Visibility for Indigenous Students and Their Languages: Analysis of Home Language Data in Federal Reports across Seven U.S. States

Abstract

There is an increasing number of children in the U.S. classified as English Learners (ELs). Accurately identifying and supporting ELs in their academic settings entails understanding their non-English language experiences. This study presents findings from language reporting practices from seven U.S. states by examining how states account for the linguistic diversity of Indigenous Mesoamerican languages. Our findings reveal varied state approaches and underscore the limitations of current federal guidance, which limits the recognition of students’ non-English language experiences. We advocate for updating language identification practices and policies and propose a new framework for accurate language identification and continuous monitoring of student linguistic diversity.

1. Introduction

The history of the linguistic landscape of the United States (U.S.) reflects a varied and complex multilingual reality (Ovando 2003; Rumbaut and Massey 2013; Umansky et al. 2022). English monolingualism has never been the norm. Members of Native American communities have been historically multilingual, possessing communicative skills in both tribal languages and lingua francas such as Chinuk Wawa and Plains Indians Sign Language (Campbell 1997; Wiley and Wright 2004; Davis 2010; Gall et al. 2021). Therefore, multilingualism and linguistic diversity in the U.S. is not a new topic, as the languages used at home have varied throughout history (Nieto 2009). Current U.S. demographics continue to demonstrate marked diversity in terms of race, ethnicity, and language (U.S. Census Bureau 2023, n.d.). Notably, young children speaking languages other than English at home are the fastest-growing subgroup in the U.S. (National Academies of Sciences, Engineering, and Medicine 2017). This diverse group includes children both U.S.-born and born elsewhere, encompassing various Indigenous languages from North America and beyond (Kroskrity 2018; Mackey 2012).

The educational experiences of these children learning more than one language in the U.S. are regulated by a combination of federal policies, including civil rights laws and special education mandates (Bilingual Education Act [BEA] 1968; Lau v. Nichols 1974; Mancilla-Martinez et al. 2023; Soto-Boykin et al. 2023). Depending on the context, these children are designated with a wide range of different labels like English learners, dual-language learners, multilingual learners, etc. (Hammer et al. 2014; Umansky and Reardon 2014). Specifically, in U.S. schools, the federal designation for multilingual children in K–12 settings is English learner (EL), although it is not applied universally to multilingual children. EL classification is assigned to children who have been identified as having exposure to languages other than English and have undergone a formal evaluation process that entitled them to English language support services (ESSA 2015; Linquanti et al. 2013; Umansky and Porter 2020; Umansky and Reardon 2014).

Prior research underscores the importance of knowing children’s language use and language history beyond their EL status (Bedore et al. 2016; Castilla-Earls et al. 2020; Paradis et al. 2010). Notably, there is a call to prepare educators and related service providers to create educational practices that value and leverage students’ language and cultural experiences to enhance their academic outcomes (Hammer and Limlingan 2021; Vázquez-Montilla et al. 2014). Attention has been paid to the process and survey tools used to identify potential ELs. However, there is a need to focus efforts on improving the current process that enables or hinders accurate identification of the EL student’s non-English language. Since a non-English language is the first step that determines if a child will be further evaluated to determine the need for EL classification and influences their academic trajectory, it is paramount to probe this language identification process further. Verification of a child’s language history is also important in addressing the multidimensional issue of disproportionality and the challenges of underidentification and overidentification of children who use languages other than English for special education services (Artiles et al. 2010; Counts et al. 2018; Mancilla-Martinez et al. 2023; Morgan et al. 2015). Inaccurate language information can potentially lead to misdiagnosing a child with a language or learning disability, rather than identifying a language learning difference that can be attributed to influence from their primary language (Ebert and Kohnert 2016; Castilla-Earls et al. 2019). Thus, there is a need to investigate the contextual factors at both the state and federal levels, as well as the policies and guidelines available for schools to use in the accurate identification of native languages, the federal term used to refer to non-English home languages (U.S. Department of Education 2023).

Presently, there are 5 million children in the U.S. classified as Els, and approximately 75% of these children are documented to use Spanish in their homes (NCES 2023). In this paper, we argue that this high percentage of presumed Spanish speakers is questionable. To do so, we delve into the linguistic diversity of Indigenous peoples in the region of Mesoamerica, a region that spans the southern half of what is now Mexico and into about a third of Central America, and where hundreds of Indigenous languages unrelated to Spanish are spoken. We analyze data from Title III home languages reporting from seven states that show that few of these Indigenous languages are accounted for in federal reporting. This analysis contributes to the emerging literature focused on bringing visibility to Indigenous Mesoamerican communities, who contribute to the social and economic fabric of the U.S. (consult Martinez et al. 2021; Campbell-Montalvo 2023), and to the established literature on the country’s linguistic diversity. Specifically, this paper advocates for a granular documentation of students’ linguistic repertoires not only to accurately identify Els, but, more importantly, to improve assessment practices among students who might not be developing in line with the norm of Spanish-speakers learning English.

1.1. Overview of Legislation, Policies, and Practices for EL Education

To safeguard the educational rights of ELs, federal laws, policies, and landmark court decisions have created an intricate system that safeguards the educational experiences of ELs. Among the most influential are Title VI (2017) of the Civil Rights Act of 1964, the Equal Educational Opportunities Act (EEOA) of 1974, the Supreme Court rulings in the case of Lau v. Nichols (1974), Castañeda v. Pickard (1981), Plyler v. Doe (1982), and Every Student Succeeds Act (ESSA) of 2015. These regulations and laws mandate that U.S. public schools create accessible educational programs for ELs, overseen by the Educational Opportunities Section within the Civil Rights Division of the U.S. Department of Justice (U.S. Department of Justice 2023).

Title VI of the Civil Rights Act of 1964 initially prohibited discrimination based on race, color, and national origin, which was then extended to children whose primary language was not English. The Bilingual Education Act [BEA], known as Title VII of the Elementary and Secondary Education Act (ESEA), enacted in 1968, allocated federal funds to school districts for bilingual programs supporting students categorized as having limited proficiency in the English. Stricter requirements for supporting ELs in education settings came in the form of court rulings and legislation: Lau v Nichols (1974), Castañeda v. Pickard (1981), and Plyler v. Doe (1982). Lau v. Nichols (1974) affirmed that educational programs must ensure ELs’ meaningful participation in academic content regardless of their primary language, leading to the codification of these principles in the EEOA of 1974. The EEOA (1974) specifically required school districts to accommodate students regardless of nationality and provide resources and services to “overcome language barriers that impede equal participation” in instructional programs (Pub.L. 93-380, 20 USC 1703). Castañeda v. Pickard (1981) established criteria for effective educational programs for non-native English speakers, emphasizing sound educational theory, adequate resources, and personnel to implement the program, while the program evaluation for adjustments to ensure language learning (Castañeda v. Pickard 1981, 446 US 493). Plyler v. Doe (1982) reinforced that all children, regardless of immigration status, are entitled to free public education (457 U.S. 202 1982).

Recent legislation, such as the Every Student Succeeds Act (ESSA 2015), shifted oversight of EL programs from federal to state and local education agencies (Callahan et al. 2022). States are now responsible for implementing EL identification procedures and supporting ELs’ academic achievement and English proficiency. ESSA (2015) mandates that State Education Agencies (SEAs) identify languages spoken at home other than English and outline procedures for EL identification (within 30 days of enrollment) and reclassification (ESSA § 1111(b)(2)(F)(i)). The formal EL classification process is conducted irrespective of the child’s birthplace, whether in the U.S. or not. A standardized assessment that evaluates the child’s proficiency of English reading, writing, listening, and speaking is typically administered soon after initial school registration and must occur within the first 30 days of enrollment (Abedi 2008; ESSA 2015). Once classified, ELs become a subgroup of federally protected students who are entitled to a fair, equitable, and high-quality education with instructional support for their English language development (ESSA 2015 SEC 1001.20 U.S.C. 6301; Lau v. Nichols 1974). These students retain the EL designation until they meet the reclassification criteria established by their state’s definition for English proficiency, and if they are not reclassified within 5 years, they are considered Long-Term ELs (NCES 2023; Thompson 2015; U.S. Department of Education 2016).

1.2. Home Language Surveys

To meet the 30-day requirement of EL identification, schools traditionally use Home Language Surveys (HLS) upon enrollment to identify potential ELs, with this information managed through Student Information Systems ([SIS]; Bailey and Kelly 2012). These systems, essential for daily student management, store critical data, including attendance, schedules, grades, special education status, EL status, and students’ native languages (Kusakunniran et al. 2014; Aeries Software 2024). School districts select their SIS, and during coschool registration, office staff use HLS information and enter it into the SIS using specific ISO language codes (ESSA 2015). This ensures schools nationwide accurately record languages spoken at students’ homes during registration.

Inaccuracies with HLS for EL Identification

The accuracy, or lack thereof, of home language identification in schools merits scrutiny beyond simplistic EL and non-EL categorizations. Despite potential negative implications of inaccurate language data, there has been insufficient investigation into HLS inaccuracies, which can obscure students’ true linguistic backgrounds. Minoritized languages, including Indigenous languages, may be overlooked due to HLS insensitivity (NCES 2023; Pentón Herrera 2018, 2021; Campbell-Montalvo 2021; Martinez et al. 2021). Research examining parent responses on HLS surveys has indicated that parents may inaccurately report home languages, potentially resulting in children not receiving optimal instructional supports aligned with their language learning needs (Abedi 2008; Bailey and Kelly 2012; Kim et al. 2018).

Additionally, HLS surveys are inconsistent across states. Salerno and Andrei (2021) systematically reviewed HLS surveys from 50 states, finding inconsistencies in question clarity (e.g., ranging from yes/no, multiple choice, and open-ended questions) and format (e.g., number of questions ranging from two to nine questions). It was also found that HLS administration practices differed, influencing EL testing and identification processes across states for students with similar language profiles. Due to the inconsistencies, Salerno and Andrei (2021) advocated for standardized HLS validation to ensure consistent results for multilingual children.

1.3. Federal Reporting Requirements and Limitations

Each year, SEAs are mandated by Title III, Part A of the ESSA (2015) to report demographic data to the U.S. Department of Education (ED). The ED collects these data through two processes: EDFacts, which centralizes data collections for education policy and decision-making, and the Consolidated State Performance Report (CSPR), a mandated report to monitor ESSA implementation. To aide in data collection, ED provides a Guide to Collecting and Reporting Title III Data, last updated in March 2023 (Office of Elementary and Secondary Education 2024). Key data requirements among student demographics include student counts by EL status, native language, grade level, race/ethnicity, and disability status.

Notably, the inaccuracies in documenting students’ languages is exacerbated by the federal reporting requirements. The guidance provided to state agencies regarding recording and reporting of home languages to ED is for states to use permitted values and codes using ISO 639-2 Code List, the registration authority of which is the Library of Congress (2013). This list provides some 500 three-letter codes for the representation of names of languages.

Restricting Title III reporting to the ISO 639-2 raises several problems. First, the world is known to have some 8000 languages in use at this time (Hammarström et al. 2023), a number that far exceeds the 500 or so labels in the ISO 639-2. It is not known how many of the world’s languages are used within the U.S. since similar undercounting and lumping of languages is practiced in U.S. census counts. However, research has found linguistic diversity in regions of the U.S. that very much goes beyond the scope of the ISO 639-2. For instance, Perlin et al. (2021) report on the documentation of some 700 languages in New York City alone.

Second, the ISO 639-2 is inconsistent in that it assigns a code to language families, language branches, and individual languages in a flat structure that disregards the taxonomy of the world’s linguistic diversity, which, to date, is highly developed as evidenced, for instance, in the Glottolog (www.glottolog.org (accessed on 6 February 2024), Hammarström et al. 2023). Thus, the ISO 639-2 unevenly favors the language families of dominant international languages by providing them significant granularity while obscuring other languages and even entire language families. For instance, there are codes for Spanish (spa) and French (fre/fra), there is a code for Romance Languages (roa), which is the branch that Spanish and French belong to, and a code for the family of Indo–European Languages (ine) under which they are classified.

Third, the Guide to Collecting and Reporting Title III Data suggests that “In the rare case where a language code does not map to another code that is part of the ISO 639-2, students speaking that language should be left out of the count by native language but still included in the education unit total” (Office of Elementary and Secondary Education 2024, p. 14). Considering that the Glottolog identifies at this time over 8000 languoids (Hammarström et al. 2023), and the ISO 639-2 lists some 500 codes only, the “rare cases” amount to about 95% of the world’s languages.

The COVID-19 Farmworkers Project ([COFS], Martinez et al. 2021) provides data to illustrate the impact of the inadequacies that come from restricting the documentation of home languages to the codes in the ISO 639-2. The COFS found that within a sample of only 300 farmworkers surveyed in rural areas of Oregon, 29 distinct Indigenous Mesoamerican languages were found to be spoken. On a closer look at this set of languages for the study presented here, we found that for 16 of these languages to be documented in a HLS, they would need to be mapped onto a hypernym of a language branch or family. This is the equivalent to proposing that speakers of Spanish and French should be documented by mapping them onto the label Romance Languages (roa), along with 76 other languages, which are mostly mutually unintelligible like Romanian. Further, an additional 13 languages in the COVID-19 Farmworkers Project sample cannot even be mapped onto any hypernym because no label for a relevant language branch or family is included in the ISO 639-2. These 13 languages can only be identified as North American Indian Languages (nai). Doing so would be the equivalent of recording Spanish or French as Indo–European languages (ine) along with more than 500 other languages such as Hindi, Kurdish, or Gaelic. Of course, this is not how these two dominant languages are treated. They are provided dedicated ISO codes that closely approximate to the home language of a student growing up with them.

1.4. Mesoamerican Languages as a Case Study: Documentation Challenges and Implications

The aforementioned COFS (Martinez et al. 2021) explored the impact of inaccurate identification of a person’s linguistic inventory in relation to health and well-being in the context of the COVID-19 pandemic. The COFS prompted the co-authors of the present study to investigate the impact of inaccurate identification of home languages in the school setting. There is prior work that demonstrates that members of Mesoamerican communities from Mexico or Guatemala often have as dominant a language as their community’s Indigenous language but are erroneously identified as Spanish speakers. Pérez Báez (2012) provides a case study of speakers of San Lucas Quiaviní Zapotec who, already in the 1980s in Los Angeles, were confronted with the need to integrate into the Spanish-speaking community of the area despite not necessarily having learned Spanish in Mexico. Velasco (2014) reports on the experience of families of Mixtec origin as they navigate the schooling experience of their children in New York City. More recently, Campbell-Montalvo (2023) analyzes the processing of demographic data from Indigenous students of Latin American origin, leading to the erasure of the Indigenous identities in Florida schools. Campbell-Montalvo revealed a discrepancy in the documentation of Indigenous languages within school records, finding that the recording of students’ languages was often reduced to one home language, and that Indigenous languages were being omitted from official school language records by a factor of 19. Pérez and Vásquez (2024) make explicit proposals to render the school environment more culturally appropriate for a diversity of students.

Due to the importance of knowing a child’s home language for future educational planning, and the history of disproportionate placement of ELs in special education, it is important to look at the ordinary task of recording home language in greater detail. The level of detail needed to accurately record the home language of students of Indigenous Mesoamerican origin is considerable and not widely understood outside the realm of a couple of academic disciplines such as linguistics and anthropology. We endeavor to provide relevant details about the linguistic diversity of Mesoamerican languages as to contextualize the argument that contemporary home language documentation practices and, more specifically, restricting such documentation to the ISO 639-2 leads to an erasure of the identities of students and a misunderstanding of their linguistic repertoires, and that they may have detrimental impacts to their schooling experience and outcomes from it.

1.5. Linguistic Diversity of Mesoamerican Languages

Mesoamerica has long been recognized as an area of great linguistic and cultural diversity. Geographically, the Mesoamerican linguistic region extends roughly from the southern half of Mexico to the northern half of Central America. Within this region, several language families can be found: the Otomanguean, Mayan, Totonacan–Tepehuan, and Mixe–Zoquean. In addition, languages of the Corachol–Aztecan branch of the Uto–Aztecan language family are spoken in Mesoamerica. Further, there are several isolates (small groups of languages not known to be related to any existing language families): Purepecha, Oaxaca Chontal, Huave, and Xinca languages (Campbell et al. 1986; Instituto Nacional de Lenguas Indígenas de México 2008; Suárez 1983).

All Mesoamerican language groups together amount to well over 250 documented Indigenous languages. However, broad and imposed ethnic or linguistic group names have led to an underestimation of the diversity of Mesoamerican peoples and their languages. For instance, the term “Mixtec”—an imposed term in and of itself—refers to a branch of the Otomanguean family of languages. The Mixtec branch encompasses at least 53 distinct languages, which are largely mutually unintelligible, and which represent a history of language diversification, the process by which a language develops differently in different communities, thereby providing way to more languages with distinct features. The history of diversification of Mixtec languages spans approximately 2000 years (Josserand 1983). Yet the term “Mixtec” by itself is often used as if there were a single Mixtec language common to all Mixtec peoples.

This is the case even in the scholarly literature. To take but one example cited in this paper, Campbell-Montalvo (2023) introduces the language repertoires of students in the researched schools and lists languages using lumping labels such as Mixtec, Trique, Náhuatl, Zapotec, and Otomí (p. 65). Contrast this with the fact that English, German, Dutch, Swedish, Frisian, Icelandic, and numerous other languages of Northern Europe belong to the Germanic branch of Indo–European languages. However, no speaker of any of these languages would be described in a school context as a speaker of Germanic, nor would they be expected to understand and comfortably converse with speakers of Germanic languages other than their own. Yet this expectation is placed upon speakers of Mesoamerican languages.

Another example of misconstrued understandings of the linguistic diversity of Mesoamerican peoples is in Campbell-Montalvo (2023), surprisingly. The author presents rigorous research and compelling data and arguments to advocate for documenting with accuracy the languages of students of Mesoamerican origin in U.S. schools. In discussing school and parent relationships, the author describes an instance where she shared with a school teacher “about how some students’ families … speak pre-Aztec languages like Mixtec”. To refer to a Mesoamerican language as pre-Aztec is not consistent with any established practice in linguistics to refer to Mesoamerican languages. Languages of the Aztec branch of the Uto–Aztecan language family and languages of the Mixtec branch belonging to the Otomanguean language family have coexisted in Mesoamerica for at least 1500 years (Suárez 1983 inter alia).

More broadly, this linguistic diversity is poorly understood in many contexts, thereby exacerbating the erasure of linguistic and cultural identities. Campbell-Montalvo (2023) reports that Indigenous people from Mesoamerica living in the U.S. are often categorized under broader census categories defined in terms that are disassociated from Indigenous communities and ways of life. Some of these categories are derived from nation–state labels related to country of origin such as Guatemalan or Mexican. Other categories are even broader and are associated with colonial concepts and processes (Fox and Rivera-Salgado 2004; Stephen 2007; Batz 2014; Peñalosa 1986; Yescas 2010; Campbell-Montalvo 2021; Martinez et al. 2021; Pérez Báez et al. 2022). The label Hispanic refers to the Spanish language imposed during colonial times and nation–state building processes. The labels LatinX, Latine, Latino, and Latina, despite them having permutations aimed at inclusion, derive from the concept of Latin America, which relates directly to the contemporary expression of Spanish colonization. All these processes—Spanish colonization, nation–state building and the imposition of Spanish—have been dramatically detrimental to the well-being of Indigenous communities throughout the American continent and the sustainability of their languages and cultures (Martínez Cobo 1986). Thus, using labels stemming from these colonial and homogenizing processes to refer to the diverse populations of Indigenous Mesoamerican origin amounts to perpetuating colonialism.

It should be noticed that the population in the U.S. originating from the American continent south of the U.S.–Mexico border is in fact composed of numerous ethnic groups, with 24% identifying as being Afro-descendants, 29% as being mestizo, and 11% as being Indigenous (Druker-Ibanez and Caceres-Jensen 2022). For this and the various other reasons presented in this subsection, it is crucial to understand the cultural and linguistic diversity of these populations to adequately know their abilities, desires, and needs. For detailed information about the diversity of the many Mesoamerican language families and languages, please refer to supplementary material.

1.6. Research Questions

The study presented here is driven by two main research questions as follows:

• What is the current system/framework for the identification and reporting of languages in the following states: California, Florida, Georgia, New York, Texas, Oregon, and Utah?
• What is the alignment between language coding systems states are using, the ISO639-2 Codes for the Representation of Names of Languages mandated in federal reporting of home languages, and the state-of-the-art knowledge about the world’s linguistic diversity reflected in the ISO 639-3?

The primary objective of this present study was to conduct an exploratory study on current identification language practices in seven states in the United States with substantial EL student populations. State educational agencies have reported varied growth patterns of ELs, with increases ranging from 3% to around 700% in the past 20 years (Office of English Language Acquisition [OLEA] 2021). These states include established immigrant destination states like California, Texas, New York, and Florida, as well as new immigrant destination states such as Georgia, Utah, and Oregon (Gleeson and Bada 2019; Dondero and Muller 2012). These states were chosen as they are likely to reflect a broad range of linguistic diversity. Our focus was to understand how these states identify and document the non-English languages of EL students, specifically Indigenous Mesoamerican languages.

2. Materials and Methods

Using the research strategy of a collective case study (Stake 1995), data were systematically collected from seven state education department websites, with a focus on student language data and state language codes. These data were then coded for analysis (see supplementary material). This approach allowed for an in-depth exploration of language identification practices and policies across multiple contexts, providing comparative insights.

In this study’s context, each case was defined as the language identification practices and policies of a specific state’s education system. Each case includes publicly available data related to EL students’ native and home languages and state-approved language codes. The boundaries of each case were delineated by the availability of data on state education websites. Specifically, this included data reports, data dashboards, standard reports on student language, and student information system manuals related to language codes. The sample section involved purposively selecting seven states (e.g., Texas, Georgia, New York, Utah, California, Florida, and Oregon) based on their demographic diversity and the presence of significant EL populations. These states were chosen to provide a comprehensive understanding of varying language identification practices and policies across different educational contexts.

2.1. Data Collection and Analysis

Qualitative analysis was conducted to identify themes and patterns related to the presence and granularity of Mesoamerican languages in the data. For each of the selected states, the research team focused on sections of documents related to language identification practices and policies. With respect to student-level data, the team searched state education websites for data reports, data dashboards, and standard reports related to EL native and home language. To locate state-approved language codes, the research team searched for list of language codes on the state education websites or student information system manuals. The data were extracted and coded into predefined categories within a shared Excel document. The primary focus was to identify mentions of Mesoamerican languages, whether in the state language code sets or in the publicly available recorded student language data. When specific Mesoamerican languages were identified, the language and its level of granularity were noted.

To facilitate the analysis of language identification practices across the seven states, several key categories were established. First, we assessed the availability of publicly accessible data on student language, which were coded as “Yes” or “No”. When public data were found, we further coded the year of the data and granularity of the language data, noting whether language details were provided at the county, district, school level, or not reported. Moreover, we searched for the presence of Mesoamerican languages. These languages, if present, were documented. Lastly, the states’ language-coding systems were located and compared to the federal language-coding standards, specifically ISO 639-2, to identify any alignments or discrepancies. Any differences, such as the addition of an Indigenous Mesoamerican language to the state language codes or changes to the coding system, were noted.

2.2. Ethical Considerations

To ensure that no private or confidential information was accessed or used, this study relied solely on publicly available data from state websites. All data used were treated with confidentiality and were reported in an aggregated and anonymized manner to protect the identity of individuals or institutions mentioned in the data.

3. Results

In this section, we report on the data obtained for the states of Texas, Georgia, New York, Utah, California, Florida, and Oregon and provide an interpretation of the extent to which current practices visibilize or invisibilize students whose home language or languages includes an Indigenous Mesoamerican language.

3.1. Texas

We consulted the Texas Department of Education website and located the Emergent Bilingual/English Learner Student Reports by Home Language and Grade report that is a snapshot of the statewide data system. The comma-delimited file with Home Language and Grade for the school year 2023–2024 was consulted. Zero Mesoamerican languages were identified. It was noted that there was a language category titled “Other Languages” and a frequency count for this category across PK to Grade 12. The Texas List of Language Codes was on the Texas Student Data System website that provides a language-code table for the last published version of 2.1.2023. This list does not conform to the ISO 639-2 or ISO 639-3, using numerical codes rather than letter codes. There are also only 108 language codes listed for the 2022–2023 and 2023–2024 school year, of which Code 99 is for “Other Languages”.

3.2. Georgia

We consulted the Georgia Department of Education and were unable to locate publicly available student data. We were able to locate a documented titled “Georgia Department of Education Language Codes” that depicted a code, primary language, and the changes made in FY23. This list contains codes that do not conform to the ISO 639-2 or ISO 639-3, using numerical numbers rather than three-letter codes. Additionally, this list contains a reduced list of language labels, with 124 language codes available for staff to use. Among the language labels relevant to Mesoamerican languages, the Georgia Language codes include the code 036 (Mixteco), 037 (Nahuatl), 038 (Zapoteco), and a broad language code (035) titled “Central American Indian Languages” (which was defined as including Mayan Languages such as K’iche, Q’eqchi, Mam, and Q’anjob’al).

3.3. New York

Publicly available student language information for New York is limited to the top five languages counted in each district, accessible through the English Language Learners Database provided by the New York State Department of Education. Notably, Mesoamerican languages did not appear among the top five languages in New York districts. To obtain additional information about the language codes available to schools in the state, we consulted the Student Information Repository Systems (SIRS) Manual Version 18.11 for reporting Data for the 2022–2023 School Year and the Language Codes and Description table. This list conforms to the ISO 639-2 format, using three-letter codes, and includes the Mesoamerican language labels Mayan (myn), Zapotec (zap), Nahuatl (nah), and Otomian (oto). No other Mesoamerican language codes were included. Compare this to the Language Map of New York City, which has documented speakers of Amuzgo, Chinantec, Cuicatec, Mazahua, Mazatec, Mixtec, Otomí, Tlapanec, Triqui, and Zapotec languages belonging to the Otomanguean family, the Mayan languages Chuj, Ixil, Kaqchikel, K’iche’, Mam, Poqomchi’, Q’anjob’al, Q’eqchi’, Tz’utujil, and Tzotzil, as well as Nahuatl, Totonac, and Tepehua languages, and the isolate P’urhépecha.1

3.4. Utah

We consulted the Utah State Board of Education and were unable to locate publicly available student native language data. We consulted the UTREx Data Clearinghouse File Specification for 2023–2024 to locate the state language codes. The codes listed conform to the ISO 639-2 naming conventions, listing the language followed by a three-letter code. However, the list from the UTREx Data Clearinghouse File Specification differs from the ISO 639-2 list in that it is has reduced a list of language labels, including only 503 languages out of 506 languages in ISO 639-2. In terms of labels available for use for Mesoamerican languages, the following were identified: Nahuatl languages (NAH), Zapotec languages (ZAP), Mayan languages (MYN), and Otomian languages (OTO), and Central K’iche’ (QUC), a Mayan language in and of itself separated from the rest of the language family. It was unclear why Central K’iche’ was the only language within the Mayan languages to get an individualized language code apart from the Mayan languages code. Aside from Central K’iche’, there were no other Mesoamerican languages identified with a level of granularity to document the exact Mesoamerican language. There is a code for Central American Indian Languages (CAI), which could subsume some Mesoamerican languages such as Pipil or Xinca languages.

3.5. California

We consulted the California Longitudinal Pupil Achievement Data System (CALPADS) Code Sets, Version 15.1 of the California Department of Education dated 1 September 2023.2 The CALPADS included codes consistent with the ISO 693-2.

Table 1. CALPADS code sets.

Row Number	Code Set Name	Coded Value	Name	Definition	Start Date	End Date
2808	Language	oto	Otomian languages (Mixteco)	Otomian languages (Mixteco)	1 July 1990	N/A
2762	Language	myn	Mayan languages	Mayan languages	1 July 1990	N/A
2775	Language	nah	Nahuatl languages	Nahuatl languages	1 July 1990	N/A
2790	Language	nai	North American Indian languages	North American Indian languages	1 July 1990	N/A
2944	Language	zap	Zapotec	Zapotec	1 July 1990	N/A
2434	Language	49	Mixteco	Mixteco	1 July 1990	30 June 2023
2453	Language	71	Zapoteco	Zapoteco	1 July 1990	30 June 2023
2490	Language	A9	Nahuatl languages	Nahuatl languages	1 July 1990	30 June 2023
2492	Language	B2	North American Indian languages	North American Indian languages	1 July 1990	30 June 2023

below identifies the relevant codes in the CALPADS Code Sets. These codes show the expected patterns in that they only provide codes for a few language families or branches, notably the Mayan language family, the Nahuatl branch of Uto—Aztecan languages, and the Otomian and Zapotec branches of the Otomanguean language family.

Two points are noteworthy about the CALPADS code sets. The first is that while there is a numerical coded value for Mixteco as a language unit, this code was retired on 1 July 2023. Subsequently, “Mixteco” was incorrectly subsumed under the ISO code oto, corresponding to Otomian languages. Otomí languages constitute but one of several branches of the Otopamean branch of Otopame—Chinantecan languages of the Western Otomanguean branch. A breakdown of the relevant classification details from the Glottolog is provided in Figure 1.3 The Glottolog recognizes 11 Otomian languages distributed between the Mazahua and the Otomi branches. As can be observed in Figure 1, these branches are distant from the 53 Mixtec languages under the Eastern Otomanguean branch recognized in this classification. ISO 693-2 does not identify Mixtec languages in any way, which is reflected in the lack of representation in the CALPADS, although it does not explain the incorrect classification of Mixtec languages as Otomian.

The second observation that can be made based on the CALPADS is that there appears to be course content related to some of the language groups in question, including “Mixteco”. In addition, while Mayan languages are recognized in the ISO 693-2 and, therefore, in the CALPADS as a family unit without identification of the individual languages, there is recognition of individual languages as a course content area as shown in

Table 2. CALPADS course content.

Row Number	Code Set Name	Coded Value	Name	Definition	Start Date	End Date
589	Course Content Area Subcategory	LANG-49	Mixteco	Mixteco	1 July 1990	N/A
608	Course Content Area Subcategory	LANG-71	Zapoteco	Zapoteco	1 July 1990	N/A
644	Course Content Area Subcategory	LANG-A7	Mayan languages		1 July 1990	N/A
	Languages include but are not limited to Wasteko, Lakantun, Yukateko, Itzaj, Mopan, Ch’ol, Chontal, Ch’orti, Tzeltal, Tzotzil, Chuj, Tojolab’al, Akateco, Popti, Mocho, Q’anjob’al, Mam, Tektiteko (Teko), Awakateko, Ixil, Q’eqchi, Uspanteko, Kaqchikel, K’ichee, Sakapulteco, Sipakapense, Tz’utujiil, Poqomchi, and Poqomam (Poqomjo)
646	Course Content Area Subcategory	LANG-A9	Nahuatl languages	Nahuatl languages	1 July 1990	N/A
648	Course Content Area Subcategory	LANG-B2	North American Indian languages	North American Indian languages	1 July 1990	N/A

. The languages listed in Table 2 is consistent with those recognized by the Glottolog, albeit without granularity at the level of varieties within languages such as Mam and Tzotzil. These varieties may be mutually intelligible to various degrees or not be mutually intelligible at all.

3.6. Florida

We consulted the Florida Department of Education Information Database on Automated Student Information System dated 2022–2023, Appendix N: Language Codes.4 A summary of the language codes from Appendix N can be seen in

Table 3. Florida Appendix N language codes.

Code Category	Code	Language	Change	Date of Change
Languages	EK	Akateko
Indigenous Languages of the Americas	AX	Aztec
Indigenous Languages of the Americas	CD	Cakchiquel
Indigenous Languages of the Americas	CR	Chalchiteco
Indigenous Languages of the Americas	JU	Chuj
Indigenous Languages of the Americas	IX	Ixil
Indigenous Languages of the Americas	KX	Kanjoval
Indigenous Languages of the Americas	MF	Mam
Indigenous Languages of the Americas	MH	Mayan
Indigenous Languages of the Americas	MQ	Mixtec
Indigenous Languages of the Americas	PW	Popti
Languages	PI	Poqomchi	Added	12 August 2022
Indigenous Languages of the Americas	PI	Poqomchi		12 August 2022
Indigenous Languages of the Americas	OL	Quekchi
Indigenous Languages of the Americas	ON	Quiche
Indigenous Languages of the Americas	TQ	Tarascan
Indigenous Languages of the Americas	YH	Zapotec

. This list contains codes that do not conform to the ISO 639-2, using two-letter codes rather than the three-letter codes. Also, the language labels listed are different than those listed in ISO 639-2. More specifically, the Appendix N: Language Codes is more reduced than the ISO 639-2 in that it lists 387 labels as compared to 506 labels. However, the Appendix N: Language Codes also differs from the ISO 639-2 in that it includes language labels not present in the standard and that are relevant to the recognition of Mesoamerican language communities.

Florida’s Appendix N: Language Codes includes 17 language labels relevant to Mesoamerican languages. Some are broad labels such as Aztec (AX), a Uto—Aztecan branch with 31 recognized languages (as seen in Figure 2), Mixtec (MQ) and Zapotec (YH), both Otomanguean branches with 53 and 57 recognized languages, respectively, and Mayan (MH), a family with 34 recognized languages. In contrast, other labels provide much needed granularity for the Mayan family of languages: Akateko (EK), Cakchiquel (CD), Chalchiteco (CR), Chuj (JU), Ixil (IX), Kanjoval (KX), Mam (MF), Popti (PW), Poqomchi (PI), Quekchi (OL), and Quiche (ON). The inclusion of Chalchiteco (CR) is noteworthy because Chalchiteco is not listed in the Glottolog (as of 20 February 2024), nor in most classifications of Mayan languages. Rather, it is considered to be a variety of Aguacateco, although the Chalchitec people are recognized as distinct from Aguacatec people (Campbell 2017). Therefore, the inclusion of Chalchitec in the Appendix N: Language Codes suggests an involvement of a school or school district by and/or with members of the Chalchitec community that may have informed the language codes list. Also included in Appendix N: Language Codes, but not in the ISO 639-2, is the label Tarascan (TQ), which is considered an isolate unrelated to any other Mesoamerican language family, and which has a few varieties.

3.7. Oregon

The Latino/a/x and Indigenous* Student Success Plan 2022 Biennial Report to the Oregon Legislature reports that in 2020, the Oregon Department of Education (ODE) launched an effort to revise the Language of Origin code list. This effort included the inclusion of languages relevant to the nine federally recognized tribes of the state and some 150 codes for Mesoamerican languages. Working with the University of Oregon Language Revitalization Lab directed by Gabriela Pérez Báez, the co-author of this paper, and the ODE added codes for 58 Zapotec languages, 54 Mixtec languages, in addition to the hypernym Mixtec, 36 Nahua languages, 15 Mayan languages, including nine codes for Cakchiquel varieties, codes for three Triqui languages, in addition to the hypernym Trique, and for two Purepecha languages, in addition to the hypernym Tarascan.5

The EL Data Collection Submission Guide explicitly states that Language of Origin data collection is required, and among other recommendations, states that the collected data may not include the code 0000 Not Applicable.6 This is quite relevant in improving the accuracy of data collection over the last few years. The Oregon Statewide Annual Report Card (p. 9) for the 2018–2019 school year reported that out of 53,559 ELs, “1408 students did not list a specific language (non-applicable to reporting)” and “1438 students were also listed as “Other Language”. This amounts to 5% of Oregon students in the year 2018–2019 not being adequately recognized in their schools and, therefore, in the agency more broadly. Four years later, the Oregon Statewide Report Card 2022–2023 (p. 10) reported a total of 62,390 ELs. The ODE refers to these students as multilingual learners and reports having documented 333 languages across all Oregon schools. Then, 1356 students were listed as users of “Other Language”, and no students were listed as 0000 Not Applicable. This represents a reduction of the proportion of students not adequately recognized from 5% to 2%.

The Mayan language Mam is listed in the report to be among the 20 most common languages of origin in Oregon public schools, and while it is the only Mesoamerican language listed in the report card, and none of its varieties are identified, the report states that “There are over 7500 students represented in the 315 languages not included in this report”. Thus, we infer from the report and the updated Language of Origin Codes List that most other students’ languages were documented to a significant level of granularity.

4. Discussion

In conducting research for this article, we recognize the multifaceted nature of language policy that has been shaped by monoglossic ideologies, the politics of difference, and raciolinguistic ideologies (Campbell-Montalvo 2023; Hult and Hornberger 2016; Flores and Rosa 2015; Ovando 2003). Historically, language planning and policies have been framed around competing views about language, multilingualism, and use of socio-political agendas to exert social control (Wiley and Wright 2004). These factors collectively influence the educational experiences and identity formation of multilingual students. Monoglossic ideologies, which prioritize a singular linguistic standard, typically English, marginalize the linguistic repertoires of multilingual students, undermining their cultural and linguistic assets (García and Torres-Guevara 2009). The politics of difference further exacerbate these challenges by establishing linguistic hierarchies that privilege certain languages over others, which can affect the equitable treatment of multilingual learners in educational settings (Kozleski et al. 2012). Raciolinguistic ideologies intersect with these dynamics, reinforcing racial and linguistic stratifications suggesting that the linguistic practices of multilingual learners from racialized backgrounds are inherently deficient compared to the standardized norms (Flores and Rosa 2015). Together, these perspectives highlight the need for language policies that, at the very least, acknowledge the linguistic diversity of multilingual learners, promoting an educational environment that is inclusive and equitable.

The current language policies and practices with EL students exist within a system of established policies that set forth a common protocol to distinguish between students who should be identified as ELs versus those who should not (Bailey and Carroll 2015; Pompa and Villegas 2017; Umansky and Porter 2020). The primary objective of these processes is to determine a child’s need for EL programming and to establish state accountability for how public schools will enhance and support EL academic achievement (Gándara and Hopkins 2010; Pompa and Villegas 2017). However, the limitations of these current language policies and practices with EL students highlight a gap in the classifying and recording of non-English languages. Addressing this gap is crucial for transforming policies toward more inclusive educational outcomes, particularly for students from minority language groups.

4.1. Multilingualism, Language Proficiency, and Academic Performance

Exceedingly, research on multilingual children emphasizes the importance of documenting the language input that children receive in their home. Variability in language input from different communication partners has been found to fluctuate and can impact a child’s linguistic abilities across their languages (Castilla-Earls et al. 2019; Halle et al. 2012; De Houwer 2014). In fact, a central aspect of understanding multilingual children’s academic trajectory is to explore how an exposure to, and use of, multiple languages influences children’s linguistic and cognitive and academic development (Hopewell and Escamilla 2014; Luo et al. 2020; Suárez-Orozco et al. 2010; Su et al. 2022). Specifically, factors such as the characteristics of their language and cultural environment may be crucial to shaping their academic outcomes. For instance, past research indicates that the knowledge of a children’s home language is important to understanding children’s later English literacy skills.

Lewis et al. (2016) found that home language use and literacy activities like mother—child book reading and storytelling in their home language were important to children’s English oral comprehension, in addition to maintaining and enhancing Spanish language abilities. Similarly, Goodrich et al. (2021) explored how factors within the home language environment, such as language exposure, and family reading habits influenced the initial level and growth rate of English and Spanish vocabulary of 944 Spanish—English children when they controlled for child age, socioeconomic status, and initial vocabulary knowledge. Their findings revealed that the amount of Spanish used in the home correlated with Spanish vocabulary, while home literacy activities like the number of books and frequency of parental reading were associated with improvements in English vocabulary.

Lindholm-Leary and Block (2010) examined the performance of 659 children from Hispanic backgrounds in California, comparing their English and math performance for those educated in mainstream English programs compared to those educated in bilingual programs. Students were categorized as English Proficient or as ELs. They found that both ELs and EP students in bilingual programs scored higher on English proficiency tests than those in mainstream English classrooms. Similar results were observed in math exams. Overall, students in bilingual programs regardless of socioeconomic status performed as well or better than peers in English-only programs.

Research by Swanson et al. (2018) examined the growth in the executive component of working memory and math performance in EL children, demonstrating that bilingual proficiency was found to positively impact math and cognitive performance in children with math difficulties. It was found that by Grade 3, children with math difficulties who possessed proficient Spanish—English skills outperformed less proficient bilingual children with comparable math difficulties on measures of math calculation, fluid intelligence, reading, and Spanish working memory. In all, understanding EL children’s academic trajectories and development requires educators to attend to all the language learning happening alongside their English language learning.

It is, therefore, critical for educators to understand a child’s language exposure and use shape to better support their academic development. However, accurate language documentation, or how a school or educator learns about child’s language history, does not exist in a vacuum. Instead, it is situated within long-standing legislative frameworks and policies.

4.2. Language Codes and Obscuring Languages

The presence of Mesoamerican people in the U.S. is not a recent development. Much scholarship has focused on population movements from the Mesoamerican region into the U.S., prompted by the Bracero Program in the 1940s (Cohen 2011). However, population movements between Indigenous peoples in Mesoamerica and those in latitudes further north of the continent have been documented as dating back to before the arrival of European settlers (Pérez Báez et al. 2022). Despite this long history, the ability to identify, document, and support the linguistic repertoires of Mesoamerican children in U.S. schools in contemporary times is only incipient. As our results indicate, the current framework for documenting language use in schools is intricately connected with the EL identification process and the federal guidance, which recommends using the ISO 639-2 codes to document non-English languages. And, as we have seen in this paper, there are many limitations to the ISO 639-2 language codes, which can lead to schools overlooking the cultural and linguistic diversity present in U.S. classrooms.

Within the seven states that we explored, we observed a wide range of approaches to non-English language documentation. Some states create new language codes, while others adhere to the ISO 639-2 language code standards and others reduce even further this already limited inventory of language labels. Adherence to the ISO-639-2 language coding standards restrict state educational agencies and, in turn, school districts, in that they are only able to identify one broad language family, Mayan, two branches of the Otomanguean language family, Zapotec and Otomian, and the Nahuatl branch of the Uto—Aztecan family.

Deviations from the ISO 639-2 code list for the state reporting analyzed in this study entailed the creation of novel language codes that would allow for the inclusion of otherwise overshadowed language families. For instance, Georgia used numerical codes instead of the standard three-letter codes, allowing for the inclusion of the Mixteco language branch. Florida’s language codes included a more comprehensive list of Mesoamerican languages using both broad labels and more granular language labels. Contrast this with Texas, which did not include any Mesoamerican language codes and used numerical values instead of the ISO 639-2 documentation standard. California was found to both adhere and deviate from the ISO 639-2 standards. It included the four broad Mesoamerican language codes listed above, and it deviated in that the Mixteco language branch had initially been provided a unique numerical code, but it has since been retired to be miscategorized as a branch of the Otomian language branch. Oregon demonstrates a proactive inclusion of numerous Mesoamerican language codes and has the most granular level of representation among the datasets from the seven states analyzed.

The inconsistencies we observed demonstrate a variability in how state department educational agencies approach language documentation. In a utopian school system, the very initial identification of children who are learning two or more languages aside from English would center around understanding children’s linguistic inventory. Instead, language documentation procedures, as they currently exist in schools and as mandated by federal policy, are not prioritizing an understanding of the diverse languages and unique cultural backgrounds of students in U.S. schools. The home language documentation procedures are limited in their focus on setting into motion EL identification assessment procedures. The current non-English language documentation infrastructure is inadequate for accurately identifying children’s entire linguistic repertoires, which can lead to severe inequities.

4.3. Impact of Home Language Identification

The process by which home languages are identified can have lasting consequences for students (Umansky 2016). While there are federal mandates for schools to identify children’s native language and non-English languages to fulfill Title III of ESSA and to report these data to ED, it becomes apparent from this study that not all languages will be accurately recorded due to limitations at both the federal and state level.

And yet identifying non-English language use in the home among multilingual learners plays a pivotal role in fulfilling the mandates of the Individuals with Disabilities Education Act [IDEA] (2004). IDEA stipulates that children requiring special education and related services must be “identified, located, and evaluated” (34 Code of Federal Regulations [C.F.R.] Sec. 300.111), with evaluations considering the child’s age and language background. This is particularly important as IDEA’s provisions—ranging from Part C’s early intervention for infants and toddlers to Part B’s services for children aged 3 to 21—require that assessments, especially for multilingual children, consider the child’s native language to ensure an accurate understanding of their academic, developmental, and functional abilities. Specifically, Part B includes language evaluation requirements, directing those assessments for culturally and linguistically diverse students be conducted in the child’s native language or other mode of communication to ensure accurate information about the child’s academic, developmental, and functional abilities, unless it is not feasible to do so (IDEA 34 C.F.R. Sec. 300.304 (c)(1)(ii)).

Past research has found that ELs are disproportionately placed in more restrictive environments and are found to be overrepresented in certain disability categories, such as intellectual disabilities, specific learning disabilities, and speech and language impairment, as compared to their non-EL counterparts (De Valenzuela et al. 2006; Artiles et al. 2005). Understanding a child’s language exposure is, therefore, critical to undertaking equitable evaluations under IDEA (2004) eligibility. To comprehensively assess multilingual children suspected of having a language or learning disability, evaluators need to integrate information from all their languages to generate an accurate and valid representation of the child’s overall abilities (Bedore and Peña 2008). Without adequate knowledge of languages used in a child’s home, educators will not be able to make sound educational decisions, including determining if the root cause of a child’s struggle with academic content is a result of typical language learning variability or due to an underlying disability (Dollaghan and Horner 2011; Kohnert 2010; Goodrich et al. 2023). Yet, as revealed by this exploratory study that focuses on Indigenous Mesoamerican languages, current language practices in both established immigrant destination states and new EL destination states may not effectively yield accurate documentation of language data for all children.

The current practice of using a home language survey to locate a non-English language for the purpose of initiating EL identification, followed by the use of state codes that are entered into a student information system database, is currently obscuring children who may use an Indigenous Mesoamerican language. As a result, the student-level native language data reported to ED may be incomplete, omitting or obfuscating the linguistic diversity present in a school, district, and state.

4.4. EL Assessment Frameworks

To dissect existing policies and guidelines relevant to the identification of EL students, it is important to review past frameworks diving into the federal, state, and local school district levels that affect EL students directly. In doing so, it will become apparent that achieving accurate language identification and documenting all a child’s language experiences for ELs is one step that has yet to be critically examined. Accurate documentation of non-English language exposure has the potential to influence other aspects of EL experiences such as the language supports students receive, their reclassification rates, and their referral and identification of ELs for special education services (Gersten and Baker 2000; Jiménez-Castellanos and García 2017).

Bailey and Carroll (2015) proposed a theory of action for EL assessment policies, highlighting four main components, each producing an output essential for the next. This framework critiques current EL assessment practices, emphasizing the integration of language proficiency and academic performance due to the high stakes of EL testing. The four components are: the home language survey to determine if a non-English language is used at home; screening and assessment to evaluate English proficiency and need for language support; annual proficiency measurement to track progress and inform decisions on eligibility and readiness for grade-level content without language support; and reclassification based on multiple measures, including proficiency assessments, academic performance, teacher recommendations, and parental input. Umansky and Porter (2020) developed a conceptual education policy framework emphasizing state-level involvement in EL programming. Their framework is organized around three principles—understanding student needs, providing high-quality instruction, and supporting K—12 education systems—and includes nine key policy areas: EL diversity, assessment complexities, academic content access, language development instruction, bilingual education, teacher preparation, funding systems, and alignment from pre-K through secondary education. This framework stresses differentiated policies for various EL subgroups, including students with disabilities, newcomers, and long-term ELs, and it addresses the need for assessments that consider linguistic diversity and instructional needs. Jiménez-Castellanos and García (2017) examined the impact of federal and state policies on EL education, using Arizona as a case study. They highlight how policies like ESEA, NCLB, and ESSA have increased accountability for EL performance and integrated English language instruction with grade-level content. This framework, informed by intersectionality theory, advocates recognizing the complex identities of ELs, considering factors such as race, class, and language. They call for detailed and accurate descriptions of ELs in studies and emphasize the need for policies to acknowledge the sociocultural contexts of ELs.

As the previous policy frameworks demonstrate, language and education policies hinge on correctly identifying potential ELs. This is best illustrated by Bailey and Carroll’s (2015) systems overview of the English Learner Assessment as seen in Figure 3. The flowchart demonstrates that EL identification triggers a sequence of mandated educational processes, assessments, and monitoring. Importantly, the other frameworks all call for a systematic and coordinated process for supporting ELs, spotlighting potential gaps where the current system may fail to properly meet EL students’ needs (Jiménez-Castellanos and García 2017; Umansky and Porter 2020). While each framework provides solutions for improving EL educational experiences, they each underscore the foundational role of initial language identification. Notably, each framework advocates for a more nuanced approach to understanding and appreciating EL’s linguistic diversity and sociocultural backgrounds. Unfortunately, aside from use of the Home Language Survey to identify non-English languages, no other conceptual framework has examined how non-English languages are identified and documented in schools.

4.5. Reconceptualization of Language Identification Systems

Our review of current home language identification practices highlights significant inadequacies in the existing language documentation framework. To address these gaps, we have reconceptualized Bailey and Carroll’s (2015) systems-overview framework, emphasizing the need for federal and state educational agencies to improve their guidance and procedures. This reconceptualization aims to create a more inclusive and comprehensive approach to documenting, evaluating, and supporting the language needs of students, particularly those who use languages historically obscured by current practices. The goal is to enhance the accuracy of language documentation, ensuring that students’ linguistic abilities are properly identified, monitored, and supported.

The reconceptualization, as seen in Figure 4, begins similarly to Bailey and Carroll (2015), with the use of an HLS to identify the student’s primary language and standardized screeners to assess the English proficiency of students who do not primarily use English at home. However, for students whose primary language is not English, we propose additional evaluative steps to uncover any obscured languages the student may use or be exposed to at home and assess their abilities in these specific languages.

To achieve a more thorough understanding of a student’s linguistic background, our framework incorporates tools such as language questionnaires and interview protocols. For instance, Hammer et al.’s (2015) CECER-DLL and Paradis et al.’s (2010) ALDeQ provide scripted, interview-like approaches to evaluating the home language environment and exposure, while Marian et al.’s (2007) LEAP-Q offers a questionnaire available in multiple languages. Assessing the student’s home language abilities alongside their English proficiency is crucial for delivering adequate language development and intervention services.

A vital enhancement in our framework is the ongoing monitoring and assessment of both the student’s English proficiency and their home language abilities. As caregivers acclimate to the U.S. school system, they may disclose more information than at the time of initial registration. Additionally, the home language exposure and environment of ELs may change due to various factors, such as changes in family dynamics or caregivers increasing their use of English. This ongoing assessment process allows for accurate language documentation and ensures the allocation of appropriate resources and instructional strategies, enabling students to receive the support necessary to thrive both academically and linguistically.

Our framework addresses the critical need to visualize and document languages currently obscured by existing identification and documentation methods. By recognizing and documenting the full range of languages spoken in students’ homes, we can better support students’ educational experiences and outcomes. Accurate language documentation processes are vital to ensuring that students’ abilities, especially those using less commonly spoken languages, are properly assessed, recognized, and supported by adequate language development and intervention services.

Furthermore, our reconceptualization promotes equity by ensuring that all students, regardless of their linguistic background, have the opportunity to succeed. It counters the marginalization of historically obscured languages, recognizing them as integral to a student’s identity and educational experience. Comprehensively evaluating and monitoring both English and home languages provide a holistic understanding of a student’s linguistic repertoire, leading to more tailored and effective educational support. This reconceptualization further aims to create a more accurate and inclusive system for language identification and assessment. By enhancing the evaluation and documentation processes, we can ensure that all students receive the support they need to succeed academically and linguistically.

5. Conclusions

In this paper, we have presented home language reporting data from seven U.S. states. Some datasets show a willingness to identify with care and precision languages relevant to a body of students. However, other datasets show severe limitations in this effort. In all cases, we have shown that using the outdated and vastly incomplete ISO 639-2 Codes for the Representation of Names of Languages limits any school district and any state-level education agency from adequately recognizing the languages of students, including Indigenous Mesoamerican languages. As has been shown amply in the literature and emphasized in this paper, a neglect of students’ linguistic repertoires does not allow for the development of inclusive, equitable, and quality education. So, at a minimum, the United States Federal Government should feel compelled by the data presented here to update its reporting requirements to utilize the ISO 639-3 and keep up with its ongoing updates.7

Further, policies should be created and/or updated at the state and federal level as called to include training among teachers, educators, and language specialists, including speech language pathologists and English language specialists, to create resources and professional development opportunities to become informed about the linguistic diversity that they might encounter in a U.S. classroom. This may require collaborations with experts in a diversity of disciplines and professions beginning with, but not limited to, Linguistics, English language learning, school mental health professionals, social workers, and school—family liaison staff, among others.

We have presented a reconceptualization of the existing language documentation framework to enhance the accuracy of language documentation in which we propose that for students whose primary language is not English, additional evaluative steps should be taken, along with an ongoing monitoring and assessment of both the student’s English proficiency and their home language abilities. This reconceptualization promotes equity in two ways. First, it intends to ensure that each student’s language experiences are recognized as skills and part of their identity. Second, it is aimed at increasing the accuracy with which the assessment of support services is conducted.

To close, it is important to emphasize that while the present paper has focused on Indigenous Mesoamerican languages and their communities living in the U.S., the same approaches and principles can and should be applied to identify the linguistic repertoires of students using any other sign or oral language aside from English. The invisibilization of Indigenous Mesoamerican peoples that we have endeavored to elucidate in this paper affects numerous other language communities in the U.S. Thus, it is our hope that the lessons derived from the analysis presented here, and the recommendations that the data support, will be extended to contexts in which signers and speakers of other languages of the world are present in U.S. classrooms.