student performance.

Autonomy

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In education, the concept of autonomy is perhaps most commonly discussed in reference to professional independence in schools, particularly the degree to which teachers can make autonomous decisions about what they teach to students and how they teach it. For a more detailed discussion of this issue, see teacher autonomy.

That said, the concept of autonomy in public education may take several different forms:

  • Local-governance autonomy: In education, the degree to which local governing bodies—such as school districts and school boards—can make independent decisions about how to structure and operate public schools is a common topic of study, discussion, and debate in the United States. Those who advocate for greater autonomy in the governance of schools tend to argue that the individuals and institutions closest to, most knowledgeable about, and most invested in a school—and in the welfare and success of its educators, students, and communities—are best suited to making important decisions related to operations, academics, leadership, teaching, and improvement. This general philosophy of governance is often contrasted with state or federal educational policies that are intended to influence the structure, operation, or academic programs in districts and public schools, given that autonomy in local governance is directly related to the level of prescription articulated in state and federal education laws, regulations, and related compliance rules and requirements. Autonomy in local governance also intersects with two related educational terms and concepts: “local control” and “site-based management,” both of which refer to the ability of local institutions and governing bodies to make autonomous decisions about the management of public schools. In some states and regions, local control is a complicated and often contentious issue. In New England, for example, there is a long history of local control over public schools, typically in the form of school boards or school unions, while state-directed control of public schools is less controversial or contentious in the southern states, which do not have the same history of local control over public schools. For a more detailed discussion, see local control.
  • School autonomy: The concept of autonomy also intersects with the governance and design of specific schools. For example, charter schools—privately operated schools funded partially or entirely by public money, often in the form of student tuition paid by states and communities—are generally considered to have more autonomy when it comes to making decisions about how the school will operate and teach students. Charter-school regulations, however, can differ significantly from state to state: some states have more prescriptive or involved regulations governing the operation of charter schools, while others have more permissive policies, lighter governmental oversight, and less demanding compliance requirements. As with issues related to local governance, the autonomy of individual public schools is directly related to the level of prescription articulated in state and federal education policies, regulations, and related compliance rules and requirements.
  • Teacher autonomy: The concept of “teacher autonomy” is a common topic of discussion and debate in education. Advocates of greater teacher autonomy may argue that because teachers are in the best position to make informed decisions about a student’s education, teachers should be given as much autonomy as possible when it comes to determining instructional strategies, curriculum, and academic support. In this view, for example, more regulations, tougher job requirements, greater administrative oversight, or more burdensome teacher-evaluation procedures will inevitability stifle the instructional creativity and responsiveness of teachers, which could produce a variety of negative results, including lower student performance or higher job dissatisfaction and attrition rates among teachers. Critics of teacher autonomy tend to cite evidence that teaching quality and effectiveness is uneven, and that problems such as achievement gaps or low graduation rates indicate that measures need to be taken to improve the effectiveness of teachers and public-school instruction, including more administrative oversight, increased educational and professional requirements for new teachers, stronger evaluation systems for job performance, or penalties for poor-performing teachers.
  • Parent autonomy: In recent years, the idea of parents playing a role in the operation and management of a school has become increasingly popular and contentious. While some debates are centered on the degree of control that parents should have over what gets taught to their children—particularly when it comes to subjects that are broadly contentious in American society, such as sex education or the teaching of evolution—others are focused on issues related to leadership and management. For example, so-called “parent trigger laws” allow parents to intervene when the school their children attend is deemed “low performing.” Although laws differ from state to state, they usually allow parent groups to create petitions that, with enough signatures, can “trigger” a variety of actions, such as converting a public school into a charter school, firing and replacing the school’s administration and faculty, or closing the school and sending its students to alternate schools. In some states, laws allow committees or councils of parents to play a role in the management of schools, which can even extend to participating in decisions related to the hiring and firing of school administrators. In many cases, however, parent committees play only an advisory role in a school or district, and their recommendations may or may not be acted upon.
  • Student autonomy: In recent years, educators have increasingly discussed and debated the degree to which students should be given more autonomy in the educational process. For example, the concept of  “student voice” is often used in reference to instructional approaches and techniques that take into consideration student choices, interests, passions, and ambitions. Some educators argue that students should play a more active role in designing or selecting learning experiences in schools, and that such approaches can encourage students to be more interested in school, more motivated to learn, and more likely to take greater responsibility over their education. In addition, the terms student autonomy or learner autonomy may refer to various theories of education that suggest learning improves when students take more control or responsibility over their own learning process. For related discussions, see differentiation, personalized learning, scaffoldingstudent-centered learning, and student engagement.

Cut-Off Score

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The term cut-off score refers to the lowest possible score on an exam, standardized test, high-stakes test, or other form of assessment that a student must earn to either “pass” or be considered “proficient.” In some cases, tests may have multiple cut-off scores representing tiered levels of proficiency, such as basic, proficient, or advanced. In education, cut-off scores may also be applied in certification and licensing exams that are used to determine whether educators and other school staff are professionally “qualified.”

Whether cut-off scores are set by individual teachers on course exams or determined by groups of experts using sophisticated psychometric methods on large-scale standardized tests, all cut-off scores are informed judgments based on either individual or collective opinion, and it is impossible to demonstrate that any particular cut score is unequivocally “correct.” In other words, cut-off scores are professional judgments that fall somewhere on a continuum between art and science, subjective and objective, and arbitrary and reasoned. For a more detailed discussion, see proficiency.

For standardized tests developed by testing companies and administered to large populations of students by states and national organizations—such as the SAT, ACT, or National Assessment of Educational Progress (NAEP), for example—cut-off scores are determined though a process generally called standard setting (for criterion-referenced tests) or norming (for norm-referenced tests). In a typical standard-setting process, a test developer will form a standard-setting panel by recruiting a group of experts, such as psychometricians (specialists in the science of educational measurement) or teachers from a relevant content area. The panel will then use one or more research-based methods, developed by psychometricians and academics, for setting testing standards and determining cut-off scores. The process typically entails reviewing test items (questions, problems, tasks), determining levels of difficulty for each item, and using a statistical process, based on collective opinion, to establish a cut-off score or a set of cut scores corresponding to different levels of “proficiency” (e.g., basic, proficient, or advanced). While the complexities and nuances of standard-setting are beyond the scope of this resource, many readily available papers, reports, and resources are dedicated to explaining the intricacies of the process, including A Primer on Setting Cut Scores on Tests of Educational Achievement by Educational Testing Service.

When teachers create and grade tests or other assignments, cut-off scores necessarily rely more heavily on individual professional judgment. In addition, the criteria used to determine cut-off scores can vary widely. For example, historical precedent is often used to establish cut scores for course exams and assignments—e.g., a score of 70 has long been considered a “passing” score in many schools, regardless of the content of the test, how it was designed, or what the score represents in terms of academic achievement. The same passing score of 70 may also be applied to different types of assessments that are evaluated in different ways. For example, a score of 70 on a multiple-choice test may be determined using a simple mathematical formula—70 percent of the questions were answered correctly and 30 percent incorrectly. Yet a grade of 70 on science project or written essay may require a far more nuanced judgment about the content and quality of the work, which might be based on a single teacher’s professional opinion, for example, or on clearly defined criteria described in a rubric or scoring guide that several teachers use to evaluate student work in a more consistent manner from student to student or course to course.

Debate

Cut-off scores may become an extension of ongoing debates related to high-stakes testing—i.e., the use of tests to make important decisions about students, educators, schools, or districts. For example, “high stakes” test scores may be used to determine punishments (such as sanctions, penalties, funding reductions, negative publicity for districts and schools), accolades (awards, public celebration, positive publicity), advancement (grade promotion or graduation decisions for students), or compensation (salary increases or bonuses for administrators and teachers). High-stakes testing is one of the most controversial and contentious issues in education today, and because the consequences or benefits tied to cut-off  scores on these tests are—at their origin—based on judgments made by a relatively small number of people, cut-off scores can become the object of debate, particularly if they are perceived to be incomplete, flawed, or unfair. For more detailed discussions, see measurement error, test bias, and score inflation.

In addition, cut-off scores—and the bar for proficiency they represent—can diverge significantly from system to system, state to state, test to test, school to school, and course to course, or from year to year when changes are made to learning standards and accompanying tests. All proficiency levels change in direct relation to the methods used to determine cut-off scores. It is therefore possible, for example, to alter the perception of student “proficiency” by raising or lowering cut-off scores on tests, or by changing the process or criteria used to determine them. In fact, some states have been accused of manipulating the perception of student proficiency by lowering cut-off scores or developing tests that are based on low standards—e.g., an eleventh-grade test that evaluates student performance based on content knowledge and skills they should have learned in eighth grade. For these reasons, proficiency determinations based on cut-off scores may become a source of confusion, debate, controversy, and even deception.

Psychometricians, researchers, and other specialists specific may also debate the specific standards-setting processes used to determine cut-off scores on standardized tests, but these debates rarely extend beyond academia.

Standards-Based

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In education, the term standards-based refers to systems of instruction, assessment, grading, and academic reporting that are based on students demonstrating understanding or mastery of the knowledge and skills they are expected to learn as they progress through their education. In schools that use standards-based approaches to educating students, learning standards—i.e., concise, written descriptions of what students are expected to know and be able to do at a specific stage of their education—determine the goals of a lesson or course, and teachers then determine how and what to teach students so they achieve the learning expectations described in the standards.

In the United States, most standards-based approaches to educating students use state learning standards to determine academic expectations and define “proficiency” in a given course, subject area, or grade level. The general goal of standards-based learning is to ensure that students are acquiring the knowledge and skills that are deemed to be essential to success in school, higher education, careers, and adult life. If students fail to meet expected learning standards, they typically receive additional instruction, practice time, and academic support to help them achieve proficiency or meet the learning expectations described in the standards. Standards-based learning is common in American elementary schools, but it is becoming more widely used in middle and secondary schools.

In most cases, standards-based learning, standards-based instruction, or standards-based education, among other similar terms, are synonyms for proficiency-based learning or competency-based learning (two terms that are themselves synonymous). Defining standards-based learning is further complicated by the fact that educators not only use a wide variety of terms for the general approach, but the terms may or may not be used synonymously from place to place. A few of the other common synonyms include mastery-based, outcome-based, and performance-based education, instruction, or learning, among others. In addition, there is a subtle but significant difference between standards-based and standards-reference—see the explanation below.

Standards-Based vs. Standards-Referenced

The distinction between standard-based and standards-referenced is often a source of confusion among educators and the public—in part because the terms are sometimes used interchangeably, but also because the distinction between the two is both subtle and nuanced. In brief, standards-referenced means that what gets taught or tested is “referenced” to or derived from learning standards (i.e., standards are the source of the content and skills taught to students—the original “reference” for the lesson), while standards-based refers to the practice of making sure students learn what they were taught and actually achieve the expected standards (i.e., that students meet a defined standard for “proficiency”). In a standards-referenced system, teaching and testing are guided by standards; in a standards-based system, teachers work to ensure that students actually learn the expected material as they progress in their education.

Another way of looking at it is that standards-referenced refers to inputs (what is taught) and standards-based is focused on outputs (what is learned).

While a particular course may be standards-referenced, for example, it doesn’t necessarily mean that it is standards-based in the sense that the term is predominately used by educators. However, all standards-based curricula, instruction, and tests are—by necessity—standards-referenced. For example, all fifty states in the United States have developed and adopted learning standards that schools and teachers are expected to follow when they create academic programs, courses, and other learning experiences (before the 1980s and 1990s, states did not have learning standards). In theory, these educational policies suggest that all American public schools either are or should be teaching a standards-referenced curriculum. Yet comparatively few public schools are authentically standards-based in the sense that students are required to demonstrate achievement of expected standards, and meet defined proficiency expectations, as they progress through their education. For a more detailed discussion, see proficiency-based learning.

The following examples will help to illustrate the distinction between standards-based and standards-referenced:

  • Assessment: Say a teacher designs a standards-referenced test for a history course. While the content of the test may be entirely standards-referenced—i.e., it is aligned with the expectations described in learning standards—a score of 75 may be considered a passing score, suggesting that 25 percent of the taught material was not actually learned by the students who scored a 75. In addition, if only test scores and assignments are summed and averaged, the teacher may not know what specific standards students have or have not met. For example, a student may be able to earn a “passing” grade in a ninth-grade English course, but still be unable to “demonstrate command of the conventions of standard English grammar and usage when writing and speaking” or “demonstrate understanding of figurative language, word relationships, and nuances in word meanings”—two ninth-grade standards taken from the Common Core State Standards. If the teacher uses a standards-based approach to assessment, however, students would only “pass” a test or course after demonstrating that they have learned the knowledge and skills described in the expected standards. The students may need to retake a test several times or redo an assignment, or they may need additional help from the teacher or other educational specialist, but the students would need to demonstrate that they learned what they were expected to learn—i.e., the specific knowledge and skills described in standards.
  • Curriculum: In most high schools, students typically earn credit for passing a course, but a passing grade may be an A or it may be a D, suggesting that the awarded credit is based on a spectrum of learning expectations—with some students learning more and others learning less—rather than on the same learning standards being applied to all students equally. And because grades may be calculated differently from school to school or teacher to teacher, and they may be based on different learning expectations (for example, some courses may be “harder” and others “easier”), students may pass their courses, earn the required number of credits, and receive a diploma without acquiring the most essential knowledge and skills described in standards. In these cases, the curricula taught in these schools may be standards-referenced, but not standards-based, because teachers are not evaluating whether students have achieved specific standards. In standards-based schools, courses, and programs, however, educators will use a variety of instructional and assessment methods to determine whether students have met the expected standards, including strategies such as demonstrations of learningpersonal learning plansportfoliosrubrics, and capstone projects, to name just a few.
  • Grading: In a standards-referenced course, grading may look like it traditionally has in schools: students are given numerical scores on a 1–100 scale and class grades represent an average of all scores earned over the course of a semester or year. In a standards-based course, however, “grades” often look quite different. While standards-based grading and reporting may take a wide variety of forms from school to school, grades are typically connected to descriptive standards, not based on test and assignment scores that are averaged together. For example, students may receive a report that shows how they are progressing toward meeting a selection of standards. The criteria used to determine what “meeting a standard” means will defined in advance, often in a rubric, and teachers will evaluate learning progress and academic achievement in relation to the criteria. The reports students receive might use a 1–4 scale, for example, with 3s and 4s indicating that students have met the standard. In standards-based schools, grades for behaviors and work habits—e.g., getting to class on time, following rules, treating other students respectfully, turning in work on time, participating in class, putting effort into assignments—are also reported separately from academic grades, so that teachers and parents can make distinctions between learning achievement and behavioral issues. See the following example of a standards-based report card:

Sample_Standards-Based_Report_Card

Competency-Based Learning

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Competency-based learning refers to systems of instruction, assessment, grading, and academic reporting that are based on students demonstrating that they have learned the knowledge and skills they are expected to learn as they progress through their education. In public schools, competency-based systems use state learning standards to determine academic expectations and define “competency” or “proficiency” in a given course, subject area, or grade level (although other sets of standards may also be used, including standards developed by districts and schools or by subject-area organizations). The general goal of competency-based learning is to ensure that students are acquiring the knowledge and skills that are deemed to be essential to success in school, higher education, careers, and adult life. If students fail to meet expected learning standards, they typically receive additional instruction, practice time, and academic support to help them achieve competency or meet the expected standards.

Defining competency-based learning is complicated by the fact that educators not only use a wide variety of terms for the general approach, but the terms may or may not be used synonymously from place to place. A few of the more common synonyms include proficiency-basedmastery-basedoutcome-basedperformance-based, and standards-based education, instruction, and learning, among others.

In practice, competency-based learning can take a wide variety of forms from state to state or school to school—there is no single model or universally used approach. While schools often create their own competency-based systems, they may also use systems, models, or strategies created by state education agencies or outside educational organizations. Competency-based learning is more widely used at the elementary level, although more middle schools and high schools are adopting the approach. As with any educational strategy, some competency-based systems may be better designed or more effective than others.

Recently, the terms competency-based learning or competency-based education (and related synonyms) have become more widely used by (1) online schools or companies selling online learning programs, and (2) colleges and universities, particularly those offering online degree programs. It should be noted that “competency-based learning,” as it is typically designed and implemented in K–12 public schools, can differ significantly from the forms of “competency-based learning” being offered and promoted by online schools and postsecondary-degree programs. At the collegiate level, for example, competency-based learning may entail prospective adult students receiving academic credit for knowledge and skills they acquired in their former careers—an approach that can reduce tuition costs and accelerate their progress toward earning a degree. It should also be noted that many online schools and educational programs, at the both the K–12 and higher-education levels, have also become the object of criticism and debate. Many for-profit virtual schools and online degree programs, for example, have been accused of offering low-quality educational experiences to students, exploiting students or public programs, and using the popularity of concepts such as “competency-based education” to promote programs of dubious educational value. When investigating or reporting on competency-based education, it is important to determine precisely how the terms are being used in a specific context.

Reform

Competency-based learning is generally seen as an alternative to more traditional educational approaches in which students may or may not acquire proficiency in a given course or academic subject before they earn course credit, get promoted to the next grade level, or graduate. For example, high school students typically earn academic credit by passing a course, but a passing grade may be an A or it may be a D, suggesting that the awarded credit is based on a spectrum of learning expectations—with some students learning more and others learning less—rather than on the same consistent standards being applied to all students equally. And since grades may be calculated differently from school to school or teacher to teacher, and they may be based on divergent learning expectations (i.e., some courses might be “harder” and others “easier”), it may be possible for students to pass their courses, earn the required number of credits, and receive a diploma without acquiring important knowledge and skills. In extreme cases, for example, students may be awarded a high school diploma but still be unable to read, write, or do math at a basic level. A “competency-based diploma” would be a diploma awarded to students only after they have met expected learning standards.

While the goal of competency-based learning is to ensure that more students learn what they are expected to learn, the approach can also provide educators with more detailed or fine-grained information about student learning progress, which can help them more precisely identify academic strengths and weakness, as well as the specific concepts and skills students have not yet mastered. Since academic progress is often tracked and reported by learning standard in competency-based courses and schools, educators and parents often know more precisely what specific knowledge and skills students have acquired or may be struggling with. For example, instead of receiving a letter grade on an assignment or test, each of which may address a variety of standards, students are graded on specific learning standards, each of which describes the knowledge and skills students are expected to acquire.

When schools transition to a competency-based system, it can entail significant changes in how a school operates and how it teaches students, affecting everything from the school’s educational philosophy and culture to its methods of instruction, testing, grading, reporting, promotion, and graduation. For example, report cards may be entirely redesigned, and schools may use different grading scales and systems, such as replacing letter grades with brief descriptive statements—e.g., phrases such as does not meetpartially meetsmeets the standard, and exceeds the standard are commonly used in competency-based schools (although systems vary widely in design, purpose, and terminology). Schools may also use different methods of instruction and assessment to determine whether students have achieved competency, including strategies such as demonstrations of learninglearning pathwayspersonal learning plansportfoliosrubrics, and capstone projects, to name just a few.

Debate

While there is a widespread agreement that students should be held to high academic expectations, and that public schools and teachers should make sure that students acquire the most important knowledge and skills they will need to succeed in adult life, there is often disagreement and debate about the best way to achieve these goals. For this reason, debates about competency-based learning tend to be focused on the methods used by schools, rather than the overall objective of the strategy (i.e., all students meeting high standards and achieving proficiency—a goal that few dispute).

Proponents of competency-based learning may argue that the approach greatly improves the chances that students will learn the most critically important knowledge, concepts, and skills they will need throughout their lives, and that competency-based learning can help to eliminate persistent learning gapsachievement gaps, and opportunity gaps. For these reasons, advocates of competency-based learning argue that the practice is a more equitable approach to public education, since it holds all students to the same high standards regardless of their race, ethnicity, gender, or socioeconomic status, or whether they attend schools in poor or affluent communities (uneven standards being applied to minority and non-minority students, or the uneven quality of teaching and facilities from school to school, are believed to be major contributing causes of issues such as achievement gaps). Proponents may also point to the weaknesses or failures of existing systems—which allow students to get promoted from one grade to the next and earn a diploma without acquiring important knowledge and skills—as evidence that competency-based approaches, of whatever sort, are needed. For a related discussion, see social promotion.

Critics of competency-based learning may argue that the transition will require already overburdened teachers to spend large amounts of time—and possibly uncompensated time—on extra planning, preparation, and training, and that competency-based learning can be prohibitively difficult to implement, particularly at a statewide level. Critics may also take issue with the learning standards that competency-based systems utilize, or with the specific features of a system used in a particular school. For example, parents often express concern that the abandonment of traditional letter grades, report cards, transcripts, and other familiar academic-reporting strategies will disadvantage students who are applying to colleges and universities (because the reporting strategies will be unfamiliar to college-admissions professionals, or because competency-based systems may eliminate many of the competitive dimensions of academic achievement, such as GPAs or class rank, that tend to favor high-achieving students). Others may question whether there is sufficient evidence that competency-based learning will actually work as intended.

Student Engagement

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In education, student engagement refers to the degree of attention, curiosity, interest, optimism, and passion that students show when they are learning or being taught, which extends to the level of motivation they have to learn and progress in their education. Generally speaking, the concept of “student engagement” is predicated on the belief that learning improves when students are inquisitive, interested, or inspired, and that learning tends to suffer when students are bored, dispassionate, disaffected, or otherwise “disengaged.” Stronger student engagement or improved student engagement are common instructional objectives expressed by educators.

In many contexts, however, student engagement may also refer to the ways in which school leaders, educators, and other adults might “engage” students more fully in the governance and decision-making processes in school, in the design of programs and learning opportunities, or in the civic life of their community. For example, many schools survey students to determine their views on any number of issues, and then use the survey findings to modify policies or programs in ways that honor or respond to student perspectives and concerns. Students may also create their own questions, survey their peers, and then present the results to school leaders or the school board to advocate for changes in programs or policies. Some schools have created alternative forms of student governance, “student advisory committees,” student appointments to the school board, and other formal and informal ways for students to contribute to the governance of a school or advise superintendents, principals, and local policy makers. These broader forms of “student engagement” can take a wide variety of forms—far too many to extensively catalog here. Yet a few illustrative examples include school-supported volunteer programs and community-service requirements (engaging students in public service and learning through public service), student organizing (engaging students in advocacy, community organizing, and constructive protest), and any number of potential student-led groups, forums, presentations, and events (engaging students in community leadership, public speaking, and other activities that contribute to “positive youth development“). For a related discussion, see student voice.

In education, the term student engagement has grown in popularity in recent decades, most likely resulting from an increased understanding of the role that certain intellectual, emotional, behavioral, physical, and social factors play in the learning process and social development. For example, a wide variety of research studies on learning have revealed connections between so-called “non-cognitive factors” or “non-cognitive skills” (e.g., motivation, interest, curiosity, responsibility, determination, perseverance, attitude, work habits, self-regulation, social skills, etc.) and “cognitive” learning results (e.g., improved academic performance, test scores, information recall, skill acquisition, etc.). The concept of student engagement typically arises when educators discuss or prioritize educational strategies and teaching techniques that address the developmental, intellectual, emotional, behavioral, physical, and social factors that either enhance or undermine learning for students.

It should be noted that educators may hold different views on student engagement, and it may be defined or interpreted differently from place to place. For example, in one school observable behaviors such as attending class, listening attentively, participating in discussions, turning in work on time, and following rules and directions may be perceived as forms of “engagement,” while in another school the concept of “engagement” may be largely understood in terms of internal states such as enthusiasm, curiosity, optimism, motivation, or interest.

While the concept of student engagement seems straightforward, it can take fairly complex forms in practice. The following examples illustrate a few ways in which student engagement may be discussed or addressed in schools:

  • Intellectual engagement: To increase student engagement in a course or subject, teachers may create lessons, assignments, or projects that appeal to student interests or that stimulate their curiosity. For example, teachers may give students more choice over the topics they are asked to write about (so students can choose a topic that specifically interests them) or they may let students choose the way they will investigate a topic or demonstrate what they have learned (some students may choose to write a paper, others may produce short video or audio documentary, and still others may create a multimedia presentation). Teachers may also introduce a unit of study with a problem or question that students need to solve. For example, students might be asked to investigate the causes of a local environmental problem, determine the species of an unknown animal from a few short descriptions of its physical characteristics and behaviors, or build a robot that can accomplish a specific task. In these cases, sparking student curiosity can increase “engagement” in the learning process. For related discussions, see authentic learning, community-based learning, differentiation, personalized learning, project-based learning, and relevance.
  • Emotional engagement: Educators may use a wide variety of strategies to promote positive emotions in students that will facilitate the learning process, minimize negative behaviors, or keep students from dropping out. For example, classrooms and other learning environments may be redesigned to make them more conducive to learning, teachers may make a point of monitoring student moods and asking them how they are feeling, or school programs may provide counseling, peer mentoring, or other services that generally seek to give students the support they need to succeed academically and feel positive, optimistic, or excited about school and learning. Strategies such as advisories, for example, are intended to build stronger relationships between students and adults in a school. The basic theory is that students will be more likely to succeed if at least one adult in the school is meeting with a student regularly, inquiring about academic and non-academic issues, giving her advice, and taking an interest in her out-of-school life, personal passions, future aspirations, and distinct learning challenges and needs.
  • Behavioral engagement: Teachers may establish classroom routines, use consistent cues, or assign students roles that foster behaviors more conducive to learning. For example, elementary school teachers may use cues or gestures that help young students refocus on a lesson if they get distracted or boisterous. The teacher may clap three times or raise a hand, for example, which signals to students that it’s time to stop talking, return to their seats, or begin a new activity. Teachers may also establish consistent routines that help students stay on task or remain engaged during a class. For example, the class may regularly break up into small groups or move their seats into a circle for a group discussion, or the teacher may ask students on a rotating basis to lead certain activities. By introducing variation into a classroom routine, teachers can reduce the monotony and potential disengagement that may occur when students sit in the same seat, doing similar tasks, for extended periods of time. Research on brain-based learning has also provided evidence that variation, novelty, and physical activity can stimulate and improve learning. For a related discussion, see classroom management.
  • Physical engagement: Teachers may use physical activities or routines to stimulate learning or interest. For example, “kinesthetic learning” refers to the use of physical motions and activities during the learning process. Instead of asking students to answer questions aloud, a teacher might ask students to walk up to the chalkboard and answer the question verbally while also writing the answer on the board (in this case, the theory is that students are more likely to remember information when they are using multiple parts of the brain at the same time—i.e., the various parts dedicated to speaking, writing, physical activity, etc.). Teachers may also introduce short periods of physical activity or quick exercises, particularly during the elementary years, to reduce antsy, fidgety, or distracted behaviors. In addition, more schools throughout the United States are addressing the physical needs of students by, for example, offering all students free breakfasts (because disengagement in learning and poor academic performance have been linked to hunger and malnutrition) or starting school later at a later time (because adolescent sleep patterns and needs differ from those of adults, and adolescents may be better able to learn later in the morning).
  • Social engagement: Teachers may use a variety of strategies to stimulate engagement through social interactions. For example, students may be paired or grouped to work collaboratively on projects, or teachers may create academic contests that students compete in—e.g., a friendly competition in which teams of students build robots to complete a specific task in the shortest amount of time. Academic and co-curricular activities such as debate teams, robotics clubs, and science fairs also bring together learning experiences and social interactions. In addition, strategies such as demonstrations of learning or capstone projects may require students to give public presentations of their work, often to panels of experts from the local community, while strategies such as community-based learning or service learning (learning through volunteerism) can introduce civic and social issues into the learning process. In these cases, learning about societal problems, or participating actively in social causes, can improve engagement.
  • Cultural engagement: Schools may take active steps to make students from diverse cultural backgrounds—particularly recently arrived immigrant or refugee students and their families—feel welcomed, accepted, safe, and valued. For example, administrators, teachers, and school staff may provide special orientation sessions for their new-American populations or offer translation services and informational materials translated into multiple languages. Students, families, and local cultural leaders from diverse backgrounds may be asked to speak about their experiences to students and school staff, and teachers may intentionally modify lessons to incorporate the history, literature, arts, and perspectives of the student ethnicities and nationalities represented in their classes. School activities may also incorporate multicultural songs, dances, and performances, while posters, flags, and other educational materials featured throughout the school may reflect the cultural diversity of the students and school community. The general goal of such strategies would be to reduce the feelings of confusion, alienation, disconnection, or exclusion that some students and families may experience, and thereby increase their engagement in academics and school activities. For related discussions, see dual-language education, English-language learnermulticultural education, and voice.

Hidden Curriculum

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Hidden curriculum refers to the unwritten, unofficial, and often unintended lessons, values, and perspectives that students learn in school. While the “formal” curriculum consists of the courses, lessons, and learning activities students participate in, as well as the knowledge and skills educators intentionally teach to students, the hidden curriculum consists of the unspoken or implicit academic, social, and cultural messages that are communicated to students while they are in school.

The hidden-curriculum concept is based on the recognition that students absorb lessons in school that may or may not be part of the formal course of study—for example, how they should interact with peers, teachers, and other adults; how they should perceive different races, groups, or classes of people; or what ideas and behaviors are considered acceptable or unacceptable. The hidden curriculum is described as “hidden” because it is usually unacknowledged or unexamined by students, educators, and the wider community. And because the values and lessons reinforced by the hidden curriculum are often the accepted status quo, it may be assumed that these “hidden” practices and messages don’t need to change—even if they are contributing to undesirable behaviors and results, whether it’s bullying, conflicts, or low graduation and college-enrollment rates, for example.

It should be noted that a hidden curriculum can reinforce the lessons of the formal curriculum, or it can contradict the formal curriculum, revealing hypocrisies or inconsistencies between a school’s stated mission, values, and convictions and what students actually experience and learn while they are in school. For example, a school may publicly claim in its mission or vision statement that it’s committed to ensuring that all students succeed academically, but a review of its performance data may reveal significant racial or socioeconomic discrepancies when it comes to test scores, graduation rates, and other measures of success. And because what is not taught in school can sometimes be as influential or formative as what is taught, the hidden curriculum also extends to subject areas, values, and messages that are omitted from the formal curriculum and ignored, overlooked, or disparaged by educators.

While the hidden curriculum in any given school encompasses an enormous variety of potential intellectual, social, cultural, and environmental factors—far too many to extensively catalog here—the following examples will help to illustrate the concept and how it might play out in schools:

  • Cultural expectations: The academic, social, and behavioral expectations established by schools and educators communicate messages to students. For example, one teacher may give tough assignments and expect all students to do well on those assignments, while another teacher may give comparatively easy assignments and habitually award all students passing grades even when their work quality is low. In the high-expectations class, students may learn much more and experience a greater sense of accomplishment, whereas students in the low-expectations class may do just enough work to get by and be comparatively uninterested in the lessons they are being taught. Similarly, schools may unconsciously hold students from different cultural backgrounds—for example, minorities, recently arrived immigrant students, or students with disabilities—to lower academic expectations, which may have unintended or negative effects on their academic achievement, educational aspirations, or feelings of self-worth.
  • Cultural values: The values promoted by schools, educators, and peer groups, such as cliques, may also convey hidden messages. For example, some schools may expect and reward conformity while punishing nonconformity, whereas other schools might celebrate and even encourage nonconformity. In one school, students may learn that behaviors such as following the rules, acting in expected ways, and not questioning adults are rewarded, while in other schools students learn that personal expression, taking initiative, or questioning authority are valued and rewarded behaviors. Similarly, if biased or prejudicial behaviors and statements are tolerated in a school, students may embrace the values that are accepted or modeled—either explicitly or implicitly—by adults and other students.
  • Cultural perspectives: How schools recognize, integrate, or honor diversity and multicultural perspectives may convey both intentional and unintended messages. For example, some schools may expect recently arrived immigrant students and their families to “assimilate” into American culture—for example, by requiring the students to speak English in school at all times or by not providing translated informational materials or other specialized assistance. Other schools, however, may actively integrate or celebrate the multicultural diversity of the student body by inviting students and parents to share stories about their home country, for example, or by posting and publishing informational materials in multiple languages. In one school, non-American cultures may be entirely ignored, while in another they may be actively celebrated, with students and their families experiencing feelings of either isolation or inclusion as a result.
  • Curricular topics: The subjects that teachers choose for courses and lessons may convey different ideological, cultural, or ethical messages. For example, the history of the United States may be taught in a wide variety of ways using different historical examples, themes, and perspectives. A teacher may choose to present the history of the world or the United States from the perspective of the European settlers and explorers, or she may choose to present it from the perspective of displaced Native Americans or colonized African and Asian peoples. In the first case, teaching American history from a strictly Eurocentric perspective would likely minimize or ignore the history and suffering of Native Americans (a common educational practice in past decades). Curricular topics may also often intersect with, or be influenced by, political, ideological, and moral differences that are broadly contentious in American society—e.g., teaching evolution in science courses, multiculturalism in social studies, or sex education in health courses.
  • Teaching strategies: The way that schools and teachers choose to educate students can convey both intentional and unintended messages. For example, if students earn good grades or extra credit for turning in homework on time, listening attentively, participating during class, raising their hands, and generally doing things they are told to do, the students may learn that compliance is important and that certain behaviors will be academically rewarded and allowed to compensate for learning deficiencies. On the other hand, instructional strategies such as project-based learning or community-based learning, to name just two of many possible options, may communicate specific messages—for example, that skills such as critical thinking and problem solving, and attributes such as persistence, resourcefulness, and self-motivation, are valued and important (in the case of project-based learning) or that being informed about and involved in local issues are valued and important (in the case of community-based learning).
  • School structures: The way that a school or academic program is organized and operated can convey messages to students. For example, if non-English-speaking students are largely separated from their peers for most of the school day, or students with physical or learning disabilities are enrolled in specialized programs that are relegated to windowless classrooms in the basement, these organizational decisions may have unintended effects on the students’ sense of cultural belonging, self-worth, or academic potential. In addition, the structure of a school program can also mirror or reinforce cultural biases or prejudices. For example, students of color and students from lower-income households are often disproportionately represented in lower-level courses, and special-education programs may inadvertently reinforce some of the social stigmas that children and adults with disabilities experience outside of school.
  • Institutional rules: The formal rules in a school may communicate a wide variety of intentional and unintentional messages to students. For example, some schools require students to wear school uniforms, some ban certain types of attire (short skirts, clothing with images and language considered to be inappropriate), and others have very liberal or permissive clothing policies. While the intent of formal school rules and policies is to tell students how they are expected to behave, the degree to which they are enforced or unenforced, or the ways in which they are enforced, may communicate messages the undermine or contradict their stated intent. In this case, stricter dress-code policies may communicate that students will be judged on appearances both inside and outside of school, while looser policies might communicate that they will be judged on other qualities.

Reform

Generally speaking, the concept of a hidden curriculum in schools has become more widely recognized, discussed, and addressed by school leaders and educators in recent decades. Ideas such as “white privilege,” equity, voice, and multicultural education—to name just a few—have arguably led to greater tolerance, understanding, and even celebration of racial,cultural. physical, and cognitive differences in public schools. In addition, school communities, educators, and students are more likely than in past decades to actively and openly reflect on or question their own assumptions, biases, and tendencies, either individually or as a part of a formal school policy, program, or instructional activity. For example, topics such a bullying and diversity are now regularly discussed in public schools, and academic lessons, assignments, readings, and materials are now more likely to include multicultural perspectives, topics, and examples. Political and social pressures, including factors such as the increased scrutiny that has resulted from online media and social networking, may also contribute to greater awareness of unintended lessons and messages in schools. For example, harmful, hurtful, or unhealthy student behaviors are now regularly surfaced on social-networking sites such as Facebook or Twitter, which often leads to greater awareness of student behaviors or social trends.

That said, a “hidden curriculum” is, by nature, obscured or unacknowledged, which means that many of its lessons and messages are difficult to perceive or measure for any number of reasons. For example, long-standing policies may become so deeply embedded in a school culture that people simply forget to question them, or a school faculty that prides itself on celebrating multicultural diversity may find it emotionally difficult to acknowledge and openly discuss behaviors that might contradict that self-perceived identity. For this reason, every school will always have some form of hidden curriculum.