The Long-Term English Language and Literacy Outcomes of First-Generation Former Child Immigrants in...

CHILD IMMIGRANTS’ LONG-TERM ENGLISH LANGUAGE OUTCOMES 1

The Long-Term English Language and Literacy Outcomes of First-Generation

Former Child Immigrants in the United States.

Becky H. Huang

Department of Bicultural-Bilingual Studies

University of Texas San Antonio

Alison L. Bailey

Department of Education

University of California, Los Angeles

Correspondence should be sent to Becky H. Huang, Department of Bicultural-Bilingual

Studies, College of Education and Human Development, The University of Texas at San

Antonio, One UTSA Circle, San Antonio, TX 78249, USA. Phone: 210-458-5573; Email:

[email protected]

mailto:[email protected]


Abstract

Background/Context: Children from Asian ethnic backgrounds currently constitute the second

largest group of child immigrants in the United States. Although stereotyped as model minority

students due to their academic and economic success, studies have revealed that many Asian

immigrant students struggle in school. Research has also shown that, compared to child

immigrants from an Indo-European language background such as Spanish and French, Asian

child immigrants experience more challenges in learning English as a second language (L2) due

to greater cross-linguistic differences. However, little is known about the long-term English

language outcomes of first-generation Asian child immigrants.

Purpose/Objective/Research Question/Focus of Study: The present study examines the effects of

learner-level and input-level factors on first-generation Asian child immigrants’ long-term

English outcomes.

Research Design: Data for the current study are selected from a larger correlational and cross-

sectional study that examined the effect of the age of arrival variable on Chinese immigrants’

English L2 outcomes. We used two criteria to select participants from the larger study: 1) those

who had arrived in the U.S. between the ages of 5 to 18 (to qualify as a “child immigrant”), and

2) those who had resided in the U.S. for at least 10 years (to examine long-term outcomes).

These criteria resulted in the current sample of 69 participants. The English language proficiency

data include participants’ phonological production ratings, performances on a grammaticality

judgment task, and their self-ratings of English proficiency in listening, speaking, reading, and

writing.


Conclusions/Recommendations: The current study showed a complex interplay of factors

affecting former child immigrants’ English L2 acquisition. Although age of arrival played a

critical role in their L2 learning outcomes, it exerted varying degrees of influence by L2 domain.

Age of arrival was a strong predictor of L2 phonological production, grammar knowledge, and

oral language proficiency, but not literacy skills. L2 input, language learning aptitude, and child

immigrants’ affective status also contributed to their L2 outcomes, and carried more weight than

age of arrival. We interpreted the results to be in line with the multiple sensitive period

hypothesis in developmental psycholinguistics research. The results also suggested that literacy

is not susceptible to age-related effects in the same way in which oral language and more

specifically the phonological and syntactic systems are. Literacy as a cultural construct rather

than a biologically-unique human system is intensively taught throughout the school years and

curriculum. Malleable factors, such as instruction and reading strategies, are thus perhaps more

important in determining child immigrants’ long-term literacy outcomes.

(Word Count = 400)


Acknowledgment

Data in the current study were collected as part of the first author's dissertation research at

UCLA, which was funded by the UCLA Dissertation Year Fellowship, the Chiang Ching-Kuo

Foundation for International Scholarly Exchange Dissertation Fellowship, and the Dissertation

Grant Program of the journal Language Learning. We would like to thank Lyn Corno and three

anonymous reviewers for their helpful comments. All remaining errors are our own.


The Long-Term English Language and Literacy Outcomes of First-Generation

Former Child Immigrants in the United States

The current study focuses on the long-term English language outcomes of a sample of

first-generation child immigrants from Asian, specifically Chinese, ethnic backgrounds. Children

from Asian ethnic backgrounds currently constitute the second largest group of child

immigrant/English Language Learner (ELL) students in the United States (U.S. Census Bureau,

2013), and have consistently done so since the 1970s, covering the period when the former child

immigrant participants in this study were growing up in the U.S. (National Center for Education

Statistics, 1992).

First-generation, foreign-born children arrive in the U.S. prior to college at varying ages

(birth-18 years)1 and have varying length of residence in the U.S. There is also great diversity in

these children’s first language (L1) proficiency, English language proficiency, socioeconomic

status, and prior schooling experiences. In contrast with their second generation, U.S.-born peers,

foreign-born child immigrants struggle more to acquire the English language and adjust to the

new culture (Cortes, 2006; Kim & Suarez-Orozco, 2014; Suárez-Orozco, Suárez-Orozco, &

Todorova, 2008). They also tend to underperform their native-English speaker (NES) or second-

generation, U.S.-born peers (Conger, 2009; Kieffer, 2008; Thomas & Collier, 2002).

Although stereotyped as model minority students due to their academic and economic

success (Cheryan & Bodenhausen, 2000; Lee, 1998), studies have revealed that many Asian

immigrant students struggle in school (Hammer, Jia, & Uchikoshi, 2011). Research has also

shown that, compared to child immigrants from an Indo-European language background such as

Spanish and French, Asian child immigrants experience more challenges in learning English as a

second language due to greater cross-linguistic differences (Bialystok, McBride-Chang, & Luk,


2005; Bialystok, Luk, & Kwan, 2005). However, little is known about the long-term English

language outcomes of first-generation Asian child immigrants.

The present study examines the effects of learner-level (e.g., gender, socio-economic

status, age of arrival) and input-level factors (e.g., exposure to English, length of ESL

instruction) on first-generation Asian child immigrants’ long-term English outcomes. Given the

limited research on the long-term English language outcomes of first-generation Asian child

immigrants in particular and of first-generation child immigrants in general, the current study

fills an important gap in the literature. Although the results may not generalize to all first-

generation child immigrant populations in the U.S., they help shed light on the processes and

outcomes of English language learning in a second-language (L2) speaking context. The results

inform both L2 learning theories and educational practices for child immigrants. In the following

sections, we first review the existing literature on former child immigrants’ long-term English

language and literacy outcomes. We also describe our data source, the descriptive and bivariate

correlation results as well as regression models. We then discuss the results and conclude with

implications for educational practices and future research.

Literature Review

Second Language Research on Child Immigrants’ Long-Term English Language Outcomes

Research on child immigrants’ long-term L2 outcomes are generally drawn from two

fields: L2 acquisition research and educational linguistics research. The former has produced

abundant research that examine the predictors of immigrants’ long-term L2 outcomes, yet the

majority focuses on addressing the critical period hypothesis debate via testing the effect of the

age of arrival (AoA) variable (e.g., Birdsong & Molis, 2001; DeKeyser, 2000; Flege, Yeni-

Komshian, & Liu, 1999; Hakuta, Bialystok, & Wiley, 2003; Johnson & Newport, 1989). The


critical period hypothesis originated from biological research and suggests biological,

maturational constraints on the learning of an L2. This body of research is typically grounded in

the structural linguistics perspective that views language as an innate, symbolic system

consisting of discrete and hierarchical domains such as phonetics, phonology, semantics, and

grammar (Chomsky, 1986; Pinker, 1994). The most commonly studied domains are phonology

(Asher & Garcia, 1969; Flege et al., 1999; Flege, Munro, & Mackay, 1995; Huang & Jun, 2011)

and grammar (Bialystok & Miller, 1999; Birdsong & Molis, 2001; DeKeyser, 2000; Johnson &

Newport, 1989). These two domains have been hypothesized to be subject to effects of brain

maturation and loss of plasticity whereas the learning of vocabulary utilizes higher-order

association mechanism that is not susceptible to an aging effect (Pulvermüller, & Schumann,

1994). Furthermore, this research also precludes literacy, which is considered a cultural construct

rather than a biologically endowed system unique to human beings (Chomsky, 1986; MacSwan

& Pray, 2005; Pinker, 1994).

In general, this body of research shows that AoA exerts a robust effect on immigrants’

long-term L2 outcomes. Those with younger AoAs achieve higher L2 proficiency than those

with older AoAs. The negative correlation between AoA and L2 outcomes is globally linear

among child immigrants (DeKeyser, 2000; Johnson & Newport, 1989; Flege et al., 1999;

Hakuta, et al., 2003; Huang, 2013). Although the negative relationship between AoA and L2

outcomes is consistent across studies, L2 acquisition researchers debate the cause of age-related

effects. Proponents of the critical period hypothesis attribute the AoA effect to the loss of brain

plasticity due to the closing of the critical window of opportunity (Abrahamsson & Hyltenstam,

2009; DeKeyser, 2000; Johnson & Newport, 1989; Patkowski, 1990), while opponents of the

hypothesis argue that L2 input or socio-cultural variables, not AoA per se, are responsible for the


negative correlations between AoA and long-term L2 outcomes (Bialystok & Hakuta, 1994; Jia,

Aaronson, & Wu, 2002). L2 acquisition researchers have also found that child immigrants do not

necessarily catch up with their NES peers even after prolonged immersive exposure to the L2 in

an L2-speaking context (Flege et al., 1999; Granena & Long, 2013; Huang, 2013), and that the

AoA variable affects speech production outcomes more strongly than grammar outcomes (Flege

et al., 1999; Huang, 2013).

In addition to the AoA variable, some studies have examined the effects of other

predictors such as length of residence in the L2-speaking country, self-estimated L2 input, L1

proficiency, self-reported motivation, and language learning aptitude, and showed that these

variables correlated with long-term L2 outcomes to varying degrees (Birdsong & Molis, 2001;

Flege et al., 1999; Huang, 2013; Jia et al., 2002; Johnson and Newport, 1989; Moyer, 2004,

2007). For example, Flege and colleagues (1999) assessed the speech production and grammar

outcomes of 240 Korean immigrants in the U.S. whose ages of arrivals (AoAs) ranged from 1 to

23. All immigrants had lived in the U.S. for at least eight years. Grammar knowledge was

measured with a grammaticality judgment task, and phonological production was determined by

a panel of NES raters’ perceptions of the global foreign accents in participants’ speech recording.

Various information such as participant’s length of residence, L2 input, and language learning

aptitude, was also collected via a questionnaire. Results revealed a robust effect of AoA for both

grammar and speech production outcomes. However, the effect of AoA on grammar outcome

disappeared after controlling for participants’ years of education in the U.S., whereas AoA’s

effect on speech production remained significant, suggesting potential maturational constraints

on L2 speech production but not on grammar learning. Additionally, participants’ self-estimated


language learning aptitude, English media input, and motivation to learn English were also found

to contribute to their English grammar and speech production outcomes.

In a study that focused on predictors of long-term English grammar outcomes, Jia and

colleagues tested 112 immigrants in the U.S. with a wide range of AoA (1-38) and from a variety

of native language backgrounds. Grammar knowledge was assessed via a reading and a listening

grammaticality judgment task, and predictors were collected via a language background

questionnaire. The results revealed AoA to be a significant predictor for immigrants’ grammar

outcomes. However, mother’s English proficiency and number of English speakers at home also

significantly predicted English grammar outcomes, suggesting the importance of L2 input.

To summarize, this body of research was grounded in a structural linguistics theoretical

framework and focuses on L2 phonological and grammar outcomes. The results revealed a

robust effect of AoA on child immigrants’ long-term L2 phonological outcomes, but the effect

on L2 grammar outcomes was less clear. Language learning aptitude, L2 input, L1 proficiency,

and affective variables were also found to correlate with long-term L2 outcomes in some studies.

Educational Linguistics Research on Child Immigrants’ Long-Term English Language and

Literacy Outcomes

Educational linguistics and policy researchers have contributed to a second body of

research examining child immigrants’ long-term L2 outcomes (Cogner, 2009; Collier, 1987;

Cummins, 1981; Hakuta, Butler, & Witt, 2000; Slama, 2011). In contrast to the dominance of

structural linguistics perspective in L2 acquisition research, educational linguistics research

conceptualizes language from several different viewpoints, such as the systemic functional

linguistics perspective that considers language as meaning- and context-based rather than

structure-based, and users’ choices of specific lexical and grammatical registers are driven by the


functional purposes of language tasks (Halliday, 1994; Schleppegrell, 2002). Another widely

adopted view of language is the distinction between social and academic language (Cummins,

1980, 2000; Bailey, 2007; Scarcella, 2003; Snow, 2010). Cummins (1980, 2000) argued that the

day-to-day languages that learners use to socially interact with others, i.e., Basic Interpersonal

Communication Skills (BICS), is typically context-embedded and cognitively undemanding. In

contrast, Cognitive Academic Language Proficiency (CALP) refers to formal, academic

language uses that are both context-reduced and cognitively demanding.

In contrast to the wide uses of researcher-developed grammaticality judgment tasks and

phonetic/phonological analyses in L2 acquisition research, educational linguistics researchers

generally use results from state-mandated standardized language tests as measures of L2

proficiency (for exceptions see MacSwan & Pray, 2005). Additionally, L2 acquisition

researchers select immigrant participants based on their AoA and LoR. However, educational

linguistics researchers are mainly concerned with improving child immigrants’ academic

achievements, and thus tends to focus on a subset of struggling child immigrants, known as or

categorized as English language learners (ELL) or Limited English Proficiency (LEP) students

depending on the designations of their school districts, who do not have grade-level appropriate

English proficiency in oral language and literacy, and/or are at risk for academic failure (Bailey

& Carroll, 2015).

To inform education policy, linguists in educational settings have gone beyond

determining if child immigrants’ English language proficiency is comparable to the NES norms

to further investigate how long it takes for children to catch up with their NES peers. As

reviewed in the previous section, results from the L2 acquisition research suggest discrepancies

across L2 domains; child immigrants are observed to perform comparably with NES peers in


grammar (Birdsong & Molis, 2001; Flege et al., 1999; Huang, 2013, but see Granena & Long,

2013) but not in phonological production (Flege et al., 1999; Granena & Long, 2013; Huang,

2013). However, results from the educational linguistics research are more mixed. While some

showed that child immigrants/ELL students caught up with NESs by seven years of immersive

exposure in an L2-speaking context (Cogner, 2009; Cortes, 2006; Hakuta et al., 2000; MacSwan

& Pray, 2005), others have found that they still fell behind their NES peers (Kieffer, 2008;

Klesmer, 1993; Slama, 2011; Wright & Ramsey, 1970). These discrepancies may be partly

attributed to the differences in the language measures used. Studies that found comparable

performances between child immigrants/ELL students and NESs tend to assess grammatical

knowledge, such as Bilingual Syntax Measure (BSM) used in MacSwan and Pray (2005), or

social language proficiency, such as Language Assessment Battery (LAB) and Idea Proficiency

Test (IPT) (Butler & Stevens, 2001) used in Cogner (2009) and Hakuta et al. (2000),

respectively. In contrast, those that observed child immigrants’/ELL students’ persistent, lower

performances generally compared their academic language proficiency (Slama, 2011) or reading

achievement (Kieffer, 2008) with NESs. The mixed findings could also result from differences in

the sample characteristics (e.g., first-generation, foreign-born child immigrants vs. second-

generation, U.S.-born ELL students) or in the input/instruction child immigrants received (e.g.,

sheltered English immersion, bilingual education, or two-way immersion programs).

Unfortunately, specific information about child immigrants’ generation status and

instruction/program type was missing in many of the existing educational linguistics studies.

To illustrate, one of the most relevant and widely cited studies was conducted by Hakuta,

et al. (2000), who analyzed test data from two school districts (n =1800) to examine the amount

of time required for ELL students to attain proficiency in oral (social) and academic language.


The ELL students in the study were in Grade 1 to 6 at the time of testing, and were classified as

ELL since they were in kindergarten. They were from Spanish and Vietnamese backgrounds.

Hakuta and colleagues adopted the BICS/CALP distinction while acknowledging that the

distinction may be oversimplifying the construct of language proficiency. The language

proficiency measures used in District A were the Idea Proficiency Test (IPT) as an oral (social)

language test, and the MacMillan Informal Reading Inventory and a district-developed writing

test as measures of academic English proficiency. District B used the Woodcock-Muñoz

Language Survey-Revised (WMLS-R), a standardized, norm-referenced test that evaluated both

oral (social) and academic language. Hakuta and colleagues found that it took ELL students an

average of 3 to 5 years to develop oral proficiency, and 4 to 7 years to develop academic English

proficiency. However, it was unclear whether the ELL students in the study were born in the

U.S. or were foreign-born child immigrants.

Although the two bodies of literature differ in their findings about whether immigrant

participants perform comparably to their NES peers in English language proficiency tasks, the

two fields converge to show an older learner advantage (older biological age) in the initial rate of

acquisition (MacSwan & Pray, 2005) and a younger learner advantage (younger ages of initial

L2 exposure in an L2-speaking context) in long-term L2 outcomes in phonology (Flege et al.,

1999; Huang, 2013), grammar (DeKeyser, 2000; Johnson & Newport, 1989), and basic oral

language proficiency (Cogner, 2009).

In sum, L2 acquisition research and educational linguistics research converge to reveal an

AoA effect, but diverge in whether or not immigrants catch up to NES norms in various L2

domains. In addition to AoA, a variety of other learner-level variables, such as their socio-

economic status, motivation, language learning aptitude, were also found to play a role in


immigrants’ L2 outcomes. However, although first-generation child immigrants were shown to

be at higher risks for low English proficiency and academic failure (Cortes, 2006; Kieffer, 2008;

Slama, 2009), none of these empirical studies focused on first-generation child immigrants’ long-

term L2 linguistic outcomes after they have lived in the L2-speaking country for over a decade.

L2 acquisition research generally included adult immigrants (immigrants who arrived in the L2-

speaking country as adults) in the sample or even focused solely on adult immigrants (Bongaerts,

1999; Lardiere, 2007) rather than on child immigrants. These studies also aimed at addressing

the theoretical debate on the critical period hypothesis rather than understanding learner-level

predictors of L2 outcomes. On the other hand, educational linguistics research that examined

immigrants’ long-term L2 outcomes are relatively limited, and none of the existing studies

tracked L2 outcomes beyond seven years of exposure in an L2-speaking context. Several of the

existing studies were conducted in the 1970s and 1980s (Collier, 1987; Ramsey, & Wright, 1974;

Wright, & Ramsey, 1970), and the results need to be updated. Furthermore, virtually none of

these educational linguistics studies included an NES comparison group, but inferred an ELL-

NES comparison based on child immigrants/ELL students’ performances on standardized L2

proficiency tests with NES norming samples.

The Present Study

As discussed earlier, the number of language minority students in the U.S. has grown

exponentially in the past few decades, yet relatively little is known about their long-term English

L2 outcomes. In particular, Asian child immigrants constitute the second largest group of child

immigrant/ELL students in the U.S., but research on L2 outcomes of this subgroup is very

limited (Hammer et al., 2011). The present study thus aims to fill this gap in the literature and

provide a descriptive account of the predictors of long-term English language and literacy


outcomes for first-generation former child immigrants from Asian backgrounds. The study also

addresses an important education question that is still under debate in the literature: whether or

not first-generation child immigrants catch up with their monolingual, NES peers after decades

of potential exposure to English. Although the current results may not generalize to other

subgroups of child immigrants in the U.S. from different socioeconomic or native language

backgrounds, they nonetheless provide a much-needed exploratory understanding of a topic that

is critical for both L2 acquisition and educational linguistics researchers.

In addition to the main contributions described above, the study also presented three

improvements from previous studies. First, while existing studies utilized either researcher-

developed psycholinguistic instruments or self-report census data (Hakuta, et al., 2003) or

secondary data obtained from school districts or states (e.g., Hakuta et al., 2000; Selma, 2011),

the current study included both subjective (self-report) and objective (researcher-developed) L2

measures. As other researchers have suggested (Luk & Bialystok, 2013), combining both

objective and subjective measures yields more informative results than using either measure

alone. Also, very few studies have compared child immigrants’ L2 proficiency concurrently

across multiple domains and skills or used multiple language measures (for exceptions see Flege

et al., 1999; Hakuta et al., 2000; Huang, 2013). In addition to examining two discrete L2

domains (i.e., phonological production and grammar knowledge), the present study added self-

ratings of L2 skills in reading, writing, speaking, and listening. Finally, many of these empirical

studies only included a narrow range of learner-level variables rather than surveying a

comprehensive list of predictors that may contribute to L2 outcomes (Hakuta, et al., 2000;

Slama, 2011). Important information such as child immigrants’/ELL students’ L1 proficiency,

L2 exposure and input, and program of language instruction was missing in these educational


linguistics research studies. The current study addressed this issue and surveyed a wide range of

learner variables, including cognitive, social, and affective variables, as predictors of L2

outcomes. These improvements allowed for a more comprehensive and in-depth empirical

investigation of the language proficiency outcomes of first-generation child immigrants from

Asian backgrounds, as well as the predictors of their language outcomes.

The current study is guided by two research questions: 1) What are the predictors of first-

generation former child immigrants’ (age of arrival: 5yrs-18yrs) long-term English language

proficiency outcomes in phonological production, grammatical knowledge (grammar hereafter),

oral language proficiency, and literacy? 2) Do first-generation former child immigrants catch up

with their monolingual English-speaking peers after more than two decades of prolonged

exposure to English in the U.S.?

Based on the literature review, we expected to see a robust effect of Age of Arrival

(AoA) on phonological production, grammatical knowledge, and oral language proficiency. In

contrast, literacy domain will not be susceptible to the AoA effect because it is a cultural

construct. We also predicted that AoA would have a stronger effect on L2 phonological

production than on grammar outcomes, and that child immigrants would perform comparably to

NESs in grammar, oral language proficiency, and literacy, yet maintain a non-native accent in

phonological production even after prolonged residence in the U.S.

In terms of the other predictors of the four outcomes, we expected to see L2 input having

a strong influence on all four domains, and that language learning aptitudes would predict all but

literacy outcomes because empirical evidence linking language learning aptitude and literacy is

absent in the literature. We also anticipate an inverse relationship between Mandarin language

proficiency and L2 outcomes. Finally, we expect to observe significant effects of psychological


factors, such as positive/negative attitudes toward L2 learning, on child immigrants’ long-term

L2 outcomes.

Method

Participants

Data for the current study are selected from a larger correlational and cross-sectional

study that examined the effect of the Age of Arrival (AoA) variable on Chinese immigrants’

English L2 outcomes. To ensure that participants had an opportunity to reach “ultimate

attainment” based on the predictions of the critical period hypothesis for L2 acquisition, all

participants had resided in the U.S. for at least 5 years. Because the larger study aimed to

examine successive L2 acquisition rather than the simultaneous acquisition of two first languages

(i.e., bilingual first language acquisition, Genesee & Nicoladis, 2006), only participants who

spoke their L1 (i.e., Mandarin) before age five and had no prior immersion exposure to English

before they arrived in the U.S. were included. To compare the results with previous studies such

as Johnson & Newport (1989) and Birdsong & Molis (2006), the sample in the larger study was

also selected purposively based on participants’ education level. All participants were at least

college-educated or were current college students. Participants were recruited from major coastal

cities in the U.S. through flyers posted on university campuses, Mandarin heritage language

classes, personal contacts, and referrals from participants, and were screened via email or over

the phone to ensure that they met the selection criteria before they were invited to participate.

The original sample included 118 participants who arrived in the U.S. between age 5 to 27.

The shared goal of examining Asian immigrants’ English L2 outcomes between the

larger and the current study justified using a subsample from the larger study for the current

investigation. However, in contrast to the larger study that covered a wide range of ages of


arrival from early childhood to adulthood (i.e., 5-27) to specifically test age of arrival (AoA)

effects on such factors as English phonology, the current study focused on understanding the

predictors of long-term English L2 outcomes of child immigrants’ (i.e., only those participants

who arrived in the U.S. prior to age 18). Based on the specific purpose of the current study to

document the long-term outcomes of child immigrants from Asia, we used two criteria to select

participants from the larger study: 1) those who had arrived in the U.S. between the ages of 5 to

18 (to qualify as a “child immigrant”), and 2) those who had resided in the U.S. for at least 10

years (to examine long-term outcomes). These criteria resulted in the current sample of 69

participants. All participants were first-generation, foreign-born former child immigrants,

currently aged between 20-45 years, who were originally from China or Taiwan, and reported

Mandarin Chinese as their L1. To answer our research question about whether child immigrants

catch up with their NES peers after prolonged exposure to English, we also used the language

data of 20 NESs from the larger study for comparison. The NESs were recruited from the same

universities and regions, and were comparable to the child immigrants on gender (X2 (1) = .267,

p = .606), current age (t (87) = -1.236, p = .220) and educational level, i.e., total years of

education received in the U.S. (t (87) = -.292, p = .771)2. We also examined the ranges and

distributions of the continuous variables (current age and educational level) for the two groups to

ensure comparability3.

Background Survey Data (Learner-Level Predictors). The survey data include

participants’ responses to questions in nine main constructs: Demographic, L2 Input, English

Language Proficiency, Mandarin Language (L1) Proficiency, Language Aptitude, Motivation,

Use of Language Learning Strategy, Cultural Affiliation, and Psychological-Affective Attitude.

For questions in the Demographic construct, participants self-reported their demographic


information, such as their age of arrival, current age, length of residence in the U.S., years of

education, etc4. For questions in the L2 Input construct, participants rated their parents’ English

proficiency on a scale of 1 (No proficiency) to 9 (Native-like), and estimated their own English

language input in different modalities (literacy, oral language, and media) in percentages. For the

English Language and Mandarin Language Proficiency constructs, participants self-rated, on a

scale of 1 (No proficiency) to 9 (Native-like), their English and Mandarin language proficiency

in reading, writing, speaking, and listening when they first arrived in the U.S. and at the time of

testing. Their self-ratings of the four skills were averaged to create a composite score. For the

Language Aptitude construct, participants evaluated their own sound processing ability, musical

ability, and language learning ability on a scale of 1 (Poor) to 9 (Excellent).

Data for the remaining four constructs (Motivation, Use of Language Learning Strategy,

Cultural Affiliation, and Psychological-Affective Attitude) involved participants’ responses to

each question on a scale of 1 (Strongly Disagree) to 9 (Strongly Agree), for both the initial few

years and the most recent few years of their residence in the U.S.. To illustrate, one of the

questions in the Cultural Affiliation construct was “I have a sense of belonging to American

culture.” Participants answered the question on a scale of 1 (Strongly Disagree) to 9 (Strongly

Agree) for their initial time period and for their most recent time period in the U.S. The

distinction between initial and recent time periods was motivated by empirical findings that

suggested discrepant patterns between predictors in the two time periods and language outcomes

(See Birdsong & Molis, 2001). See Appendix A for additional sample questions from the

questionnaire.


Due to the constraints of the sample size, we tried to reduce the large number of variables

derived from the survey for correlational analysis. See Table 1 for the complete list of survey

variables after data reduction.

English Language and Literacy Data (Outcome Variables)

The English language proficiency data include participants’ phonological production

ratings, performances on a grammaticality judgment task, and their self-ratings of current

English proficiency in listening, speaking, reading, and writing on a 1-9 scale (1= poor, 9 =

native-like). Phonological production ratings were derived from NES raters’ ratings of each

participant’s read-aloud speech. All participants were recorded reading a paragraph from the

Speech Archive website (Weinberger, 2013) (See Appendix B), and their recordings were then

all evaluated by the same five NES raters on a 1-9 scale (1 = strong foreign accents, 9 = like a

native English speaker). All NES raters were also recruited from coastal cities in the U.S., and

the average age was 25. They were all born and raised in the U.S. The five raters’ ratings were

averaged as the outcome variable.

The grammaticality judgment data include participants’ percentage correct scores on a

grammaticality judgment task. All participants judged the grammaticality (Correct vs. Incorrect)

of 112 English sentences on a computer, and their percent correct scores on the task were used as

the outcome variable. The structures evaluated include standard English structures such as

determiners, past tense, plurals, particle movement, and pronominalization. See Appendix C for

a list of sample sentences.

Participants’ self-ratings of listening and speaking proficiency were averaged to create an

oral language proficiency composite, and so were their ratings of reading and writing as a


literacy composite (both ranges = 0 - 9). The two composite scores are highly correlated with the

original ratings (r = .91 - .94).

Results

Sample Characteristics

Table 1 presents the descriptive information for the learner-level variables. The current

sample of former child immigrants arrived in the U.S. at the mean age of 10 and have lived here

for an average of 20 years. Their English proficiency was fairly low when they first arrived, and

their initial native language proficiency was high, but it had declined over the years. Based on

self-evaluations, they had above-average language learning aptitude. They were also highly

motivated English learners, and frequently used language learning strategies. They identified

with the American culture more strongly now than they first arrived, and the strength of

identification with their own cultural heritage had also increased since they immigrated to the

U.S. Compared to their first post-immigration years, they were less likely to feel self-conscious

about their English language proficiency or avoid using English.

Overall, they reported an English-dominant environment with at least 70% of English

exposure in daily life in multiple domains (oral language, literacy and media). Their parents’

English proficiency was rated as slightly below average. However, compared to the language

environment when they first arrived, their exposure to oral language in the L2 increased from

50% to 70%, possibly because of the increase in their own L2 proficiency. Their exposure to

literacy and media in the L2 were similarly high both in the initial years upon arrival and in their

current daily life.

< Insert Table 1 about here >


Long-Term English Language and Literacy Outcomes

As shown in Table 2, after over a decade of residence in the U.S., child immigrants in the

current sample were still perceived as speaking with a mild non-native accent (M = 6.40 out of 9)

and received significantly lower foreign accent ratings than the NES controls (t(87) = 7.490; p

< .001). They scored high on the grammaticality judgment task, although still lower than NES

controls (t(87) = 6.867; p < .001). Child immigrants’ self-ratings of oral language and literacy

skills were at ceiling, though still fell short of native-like (i.e., a rating of 9)5. We also examined

the proportions of participants who rated themselves as native-like by L2 domain; approximately

40% of the participants reported native-like proficiency in receptive skills (Listening and

Reading) and 30% reported native-like proficiency in productive skills (Speaking and Writing).

In other words, only about one-third of the child immigrants in the study believed they had

attained native-like L2 proficiency.

The four language outcomes were all significantly correlated with each other, though the

strength of association varied among the language dimensions (r = .268 - .695, See Table 3). The

positive correlations between the objective measures (foreign accents and grammar) and

subjective measures (self-ratings of oral language and literacy) corroborate previous findings by

Jia and colleagues (2002) and Hakuta and D’Andrea (1992). However, the current patterns

appeared to suggest a distinction between objective and subjective measures: the association

between the two objective measures was higher than their respective associations with subjective

measures, and the same patterns held for objective measures. Comparing across the four

language outcomes descriptively, former child immigrants reached slightly higher level of oral

language than literacy proficiency. Their phonological production outcomes, as indexed by the

foreign accent ratings, were also worse than both oral language and literacy outcomes. There was


also greater variation in the foreign accent ratings than in their self-ratings of oral language and

literacy proficiency. Although the foreign accents, oral language and literacy outcomes were all

measured on a 1-9 Likert scale, they assessed different theoretical constructs, so we did not

conduct any inferential statistics for comparison between them.



Predicting Long-Term English Language and Literacy Outcomes

We first conducted bivariate correlation analyses to examine the relationships between

the learner-level characteristics and their English language and literacy outcomes. As shown in

Table 4, there were both similarities and differences in the correlation patterns across domains.

In general, Age of Arrival (AoA), years of education in the U.S., input-related variables (English

media input and oral language input, etc.), and tendency to avoid using English were

significantly correlated with all L2 outcomes.

The cross-domain differences included: 1) language aptitude is positively correlated with

grammar and oral language proficiency, but not with foreign accent ratings or literacy outcomes,

2) current Mandarin language proficiency is negatively correlated with foreign accent ratings and

grammar scores, but not with oral language proficiency and literacy ratings, 3) degrees of

identification with American culture is positively correlated with only oral language self-ratings

and not with other L2 domains, 4) initial heritage culture appreciation is negatively correlated

grammar, but not with foreign accent ratings or self-ratings of oral language proficiency and

literacy, 5) current heritage culture appreciation is positively related to foreign accent ratings and

oral language proficiency but not with grammar and literacy, 6) motivation is negatively


correlated with all domain but self-ratings of oral language proficiency, 7) feelings of

embarrassment is negatively correlated with all domain but foreign accent ratings.


Based on the results from bivariate correlations, we conducted multiple regression

analyses to further understand the best learner-level predictors to long-term outcomes. We

selected variables that yielded significant correlations (p < .05) with the L2 outcome variables to

enter in the regression model, and used stepwise regression technique to select the best subset of

predictors that would explain the maximum amount of variance6. We opted to use stepwise

regression because of the descriptive and exploratory nature of the current study and the

constraint of the sample size in relation to the relatively large number of potential predictors. The

default “enter” method to force all potential predictors in the linear regression model would have

over fitted the model. Stepwise regression utilized mathematical algorithms to select predictor

variables: variables that increased F value by at least 0.05 were included and variables that

increased F value by less than 0.1 were excluded. Using the guidelines from Cohen, Cohen,

West, and Aiken (2013), we also verified that the regression models met the assumptions of

linearity, homoscedasticity, normality, and no excessive multicollinearity (tolerance value > .01

and VIF < 10).

We conducted separate stepwise regression analyses for the four language/literacy

outcomes and present the results in Tables 5-8. The regression analyses with the four outcomes

as the dependent variables revealed both similarities and differences in the set of predictors for

different domains. Although AoA was a significant predictor for foreign accents, grammar, and


oral language, it was not a significant predictor for literacy outcomes. The strength of AoA also

varied among the three significant English L2 domains.

The analysis using foreign accent outcomes revealed a three-predictor model (See Table

5, Step 3): AoA, amount of current oral English language input, and motivation. Based on the

magnitude of the standardized coefficients, current oral language input was more strongly related

to foreign accents (β = .460; p < .001) than AoA (β = -.426; p < .001) and current motivation (β

= -.184; p < .05). The three predictors combined accounted for about 50% of the variances in the

foreign accent ratings. In contrast to the three-predictor model for foreign accent outcomes, the

model for explaining the variance in grammar outcomes (55%) yielded five predictors. In

addition to AoA (β = -.271; p = .003), current oral English language input (β = .378; p < .001)

and current motivation (β= -.257; p = .004), language aptitude (β = .274; p = .002) and initial

level of heritage culture appreciation (β = -.250; p =.004) were also found to predict grammar

outcomes to varying degrees. Similar to the foreign accent outcomes, current oral language input

was the strongest predictor to grammar outcomes. The other four predictors were of similar

strength.



For oral language outcomes, the regression analyses revealed a three-predictor model. In

the order of strength of association, oral language outcomes were predicted by language aptitude

(β = .354; p = .001), AoA (β = -.308; p = .002), and tendency to avoid using English (β = -.305; p

= .005). The three predictors combined accounted for approximately 40% of the variances in the

sample.


In contrast to the other three domains, AoA was not a significant predictor of literacy

outcomes. Instead, only avoidance (β = -.390; p = .001) and current motivation (β = -.251; p

= .025) were found to predict literacy outcomes, and the two predictors combined explained

approximately only 22% of the variance.



Discussion

Given the large and ever-increasing number of child immigrants in the U.S., and the close

relationships between their English language proficiency, academic achievement (Ardasheva, &

Tretter, 2013; Halle, Hair, Wandner, McNamara, & Chien, 2012; Kim & Suarez-Orozco, 2014;

Suarez-Orozco, Gaytan, Bang, Pakes, O’Connor, & Rhodes, 2010), and psychological

adjustment (Liu, Benner, Lau, & Kim, 2009; Noels, Pon, & Clément, 1996), it is surprising that

specific research on child immigrants’ English language and literacy development, particularly

long-term outcomes, is very limited (Saunders, & O’Brien, 2006). The current study examined

the long-term English language and literacy outcomes of 69 first-generation, foreign-born former

child immigrants from Chinese ethnic backgrounds. All participants had lived in the U.S. for at

least 10 years and on average 20 years. The study included both subjective and objective

language proficiency data obtained from assessments/surveys and learner-level predictors

obtained from a survey. The four English L2 domains under study included foreign accents

(phonological production) and grammar knowledge measured through psycholinguistic,

experimental tasks, and participants’ self-ratings of oral language and literacy proficiency.


Twenty NESs selected to have comparable values for gender, current age and education level

also provided objective language performance data as the baseline for comparison. The learner

variables covered a comprehensive list of constructs, including Age of Arrival (AoA), years of

U.S. education, motivation, cultural identity, language aptitude, language input, etc. We asked if

the child immigrants had caught up with NESs in multiple language and literacy domains after

an average of 20 years of residence in the U.S. and exposure to English. We also investigated the

predictors of former child immigrants’ language outcomes.

Below, we summarize and interpret the results of our two research questions. We first

discuss the divergent AoA effect we found across L2 domains, followed by the finding of

multiple predictors for participants’ long-term outcomes and the comparison between child

immigrants and their NES peers. Throughout our discussion, we also explain whether our

expected outcomes are supported by the results, and how our results compare to previous

research.

Divergent Effects of Age of Arrival (AoA) across L2 Domains

Our first research question pertained to the predictors of first-generation former child

immigrants’ long-term English language outcomes. We expected to find a robust Age of Arrival

(AoA) effect on phonological production, grammar and oral language, but not necessarily on

literacy. The current results supported our expectations and were in line with previous L2

acquisition research (e.g., Flege et al., 1999). Although AoA significantly correlated with all four

English language domains in bivariate correlation analyses, once the effects of other variables

were controlled for in a regression model, AoA was no longer a significant predictor of literacy

outcomes. The current study is one of the first to provide empirical evidence for the prediction

that critical period hypothesis applies to oral language outcomes only. As a cultural construct,


literacy is not bound by the age effect, but is likely dependent on more malleable factors such as

instruction and practice. However, we are cautious to interpret this non-significant finding in a

conclusive way because the size of the effect of AoA on literacy may be small and our sample

size may be too modest with which to detect a significant impact.

Comparing the predictive strength of AoA across domains, we found that AoA exerted a

stronger effect on phonological production (β = -.426) and oral language (β = -.308) than on

grammar outcomes (β = -.271). This particular finding also confirmed our expectation, and

corroborated previous research comparing AoA effects on phonological production and grammar

concurrently (Flege, MacKay, & Meador, 1999; Flege et al., 1999; Huang, 2013). The divergent

effects of AoA across L2 domains appeared to corroborate developmental psychology and

psycholinguistics theory of “multiple critical/sensititve” period hypothesis (Newport, Bavelier, &

Neville, 2001; Pulvermüller & Schumann, 1994; Singleton & Ryan, 2004). The multiple

critical/sensitive period hypothesis argues for multiplicities of the critical period mechanism. The

critical windows differ by areas of languages (phonetics/phonology, lexicon, syntax), and the

closure for phonetics/phonology is generally believed to end the earliest, followed by the closure

for syntax (Long, 2005; Newport et al., 2001).

Multiple Predictors to Successful L2 Outcomes

In addition to Age of Arrival (AoA), we expected L2 input to be a strong predictor

for all language/literacy outcomes. The current results supported this as well as corroborated

previous results that showed a strong impact of L2 input on L2 linguistic outcomes (Flege et al.,

2009; Huang, 2013). It is worth noting that, child immigrants’ self-reported English input was, in

fact, a stronger predictor of both their phonological production and grammar outcomes than AoA

was. This particular finding spelled good news for parents and educators of child immigrants, as

http://www.bcs.rochester.edu/people/newport/pdf/Newport_Bav_Nev01.pdf

http://www.bcs.rochester.edu/people/newport/pdf/Newport_Bav_Nev01.pdf


the result highlighted the importance of a supportive, input-rich environment for successful long-

term L2 outcomes.

The positive effects of language aptitude on child immigrants’ language outcomes also

confirmed our expectations and were in line with results of numerous prior studies

(Abrahamsson & Hyltenstam, 2009; DeKeyser, 2000; Flege et al., 1999; Purcell & Suter, 1980;

Thompson, 1991). Although aptitude has traditionally been considered a static trait across life

span (Ioup et al., 1994; Skehan, 1989), some researchers argued for its flexibility and learnability

(Grigorenko, Sternberg, & Ehrman, 2000; McLaughlin, 1990). For example, Grigorenko and

colleagues (2000) proposed a new conceptualization of language aptitude as information

processing skills that can be trained and learned. The new perspectives thus open the possibility

of facilitating and developing learners’ language aptitudes, making the language aptitude

construct relevant for L2 learners and their educators.

Furthermore, based on previous research on Mandarin-speaking immigrants (Jia et al.,

2002), we expected that psychological/affective factors would also predict the long-term L2

outcomes of child immigrants from Mandarin Chinese L1 background, and the expectation was

supported. Those who reported avoiding using English more frequently also evaluated their oral

language and literacy proficiency to be lower than those who reported less avoidance. The results

also corroborated research with Spanish-speaking immigrants by Birdsong and Molis (2001),

which showed that avoidance and self-consciousness correlated with immigrants’ English

language proficiency. On the other hand, child immigrants’ self-reported level of motivation to

learn English was also a negative predictor of their English grammar and literacy outcomes. We

interpreted this finding to mean that their motivation served as a proxy of their English


proficiency; those with lower language proficiency felt more concerned with and motivated to

improve their proficiency.

Our prediction of an inverse relationship between child immigrants’ Mandarin (L1)

language proficiency and L2 outcomes was partially supported. Current Mandarin language

proficiency was significantly correlated with phonological production and grammar outcomes,

but not with their self-evaluations of oral language proficiency and literacy. The results

corroborated the study by Yeni-Komshian and colleagues (2000), in which they found an inverse

correlation between Korean former child immigrants’ native-likeness in their pronunciation of

their L1 (Korean) and their pronunciation of their L2 (English). However, in the current study,

after controlling for the effects of other predictors in the regression model, the effect of former

child immigrants’ Mandarin language proficiency was no longer significant, suggesting that L1

proficiency contributed to L2 outcomes in an indirect way.

Catching up and Falling Behind

Our second research question asked if first-generation former child immigrants

eventually catch up with their NES peers after prolonged residence in an English-speaking

context. We expected child immigrants to perform comparably to NESs in all but phonological

production domain. Results from the study, however, only partially supported our expectation.

After an average of two decades of residence in the U.S., child immigrants reached very high

levels of proficiency across all domains. However, their proficiency levels were still not

comparable to those of NES controls in phonological production and grammar knowledge. The

majority of them (approximately two-thirds) also self-reported less-than-native-like proficiency

in oral language and literacy skills. In other words, after a prolonged period of exposure, child


immigrants in the current study did not catch up with their NES peers in their English L2

proficiency.

The current results corroborated previous L2 acquisition research that showed L2

learners’ less-than-native-like proficiency in phonological productions and grammar knowledge

(e.g., Flege et al., 1999; Granena & Long, 2013; Huang, 2013). However, the results contradicted

some educational research studies that found child immigrants catching up with their NES peers

within seven years of full immersive exposure in an L2-speaking context (Cogner, 2009; Hakuta

et al., 2000; MacSwan & Pray, 2005). The discrepancies between the current results and previous

studies may be attributed to differences in methodology, specifically in participants’

backgrounds and language measures. While the current study employed both psycholinguistic

measures that evaluated discrete L2 structures and participants’ self-reports of oral language and

literacy proficiency, previous studies used standardized language assessments, such as IPT and

LAB, to measure general L2 proficiency. It is possible that the psycholinguistic measures were

more difficult than standardized language assessments. Additionally, whereas the participants in

the current study were all first-generation, foreign-born child immigrants, previous studies may

have included second-generation, U.S.- born child immigrants. The inconsistencies could be due

to the different sample characteristics since first-generation child immigrants are generally at

higher risk for lower English proficiency than their second-generation counterparts (Kieffer,

2008; Slama, 2009). Furthermore, at the time of testing, these participants resided in major

coastal cities in the U.S. where there were many other Chinese immigrants. The average self-

estimated L2 oral input was approximately 70% for the current sample, though there was a wide

range (4% - 100%) and a great amount of variation (SD = 20%). The current sample may thus

have less L2 exposure compared to child immigrants living in regions with far less Chinese


immigrant population. As our results demonstrated, the amount of L2 input significantly

predicted L2 outcomes, and the results may have differed had we included a sample who

predominantly used English in their daily life.

Another possible explanation for child immigrants’ less-than-native-like L2 proficiency

is the concept of fossilization (Han, 2004; Selinker, 1972), a construct in L2 acquisition research

relating to the stagnation of progress in L2 development and applying to both child and adult L2

learners. Researchers believe that fossilization is a cognitive mechanism that affects L2 learning

and is persistent and resistant to external interventions such as L2 learner’s motivation and

efforts. Despite their prolonged full immersion experience in the L2-speaking country, child

immigrants in the current study may have experienced fossilization in their L2 learning at one

point and ceased to make progress toward the target language forms. Alternatively, they may

have reached target forms at one point but regressed to non-target forms due to lack of

stabilization of the linguistic forms.

It is important to note that, although the first-generation, foreign-born child immigrants in

the study still fell behind their NES peers in L2 proficiency, they had nonetheless achieved very

high levels of English language proficiency, and all of them had obtained or were in the process

of obtaining a college degree at the time of testing. Their academic performances thus did not

seem to have suffered from their less-than-native-like proficiency. In fact, several recent studies

found that reclassified, English proficient child immigrants in elementary and middle grades

either performed comparably (Kim & Herman, 2009) or outperformed their monolingual NES

peers on content-area assessments (Ardasheva, Tretter, & Kinny, 2012). A growing body of

psychological research has also claimed a bilingual advantage in cognitive functioning and


metalinguistic awareness (Adesope, Lavin, Thompson, & Ungerleider, 2010; Bialystok, 1999;

Bialystok & Martin, 2004, although see Morton (2014) for a recent critique of this literature).

Conclusion and Future Directions

To conclude, the current study showed that former child immigrants’ L2 acquisition is a

complicated process involving multiple factors. Although age of arrival (AoA) played a critical

role in their L2 learning outcomes, it exerted varying degrees of influence by L2 domain. AoA

was a strong predictor of L2 phonological production, as manifested in child immigrants’

degrees of foreign accents in their speech. It also predicted grammar knowledge and self-

reported oral language proficiency, but not literacy skills. Although AoA remained a significant

predictor of phonological production, grammar knowledge and oral language proficiency

controlling for the effects of other variables, it was not the strongest predictor. L2 input,

language learning aptitude, and child immigrants’ affective status also contributed to their L2

outcomes, and weighed more than AoA. We interpreted the results to be in line with the multiple

sensitive period hypothesis in developmental psycholinguistics research. While tentative due

perhaps to a modest sample size, the results also suggested that literacy is not susceptible to age-

related effects in the same way in which oral language and more specifically the phonological

and syntactic systems are (MacSwan & Pray, 2005; Pinker, 1994). Literacy is a cultural construct

rather than a biologically-unique human system, and as such is intensively taught throughout the

school years and curriculum. Malleable factors, such as instruction and reading strategies, are

thus perhaps more important in determining child immigrants’ long-term literacy outcomes.

The results entail practical implications for educators and parents of child immigrant ELL

students. Specifically, ample support and encouragement should be provided for child immigrant

ELLs to develop their L2 literacy skills. The positive effects of L2 input on former child


immigrants’ L2 outcomes also demonstrated the importance of an input-rich environment for

facilitating L2 development, and suggested collaborative efforts between schools and families to

create such an environment for child immigrant ELL students (Aikens, & Barbarin, 2008;

Duursma et al., 2007; Molfese, Modglin, & Molfese, 2003).

Furthermore, we believed that the positive results about the influence of malleable

factors, i.e., L2 input, language aptitude, and affective factors, spelled good news for educators

and urged for research into these variables. To illustrate, former child immigrants’ self-reported

frequency of avoiding using L2 (English) was negatively associated with their oral language and

literacy outcomes. To improve current child immigrant ELL students’ English learning

outcomes, it would be worth incorporating specific tasks and strategies throughout the school

curriculum to increase their exposure to English and opportunities for meaningful use of English.

The opportunity to use L2 meaningfully in various contexts is fundamental to successful L2

learning (Ortega, 2009). The responsibility should be shared by both the families and educators

of child immigrant ELL students to provide a wide variety of routines and opportunities for

formal and informal (i.e., out of school) exposure to and use of both L1 and L2 (Bailey &

Osipova, in press).

The study also found that first-generation, foreign-born former child immigrants did not

catch up with NESs in their English L2 proficiency after a prolonged period of exposure.

Nonetheless, they had achieved very high levels of proficiency across all L2 domains, and had

also successfully completed or were working toward a college degree at the time of testing. We

concluded that the former child immigrants may have experienced fossilization in L2

development, and/or that their L2 learning environment was not optimal. It is important to note


that, despite still falling slightly behind their NES peers, they had acquired impressive, advanced

L2 proficiency.

In particular, the results on phonological production, combined with previous research,

suggest potential age-related constraints for achieving native-like pronunciation. Although

native-like pronunciation is not part of the K-12 academic curriculum and requirements, some

assessments of reading fluency involve reading aloud, and non-native-like pronunciation may

thus play a role in the evaluations of child immigrants’ reading proficiency. Educators should

take this finding into consideration and try to provide accommodations for such variations

without compromising the validity of read-aloud assessments.

Alternatively, although falling short of native-like L2 proficiency in pronunciation as

well as in other oral language domains in the L2, these child immigrant ELL students’ academic

performances did not seem to be hindered, possibly because their L2 proficiency was sufficiently

advanced. We thus urge researchers and educators to also reconsider the “native-like”

expectations/standards for ELL students’ L2 outcomes. Because not all ELL students can

achieve native-like proficiency in their L2, and their academic achievements did not seem to be

compromised accordingly, it may neither be realistic nor necessary to expect native-like L2

outcomes for all ELL students. The “native speaker” criterion, which is used in some English

language proficiency assessments, such as the Student Oral Language Observation Matrix

(SOLOM), need to be modified or more clearly defined to avoid confusion and frustration for

both ELL students and their families and educators.

As Grosjean (1989) argued, bilingual speakers are not two monolinguals in one.

Comparing bilinguals’ proficiency in one language against that of monolinguals may thus be

unfair to these bilingual/ELL child immigrant students. However, the limited research on the


developmental trajectories of bilinguals/second language learners poses challenges to creating

appropriate normative language proficiency assessments for this population (Bailey, 2007;

Lesaux, 2006). In a recent study, Sanchez and colleagues (2013) proposed an alternative, i.e., the

“multidimensional bilingual assessment approach,” to accurately measure bilingual/ELL

students’ language and cognitive abilities. The researchers administrated multiple cognitive and

academic language proficiency assessments in the two languages of the bilingual participants’

(i.e., Spanish and English). The results demonstrated that bilingual participants’ unique language

development trajectories impacted the reliability and validity of other assessments. The

multidimensional bilingual assessment approach appears to be a promising alternative to

comparing bilinguals against monolingual norms. To ensure the reliability, validity, and fairness

of the assessments for bilingual/ELL students, future research is needed to evaluate this and

other alternative assessment approaches.

The research reported here is one of the few studies in the field to include first-hand data

for multiple L2 domains, as well as a more comprehensive survey of learner-level predictors of

L2 outcomes. The current results afford us a better understanding of child immigrants’ long-term

English L2 outcomes, and the average length of immersive exposure to English (i.e., two

decades) exceeded that of virtually all existing studies. However, several limitations need to be

acknowledged and addressed by future research. First, the study utilized cross-sectional data that

covered a wide range of Age of Arrival for child immigrants. To investigate child immigrants’

L2 developmental trajectory, future studies should use a longitudinal design combined with

statistical techniques that model L2 growth over time. Further research using qualitative

interviews would also help provide a more in-depth understanding of child immigrants’ L2

learning history and the influence of the various predictors on their L2 outcomes. Second, the


current study did not include an objective measure of literacy but relied on participants’ self-

reporting. Future research incorporating an objective literacy measure would offer additional

insights into child immigrants’ L2 literacy outcomes. The potential reliability and validity issues

with self-report measures also call for better measures of the three learner-level predictors, L2

input, language aptitude and psychological factors, which were found to be significant predictors

of L2 outcomes. In particular, L2 input appeared to hold great potential for explaining child

immigrants’ L2 outcomes.

Although the current study distinguished between oral, literacy and media domains, we

did not examine the impact of input by context, such as informal social contexts vs. formal

classroom interactions, or the role of the L2 instruction/program types (e.g., sheltered English

instruction, bilingual education) that child immigrants received. Carhill and colleagues (2008)

found the amount of time immigrant youth spent speaking English in informal social contexts to

be predictive of their English language proficiency. Several studies comparing different types of

instructional programs had also shown the effect of L2 instruction on child immigrants’ L2

outcomes (Lindholm-Leary, 2014; Oller & Eilers, 2002). Further research is clearly needed to

fully understand the roles of L2 input and L2 instructional program in former child immigrants’

L2 development.

As an example measure of L2 input, Flege (2009) has proposed using the Experience

Sampling Method that involves asking participants at several randomly selected times during a

day to report their language exposure in the immediate past hour. There are also standardized,

objective measures of language aptitude that can be readily incorporated in future studies to

verify and compare with the current findings. Those include the Modern Language Aptitude Test


(MLAT) (Carroll & Sapon, 1959), the Pimsleur Language Aptitude Battery (PLAB) (Pimsleur,

1966), and the Defense Language Aptitude Test (DLAB) (Petersen & Al-Haik, 1976).

Finally, because the study focused on a subgroup of child immigrants, i.e., first-

generation, foreign-born child immigrants who spoke Mandarin as their first language and were

college-educated, the results may not generalize to other subgroups of child immigrants with

lower education levels or from other native language backgrounds, such as Vietnamese and

Spanish. More research on other subgroups of child immigrant students from different education,

socio-economic and native language backgrounds is clearly needed. Future studies, for example,

might attempt to mine data available in the larger scale and more nationally representative

sample provided by the Education Longitudinal Studies of 2002 (ELS: 2002)7. These data,

sponsored by the National Center for Education Statistics of the Institute of Education Sciences,

U.S. Department of Education, examined the content-area knowledge and educational

experiences/opportunities of secondary school students in the U.S., and involved a nationwide

sample from diverse school types (public vs. private) and socio-economic, racial/ethnic and

geographical backgrounds. Moreover, similar research efforts collecting new data specific to

investigating child immigrants’ long-term English L2 outcomes would greatly help shed light on

this important topic. The field would also benefit from a meta-analysis study that compares and

contrasts results from different studies to derive a comprehensive picture of child immigrants’

English language development.


Appendix A

Sample Questions from the Background Survey

Full Name: _______ Interviewer Initial:____ Date:_____ (mm/dd/yy) Main lang: ____Chi ____Eng ID:___________

Language Learning History

1. What language(s) do you and your parents speak? That is, languages that you can carry a conversation. (Check

all that apply)

You __ Mandarin __Taiwanese __ Cantonese ___English ___Other (specify languages/dialects&age of learning)

Mother __ Mandarin __Taiwanese __ Cantonese ___English ___Other (specify languages/dialects&age of learning)

Father __ Mandarin __Taiwanese __ Cantonese ___English ___Other (specify languages/dialects&age of learning)

2. Please rate your parents’ English proficiency. (Circle)

MOTHER

Listening & Speaking

Pronunciation/Accent

Reading & Writing

FATHER

Listening & Speaking

Pronunciation/Accent

Reading & Writing

No proficiency 1 2 3 4 5 6 7 8 9 Native-like








3. What language or languages do your parents usually speak to each other at home? (If not applicable, write NA in

the “Other”)

____ Mandarin ____Taiwanese ____ Cantonese ____English _____________Other languages/dialects (specify)

4. At what age did you start learning English? (i.e. first study of one semester or more) Age ______

5. Where did you start to learn English? _____ In my native country _____ In the US ______ Other (specify)

6. How did you start to learn English? (please check all the appropriate answers)

____ In school class taught by a native speaker _______ In school class taught by a non native speaker

_____ Taught by a native speaker (______________) _______ Taught by a non native speaker (___________)

_______ Self learning (please specify how________________ ) _______ Picked it up naturally

7. How frequent is the English instruction, and for how long? (Write NA if not applicable)

8. Have you received any intensive training in English pronunciation/accent correction? ______Yes _______ No

If yes, please describe the training you received (when/where/details of the training): ______________________________

9. Please list all places (city, country) in which you have lived for more than 3 months EXCEPT for the U.S. and your

native country. If you have not lived in other places for more than 3 months, please just leave the question blank.

(a) _____________________ from ________ (month, year) to _________ (month, year)

(b) _____________________ from ________ (month, year) to _________ (month, year)


Appendix B

Stimuli for the Phonological Production Task

Please call Stella. Ask her to bring these things with her from the store: Six spoons of fresh

snow peas, five thick slabs of blue cheese, and maybe a snack for her brother Bob. We also

need a small plastic snake and a big toy frog for the kids. She can scoop these things into

three red bags, and we will go meet her Wednesday at the train station.


Appendix C

Target Structure and Sample Sentences for Grammaticality Judgment Task

Structure Type Examples

JN Items (Johnson & Newport, 1989; DeKeyser, 2000)

Determiner Tom is reading a book in the bathtub.

*Tom is reading book in the bathtub.

Particle Movement Kevin called Nancy up for a date.

*Kevin called Nancy for a date up.

Past Tense

Last night the old lady died in her sleep.

*Last night the old lady die in her sleep.

Plurals

A shoe salesman sees many feet throughout

the day.

*A shoe salesman sees many foots throughout

the day.

Present Progressive

Janet is wearing the dress I gave her.

*Janet is wear the dress I gave her.

Pronominalization

John took a sweater along but didn’t put it on.

*John took a sweater along but didn’t put on.

Subcategorization

The little boys laughed at the clown.

*The little boys laughed the clown.


Third Person Singular

John’s dog always waits for him at the corner.

*John’s dog always wait for him at the corner.

Wh-Question

What is Martha bringing to the party?

*What Martha is bringing to the party?

Yes-No Question

Is the baby being held by his mother?

*Is being the baby held by his mother?

Complex NP - Noun Complement

*What did Tom believe the claim that Ann

saw?

Complex NP - Relative Clause

*What did Sam see the man who stole?


Notes

1. We adopt the United States Department of Health and Human Services’ (2009) definition

of “children” to refer to immigrants who arrive in the U.S. before age 18.

2. We are aware of the controversies surrounding the “native speaker” construct (Davies,

2004; Ortega, 2013). However, because the purpose of the study is to examine whether

child immigrants catch up with their NES peers in their L2 (English) proficiency, we

opted to sample an educated NES group to ensure homogeneity in the baseline data for

comparison. The NES comparison group indeed performed at ceiling on both of our

language measures, and the variations within the NES group were also small (see Table

2), suggesting homogeneity in their English language proficiency.

3. The means, standard deviations and ranges of the current age variable are 28.45, 5.75,

and 20-41 for the NES group, and 30.14, 5.30, and 20-44 for the Child Immigrant group.

The values for the education level variable are 18.25, 2.17, and 15-24 for the NES group,

and 18.42, 2.45, and 13-24.5 for the Child Immigrant group.

4. NES participants also filled out a brief survey reporting their demographic information

where applicable.

5. As mentioned in Footnote 2, we use “native-like” while acknowledging the contested

nature of the term in the applied linguistics field (see Davies, 2004 for definitions and

discussion).

6. Although “age” was significantly correlated with foreign accent ratings and grammar

outcomes, because of the linear function between “age,” “age of arrival,” and “length of

residence,” and the lack of this variable’s predictive power shown in previous studies, we

did not select “age” to enter in the stepwise regression models.

7. We thank an anonymous reviewer for bringing our attention to this database.


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Table 1. Means, Standard Deviations and Ranges of the Background Variables/Predictors from

Survey

Child Immigrants (n = 69)

Demographic

Age of Arrival 10.12 (3.39) [5-18]

Age 30.15 (5.30) [20-44]

Length of Residence 19.56 (5.21) [9.3 - 30]

Gender 30 female, 39 male

Years of U.S. Education 13.67 (3.64) [5-23]

Years of ESL in the U.S. 2.02 (1.44) [0-6]

Total Years of Education 18.43 (2.45) [13-24.5]

English Language Proficiency

Initial English Proficiency Composite 1.61 (1.01) [1-5]

Mandarin Language Proficiency

Initial Mandarin Proficiency Composite 8.32 (0.93) [5-9]

Current Mandarin Proficiency Composite 6.01 (1.83) [2-9]

Language Aptitude

Language Aptitude Composite

6.40 (1.44) [2.20-9.00]

Motivation

Initial Motivation Composite 6.81 (2.45) [1-9]

Current Motivation Composite 6.66 (2.16) [1-9]

Use of Language Learning Strategy

Initial Language Learning Strategy Composite 5.76 (2.49) [1-9]

Current Language Learning Strategy Composite 7.14 (1.73) [2-9]

Cultural Affiliation


Initial American Culture Identification Variable 3.20 (2.28) [1-9]

Current American Culture Identification Variable 6.87 (2.03) [1-9]

Initial Heritage Culture Appreciation Variable 7.03 (2.18) [1-9]

Current Heritage Culture Appreciation Variable 7.99 (1.31) [4-9]

Psychological-Affective

Initial Embarrassment Variable 6.55 (2.70) [1-9]

Current Embarrassment Variable 4.25 (3.20) [1-9]

Initial Avoidance Variable 6.03 (2.83) [1-9]

Current Avoidance Variable 2.09 (2.08) [1-9]

L2 Input

Parents’ English Proficiency Composite 4.04 (2.03) [1-9]

Initial Oral English Input (Avg. %) 51.94 (16.76) [23.90 - 90.30]

Current Oral English Input (Avg. %) 72.28 (20.79) [4-100]

Initial English Literacy Input (Avg. %) 87.07 (15.39) [36.67-100]

Current English Literacy Input (Avg. %) 89.39 (14.14) [20-100]

Initial English Media Input (Avg. %) 78.14 (27.60) [8.33-100]

Current English Media Input (Avg. %) 79.26 (20.42) [0 -100]


Table 2. Descriptive Results (Means and Standard Deviations) of the Language Outcomes

Child Immigrants

(n = 69)

Native Speakers

(n = 20)

t-test

Foreign Accent Ratings 6.40 (1.46) 8.86 (0.20) t (87) = 7.490;

p <.001

Grammar Scores

(% Correct)

85.44 (6.17) 95 (3) t (87) = 6.867;

p <.001

Oral Language

(Listening/Speaking)

7.93 (.94) NA NA

Literacy (Reading/Writing) 7.75 (1.10) NA NA


Table 3. Correlation Matrix for Language Outcomes

1 2 3 4

1. Foreign Accent Ratings --

2. Grammar .692** --

3. Oral Language (L&S) .434** .460** --

4. Literacy (R&W) .268* .332** .695** --


Table 4. Correlations between the Language/Literacy Outcomes and Background Variables

Foreign

accent

ratings

Grammar Oral

Language

Proficiency

Literacy

Demographic

Age of Arrival (AoA) -.560** -.489** -.355** -.301*

Age -.339** -.365** -.231 -.080

Length of Residence -.009 -.022 .067 .165

Years of U.S. Education .441** .404** .251* .278*

Years of ESL in the U.S. -.096 .002 .039 -.063

Total Years of Education -.092 -.028 -.138 -.031

Initial English Proficiency

Initial English Proficiency

Composite (oral)

-.039 -.092 -.007 -.154

Mandarin Language

Proficiency

Initial Mandarin Proficiency

Composite

.031 .002 .117 .206

Current Mandarin Proficiency

Composite

-.439** -.499** -.165 -.127

Language Aptitude

Language Aptitude Composite .206 .308* .475** .213

Motivation


Initial Motivation Composite -.132 -.088 -.023 -.062

Current Motivation Composite -.360** -.423** -.217 -.299*

Use of Language Learning

Strategy

Initial Language Learning

Strategy Composite

-.141 -.057 -.013 -.041

Current Language Learning

Strategy Composite

-.087 .017 .123 .037

Cultural Affiliation

Initial American Culture

Identification Variable

-.011 .010 .000 -.039

Current American Culture

Identification Variable

.102 .186 .253* .048

Initial Heritage Culture

Appreciation Variable

-.205 -.354** .012 -.006

Current Heritage Culture

Appreciation Variable

.250* .214 .327** .141

Psychological-Affective

Initial Embarrassment Variable -.139 -.105 -.080 -.117

Current Embarrassment Variable -.134 -.289* -.305* -.297*

Initial Avoidance Variable -.127 -.091 -.057 -.069

Current Avoidance Variable -.432** -.451** -.463** -.358**

L2 Input


Parents’ English Proficiency .305* .407** .188 .285*

Initial Oral English Input .318** .348** .179 -.112

Current Oral English Input .553** .531** .306* .214

Initial English Literacy Input .179 .233 .194 .066

Current English Literacy Input .238* .210 .203 .009

Initial English Media Input .230 .351** .373** .343**

Current English Media Input .270* .272* .296* .140

Note. *p < .05 **p < .01


Table 5. Stepwise Regression Coefficients for Analysis Predicting Accent Ratings (n = 69)

Variable B SE β t p r rpartial Adj. R2 R2 ΔR2

Step 1 (Constant) 8.78 0.47 18.58 .000 .28 .29

Age of Arrival (AoA) -0.23 0.05 -0.54*** -5.22 .000 -0.54 -0.54

Step 2 (Constant) 5.96 0.67 8.95 .000 .49 .51 .21


Oral English language

input (current) 0.04 0.01 0.47*** 5.28

.000 0.53 0.55

Step 3 (Constant) 6.57 0.71 9.21 .000 .51 .54 .03



input (current) 0.04 0.01 0.46*** 5.35

.000 0.53 0.56

Motivation (current) -0.12 0.06 -0.18* -2.06 .044 -0.34 -0.25

B = Unstandardized beta coefficient, SE = Standard error of the unstandardized beta coefficient, β = Standardized beta coefficient,

* p < 0.05, ** p < 0.01, *** p < 0.001

Note. Excluded predictors (Beta/p value): Years of U.S. Education (β = -.040; p = .769); Current Mandarin Proficiency (β = -.016; p

= .887); Avoidance (current) (β = -.138; p = .138); Parents’ English Proficiency (β = -.019; p =.845); Oral English Language Input

(initial) (β = .132; p = .136); English Media Input (initial) (β = .039; p = .670); Heritage Culture Appreciation (current) (β = .040; p

=.654); English Literacy Input (current) (β = .086; p = .328)


Table 6. Stepwise Regression Coefficients for Analysis Predicting Grammar (n = 69)


Step 1 (Constant) 73.78 2.67 27.61 .000 .23 .24


input (current) 0.16 0.04 0.49*** 4.57 .000 0.49 0.49

Step 2 (Constant) 82.46 3.23 25.54 .000 .38 .40 .15


input (current) 0.14 0.03 0.43*** 4.39 .000 0.49 0.48


Step 3 (Constant) 86.19 3.28 26.26 .000 .45 .47 .08


input (current) 0.14 0.03 0.43*** 4.66 .000 0.49 0.51

Age of Arrival (AoA) -0.55 0.18 -0.31** -3.14 .003 -0.46 -0.37

Motivation (current) -0.81 0.27 -0.29** -3.02 .004 -0.41 -0.36

Step 4 (Constant) 80.56 3.69 21.86 .000 .50 .53 .06


input (current) 0.13 0.03 0.38*** 4.30 .000 0.49 0.48




Language Aptitude 1.05 0.37 0.25** 2.85 .006 0.33 0.34

Step 5 (Constant) 83.73 3.63 23.04 .000 .56 .59 .06


input (current) 0.12 0.03 0.38*** 4.49 .000 0.49 0.50




Heritage Culture

Appreciation (initial) -0.70 0.23 -0.25** -2.97 .004 -0.34 -0.36


* p < 0.05, ** p < 0.01, *** p < 0.001

Note. Excluded predictors (Beta/p value): Years of U.S. Education (β = -.036; p = .783); Current Mandarin Proficiency (β = -.103; p

= .353); Embarrassment (current) (β = -.144; p = .110); Avoidance (current) (β = -.090; p = .345); Parents’ English Proficiency (β

= .094; p =.331); Oral English Language Input (initial) (β = .063; p = .501); English Media Input (initial) (β = .022; p = .822); English

Media Input (recent) (β = -.049; p =.608).


Table 7. Stepwise Regression Coefficients for Analysis Predicting Oral Language (n = 69)


Step 1 (Constant) 8.43 0.14 58.56 .000 .25 .26

Avoidance (current) -0.25 0.05 -0.51*** -4.84 .000 -0.51 -0.51

Step 2 (Constant) 6.97 0.52 13.38 .000 .33 .35 .09

Avoidance (current) -0.19 0.05 -0.38** -3.47 .001 -0.51 -0.40


Step 3 (Constant) 7.63 0.53 14.42 .000 .41 .44 .09





* p < 0.05, ** p < 0.01, *** p < 0.001

Note. Excluded predictors (Beta/p value): Years of U.S. Education (β = -.116; p = .440); Embarrassment (current) (β = -.125; p

= .219); Oral English Language Input (current) (β = .136; p = .177); English Media Input (initial) (β = .065; p = .557); Heritage

Culture Appreciation (current) (β = .187; p =.054); Current American Culture (current) (β = .070; p =.481)


Table 8. Stepwise Regression Coefficients for Analysis Predicting Literacy (n = 69)


Step 1 (Constant) 8.24 0.18 46.87 .000 .17 .19

Avoidance (current) -0.25 0.06 -0.43*** -3.88 .000 -0.43 -0.43

Step 2 (Constant) 9.04 0.39 23.30 .000 .22 .25 .06


Motivation (current) -0.13 0.06 -0.25* -2.30 .025 -0.31 -0.27


* p < 0.05, ** p < 0.01, *** p < 0.001

Note. Excluded predictors (Beta/p value): Age of Arrival (β = -.195; p = .088); Embarrassment (current) (β = -.112; p = .364); Years

of U.S. Education (β = .107; p = .372); English Media Input (initial) (β = .147; p = .225); Parents’ English Proficiency (β = .144; p

= .211)

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