Cross Language Transfer of Metalinguistic Awareness: a Meta-Analytic

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Cross Language Transfer of Metalinguistic Awareness: A Meta-Analytic

Structural Equation Model for Chinese-English Bilingual Children

A dissertation submitted to the

Graduate School of the University of Cincinnati

in partial fulfillment of the

requirements for the degree of

Doctor of Education

in Literacy/Second Language Studies

Of College of Education, Criminal Justice, and Human Services

Xuejiao Diao

M.Ed. University of Cincinnati, OH, USA

April 2014

Committee Chair: Mary Benedetti, Ed.D.

ABSTRACT

While a number of studies have been conducted to investigate the construct of metalinguistic awareness in Chinese-English bilingual children, the results are conflicting regarding whether bilingualism facilitates the transfer of metalinguistic skills across English and

Chinese. This dissertation was designed to offset the shortcomings of relatively small sample sizes in prior research by synthesizing prior study results using meta-analysis and meta-analytic structural equation modeling. These methods were used in order to reveal a holistic picture of the construct of metalinguistic awareness and its relationship with other moderators. Using meta- analysis, this study examined if Chinese-English bilinguals and Chinese or English monolinguals have equal performance on various metalinguistic tasks. A proposed Bilingual Metalinguistic

Awareness Model was then fitted to the meta-analytic data to bring to light the best measurement model for the construct of metalinguistic awareness and its relationship with Chinese and

English language proficiency, cognitive development, language instructional methods, and social influence.

The dissertation analyzed data from 49 studies, including, 27 correlation matrices, and found no statistical differences between Chinese or English monolingual children and Chinese-

English bilingual children in terms of metalinguistic awareness. The study also found the good fit of the measurement part of the Bilingual Metalinguistic Awareness Model. Significant correlations were identified between Chinese and English metalinguistic awareness, metalinguistic awareness and cognition. However, Chinese and English language proficiency were found not to be significantly correlated with metalinguistic awareness. The findings were interpreted in light of the heterogeneity and methodological flaws of studies included.

Theoretical and pedagogical implications were also discussed.

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ACKNOWLEDGEMENTS

I would like to take this opportunity to thank all the people who have encouraged and guided my research. I express my deepest gratitude and sincere thanks to my advisor Dr. Mary

Benedetti for her valuable guidance, warm encouragement, and continuous support in my doctoral study and research.

I would also like to thank my committee member Dr. George Richardson. His insightful comments and immense knowledge in statistics are instrumental to my research. I would also like to thank my committee member Dr. Cathryn Crosby for her enthusiasm, support and remarks. I also express my gratitude to the faculty at School of Education, University of

Cincinnati. In particular, I would like to thank Drs. Virginia Gonzalez and Leigh Lihshing Wang for their input, expertise, and help.

I thank my parents Xingtian Diao and Conghui Wang for their unconditional love. I could not have lived my dreams without their support. I also thank my parents in law Zhanjun Guo and

Yuexia Zhang for helping me taking care of my daughter when I was working toward my degree.

Finally, and most importantly, I would like to thank my husband Wei Guo. His love, devotion, encouragement, and patience give me strength and confidence to tackle challenges head on. I also thank my daughter Angelina for giving me inspirations in this dissertation research. Seeing her grow everyday brings me immense happiness and I dedicate my dissertation to her.

TABLE OF CONTENTS

ABSTRACT ...... ii

ACKNOWLEDGEMENTS ...... iv

TABLE OF CONTENTS ...... v

LIST OF TABLES ...... vii

LIST OF FIGURES ...... viii

1. INTRODUCTION ...... 1

1.1. Statement of Problems ...... 1

1.2. Purposes of the Study ...... 4

1.3. Research Questions ...... 4

1.4. Significance of the Study ...... 5

2. LITERATURE REVIEW ...... 7

2.1. What Is Metalinguistic Awareness? ...... 7

2.2. Domains of Metalinguistic Awareness ...... 8

2.3. Cognition and Metalinguistic Awareness ...... 16

2.4. Language Proficiency and Metalinguistic Awareness ...... 18

2.5. Language Instruction and Metalinguistic Awareness ...... 19

2.6. Sociocultural Factors and Metalinguistic Awareness ...... 21

2.7. Age and Metalinguistic Awareness ...... 21

3. THE BILINGUAL METALINGUISTIC AWARENESS MODEL ...... 23

4. METHODS ...... 25

4.1. Meta-Analysis ...... 25

4.2. Structural Equation Modeling ...... 26

4.3. Meta-Analytic Structural Equation Modeling ...... 26

4.4. Data Collection ...... 27

4.5. Data Analysis ...... 31

5. RESULTS ...... 37

5.1. Results of Meta-Analysis ...... 37

5.1.1 Description of Studies ...... 37

5.1.2 Publication Bias ...... 38

5.1.3 Overall Effect of Chinese-English Bilingualism ...... 40

5.1.4 Effects of Moderating Variables ...... 43

5.2. Results of Meta-Analytic Structural Equation Modeling ...... 48

5.2.1 Description of Studies ...... 48

5.2.2 Fixed-Effects Model ...... 48

5.2.3 Random-Effects Model ...... 52

6. DISCUSSION ...... 55

6.1. Discussion of Meta-Analysis ...... 55

6.2. Discussion of Meta-Analytic Structural Equation Modeling ...... 57

7. CONCLUSION ...... 62

8. LIMITATIONS ...... 64

REFERENCES ...... 65

APPENDIX ...... 73

Appendix A. Coding Sheet ...... 73

LIST OF TABLES

Table 1 Metalinguistic Awareness Domain Measurements in Previous Studies ...... 9

Table 2 Results of effect sizes and Q statistic for overall effects of Chinese-English

billingualism ...... 41

Table 3 Homogeneity Analyses and Mean Effect Sizes for Theoretically Derived

Moderators ...... 45

Table 4 Homogeneity Analyses and Mean Effect Sizes for Theoretically Derived

Moderators ...... 47

Table 5 Parameter estimates in fixed-effects model ...... 51

Table 6 Parameter estimates and 95% CI in random-effects model ...... 53

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LIST OF FIGURES

Figure 1 Bilingual Metalinguistic Awareness Model ...... 24

Figure 2 Forest plot of 95% confidence intervals of the random effect sizes ...... 42

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1. INTRODUCTION

Metalinguistic awareness refers to the ability to consciously reflect on and manipulate the rules, structures, and functions of language (Mora, 2005). The construct has emerged as a crucial component in young children‘s cognitive development, language acquisition, literacy acquisition, and brain functioning (See Bialystok, 2001a for review). More recently, the term has been used to explain the execution and transfer of linguistic knowledge across languages (Bialystok,

2001a). Most research on metalinguistic awareness target bilingual children who learn two alphabetic languages, such as Spanish and English (Bialystok, 2001b). These studies indicate how metalinguistic awareness learned in one language can be applied to the other language, thus enhancing children‘s reading and writing achievements (Bialystok, Majumder, & Martin, 2003;

Carlisle, Beeman, & Davis, 1999; Cummins, 1979; Cummins, 1991; Oller & Eilers, 2002;

Campbell & Sais, 1995). As there are more and more children learning two languages from distinctive language families, researchers have increased their focus on these children, particularly on Chinese-English bilingual children (Bowey, 1995; Bruck & Genesee, 1995;

Campbell & Sais, 1995; Homer, 2000; Huang & Hanley, 1995; Ku & Anderson, 2003; Shu &

Anderson, 1999; Wang, Perfetti, & Liu, 2005; Wang, Sagae, & Mitamura, 2006).

1.1. Statement of Problems

Despite recent interest in cross-linguistic transfer of metalinguistic awareness among

Chinese-English bilingual children, several problems in the literature remain. One of these issues pertains to additive/subtractive Chinese-English bilingualism. Lambert (1977) first differentiated an additive form of bilingualism from a subtractive form. The additive form involves maintaining all abilities in the first language while acquiring a second language. The two languages positively influence each other and the child‘s overall cognitive development. In

contrast, in the subtractive form of bilingualism, the two languages compete with each other, resulting in semilingualism, a situation where children are unable to function well in both languages and usually score lower on cognitive tests like intelligence tests or assessments of executive functions. Supporters of additive Chinese-English bilingualism confirmed cross- linguistic transfer of metalinguistic awareness in their studies. However, other research provided counter evidence and claimed that metalinguistic awareness in one language cannot be transferred to the other (Bruck & Genesee, 1995; Homer, 2000; Huang & Hanley, 1995; Ku &

Anderson, 2003; Wang, Perfetti, & Liu, 2005; Wang, Sagae, & Mitamura, 2006). Additional research is needed to resolve the controversy over the additive/subtractive Chinese-English bilingualism.

A second problem pertains to whether metalinguistic awareness depends on the specific measurement and the language being tested. The majority of the researchers described language processing in terms of the primitive elements of mental consciousness and examined metalinguistic awareness as dissected subcategories (Hergenhahn, 2009; Uttal, 2000). The majority of the studies choose to investigate only one or two dimensions of the construct. Hence, it is hard to synthesize the research that has been conducted because of the use of varying measures. Also, as mentioned earlier, the majority of research reached conclusions about the effects of bilingualism based on the data collected on Spanish/English bilingual children.

However, due to the many linguistic similarities between Spanish and English, and the sharp contrast between Chinese and English writing systems, Chinese-English bilinguals‘ language processing may differ drastically. Thus, evidence from the Chinese-English bilingual population may further answer the question regarding additive/subtractive bilingualism as a whole.

A third unsolved issue is over the statement that bilingual advantage disappears as children mature. The majority of research targets children in elementary school and very few studies focused on emergent biliteracy acquisition of Chinese-English bilingual children

(Bialystok, 2001b). Some researchers claimed that children under 5-years-of-age are not mature enough to understand the concept of language structure, and they do not have the mental framework for analyzing language structure separately from language meaning (Papandropoulou

& Sinclair, 2009). Moreover, some research has shown that the initial advantage of bilingualism in certain skills of metalinguistic awareness (e.g., phonemic awareness) disappear once children achieve a certain level of reading proficiency, although there are still conflicts in the findings on the specific ages that at which this occurs (Bruck & Genesee, 1995; Campbell & Sais, 1995).

Research is needed to test this hypothesis with a larger sample of Chinese-English bilingual children across various age groups.

A fourth problem is on whether it is easier for children in Mainland China and Taiwan to transfer their phonological awareness than children in Hong Kong. Mandarin is the standard dialect in mainland China. Children in Mainland learn Pinyin, a phonetic representation system, together with new Chinese character at the early stage of literacy learning (Huang & Hanley,

1995). Similarly in Taiwan, Zhu-Yin-Fu-Hao, an alternative to Pinyin, is taught to children when they learn Chinese characters. However, there is no such phonetic representation system in Hong

Kong. Instead, teachers or more capable peers explicitly show children the pronunciation of new characters. Children then memorize the connection between the sound and the image. Huang and

Hanley (1995) called such method ―look and say‖, which relies more on children‘s working memory instead of phonological features. Differences in phonetic instructional methods have been studied by a number of researchers. Some studies hypothesized that the reading skills of

children from mainland China and Taiwan are more associated with phonological awareness as a result of learning Pinyin or Zhu-Yin-Fu-Hao whereas children in Hong Kong might have better memory because of the reinforcement of ―look and say‖ (Huang & Hanley, 1995). Although this hypothesis has been supported in some experiments (McBride-Chang et al., 2008; Marinova-

Todd, Zhao, & Bernhardt, 2010), it has not been in others (Bialystok, Majumder, & Martin,

2003; Bruck & Genesee, 1995; Huang & Hanley, 1995).

A fifth problem is the lack of conceptual models for Chinese-English bilingual children‘s metalinguistic development. Prior research solely focused on testing cross group differences instead of models that explain these differences. Though some studies measured the correlation between some cognitive development and metalinguistic awareness, there is no systematic or comprehensive model to explore how metalinguistic awareness should be measured and how the constructs are related to cognitive, developmental, instructional, and social factors.

1.2. Purposes of the Study

Due to the above mentioned controversies and gaps in existing research, this study serves two purposes. The first is to examine if the two/three groups of children (Chinese-English bilinguals, and Chinese or English monolinguals) have equal performance on various metalinguistic tasks by integrating prior research findings. The second is to explore how the construct of metalinguistic awareness should be measured and the relationship between Chinese-

English bilingual children‘s metalinguistic awareness and their language proficiency, cognitive development, instructional methods, and social influence.

1.3. Research Questions

Different populations of Chinese-English bilingual children exhibit different characteristics in their metalinguistic development. And methodological problems in previous

studies may have undermined the validity of their conclusions. To offset these shortcomings, this study uses meta-analysis to synthesize prior studies to and to examine if the two/three groups of children (Chinese-English bilinguals, and Chinese or English monolinguals) have equal performance on various metalinguistic tasks. The study also employs meta-analytic structural equation modeling to assess the fit of a conceptual model of metalinguistic awareness among

Chinese-English bilingual children metalinguistic awareness and its relationship with different language status, age, cognitive development, sociocultural backgrounds, and language proficiency. The null hypotheses that will be tested are:

1. There is no difference between Chinese-English bilingual children and Chinese or

English monolingual children in terms of metalinguistic awareness.

2. The construct of metalinguistic awareness cannot be measured by word awareness,

syntactic awareness, or phonological awareness in either English or Chinese languages.

3. There is no correlation between metalinguistic awareness and language proficiency,

cognitive development, instructional methods, or social factors.

4. Age, language settings, and first language (either Mandarin or Cantonese) are not

moderators for children‘s metalinguistic awareness.

1.4. Significance of the Study

The contribution of this study is four-folded. First, the comprehensive synthesis of metalinguistic awareness in Chinese-English bilingual children will contribute to the field with respect to the understanding of the construct of metalinguistic awareness, and how the construct should be measured. Second, the fitted conceptual model can bring to light how metalinguistic awareness is related to cognitive development, language proficiency, and social factors. Third, the comprehensive review of previous studies will identify limitations and gaps that existed in

previous studies and will offer guidance for future research designs. Fourth, based on the findings, a list of practical suggestions will be given to policy makers, teachers, parents, and monolingual and bilingual children on how to improve metalinguistic awareness.

2. LITERATURE REVIEW

This review section begins with a discussion of the definition of metalinguistic awareness and the three domains of the construct. It then reviews the five categories of moderating variables: cognition, language proficiency, language instruction, sociocultural influence, and age.

2.1.What Is Metalinguistic Awareness?

The first definition of metalinguistic awareness was made by Cazden (1974, p.29, as cited in Bialystok, 2001a) who defined metalinguistic awareness as ―the ability to make language forms opaque and attend to them in and for themselves‖. It involves special ―cognitive demands‖ and seems to be ―less easily and less universally acquired than the language skills of speaking and listening‖. Cazden also pointed out that higher-order cognitive demand may be involved in metalinguistic processing, but failed to identify specific higher-order cognitive demands that might be important.

The definition that has been widely used in research is restated by Mora (2005), who considers metalinguistic awareness as the ability to objectify language as a process for conveying meaning as well as symbol/medium in its own right. She further indicated the role it plays in explaining the execution and transfer of linguistic knowledge across languages in bilinguals and multilinguals. She classified the ability into three categories based on conscious reflection on the nature of language. The first category referred to the awareness that language had a greater potential function than simple symbols. The second category involved the awareness that words were separable from their referents. The third category brought up the awareness that language is a structure that can be manipulated. Mora‘s definition reconstructed the definition endorsed in many research studies, which have usually concentrated on one subcategory.

2.2. Domains of Metalinguistic Awareness

Three domains of metalinguistic awareness have been investigated in previous research: word awareness, syntactic awareness, and phonological awareness (see Table 1.).

Table 1 Metalinguistic Awareness Domain Measurements in Previous Studies

Domain Measurements Word awareness Word segmentation task Meaning and referent task Symbol substitution task Nonphysical nature task Syntactic awareness Grammaticality judgment task Grammaticality error correction task Grammaticality error correction and justification task Sentence ambiguity task Grammaticality judgment with misleading cues Phonological awareness Syllable awareness task Onset-rime awareness task Phonemic awareness task Tone awareness task

2.2.1. Word awareness.

The literature has concentrated on four insights that children should gain before they are fully aware of the abstract feature of words. As listed in Table 1, the first is the awareness of a segmented process that isolates a word as a significant unit. This type of awareness is usually examined through word segmentation tasks. For instance, a child will be asked to count the number of words in a sentence or define what a word is to demonstrate knowledge of the appropriate boundaries (Ben-Zeev, 1977). In this task, children must overcome the natural strategy of paying attention to meaning and instead pay attention to the word boundaries (Fox &

Routh, 1980). The natural tendency to attend to meaning may prevent young children from solving this problem.

The second awareness is the stability of meanings of the words, which is usually tested in meaning and referent tasks. The aim of these tasks is to assess children‘s belief in the stability of the meanings of words in the face of destruction of the word‘s empirical referent. For example,

Cummins (1978) conducted a study in which children were asked if the meaning of a word could remain stable even when the referenced object had ceased to exist, such as the continued existence of the word giraffe eve if there were no giraffes left in the world. This task not only assesses bilingual children‘s linguistic flexibility but also gauges children‘s reasoning ability for problems that extended beyond the domain of language.

The third type of word awareness is the arbitrary relation between words and their designated meanings. Symbol substitution tasks are always used to test this type of metalinguistic knowledge. The most famous task is the sun-moon task (Cummins, 1978), in which children were asked, ―Suppose you were making up names for things, could you then call the sun the moon and the moon the sun (p.136)?‖ After responding to this question, children

were further questioned, ―Now suppose that happened and everybody decided to call the sun the moon and the moon the sun, what would you call the thing in the sky when you go to bed at night

(p.136)?‖ Then children were asked to describe what the sky would look like when they were going to bed. To successfully solve this problem, children must dissociate the word from its conventional meaning, ignoring a fundamental part of using language.

The fourth type of word awareness is the nonphysical nature of words. Children were asked whether they could sense the physical properties of the objects that words represented.

One example from Cummins (1978) is: ―is the word book made of paper (p.137)?‖ Another example in the same study asks the question: ―does the word bird have feathers (p.137)?‖ The intention is to see if children have the awareness that words are just symbol representation of objects and do not have the tangible properties of objects.

Different from English words, which are based on alphabetic letters, Chinese character is ideographic as the majority of Chinese characters can be broken down into constituent parts, which are the smallest meaning units. As noted in Homer (2000), only about 18% of Chinese characters evolved directly from their ancient pictographs (i.e., the character ―日‖ is a pictorial symbol of the sun) and the remaining 83% are compound characters. Each of the compound characters is a combination of two or more other characters (Homer, 2000). The compound characters can be further categorized into two groups: the first group is compound ideographs, in which each radical conveys meaning of the character. For example, the character for ―forest‖—

―林‖ —is made up of two trees ―木‖. The other group accounts for the majority of compound characters. A typical character in this group contains two radicals: one conveys the meaning and the other suggests the pronunciation. For instance, in the character for meal—―饭‖, the left radical ―饣‖ means something related to food and indicates the meaning of this character; the

right radical ―反‖ suggests the pronunciation of the character but it means the opposite, which is totally irrelevant to the meaning of the character. It should be noted that in most cases, neither the phonetic nor the radical conveys information of the character exactly, and readers must either guess or have memorized the character and its proper pronunciation (Mair, 1996).

2.2.2. Syntactic awareness.

Syntactic awareness refers to the need to make a judgment about the grammatical acceptability of a sentence. The first type of syntactic awareness task involves a grammaticality judgment task. The assumption of this task is that errors can be detected only if attention is directed to the form of the sentence. Since usual processing of language takes greater account of meaning, the redirection to form constitutes an aspect of metalinguistic functioning. As a test of language proficiency, the assumption is that only native speakers can make reliable judgments about sentence acceptability, so a comparison between non-natives and natives in their judgment decisions provides an index of how proficient or ―native-like‖ the learner is. The second type of grammaticality judgment task required children to judge and then to correct the syntactic structure of sentences (Galambos & Hakuta, 1988). The third type of task required children to note any errors, correct the errors, and explain the errors (Galambos & Goldin-Meadow, 1990).

The fourth type of task required children to analyze the ambiguity in sentences and then to paraphrase the possible interpretations that are caused by the grammatical ambiguity.

Besides the conventional grammaticality judgment tasks, the fifth type of task altered the difficulty of attending to the grammatical form by introducing misleading semantic information

(Bialystok, 1986, 1988; De Villiers & De Villiers, 1972). The conventional judgment tasks required children to decide whether or not there are grammatical violations. The extent to which subjects could do this was an indication of their level of grammatical analysis. If the sentence

also contained incorrect semantic information, then it became more difficult for young children to ignore these meaning confusions and attend only to the correct structure criteria.

Chinese syntax is much easier than it looks. The characters are never modified. Children do not have to bother with conjugation, declination, masculine or feminine, singular or plural forms. At the basic level, Chinese sentence order is similar to English, which follows the structure of subject + verb + object. For instance, ―我喜欢中文‖ (I like Chinese) follow the same word order as in English. However, if one wants to build more complex sentences, some differences arise. The more complex the sentence is, the more distant the structure is from

English. Unlike English, one of the unique features in Chinese syntax is the loose word category, such as noun, verb, preposition, etc.

The part of speech of a particular word depends on the linguistic and the functional context in which it is used. For instance, the word ―给‖ /gei/ can have the function of a verb in the sentence ―给你‖, meaning to give it to you; but also of a preposition meaning it is for you in the sentence ―给你的‖. Another example is the word ―来‖ /lai/, which can be used as the verb come and the preposition from. An adjective can become a verb in some situation, so the word

―大‖ /da/ is the adjective big as well as the verb to grow up just by adding an adverb ―了‖/le/.

Since Chinese-English bilingual children need to attend to the complex linguistic and functional contexts, it would be very hard for them to determine which one is the main verb in Chinese.

Another feature of Chinese syntax is that the subject and object pronouns share the same form. Plural pronouns are the combination of singular pronouns and the suffix ―们‖. For example,

―我‖ /wo/ (I/me), ―你‖ /ni/ (you), ―他‖ /ta/ (he/she/it/him/her) become ―我们‖ /wo men/ (we/us),

―你们‖ /ni men/ (you), ―他们‖ /ta men/ (they/them). Similar to English, Chinese adjectives are

placed right before the nouns they describe. The negative adjective is formed by putting an adverb ―不‖ /bu/ before it. For instance, ―不好‖ /bu hao/ means not good. Possession can be shown by adding ―的‖ /de/ after a pronoun and before the thing that is possessed, such as ―我的‖

/wo de/ (my/mine), ―他们的‖ /ta men de/ (their/theirs).

In Chinese syntax, verbs do not change with their subjects. Chinese verbs remain the same form regardless of person, gender, number, time, etc. Hence, ―我是学生‖ /wo shi xue sheng/ (I am a student) and ―她是老师‖ /ta shi lao shi/ (she is a teacher) share the same verb ―是‖

/shi/. The particle ―已经‖ /yi jing/ is suffixed to a verb to change it to past tense, so ―他已经走了‖

/ta yi jing zou le/ means he already left. If you add a particle ―着‖ /zhe/ after a verb, it indicates the continuous aspect of an action. For example, ―他看着书‖ /ta kan zhe shu/ means he is reading a book. The particle ―过‖ can be used to suggest things that take place in a past time period by suffixing it to a verb. One example is ―我去过北京‖ /wo qu guo Beijing/, which means I have been to Beijing. Verb ―要‖ or ―想‖ can be used to indicate the future, so ―我要去北

京‖ /wo yao qu Beijing/ means I am going to Beijing.

Another aspect that deserves attention is Chinese adverbs. Quite a number of Chinese adverbs cannot be directly translated into English, such as the adverb ―得‖ /de/, ―了‖ /le/, etc, which provides linguistic contexts for the switch of the lexical class in a phrase. You can put these adverbs after a word or an adjective and it modified its meaning. In addition to the big—to grow up example, if you put the word ―了‖ /le/ after the word ―好‖ /hao/ (meaning good), the meaning changes to I am done. Or you can put them at the end of a sentence to change its meaning. Some researchers showed that Chinese-English bilingual children as young as two years of age can demonstrate syntactic sensitivity in Chinese language (Clark, 1995; Ku &

Anderson, 2003; Wang, Sagae, & Mitamura, 2006). Other researchers (such as, Chen, Ning, Bi,

& Dunlap, 2008) claimed that Chinese syntactic awareness varies with age and literacy experience; and children cannot really develop syntactic awareness until they receive explicit instruction of the metalinguistic features of the language.

2.2.3. Phonological awareness.

Phonological awareness tasks require the perception and manipulation of sound at three levels of sound structure: syllables, onsets and rimes, and phonemes (Gillon, 2004). The three levels are ordered from the coarsest awareness to the finest awareness. Despite the large variety of phonological awareness tasks, all of them require children to be able to of identify, compare, separate, combine, and generate the sounds (Gillon, 2004).

As indicated in Table 1, four types of phonological awareness tasks will be included in the proposed study. The first type of task is to assess children‘s syllabic awareness. One example from Yelland, Pollard, and Mercuri (1993) was to ask children to judge whether pictured objects had long names with more syllables or short names with fewer syllables. The second type of task aims to examine children‘s onset-rime awareness. In Bialystok, Majumder, and Martin (2003), children were asked to replace the first sound in a word with the first sound from another word and produce a new word. For instance, the word ―dry‖ could be converted to ―try‖ by substituting the first sound of ―tag‖ into the target word. Children were asked, ―take away the first sound from dry and put in the first sound from tag, what is the new word?‖ The third type of task is phonemic awareness tasks. Children would be expected to segment words into phonemes.

For example, ―what is the last sound in ‗jump‘?‖ or ―How many sounds do you hear in the word

‗jump‘?‖ Phonemic awareness tasks were widely used to assess the phonological skills of

Chinese-English bilingual children.

Syllable, the basic speech unit of Chinese language, is composed of two elements: the onset and rime. The onset is made of a single consonant and the rime contains vowel(s). All

Chinese characters are single syllabic. This result in a much smaller number of Chinese syllables and a much greater number of homophones compared to English language (Wang, Perfetti, &

Liu, 2005). Different from English, onset and rime are already the finest grain and there is no phonemic level in Chinese phonology. In order to make it easier to distinguish among so many homophones, each character is attached with one of the four tones, which is a special sound system in Chinese. Since the syllables are not represented in written Chinese, Pinyin—the

Chinese phonemic coding system is taught to help connect the sound with the print (Huang and

Hanley, 1995). When people learn a new character, they need to look up the Pinyin to learn the pronunciation. Therefore, reading Chinese appears more difficult than reading English for

Chinese-English bilingual children.

2.3. Cognition and Metalinguistic Awareness

Bialystok‘s analysis and control framework (1991) viewed metalinguistic awareness as a processing term and pointed out that any categorization based solely on skills required by the specific metalinguistic task undermined the consistency in the subcategories of linguistic competence and failed to evaluate the various developmental stages of bilingual children. The processing description (Bialystok, 1991) is based on two cognitive processes that are implicated in language acquisition: analysis of representational structures and control for selective attention.

The analysis of representational structures refers to children‘s ability to construct mental representations with more detail and structure than was part of their initially implicit knowledge.

Representations that are more explicit are more amenable to conscious access and to intentional manipulation (Bialystok, 2001b). Karmiloff-Smith (1994) articulates a theory in which

representational description is the central mechanism for cognitive development. This processing component captures the need for metalinguistic behaviors to be based on knowledge that is more explicit or more formal than that needed for more ordinary linguistic performance. On the other hand, control for selective attention is responsible for directing attention to specific aspects of either a stimulus field or a mental representation as problems are solved in real time. The need for control is most apparent when a problem contains conflict or ambiguity and the correct solution requires attending to one of the two plausible representations and inhibiting or resisting attention to the other. Tipper and McLaren (1990) have identified this development of inhibition as one of the crucial advances in attention. Problems that present greater degrees of conflict require higher levels of control of attention. These problems also elicit performance that is more metalinguistic.

In general, any tasks that place high demands on the analysis and control are metalinguistic. Greater involvement of each of the two processes makes tasks more difficult, and this difficulty results in behavior appearing to be increasingly metalinguistic (Bialystok, 2001b).

One thing that needs to be highlighted is that analysis and control are not completely independent. According to Bialystok (2001b), attention presumes exclusive focus perception on something, so greater levels of attention are invoked only when there are greater levels of representational complexity. Hence, it is expected that increases in the levels of analysis precede increases in levels of control (Bialystok, 2001b).

Bilingualism advocates believe that being proficient in two languages can add to the cognitive flexibility of the child. At an early age, children start establishing an understanding that words in different languages may imply different shades of meaning and are used with different forms. Bialystok and Hakuta (1994) pointed out that this is because bilingual children receive

more linguistic input and require a greater amount of language analysis in their reading and writing processes. Another study done by Bialystok and Martin (2004) showed that bilingual children demonstrate better inhibitory control skills, which indicates that they are better at ignoring irrelevant semantic information and only attend to language structure. This ability can be applied in other academic areas, such as mathematics (Marinova-Todd, Zhao, & Bernhardt,

2010; McBride–Chang & Kail, 2002).

On the other hand, some researchers suggested that bilingualism may have negative influences on children‘s cognitive and academic development. Cummins (1979) claimed that if a child‘s L1 has not reached certain level of proficiency, the child may develop ―semilingualism‖ or ―limited bilingualism‖. Such condition would lead to linguistic confusion among young bilingual learners and thus could disrupt their language progress. Researchers usually took into consideration the relationship between metalinguistic development and various dimensions of cognitive development, including intelligence, short-term memory, math skills, and visual skills

(McBride–Chang & Kail, 2002; McBride-Chang et al., 2008). In light of the incongruity in research findings, this study will look for evidence from previous research of how bilingualism and bicognitivism would influence metalinguistic awareness, controlling for cognitive function.

2.4. Language Proficiency and Metalinguistic Awareness

Cummin‘s Common Underlying Proficiency (CUP) Hypothesis, also called the

Interdependence Hypothesis (1991) argues for the existence of a common underlying proficiency that supports both L1 and L2 language learning. When this hypothesis is applied to reading and writing, the theory contends that when L1 reading and writing abilities reach a certain level of proficiency, involving some degree of automaticity and fluency, those underlying skills will transfer to L2 reading and writing. In other words, metalinguistic and metacognitive skills being

developed in one language can predict corresponding skills in another language acquired later in time. More specifically, phonological awareness skills, word knowledge, reading comprehension measures, and metalinguistic strategies use measures will have significant correlations between performances in L1and L2 (Dressler & Kamil, 2006).

The common underlying proficiency is the knowledge of the universal characteristics of two writing systems. The assumption made in the proposed study is that such ―deep‖ knowledge always requires relatively higher level of both analysis and control. For bilingual children, learning two languages at the same time gives them access to the universal characteristics of two writing systems and builds up their fundamental level awareness (Cummin, 1991). If there are any bilingual advantages, such ―deep‖ awareness and good command of analysis and control should offer some evidence (Dressler & Kamil, 2006).

2.5. Language Instruction and Metalinguistic Awareness

The role of teachers in helping children develop metalinguistic awareness is paramount.

Chinese-English bilingual children in EFL countries (i.e., mainland China and Taiwan) attend

Mandarin immersion programs from kindergarten through grade 12 and children start learning

English as a foreign language in grade 1. It is a requirement for teachers to explicitly explain the language structure and how it is represented in the writing system (Mather & Carstensen, 2005).

However, Moats (1994) found that many teachers are not well prepared to teach metalinguistic knowledge to young children. Compared with Chinese language teachers, EFL teachers have more implicit metalinguistic awareness, but this does not mean that they can explicitly apply it in their teaching and direct observation of children‘s performance. The only metalinguistic skill that is not taught explicitly in Hong Kong is phonological awareness. As mentioned earlier, instead of

teaching the Pinyin system or Zhu-Yin-Fu-Hao, teachers in Hong Kong take a ―look-and-say‖ method, and their teaching approach aligns well with the ESL immersion background.

Unlike the bilingual immersion environment in Hong Kong or Canada, there is no

Chinese-English bilingual program offered in U.S. K–12 public schools. Thus, many Chinese immigrant parents register their children in community-based Chinese heritage language (CHL) schools. These schools usually offer classes on weekends and are complementary to, rather than competitive with, formal education (Zhou & Li, 2003). Typically, CHL schools offer 2 hours of

Chinese language and literacy class, and one hour of a Chinese cultural performance/activity class such as calligraphy (Liao & Larke, 2008). As bilingual children receive literacy instruction in two physically and socially separated learning contexts, it is still unknown to what extent CHL schools affect Chinese-English bilingual children develop their metalinguistic and biliteracy skills.

According to Zhou & Li (2003), the teachers in CHL schools are volunteers living in the local community and mostly have not received formal education in language education. The teaching approaches employed by the Chinese teachers are learned from experience and aim to help children learn the thousands of characters needed to become functionally literate. In the

―concentrated method‖, for example, children are taught characters in clusters of about 10, which have been grouped together based on related shape, sound or meaning (Zhou & Li, 2003).

Another approach is the use of Pinyin during the beginning of literacy acquisition. Children learn Pinyin during the first few weeks, after which it is used to facilitate the learning of characters (Shu & Anderson, 1999). This proposed BMAM model will consider both English and Chinese language teachers‘ teaching techniques in order to better interpret if explicit instruction helps the development of metalinguistic awareness.

2.6. Sociocultural Factors and Metalinguistic Awareness

In an attempt to discover the simple patterns and maintain reliability, prior studies usually recruited English monolingual and Chinese-English bilingual children from a rather monochromatic context. The typical comparison is done between an English monolingual group and a Chinese-English bilingual group who are from a middle class background with educated parents who support bilingualism and keep home literacy routine. Until now, there is little empirical evidence about the development of bilingual children from other social contexts.

Aggregating research studies using meta-analysis can enable researchers to compare children‘s metalinguistic development across social classes. Bialystok (2001a) further noted that the course and timelines of children‘s language acquisition are marked by the social class in which the child resides. In addition, children‘s development of metalinguistic awareness and acquisition of biliteracy are strongly influenced by the educational expectations in the home and the parents‘ proficiencies in the two languages (Bowey, 1995). Further, peer influence greatly enhances children‘s metalinguistic awareness. According to Newman and Church (1990), by observing, collaborating, and seeking help from more capable peers, children gradually enrich their understanding of language structure and meaning. Therefore, this study takes into consideration social-economic status, parents‘ attitude towards Chinese-English bilingualism, home literacy, and peer influence as social factors and to explore if the patterns found across different language groups.

2.7. Age and Metalinguistic Awareness

In this study, children‘s metalinguistic development will be evaluated based on phases rather than the global stages espoused by the cognitive stage model. Karmiloff-Smith (1994) defined phases as the cycles of processes that recur again and again as different aspects of the

linguistic system develop. While interpreting the data, it is important to look for the possibility that a child may be at different phases of linguistic awareness, not only broadly for different components of language, (e.g., syntax, phonology, morphology), but also for different specific language forms.

3. THE BILINGUAL METALINGUISTIC AWARENESS MODEL

The Bilingual Metalinguistic Awareness Model (BMAM) is proposed in this study to examine Chinese-English bilingual children‘s metalinguistic awareness. BMAM depicts the interaction among Chinese-English bilingual children‘s cognition, age, language development, schooling, and sociocultural influences. It also highlights how metalinguistic awareness can be measured under three domains: word awareness, syntactic awareness, and phonological awareness.

As Clark (2004) described, children first set up conceptual representations, then acquire linguistic representations for talking about the experience through social interaction with their caregivers, teachers, peers, and other people in the community. Their conceptual representations of objects, relations and events that were established early in L1 serve as a general underpinning for universals in languages. As soon as children start learning L2, they begin experiencing diverged paths. For the same concept or experience, bilingual children usually create two unique sets of linguistic representations. Either of the systems would be retrieved for language processing depending on the language context. But still, there are some overlaps in the requirement of cognitive skills, sociocultural communicative skills, reading skills, and metalinguistic skills. BMAM was proposed based on a comprehensive review of the literature.

However, due to the lack of measurement in syntactic awareness and the lack of information about Chinese and English language instructional methods, and the homogeneous socioeconomic groups across studies, only part of the model (as shown in Figure 1.) could be tested.

Figure 1 Bilingual Metalinguistic Awareness Model

4. METHODS

This study combines the techniques of meta-analysis (MA) and structural equation modeling (SEM) with the intention of building on the strengths of both approaches to test if

Chinese-English bilingualism promotes the transfer of metalinguistic awareness and also to test a proposed Bilingual Metalinguistic Awareness Model using meta-analytic data. The methods section first introduces the MA and SEM. It then explains the advantages of integrating the two analytic approaches by conducting a meta-analytic structural equation modeling (MASEM). The second portion describes the detailed implementation steps including data collection and coding.

The last portion explains data analysis procedures using MA and MASEM.

4.1. Meta-Analysis

Meta-Analysis (MA) uses statistical techniques to synthesize quantitative data from a series of related studies in order to reach a conclusion that has greater statistical power than any single study due to larger sample size. MA uses effect sizes such as Cohen‘s d, Hedges‘ g,

Pearson‘s r, or odds ratios, as quantitative indices to summarize results of prior research.

Researchers also use MA to test heterogeneity among included studies. When effect sizes are found to be homogeneous, hypothesis can be tested by calculating mean effect sizes together with confidence estimates. When heterogeneity is found across studies, moderator analysis is used to examine the variations of effect sizes. MA is widely used in psychological, behavioral, and medical sciences (Hedges & Olkin, 1985; Hunter & Schmidt, 2004; Shadish & Haddock,

2009; Sutton et al., 2000).

Despite the synthesizing abilities of MA, it usually focuses on finding single effects rather than the development of explanatory theories (Shadish, 1996). Shadish suggested testing

multivariate models that include causal assumptions (e.g. mediating models) to address this problem.

4.2. Structural Equation Modeling

Structural equation modeling (SEM) is a multivariate method that aims to explore or confirm the relationships between latent and manifest variables. It can complement MA and help researchers explore the relationships between many variables. Measurement of latent variables, such as metalinguistic awareness, is usually considered to be error prone. When measurement error is not removed from ―ture‖ construct variance, this error variance can bias between construct estimates. To solve this problem, SEM enables researchers to use multiple items to measure latent constructs and partial out item measurement error from ―true‖ construct variance.

This helps researchers to locate unbiased estimates of between construct relationships.

SEM can be used in exploratory or confirmatory fashion, or for theory development and also testing. This study employs confirmatory modeling to test the proposed theoretical model: the Bilingual Metalinguistic Awareness Model (BMAM). This study will test the BMAM for fit to the data and also test the relationships between operationalized hypothetical latent variables.

4.3. Meta-Analytic Structural Equation Modeling

Meta-analytic structural equation modeling (MASEM) combines the techniques of synthesizing correlation matrices with the testing of structural equation models. MASEM firstly synthesizes the correlation matrices across studies to test the homogeneity of studies. If homogeneity is found, a pooled correlation matrix is then created. If the studies are found to be heterogeneous, moderator analysis is then conducted in order to explain the variations (Cheung

& Chan, 2005).

Such integration offers a lot of advantages and possibilities. First, MASEM builds on the strengths of both techniques and intends to answer unique research questions. As Viswesvaran and Ones (1995) suggested, some studies investigated the correlation between variables A and B, other studies examined the relationship between C and D. MASEM can help meta-analyze these variables and use the correlation estimates as input and test the relationship between all four variables. Second, the structural model can be tested with a sufficiently large sample and provides better inferences. The sample sizes in metalinguistic research are usually not very large.

Besides being a solution to good statistical power, MASEM also generate more stable parameter estimates and fit statistics (Landis, 2013; Viswesvaran & Ones, 1995).

4.4. Data Collection

4.4.1. Selection of Studies

This meta-analysis aims to provide an objective, quantitative review of the corpus of studies on how Chinese-English bilingual children make cross-language transfer of metalinguistic awareness. The search of the literature began with the goal to collect all published studies of metalinguistic awareness among Chinese- English bilingual children. The following electronic databases were searched systematically: Google Scholar, OhioLINK Electronic

Journal Center, Jstor, ProQuest Research Library, InformaWorld, Academic Research Library,

PsychInfo, and ERIC. Different combinations of keywords were used in the search: metalinguistic awareness, metalinguistic skills, metalinguistic processing, metalinguistic knowledge, and metalinguistic sensitivity in combinations with English acquisition/performance,

Chinese acquisition/performance, English reading, Chinese reading, English literacy, Chinese literacy, English, Chinese, biliteracy acquisition, bilingualism, Chinese-English bilingual,

Chinese-English biliteracy, cross-language transfer, cross-language similarity, alphabetic, non- alphabetic, word awareness, syntactic awareness, and phonological awareness.

In case the electronic databases might exclude some studies, hand searching was also used.

The hand-searched journals include Applied Psycholinguistics, Cognition, Journal of

Educational Psychology, Scientific Studies of Reading, Reading and Writing: An

Interdisciplinary Journal, Child Development, and Applied Psycholinguistics. Dissertation

Abstracts International was also hand searched to include unpublished studies.

―Snowball‖ sampling, suggested by Given (2008), was employed and the reference lists of the collected articles were searched for additional studies. Studies with identical authors were tagged in case there was overlap across study samples. For overlapping samples, only the data from the larger sample or with more measurements were included and the overlapping study was excluded from the analysis.

Initially, 64 articles and 7 dissertations related to the research topic were identified. The abstract of each article were screened against the inclusion criteria for the meta-analysis. The criteria included the reporting of (a) samples that included children only (i.e., participants were under 12 years old); (b) comparison measures of metalinguistic awareness between Chinese or

English monolingual children and Chinese-English bilingual children; (c) reporting statistics permitting the calculation or estimation of effect sizes, i.e., means and standard deviations; (d) reporting correlation matrices of variables.

Most of the studies were rejected because they did not meet the third criterion. Finally, 49 independent studies (N=4708) met the criteria for inclusion and were entered into the meta- analysis and 27 studies (N = 2,687) were included in the meta-analytic structural equation modeling.

4.4.2. Coding of Studies

The general categories of coding for each article included (a) article characteristics, (b) participant characteristics, (c) types of metalinguistic tasks, (d) measures of metalinguistic performance, (e) measures of moderating variables, and (f) correlation matrices of variables.

(see Appendix A).

Article Characteristics.

The article characteristics were defined and recorded as below:

Name of the author. The name of the first author was recorded for each article.

Year of publication. The year of publication was recorded for each article.

Funding. The sources of funding were recorded for each article.

Study design. Chinese-English monolingual participants were classified as control group, while Chinese-English bilingual participants were classified as the experimental group.

Participant Characteristics.

The participant characteristics were defined and coded as below:

Age. The mean age of each sample was recorded in years.

Location. The places where the studies were conducted were coded. For locations outside of U.S., the country where the sample was recruited was recorded. For samples from the U.S., the specific region, i.e. southwest, was recorded.

Language setting. The language environment was coded as either ESL or EFL.

First language. The participants‘ first languages were recorded as one of the three categories: Mandarin, Cantonese, or English.

Socioeconomic status. Participants‘ socioeconomic status was coded into one of the three categories: upper class, middle class, and working class.

Chinese-English schooling. The length of school and the level of explicit instruction of metalinguistic awareness were coded into three categories: good, average, and poor.

Home biliteracy. Home biliteracy was coded based on information regarding parents‘ attitude towards bilingualism, home biliteracy practices, and peer influence of metalinguistic skills.

Types of Metalinguistic Tasks.

All measures were coded. Initially, 33 tasks were included. Later the variables were grouped into the following three categories for analysis:

Word awareness tasks. Sample tasks include word segmentation, meaning and referent, symbol substitution, and nonphysical nature.

Syntactic awareness tasks. Sample tasks include grammaticality judgment task, grammaticality error correction task, grammaticality error correction and justification task, sentence ambiguity task, grammaticality judgment task with misleading cues.

Phonological awareness task. Sample tasks include syllable awareness tasks, onset-rime awareness tasks, phonemic awareness tasks, tone awareness tasks.

Measures of Metalinguistic Performance.

The measures outcomes that were coded include sample size, mean, and standard deviation, in order to calculate Cohen‘s d.

Measures of Moderating Variables.

Moderating variables that were coded included English reading task, Chinese reading task, memory task, math task, visual skill task. Sample sizes, means, and standard deviations were also collected.

Correlation Matrices of Variables.

All the correlation matrices of variables were copied to fit the conceptual model in the meta-analytic structural equation modeling process.

4.5. Data Analysis

This study employed two statistical analyses: meta-analysis (MA) and meta-analytic structural equation modeling (MASEM). MA was used to combine previous research in Chinese metalinguistic awareness and explore if Chinese-English bilingual children and English or

Chinese monolingual children differ significantly in terms of metalinguistic awareness. In other words, MA tests whether Chinese-English bilingualism facilitates the transfer of metalinguistic awareness across the two languages. MASEM was used to examine the relationship among five latent variables: Chinese metalinguistic awareness, English metalinguistic awareness, Chinese language proficiency, English language proficiency, and cognition. The following will explain the detailed procedures these two analyses.

4.5.1. Meta-Analysis.

MA was based on methods proposed by Hedges and Olkin (1985) and also described in

Cooper, Hedges, and Valentine (2009). The standardized mean difference statistic d was used to combine the effect sizes:

̅ ̅

̅ ̅ where is the mean of the bilingual group in the ith study, is the mean of the Chinese

or English monolingual group in the ith study, and is the pooled standard deviation of the two 31

groups. Effect sizes were calculated so that a positive effect size indicated a favorable outcome for the Chinese-English bilingual group.

Multiple effect sizes from each individual study were calculated and put into the meta- analysis as long as the samples were independent of each other. In cases when multiple bilingual groups were compared with a single monolingual group, or when multiple monolingual groups were compared with a single bilingual group, the effect sizes were averaged before they were put into the analysis. When there were multiple measures for both of the two groups and no specific comparisons were indicated, these data were paired based on the type of measurements and an effect size was calculated for each measurement and then averaged and entered into the meta- analysis. For cases in which one dependent variable was measured with different tasks (e.g. phonological awareness was measured by phoneme segmentation task and also verbal rhyme judgment task), an averaged effect size was obtained.

Then, the weighted effect sizes and the 95% confidence intervals were calculated. The weighted effect sizes were calculated with the formula

∑

where (i = 1, …, k) is the observed effect size, k is the number of studies, and

The 95% confidence intervals were calculated with the formula

√

Then a homogeneity test was conducted to determine whether the variance is due to variation between studies and/or sampling error. The null hypothesis of Q statistic test is calculated with

∑ ∑

If H0 is not rejected, the effect sizes are homogeneous, which suggest that all variation is due to sampling error, a common population effect was estimated, and a fixed-effects model can be used. Otherwise, when H0 is rejected and the effect sizes are heterogeneous, all variation is due to variation between studies plus sampling error. This indicates that the effects do not seem to be estimates of a single population parameter. Then a random-effects model is more appropriate.

Finally, the effects of various moderators were assessed. Meta-ANOVA was used to examine categorical variables including socioeconomic status, language setting, home biliteracy, schooling, and first language. Meta-Regression was used for continuous variables, including

English/Chinese reading proficiency, memory, math, and visual skills. All of the analyses were conducted in SPSS 17.0.

4.5.2. Meta-Analytic Structural Equation Modeling

This study used the Two-Stage Structural Equation Modeling approach (TSSEM) proposed by Cheung and Chan (2005) and Cheung (2013) to examine the relationship among five latent variables: Chinese metalinguistic awareness, English metalinguistic awareness,

Chinese language proficiency, English language proficiency, and cognition. In the first stage, correlation matrices were pooled together. A homogeneity test was conducted and the Q statistic was calculated to check the appropriate model to use: fixed-effects model or random-effects model. Fixed effects models assume the studies are homogeneous and share common effect sizes

(Bonett, 2009; Shuster, 2010) and intend to draw conclusions based on selected studies. In contrast, random-effects models assume the population correlation matrices vary across studies.

The degree of heterogeneity of the correlation matrices can be qualified by statistic proposed by Higgins et al. (2003). In the second stage, the pooled correlation matrix is used to fit the proposed structural models.

4.5.2.1.Stage I Analysis

Fixed effects models assume that the population correlation matrices are the same across all studies. The correlation matrix in ith study can be divided as a correlation matrix ( ) and a diagonal matrix of standard deviations ( ) by

∑

Under the assumption of homogeneity, constraints of P follow whereas is supposed to vary across studies. For any incomplete correlation coefficients, the missing correlations are excluded from the constraints.

A random-effects model for the correlation vectors in the ith correlation matrix is

Where is the variance component of the study-specific random effects, and

is the known sampling covariance matrix in the ith study. In conducting meta- analysis, Higgins et al. (2003) proposed the use of to quantify the degree of heterogeneity in the effect size:

̂ ̃ where ̂ is the estimated heterogeneity and ̃ is the within-study variance. can be interpreted as the proportion of the total variation of the effect size that is due to the between study heterogeneity. Higgins et al. (2003) also proposed to estimate ̃ by

∑ ̃ ∑ ∑

Where n is the number of studies. As a rule of thumb, of 25%, 50% and 75% can be considered as low, moderate, and high heterogeneity (Higgins et al., 2003).

4.5.2.2.Stage II Analysis

Cheung and Chan (2005, 2009) proposed the use of weighted least squares (WLS) to fit structural equation models. Suppose the proposed structural model on the population correlation vector in the Stage 2 analysis is , the discrepancy function

̂ ( ̂ ) ̂

and are from Stage I analysis, there is no hat in both and . This approach, as commented on in Browne (1984), is called WLS or asymptotically distribution-free method. Using the WLS estimation function, parameter estimates with appropriate SEs, test statistics and goodness of fit indices can be obtained in Stage II analysis. When the studies are heterogeneous, it is questionable to pool them with a fixed-effects model. To solve this problem, studies were grouped into relatively homogeneous subgroups based on different categorical moderators (Cheung & Chan, 2005). Age, language background, and language setting were used as categorical moderators. Studies were classified into groups and a fixed-effects MESEM was conducted for each group. Instead of having one pooled correlation matrix, several pooled correlation matrices were obtained.

After the Stage I analysis with a random-effects model, a vector of the pooled correlation matrix ̂ and its asymptotic sampling covariance matrix ̂ are estimated. The discrepancy function is the same as that under a fixed-effects model:

̂ ( ̂ ) ̂

and are observed values.

MASEM was conducted using software R. 3.0.2 and package metaSEM. The fit statistics that were used are the standardized root-mean-square residual (SRMR, Hu & Bentler, 1995), root-mean-square error of approximation (RMSEA, Steiger & Lind, 1980), and comparative fit index (CFI, Bentler, 1990). Following traditional conventions for model fit evaluation, an acceptable fit is indicated by 0.90 and above for CFI (Bentler & Bonnett, 1980). For SRMR, a good fit is indicated by 0.08 and below (Hu & Bentler, 1998). For RMSEA, a good fit is indicated by 0.05 and below, while an acceptable fit is indicated by values between 0.05 and 0.08

(Browne & Cudeck, 1993).

5. RESULTS

This section contains both the results of the meta-analysis and the meta-analytic structural equation modeling. For MA, the descriptive statistics, publication bias, overall effect of Chinese-

English bilingualism, and effects of moderating variables are presented. For MASEM, the descriptive statistics, and the results of fixed effects model and random effects model are provided.

5.1. Results of Meta-Analysis

5.1.1 Description of Studies

Forty nine studies (N = 4,708) were included in the meta-analysis. Among 4708 participants,

2549 children are Chinese-English bilinguals and 483 children are Chinese monolinguals, and

1676 children are English monolinguals. A total of 49 independent effect sizes were calculated.

Of the entire sample, 15 studies used word awareness tasks; 0 studies used syntactic awareness tasks; and 34 used phonological awareness tasks. The average age of the participants ranged from 4 to 11 years (M = 7.14, SD = 2.04). The monolingual participants‘ ages ranged from 4.42 to 11.44 years (M = 7.04, SD = 2.37) while the bilingual participants ages ranged from 4 to 8 years (M = 6.35, SD = 1.14). Among the 49 samples, a total of 29 groups of participants are

Cantonese speakers (n = 1657) and 20 groups of participants are Mandarin speakers (n = 596).

Among the 49 samples, a total of 6 groups of participants are Mandarin monolinguals (n = 544),

43 groups of participants are English monolinguals (n = 1605), 20 groups of participants are

Mandarin-English bilinguals (n = 906), and 29 groups are Cantonese-English bilinguals (n =

1503). Six cases were conducted under English as a foreign language setting while 43 were carried out in English as second language countries.

5.1.2 Publication Bias

Publication bias occurs when the publication status depends on the statistical significance of the findings (Cooper, Hedges, & Valentine, 2009). One way to assess whether a set of studies is problematic for the included studies is to examine a funnel plot. If publication bias is not present, the funnel plot appears roughly symmetrical. As shown in Figure 2, the effect sizes were evenly distributed around the underlying true effect size, with more variability in the smaller studies than the larger ones. Therefore, no publication bias was detected in this meta-analysis.

Figure 2.Scatter Plot for Publication Bias

5.1.3 Overall Effect of Chinese-English Bilingualism

The alpha level was set to 0.05. A homogeneity test (see Table 2) shows that the effect sizes were heterogeneous, with (49) = 302.74, p < 0.01, and indicated that the variation is due to variation between studies plus sampling error and the effects were not from the same population. The overall mean effect of Chinese-English bilingualism was computed under the random effects model, which allows for estimation of an average population effect. According to

Cohen‘s (1988) benchmarks of effect sizes (.20 = small, .50 = medium, .80 = large), no significant overall difference (d = -.0083, 95% CI [-.1731, .1565]) was found between

English/Chinese monolingual children and Chinese-English bilingual children in their performance in metalinguistic tasks. Figure 3 provides a forest plot of 95% confidence intervals of the random effect sizes.

Table 2 Results of effect sizes and Q statistic for overall effects of Chinese-English billingualism

Variable Q (fixed) p Q (random) p Weighted ES 95% CI Variance SE Lower Upper Bilingualism 302.74 .00 46.61 .53 -.0083 -.17 .16 .01 .08

Figure 2 Forest plot of 95% confidence intervals of the random effect sizes

5.1.4 Effects of Moderating Variables

A series of moderator analyses were conducted to investigate the influence on metalinguistic awareness due to the type of metalinguistic task, age, socioeconomic status, first language (English, Mandarin, or Cantonese), language setting (ESL; EFL), Chinese and English schooling, home literacy, parent/peer influence, Chinese-English proficiency, memory, math skills, and visual skills. Table 3 and Table 4 summarize results from the Meta-ANOVA and

Meta-Regression analyses respectively.

Type of metalinguistic task. The alpha level was set to 0.05. The difference between standardized effect sizes for monolingual group and bilingual group significantly differed depending on the type of metalinguistic task, (1) = 163.06, p < 0.00. Small to large effect sizes can be found in Chinese word segmentation task (M = -.587, 95% CI: [ −.828, -

.346]), English onset-rime awareness task (M = -1.105, 95% CI: [−1.642, -.567]), English phonological awareness task (M = .379, 95% CI: [.124 , .633]), and English word non-physical nature task (M = .46, 95% CI: [−.383, 1.302]). However, the half-widths of 95% confidence intervals in these four tasks are very large, which imprecise estimation of the effect sizes.

Bilingual children language setting. The standardized effect sizes for different bilingual groups significantly differed depending on the language setting, (2) = 42.489, p < .011.

A medium-sized effect was found in EFL setting (M = -.587, 95% CI: [−.908 and -.266).

However, the half-widths of 95% confidence interval are very large, which suggests the overly rough estimation of the effect size.

Schooling influences. Chinese heritage language schooling for bilingual children,

English schooling for monolingual children, and English schooling for bilingual children all have small to medium influence in children‘s metalinguistic awareness, with (3) = 12.613, p

< 0.046; (4) = 37.36, p < 0.02; and (5) = 141.70, p < 0.02 respectively.

However, the half-widths of 95% confidence intervals are all very large, and the effects should be interpreted with caution.

As shown in Table 3 and Table 4, a lot of variables fail to play a moderating role in predicting young children‘s metalinguistic awareness. These insignificant variables include socioeconomic status ( (6) = 8.05, p < 0.28), home biliteracy ( (7) = 9.85, p <

0.98), monolingual children‘s first language ( (8) = 47.39, p < 0.09), bilingual children‘s first language ( (9) = 179.67, p < 0.10), age (F = .43, p < 0.52), Chinese language proficiency in Chinese monolingual children (F = 0.08, p < 0.79), Chinese language proficiency in bilingual children (F = 0.62, p < 0.46), English language proficiency in English monolingual children (F = 0.27, p < 0.87) and bilingual children (F = 3.62, p < 0.06), memory in monolingual children (F = 0.15, p < 0.76) and bilingual children (F = 34.41, p < 0.11), math in monolingual children (F = 0.05, p < 0.95) and bilingual children (F = 0.82, p < 0.43), visual skills in monolingual children (F = 0.01, p < 0.93) and bilingual children (F = 7, p < 0.23).

Table 3 Homogeneity Analyses and Mean Effect Sizes for Theoretically Derived Moderators

Variable p M 95% CI Lower Upper SES 8.050 .278 Middle-Upper .348 .008 -.137 .153 Middle 229.533 -.247 -.463 -.031 Bilingual Lang Setting 42.489 .011 EFL 2.628 -.587 -.908 -.266 ESL 227.870 .039 -.112 .190 Home Biliteracy 9.852 .098 Poor 65.233 .174 -.035 .383 Intermediate 12.354 1.122 -.543 2.787 CHL Schooling 12.613 .046 Poor 37.355 -.233 -.510 0.044 Good 99.539 .133 -.194 .460 ENG Schooling (mono) 37.355 .022 Good 8.663 .010 -.135 .155 Excellent 141.699 -.054 -.431 .324 ENG Schooling (bi) 141.699 .002 Poor 29.465 -.677 -1.158 -.196 Good 8.663 -.010 -.135 .115 Excellent 47.389 .346 -.066 .758 Monolingual-1st Lang 47.389 .090 Mandarin 20.773 -.604 -.912 -.296 English 179.667 .088 -.058 .233 Bilingual-1st Lang 179.667 .095 Mandarin 76.012 -.154 -.370 .062 Cantonese 224.593 -.061 -.276 .153 Type of Test 163.058 .000 CHN WA1 2.628 -.587 -.828 .346

CHN ENG PA1 47.814 .034 -.174 .242 ENG PA2 13.383 -1.105 -1.642 -.567 ENG PA3 68.022 .379 .124 .633 ENG WA1 7.774 -.046 -.179 .088 ENG WA2 .002 -.009 -.133 .115 ENG WA4 .617 .460 -.383 1.303

Table 4 Homogeneity Analyses and Mean Effect Sizes for Theoretically Derived Moderators

Variable B Std. Error F p Age .012 .024 .261 .429 .516 CHN proficiency (monolingual) .225 .000 .003 .082 .789 CHN proficiency (bilingual) .012 .002 .003 .624 .425 ENG proficiency (monolingual) .024 .000 .002 .027 .870 ENG proficiency (bilingual) .055 -.004 .002 3.623 .064 Memory (monolingual) .733 .020 .050 .154 .762 Memory (bilingual) .944 -.055 .009 34.408 .107 Math (monolingual) .331 .015 .222 .005 .951 Math (bilingual) .047 .042 .046 .821 .432 Visual Skills (monolingual) .975 .058 .517 .013 .928 Visual Skills (bilingual) .750 -.129 .049 7 .230

5.2.Results of Meta-Analytic Structural Equation Modeling

5.2.1 Description of Studies

Twenty seven studies (N = 2,687) were included in the meta-analytic structural equation modeling. Among 2,687 participants, 782 children are Chinese-English bilinguals with Mandarin as L1, 1,864 children are Chinese-English bilinguals with Cantonese as L1, and 41 children are

English monolinguals. For the 2,646 Chinese-English bilingual children, 316 children live in an

EFL background (i.e. mainland China) while 2,330 of them are from ESL background (i.e. US,

Canada, Hong Kong). 1480 children are from elementary schools, age from 7 to 12, and the rest

1,207 children are from preschools, age from 4 to 6. Since all studies reported that the participants are from middle-class families, socio-economic status was not included in the

MASEM step as a categorical moderator. Also, since only one study briefly mentioned the instructional methods employed in Chinese weekend school, it is impossible to make cross-group comparisons, so instructional methods was also excluded from the MASEM.

In the following results section, both the fixed-effects and random-effects MASEM were reported. Since the correlation matrices of studies are heterogeneous, after pooling all studies together in the fixed-effects model, results are presented by treating age, language background, and language setting as categorical moderators. Since the results of the fixed-effects model is questionable, only the parameter estimates based on random-effects model are presented.

5.2.2 Fixed-Effects Model

The test statistics for the fixed-effects model were summarized in Table 5. The goodness- of-fit indices for Stage I analysis based on a fixed-effects MASEM approach was

and .

Based on the test statistic and the goodness-of-fit indices, the assumption of homogeneity of

correlation matrices was rejected. Thus, twenty seven studies were grouped to different age, language background and language setting groups.

Age group clusters. Among the 27 studies, 17 studies were grouped as elementary schoolers and 10 were preschoolers. The goodness-of-fit indices of Stage I analysis for elementary schoolers and preschoolers were

and , and

and , respectively. The assumption of homogeneity of correlation matrices in these two samples was rejected. The goodness-of-fit indices of the Stage II analysis for the elementary schoolers and preschoolers were

and , and

, respectively. The proposed model appears not to be fitting the data in either elementary schoolers or preschoolers. However, it should be noted that the fit indices in Stage II analysis ignored the rejection of the homogeneity of the correlation matrices in Stage I analysis, it should be interpreted with caution.

Language background clusters. Among 27 studies, 11 studies were Chinese-English bilinguals with Mandarin as L1 and 15 were Chinese-English bilinguals with Cantonese as L1.

The goodness-of-fit indices of Stage I analysis for Mandarin L1 bilinguals and Cantonese L1 bilinguals were and

, and

and , respectively. The assumption of homogeneity of correlation matrices in these two samples was rejected. The goodness-of-fit indices of the Stage II analysis for Mandarin L1 bilinguals and Cantonese L1 bilinguals were

and , and

, respectively.

The proposed model appears not to be fitting the data in either Mandarin L1 bilinguals or

Cantonese L1 bilinguals. However, it should be noted again that the fit indices in Stage II analysis ignored the rejection of the homogeneity of the correlation matrices in Stage I analysis, it should be interpreted with caution.

Language setting clusters. Among 27 studies, 22 studies were in ESL settings and 5 were in EFL settings. The goodness-of-fit indices of Stage I analysis for bilinguals in ESL settings and bilinguals in EFL settings were

, and

and , respectively. The assumption of homogeneity of correlation matrices in these two samples was rejected. The goodness-of-fit indices of the Stage II analysis for bilinguals in ESL settings and bilinguals in EFL settings were

and

, and and , respectively. The proposed model appears not to be fitting the data in either ESL or EFL settings. However, it should be noted again that the fit indices in Stage II analysis ignored the rejection of the homogeneity of the correlation matrices in Stage I analysis, it should be interpreted with caution.

Table 5 Parameter estimates in fixed-effects model

Model Cluster Fixed Stage I analysis Age cluster Elementary Age cluster preschoolers L1 cluster Mandarin L1 cluster Cantonese Setting cluster ESL Setting cluster EFL Stage II analysis Age cluster elementary Age cluster preschoolers L1 cluster Mandarin L1 cluster Cantonese Setting cluster ESL Setting cluster EFL

5.2.3 Random-Effects Model

In Stage I analysis of random-effects model, the range of the index, the percentage of total variance that can be explained by the between study effect, was from 0.71 to 0.92. This indicates that there is huge between-study heterogeneity. A random-effects model is preferred to a fixed-effects model.

The pooled correlation matrix based on the random-effects model was used to fit the five- factor CFA in Stage II analysis (see Table 6.). The goodness-of-fit indices for the proposed model were and

. The proposed model fits the data well. The results also support the proposed higher-order factor structure of the five latent variables. All standardized factor loadings are from moderate to high ranging from 0.4607 to 0.7183. However, two possible correlation between latent variables should be noted: English metalinguistic awareness and cognition highly correlated with a correlation 0.84 with a 95% CI of 0.75 to 0.93; Chinese metalinguistic awareness and cognition were also found to be highly correlated with a correlation 0.76 with a

95% CI of 0.68 to 0.84; Chinese metalinguistic awareness and English metalinguistic awareness were also found to be highly correlated with a correlation 0.65 with a 95% CI of -28.91 to 30.22.

Table 6 Parameter estimates and 95% CI in random-effects model

Estimate Lower bound Upper bound P Random-effects model Measurement loaded on latent Amatrix[1,19] intelligence on cognition 0.346526 0.292220 0.400831 *** Amatrix[2,19] memory on cognition 0.201656 0.142251 0.261060 *** Amatrix[3,19] visual skills on cognition 0.320330 0.262024 0.378636 *** Amatrix[4,19] math on cognition 0.617819 0.558728 0.676910 *** Amatrix[5,20] ENG on ENGdev 0.879236 0.791433 0.967039 *** Amatrix[6,21] ENGWA1 on ENGMA 0.194554 0.141786 0.247321 *** Amatrix[7,21] ENGWA2 on ENGMA 0.457617 0.412677 0.502556 *** Amatrix[8,21] ENGWA3 on ENGMA 0.331428 0.283711 0.379145 *** Amatrix[9,21] ENGPA1 on ENGMA 0.490195 0.442310 0.538080 *** Amatrix[10,21] ENGPA2 on ENGMA 0.476745 0.432712 0.520779 *** Amatrix[11,21] ENGPA3 on ENGMA 0.343293 0.297493 0.389092 *** Amatrix[12,22] CHN on CHNdev 0.946733 0.529183 1.364283 *** Amatrix[13,23] CHNWA1 on CHNMA 0.410268 0.368491 0.452045 *** Amatrix[14,23] CHNWA2 on CHNMA 0.443734 0.403021 0.484447 *** Amatrix[15,23] CHNWA3 on CHNMA 0.642818 0.607931 0.677705 *** Amatrix[16,23] CHNPA1 on CHNMA 0.447774 0.405212 0.490337 *** Amatrix[17,23] CHNPA2 on CHNMA 0.397569 0.355843 0.439295 *** Amatrix[18,23] CHNPA4 on CHNMA 0.427898 0.387788 0.468008 ***

Error variance of measurement Smatrix[1,1] intelligence 0.016997 0.002384 0.031610 * Smatrix[2,2] memory 0.042215 0.028177 0.056254 * Smatrix[3,3] visual skills 0.034070 0.014261 0.053880 * Smatrix[4,4] math 0.019228 0.009559 0.028897 * Smatrix[5,5] ENG 0.013750 0.001650 0.025850 * Smatrix[6,6] ENGWA1 0.013749 0.025850 0.049635 * Smatrix[7,7] ENGWA2 0.014613 0.004194 0.025031 * Smatrix[8,8] ENGWA3 0.037774 0.020978 0.054570 * Smatrix[9,9] ENGPA1 0.048817 0.029233 0.068400 * Smatrix[10,10] ENGPA2 0.014814 0.001626 0.028002 * Smatrix[11,11] ENGPA3 0.018525 0.007488 0.029562 * Smatrix[12,12] CHN 0.021448 0.003553 0.039343 * Smatrix[13,13] CHNWA1 0.034769 0.020386 0.049151 * Smatrix[14,14] CHNWA2 0.019782 0.008186 0.031378 * Smatrix[15,15] CHNWA3 0.016635 0.003670 0.029600 * Smatrix[16,16] CHNPA1 0.023238 0.011336 0.035140 * Smatrix[17,17] CHNPA2 0.025293 0.014630 0.035957 * Smatrix[18,18] CHNPA4 0.030431 0.013710 0.047150 * Smatrix[19,19] cognition 0.015047 0.003080 0.027014 * Smatrix[20,20] ENGdev 0.034114 0.033229 0.034999 * Smatrix[21,21] ENGMA 0.027955 0.013859 0.042051 *

Smatrix[22,22] CHNdev 0.019429 0.009922 0.028935 * Smatrix[23,23] CHNMA 0.011344 0.009122 0.013567 *

Factor correlation between latent Smatrix[20,19] ENGdev and cognition 0.275878 -11.352208 11.903964 Smatrix[21,19] ENGMA and cognition 0.844129 0.754090 0.934168 *** Smatrix[21,20] ENGMA and ENGdev 0.297933 -12.259693 12.855558 Smatrix[22,19] CHNdev and cognition 0.389961 -17.235156 18.015077 Smatrix[22,20] CHNdev and ENGdev 0.184614 -10.912657 11.281885 Smatrix[22,21] CHNdev and ENGMA 0.536851 -23.727143 24.800846 Smatrix[23,19] CHNMA and cognition 0.761886 0.680849 0.842922 *** Smatrix[23,20] CHNMA and ENGdev 0.248609 -10.230071 10.727289 Smatrix[23,21] CHNMA and ENGMA 0.756198 0.696966 0.815430 *** Smatrix[23,22] CHNMA and CHNdev 0.654109 - 28.909509 30.217726 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

6. DISCUSSION

The discussion section begins with interpretations of the results of meta-analysis. It then discusses the interpretations of the results of meta-analytic structural equation modeling. Finally, suggestions are provided for future researchers, policy makers, in-service teachers, parents, and

Chinese-English bilingual children on how to help children improve their metalinguistic awareness.

6.1.Discussion of Meta-Analysis

The meta-analysis combined the results of 49 studies examining the effects of Chinese-

English bilingualism on children‘s transfer of metalinguistic awareness across two languages and the moderating variables associated with the construct. No statistical differences were identified between Chinese or English monolingual children and Chinese-English bilingual children in their metalinguistic skills. This is likely due to heterogeneity between the 49 samples, which seem to be drawn from different populations. The studies involved participants in different countries and areas (i.e., China, Hong Kong, Taiwan, U.K., U.S., Canada, and Australia). The participants are from socially, culturally, and economically different backgrounds. They also receive different education at school and are at different cognitive developmental stages. These added complexities make it difficult to interpret the insignificant findings and we cannot simply draw any conclusion on either additive or subtractive Chinese-English bilingualism. It would be necessary to find common factors for each population and investigate metalinguistic awareness within the interested population.

In response to the second problem that metalinguistic awareness depends on the specific measurement and the language being tested, this meta-analysis found from aggregated data that

Chinese word awareness, English onset-rime awareness, and English phonological awareness

can be easily transferred across the two languages, while others cannot. Such results cannot be blindly interpreted without considering the quality of the included studies, particularly the measurement. As introduced in literature review, three categories of constructs fall under the broad umbrella of metalinguistic awareness. They are word awareness, syntactic awareness, and phonological awareness. However, as shown in the descriptive result, 34 studies used phonological awareness tasks, 15 studies used word awareness tasks, and 0 studies used comparable syntactic awareness tasks for both language groups. As one of the crucial domains in metalinguistic awareness and a predictor of ―native-likeness‖ in sentence production, syntactic awareness should have received equal attention from researchers. Another methodological flaw that can be easily identified is that some tasks in Chinese language are direct translation from the

English standardized test version and the adapted instruments were rarely validated before data was collected. The direct translation method brings major methodological flaws in terms of how the construct of metalinguistic awareness is measured in both languages. The use of flawed instruments renders the tasks in two languages incomparable and fails to measure the culturally and linguistically loaded characteristics of the construct of metalinguistic awareness when comparing metalinguistic awareness in young children (Gonzalez, 2002). Therefore, there is a great need for the change of methodological paradigms for the study of bilingualism and biliteracy processes.

The claim that bilingual advantage disappears when children get mature was not supported by the aggregated data, which found that age was not a predictor of metalinguistic performance. Instead, the analyses suggested that children‘s metalinguistic awareness may depend more on cognitive and language development. Children become more and more metalinguistic when they catch up in aspects such as concept of print, concept of word, and

grammaticality, which is usually the result of more explicit reading instruction. Also, children can become more metalinguistic in one domain than another. This is due to the structure of the language children learn to read and write. Their metalinguistic skill becomes more advanced when the language has a more elaborate structure in that domain, or when the writing system more clearly represents the domain of awareness. Usually, semilingualism or cognitive retardation occurs before children fully develop cognitive skills in their first language and their first language is not valued in either school or home. Therefore, it is advisable that children receive early instructions in metalinguistic awareness. Pre- and in-service teachers should receive training on explicit techniques for teaching metalinguistic awareness.

In regard to the fourth problem that it is easier for children in Mainland China and

Taiwan to transfer their phonological awareness than Hong Kong children, the integrated results of this meta-analysis are consistent with it. It confirms that EFL language setting is a significant predictor of better phonological awareness. One possible interpretation is that explicit instruction of phonetic system and phonological awareness in both languages is more important and can bring more benefits to students than simply placing them in an immersion bilingual program, which is the general practice in ESL countries.

6.2.Discussion of Meta-Analytic Structural Equation Modeling

The meta-analytic structural equation modeling (MASEM) pooled correlation matrices from twenty seven studies (N = 2,687) and fit part of the Bilingual Metalinguistic Awareness

Model (BMAM). Similar to the results from meta-analysis, MASEM also revealed the heterogeneity between studies. Because of huge heterogeneity in prior research, twenty seven studies were divided to subgroups based on children‘s age, first language (L1), and language settings to make them more homogeneous. Specifically, two age groups are preschoolers

(children age range from 4 to 6) and elementary schoolers (children age range from 7 to 12).

Two first language (L1) groups are Mandarin as L1 and Cantonese as L1. Since only one study recruited participants whose first language is English, English as L1 was not included as a subgroup in the comparison. Two language settings are ESL setting and EFL setting.

Heterogeneity was detected in the two age group clusters, in the two L1 clusters, and in the two language setting clusters. The proposed BMAM does not fit the data in any of the clusters.

However, these results should be interpreted with caution due to the significant heterogeneity found in the fixed-effects model. The analysis of random-effects model proved huge between- study heterogeneity. The heterogeneity can be explained by both between study differences and within study differences. The between study differences are manifested by the differences in children‘s ages, first languages (either Mandarin or Cantonese), language settings, schooling experience, cognitive development, and language proficiency. Study design differences, such as different controlling for age and language groups, brought in more complexity in the analysis.

For example, some studies controlled age differences by fitting correlation matrices within different age groups. Other studies, however, pooled all age groups, even monolingual and bilingual groups together, in correlation analysis. It is suggested that future studies improve research designs by better controlling for moderating variables.

The CFA analysis in Stage II of random-effect model indicated the good fit of the measurement part of the BMAM model to data. Such results indicate that both Chinese metalinguistic awareness and English metalinguistic awareness can be well measured by word awareness and phonological awareness. However, as none of the studies employed syntactic awareness tasks in their measurement of metalinguistic awareness, syntactic awareness, a crucial component of children‘s metalinguistic understanding of sentence structure and grammar, could

not be fitted in the model. Thus, we cannot blindly use only word awareness tasks and phonological awareness tasks in this model to evaluate children‘s metalinguistic performance in research or in practice. Future researchers should focus on designing quality instruments to evaluate syntactic awareness in both languages to better capture bilingual children‘s development in this domain. Despite the significance of the measurement model, it should be viewed with caution due to the significant error terms across all measurement tasks. This might be due to the heterogeneous types of tasks and the poor quality of some instruments. Therefore, policy makers, teachers, and researchers should put more efforts on design of comparable instruments in both languages to better gauge children‘s development of metalinguistic awareness.

Fitting the structural model to the data revealed that the higher-order factors, including

English metalinguistic awareness and cognition, Chinese metalinguistic awareness and cognition, and Chinese metalinguistic awareness and English metalinguistic awareness, are found to be highly correlated. This aligns with the results of meta-analysis that metalinguistic awareness can be transferred across English and Chinese. And children with more L1 metalinguistic knowledge are usually more metalinguistic aware in their L2. Besides, Children who are more cognitive developed tend to more metalinguistic aware. Specifically, children who have higher intelligence, better memory, good visual skills, and even math skills tend to perform better in metalinguistic tasks. Part of the reason is that with good cognitive skills, i.e. analysis of representational structures and control for selective attention, children can easily transfer the metalinguistic knowledge learned in one language to the other and facilitates the language learning process (Bialystok, 1991). However, language proficiency in English and Chinese are not good indicators of children‘s metalinguistic development. It might be due to the instructional

methods teachers employ in English and Chinese language schools. As discussed in literature review sections, most bilingual program take an immersion method and do not teach metalinguistic knowledge explicitly and help children with their understanding of linguistic similarities and differences in Chinese and English. Since very few researches had detailed descriptions of instructional techniques of language teachers or focused on the influence of instructional methods on development of metalinguistic awareness, we cannot make a definite conclusion on this assumption. Therefore, more research is needed to examine the influence of instructional methods on children‘s development of metalinguistic awareness. More importantly, school policy makers and in-service teachers should keep in mind of the importance of explicit instruction of metalinguistic knowledge and revise their pedagogical strategies.

Despite shedding light on the problems in existing research, this dissertation study provides more suggestions for future research. First, since the samples are drawn from different populations, future researchers should provide detailed descriptions of population and sample characteristics, making it possible to aggregate studies for each population. Second, more replications of studies are needed in the same population in order to achieve more reliable and precise estimation. Third, the instrument employed should be validated before data collection.

Adaptive test development should be used when creating new instruments or translating instruments into other language versions. It is also important for future studies to include tests on syntactic awareness in order to get a holistic picture on the construct of metalinguistic awareness.

Fourth, prior research exclusively focused on whether being Chinese-English bilingual is ―good or bad‖. The benefits of Chinese-English bilingualism cannot be evaluated solely on psycholinguistic measures. There are a lot more practical benefits that we cannot ignore. Thus, the focus in future research should shift from ―good or bad‖ to ―how to better‖. For instance, it

would be interesting to compare the effects of different instructional method of metalinguistic awareness.

7. CONCLUSION

By integrating the results from 49 studies for meta-analysis and 27 correlation matrices for meta-analytic structural equation modeling, this dissertation research found no statistical differences between Chinese or English monolingual children and Chinese-English bilingual children in their metalinguistic awareness. The study also found the good fit of the measurement part of the BMAM model for Chinese-English bilingual children. However, insignificant correlations between two latent variables: Chinese and English language proficiency and other three latent variables, including cognition, and Chinese and English metalinguistic awareness proved the inappropriateness of the structural part of the BMAM model.

In spite of this finding, it cannot be simply concluded that Chinese-English bilingual children have equal performance in metalinguistic tasks as their Chinese or English monolingual peers or the BMAM model is invalid, because the heterogeneity test found that the samples are drawn from different populations. Therefore, it is very important that future researchers include detailed descriptions of participants‘ characteristics so that other researchers can make meaningful interpretations of the results.

This dissertation study also revealed the poor quality of the instruments used in previous studies and the lack of clear delineation of the domains of the construct of metalinguistic awareness. Particularly, syntactic awareness should be given more attention in future research, and instruments should be validated before use. This study serves as a summary and evaluation of previous studies. The most important reflection is on the focus of research. In the past, additive or subtractive bilingualism received major attention. In the time when being bilingual is more common than being monolingual, this study calls for more research on how to help

Chinese-English bilingual children succeed in the two languages.

Metalinguistic awareness is an acquired knowledge of language structure and function.

Once developed, children are able to reflect on their use of language and consciously manipulate the language structure to best serve their communicative purposes. Educational policy makers, school teachers, and parents are people who can influence this learning process. Thus, attitudinal, instructional, and assessments suggestions are provided so that policy makers, teachers, and parents can intervene and accelerate the development of Chinese-English bilingual children‘s metalinguistic awareness.

First, educators and parents should be aware of the cognitive advantages and linguistic and cultural benefits that bilingualism bring, and embrace bilingualism when they make educational policies, develop lesson plans, and design home literacy activities. Second, metalinguistic knowledge training and second/foreign language training should be incorporated into current pre-service teacher training programs. Alternatively, in- service teachers can hold workshops to share teaching strategies of metalinguistic awareness and the latest research report.

Also, teachers can impart metalinguistic knowledge and teaching tips to parents through workshops or parent-teacher conference. It is suggested that word awareness are taught to children as young as 1 year old. Phonological awareness is usually taught when children are 4 to

8. And syntactic awareness requires more executive control skills and is expected to be fully developed as late as 15 years old. Third, both formative and summative assessment should be employed to measure and facilitate children‘s acquisition of metalinguistic skills. Teachers and parents can gather instant and periodic feedback to guide improvements in teaching content and strategies.

8. LIMITATIONS

The current research sought to examine the effects of Chinese-English bilingualism on children‘s metalinguistic awareness and to identify the moderating variables associated with the construct. It also aims to test the fit of the proposed BMAM model in order to understand the underlying relationship between various domains of metalinguistic awareness and moderating variables. The findings of this study need to be interpreted in light of limitations. One weakness is related to the coders and coding protocol. Since this is an independent dissertation study, it did not include more coders with exceptional substantive and theoretical knowledge of metalinguistic awareness in Chinese-English bilingual children. Since intra- and inter-rater reliability is critical to the quality of the research synthesis and meta-analytic structural equation modeling, it would be more reliable to have multiple coders for each study and to have each coder code an individual study twice.

Another weakness is the lack of adjustment for inter-study variability. It would be more valid to invite experts weight each study quality and redistribute adjusted weight to the study so that studies of good quality are given more weight towards the overall effect size. Lastly, due to the lack of measures of certain variables, i.e. instructional methods, syntactic awareness, the part of the proposed BMAM was unable to be tested. It would be interesting to conduct empirical research in the next stage in order to fit the full BMAM model and to investigate Chinese-

English bilingual children‘s metalinguistic awareness in a more holistic manner.

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APPENDIX

Appendix A. Coding Sheet

Study Characteristics Case ID Funding (No)0 (Yes) 1 Publication (No)0 (Yes) 1 Experimental (No)0 (Yes) 1

Participant Characteristics age (in years) first language (mandarin) 1 ( cantonese) 2 (english) 3

Social Influence (higher better) SES 3 2 1 Parent/Peer Influence 3 2 1 Home Literacy 3 2 1 setting (EFL) 0 (ESL) 1

Schooling Influence (measure format, density, and formal teaching of WA, SA, PA) Chinese 3 2 1 English 3 2 1

Language Proficiency Chinese n M SD English n M SD

Cognitive Influence Intelligence n M SD Memory n M SD

Outcome Measures Word Awareness (WA) n M SD 1. word segmentation n M SD 2. meaning and refence n M SD 3. Symbol substitution n M SD 4. nonphysical nature n M SD

Syntactic Awareness (SA) 1. grammaticality judgment n M SD 2. grammaticality error correction n M SD 73

3. grammaticality error correction and justification n M SD 4. sentence ambuigity n M SD

Phonological Awareness (PA) 1. syllable awareness n M SD 2. onset-rime awareness n M SD 3. phonemic awareness n M SD 4. tone awareness n M SD

Correlation Matrices All correlation estimate between variables