Melissa Keh

What Can They Tell Us About the Influence of FirstLanguage Reading Experiences on Second-Language Reading?

MELISSA KEH

When I was working as a high school English as a Second Language (ESL) teacher, I often asked my students to read text aloud. I became curious when I noticed that some of my students did not seem to sound out words that they were unfamiliar with as frequently as other students. It was this observation that prompted me to analyze my students’ oral reading errors, sometimes called miscues, to learn about whether their prior experiences reading and learning to read may have been associated with the way they approached reading in the English writing system.

Most models of reading development suggest that a) word reading is a function of interaction between three main components: phonology, orthography, and meaning (Coltheart et al., 2001; Seidenberg & McClelland, 1989); and b) that readers develop metalinguistic skills, such as awareness of phonemes and morphemes, as they learn to read. Cross-linguistic studies of reading suggest that metalinguistic skills are shaped by the orthography in which one learned to read and vary across languages (Holm & Dodd, 1996; Koda & Zehler, 2008). Koda’s (2008) Transfer Facilitation Model maintains that there are regularities in spoken language that writing systems capture, and children develop sensitivity to these regularities as they develop oral language. As we learn to read, we learn to map our spoken language onto graphic symbols, and our metalinguistic awareness aids us because we use it to recognize the smaller linguistic units (such as phonemes, syllables, and morphemes) in spoken words. With experience reading, our metalinguistic awareness increases, and it reflects the specific ways that our language is encoded in our writing system. In other words, there is some variation in the use of metalinguistic skills among readers of different languages because writing systems differ in how they encode language.

Some evidence that reading differs across languages is found in cross-linguistic research on reading. For example, readers of shallow orthographies, like Cyrillic, may approach letter strings as decodable and make more nonword errors than readers of deep orthographies, like English, who, by comparison, make more real word errors (Perfetti & Dunlap, 2008). English readers appear to rely more on phonological information than Chinese readers do (Li & Koda, 2022). And Chinese readers have been shown to make more semantic substitution errors than English readers, while English readers make more phonological errors than Chinese readers (Cheng & Caldwell-Harris, 2011). For bilinguals, reading subskills may play greater or lesser

roles in word reading comprehension in each of their languages (Li & Koda, 2022).

The high school students in my classroom had experience reading Cyrillic and Chinese and were in the process of acquiring English as an additional language in school. To learn more about their reading in English, I read about their first language writing systems and examined the oral reading errors they made when reading connected text in English. The analysis focused on patterns of real and nonword errors according to the readers’ first writing system background.

Background on English, Cyrillic, and Chinese Writing Systems As we learn to read, we learn to map our spoken language onto graphic symbols, and our metalinguistic awareness aids us because we use it to recognize the smaller linguistic units (such as phonemes, syllables, and morphemes) in spoken words. With experience reading, our metalinguistic awareness increases, and it reflects the specific ways that our language is encoded in our writing system.

Looking first at the participants’ first language writing systems will help illustrate what metalinguistic and reading skills readers of those writing systems may rely on. All writing systems represent the phonological qualities of words in written symbols (Holm & Dodd, 1996), and reading in any language activates phonology (Perfetti et al., 1992); but the way that writing systems encode language differs.

Cyrillic and English are both alphabets. Yet, while grapheme-phoneme correspondence is the basis for all alphabetic writing systems, alphabetic orthographies vary in the extent to which sounds and letters have one-to-one mappings. The English writing system is orthographically deep, in some cases, because it preserves and represents morphemes at the expense of consistent grapheme-to-phoneme correspondence (Chomsky & Halle, 1968; Mahony et al., 2000; Templeton & Scarborough-Franks, 1985). In English, although words like cat,dog, and ant can be easily “sounded out” if the reader knows the sound each letter makes, other words like enough, physique, or circus have spellings less transparently linked to pronunciation. English-speaking children are sometimes taught to read with phonics lessons and decodable texts that have regular, predictable grapheme-to-phoneme mappings (Messmer, 2005). This instructional method develops their use of the letter-sound decoding strategy (Juel & Roper-Schneider, 1985). But Mora (2001) estimates that only 75% of written words in English can be decoded with phonics generalizations. Instruction to develop other metalinguistic skills, such as morphological awareness, also appears to support word reading and spelling skill development in English (Carlisle, 2010; Nunes et al., 2003). As English readers become more proficient, they use more than sound-symbol correspondence to decode, attending to larger phonological units, morphemes, and/or whole words (Treiman, et al., 1995),

and compared to readers of shallow orthographies, English readers may make more real word errors, an indication that English readers are less likely than readers of shallow orthographies to rely on letter-sound correspondences.

Cyrillic is an alphabetic writing system that is the official alphabet for a number of languages, including Bulgarian, Mongolian, and Russian. Each of these Cyrillic orthographies has some irregularities in grapheme-phoneme correspondence, but they are all shallower than English. Shallow (or transparent) orthographies have more regular letter-sound correspondences than opaque (or deep) orthographies such as English and lend themselves to a letter-by-letter decoding approach because of that more regular grapheme-phoneme correspondence. As a result, readers from shallow orthographies are more likely to sound out words that they don’t know letter-by-letter when compared to readers of deep orthographies, and readers of deep orthographies are more likely than readers of shallow orthographies to use some of the orthographic information to arrive at a real word (if not the printed one) (Perfetti & Dunlap, 2008). As noted above, this sublexical, sound-out approach may be evident in the share of non-word errors readers of shallow orthographies make in oral reading, compared to readers of deep orthographies (Frith et al., 1998; Landerl & Wimmer, 2000; Wimmer & Goswami, 1994).

Chinese is a logographic (or morpho-syllabic) writing system. A logographic writing system has characters rather than letters; the characters represent syllables, and they also carry semantic meaning. Each Chinese character is pronounced in Mandarin Chinese with a single syllable. Unlike an alphabet, which maps symbol to phoneme (e.g., the letter “b” maps to the sound /b/) and forms a word by combining a string of phonemes, Chinese maps symbol to syllable and word or morpheme (e.g., pronounced ma/3, means horse) (Perfetti & Dunlap, 2008). In an alphabet, an individual symbol, a letter such as “b” above, carries phonological information but no meaning by itself; letters of an alphabet map only to phonemes and must be combined into morphemic chunks to have meaning. On the other hand, Chinese characters map both to meaning and sound; a Chinese character does “not allow phoneme-level mappings to function in either learning to read or in skilled reading. Instead, “[it] allow[s] reading to proceed from graphic form to meaning and from graphic form to syllable” (Perfetti & Dunlap, 2008, p. 19). “[A]pproximately 89% of Chinese characters represent unique morphemes, [so] characters usually provide the reader with visually distinct and reliable cues for decomposing polymorphemic words (Ku & Anderson, 2003, p. 406). In Mainland China, children learn to read Chinese characters with the assistance of Pinyin, “a set of symbols used to transliterate Chinese characters and combine speech sounds of the common speech into syllables” (Beijing Languages Institute, 1989, p. 37), and a similar system, Zhu-Yin-Fu-Hao, is used in Taiwan. In Hong Kong, characters have historically been learned through copying and memorization, without the accompaniment of Pinyin or Zhu-Yin-Fu-Hau (Huang & Hanley, 1995).

Cross-Linguistic Influences in Second-Language Reading

When it comes to reading in a second language, research suggests that metalinguistic skills developed in a first language transfer to reading in a second language. In a Connectionist framework “transfer can be defined as an automatic activation of well-established firstlanguage competencies, triggered by second-language input” (Koda, p. 78). Studies of transfer have suggested that Chinese readers transfer skills from their first language to reading in English. Compared to alphabet readers, they tend to rely more on orthographic knowledge and visual processing and less on phonological sensitivity to identify English words. Holm and Dodd (1996) found differences in phonological awareness between adult Chinese readers from Hong Kong (who had non-alphabetic first-language literacy experiences) and readers from Mainland China (where Pin-yin is used), Vietnam, and Australia. The Hong Kong Chinese participants in the study exhibited more difficulty in reading and spelling nonwords, and their errors were often tied to orthographic strategies; however, like all of the other participants in the study, they were highly literate and scored within 2% of each other on a real-word reading task. The observed differences between the group from Mainland China and the group from Hong Kong provide evidence of first-language reading skill transfer. The researchers conclude that “the development of phonemic awareness seems to be dependent upon alphabetic acquisition, or another form of explicit phonemic instruction” (Holm & Dodd, p. 139).

Koda (1998), on the other hand, found that adult Korean (alphabet readers) and Chinese students’ performance on phonemic awareness and decoding tasks were not significantly different; however, the two groups applied different strategies. Thirty percent of the Chinese subjects said they used visual strategies to picture the words, but only one Korean subject reported doing this. On the other hand, 12 Koreans reported use of phonological strategies to “sound out” the word, and only 3 Chinese subjects reported use of this strategy. Furthermore, although phonemic awareness and decoding correlated strongly with reading comprehension for Korean subjects, there was no clear connection between these variables and reading comprehension for the Chinese subjects.

Wang et al. (2003) found processing differences in intermediate and advanced Korean and Chinese adult ESL learners’ reading in English. Korean subjects erred more on homophone foils than spelling controls, but Chinese subjects were not significantly affected by homophone interference; rather, words spelled very similarly to the target category member resulted in more incorrect judgments. Because there was evidence of more interference from similarly spelled than less similarly spelled homophones in the Chinese participants’ reading of English, the researchers concluded that both transfer from the first language and the nature of the second language contribute to second-language reading and suggest that with time, phonology may have an increasing effect for the Chinese readers of English. Although these studies focused on adults, there is also evidence of first language transfer in young children.

Wang and Geva (2003) compared the spelling performance of second-grade Chinesespeaking ESL and native English-speaking students to investigate whether transfer of firstlanguage literacy skills to second-language literacy was evident early on. The Chinese-speaking children performed better than their English-speaking peers in remembering and spelling visually presented words, the same at spelling real words, and worse on spelling dictated pseudowords. The English-speaking children seemed most disadvantaged by tasks that made phonological recoding difficult (recalling illegitimate letter strings). The Chinese-speaking children did worse than English-speaking children on spelling dictated words that did not have meaning (the dictated pseudoword task). These results suggest that the Chinese-speaking children may have transferred visual skills and a whole-word strategy from their first-language literacy experience to learning the spellings of words in English. Leong, et al. (2005) found that older Chinese children also relied on orthographic knowledge more than phonological sensitivity to identify English words.

Taken together, these studies indicate that cross-linguistic transfer is evident in children as well as adults and occurs across languages in reading, even when the writing systems are different. Chinese readers may employ whole-word reading and visual processing skills more often than alphabet readers. Differences in the skills that second-language readers use in reading in their second language are not necessarily associated with differences in reading comprehension. And finally, the second-language writing system and exposure to that system needs to be considered in understanding second-language reading, as the second-language orthography may also influence the reader’s use of reading skills.

The Present Study

This analysis examines data from the errors multilingual students made during authentic oral reading of connected text. The specific research question was:

Do experienced Chinese (simplified) and Cyrillic readers demonstrate different error patterns from each other when reading connected, authentic text in English (a language they are acquiring)?

As Ellis and Hooper (2001) note, a lexical (or whole-word) reading strategy should result in more real word errors; whereas, a sublexical (or “sounding out” strategy) should result in more nonword errors. Compared to each other, I would expect that if first-language reading skills transfer to reading in English, Chinese readers would make more real-word errors, and Cyrillic readers would make more nonword errors because a “sounding out” strategy has been found to be more frequently used by readers of shallow orthographies than deep orthographies.

Methods

This study is a quantitative secondary analysis of oral reading data collected during a previous study that examined the outcomes of Retrospective Miscue Analysis (Goodman et al., 2014; Goodman & Marek, 1996) with adolescent, multilingual students, who were in the process of acquiring English in a U.S. public school setting. The data for the current analysis originate from a database of oral reading errors made by eight participants, four Cyrillic readers and four Chinese readers. I provide qualitative data primarily for illustration purposes.

Participants

The participants were multilinguals attending a suburban high school on the east coast of the United States. Their oral English language proficiency ranged from level 2 to level 4, as measured by the Massachusetts English Language Assessment – Oral (Massachusetts Department of Elementary and Secondary, 2010), which described1 five levels of English proficiency. All participants had arrived in the U.S. after age 10, and most had been in the U.S. for one year or less. None of the participants had experienced gaps in formal education, and all were literate in their native languages. None of the participants were known to have any exceptionalities. Four of the participants spoke Mandarin as a first language and were experienced Chinese (simplified) readers, and four spoke Mongolian, Russian or Bulgarian as a first language and were experienced readers of Mongolian, Russian or Bulgarian orthographies, which use the Cyrillic alphabet (see Table 1).

TABLE 1

Participants | Participants’ Demographic Information (N=8)

Cyrillic (N=4) Age Sex Years in U.S. Oral English proficiency Chinese (N=4) Age Sex Years in U.S. Oral English proficiency

16.25 3 M, 1 F 1 3

15 1 M, 3 F 1.38 3.25 (1.26)

(.41) (1.51)

(1.41)

(1.18) (.5)

MEAN (SD)

1This assessment is no longer in use.

Data Sources

The oral reading error data was gathered while students were reading passages from the QualitativeReadingInventory-5(QRI-5) (Leslie & Caldwell, 2011), and when they were reading passages from instructional-level texts they had selected for Retrospective Miscue Analysis (Goodman et al., 2014; Goodman & Marek, 1996). The QRI-5 is a commercial, informal assessment instrument used to determine a student’s instructional reading level. It includes narrative and expository texts from the preprimer through high school level. The QRI-5 passages participants read ranged in length from 221 words to 707 words. The reading passages students read for Retrospective Miscue Analysis were from original or adapted versions of literature that matched students’ instructional reading levels. Since the participants were in the process of acquiring English, most read third- to sixth-grade texts in English at the instructional level. I felt the content of adapted classics would be both age-appropriate and reading-level appropriate and would allow participants to choose from a selection of texts so that they would feel invested. I provided a new section or chapter from the same text each week, so text selections remained similar but new. The participants were not reading these texts for any academic course at the time of the study. The passages ranged in length from 449 words to 2,359 words. I met with the participants individually in a classroom during or after the school day on a weekly basis for reading. I concurrently wrote students’ oral reading errors on a separate transcript as they read. In most cases, I audio-recorded sessions and played the recording back before the next session to check my written record.

Prior to data collection, the study was reviewed and approved by the Institutional Review Board at my university at the time of the study and by the school district where the research was conducted. Assent and informed consent forms were collected from all participants and their parents/guardians.

Data Analysis

Following data collection for the original study, all oral reading errors (N=3,562) were entered into an Excel file. I coded each oral reading error as a real word, a nonword, or an ambiguous error. For example, if a participant read /gɪnt/ for the printed word “giant,” this was coded as a nonword error, and if a participant read “of” for the printed word “for” or “all” for the printed word “right,” these were coded as a real-word errors. Ambiguous errors sounded like real words, but I was not confident that they were not the result of the student’s pronunciation in English or a decoding error. In most cases, words I coded as ambiguous were less frequently occurring than the target word (e.g., “heeded” for “headed,” “filing” for “filling”). I coded these as ambiguous because it was less likely that the student knew the less frequent word and substituted it for the more frequent one. I also took into account foreign accent. For example, one student often read “cod” for the word “could,” but her pronunciation of the vowel in “could” was influenced by foreign accent in spoken English. Furthermore, “cod” was a lower-frequency

word than “could,” and it did not seem likely that it would be in her vocabulary, in part because it was a poor substitute in the context, given that it was the wrong part of speech for the sentence she was reading aloud.

To determine whether error patterns were significantly different by writing system background (e.g., Chinese or Cyrillic), I conducted a chi-square test of independence in SPSS. Because the majority of oral reading errors were collected when the participants were reading different texts from each other, I also examined one text that both a Cyrillic and a Chinese reader had read, to see if the difference in error patterns was observable qualitatively. This also serves as an illustration of how I coded oral reading errors.

Results

Figure 1 shows oral reading error type totals by language. The bar graph shows that a similar number of real word and nonword errors were made by Cyrillic readers, and that roughly twice as many real word errors as nonword errors were made by Chinese readers. To better understand whether this difference was statistically significant, a chi-square test of independence was conducted.

FIGURE 1

Oral Reading Error Types by First Language Writing System Background

Data screening indicated that the oral reading error data met the assumptions for a chi-square test of independence. Both variables (language group and error type) are categorical. Oral reading errors received only one error type code, and each cell had more than five observations (see Table 2). It is also assumed that the observations are independent.

The chi-square value of 85.06 is significant (p < .001), which suggests that there is an association between language and error type that is not likely due to chance. The standardized residuals for ambiguous errors were less than ± 1, so ambiguous errors were not a major contributor to the significant chi-square value. On the other hand, the standardized residuals for real word and nonword errors were all greater than ± 3. This indicates that the number of real and nonword errors made by Cyrillic and Chinese readers contributed to the significant chi-square value. The phi-coefficient was .16, indicating a small effect size (Cohen, 1988).

Figure 2 and Figure 3 show the oral reading errors made by a Cyrillic reader and a Chinese reader while reading the passage “Cats: Lions and Tigers in Your Home” from the QualitativeReadingInventory-5 (Leslie & Caldwall, 2011). Oral reading errors that were coded as real words are in blue, nonword errors are in red, and ambiguous errors are in green.

TABLE 2

Oral Reading Error Type by Language

Cyrillic

Chinese Error Type

GROUP REAL WORD NONWORD AMBIGUOUS

515 532 127

1,426 732 230

χ2 (2) = 85.06, p <.001

FIGURE 3

Chinese Reader

Discussion

The results suggest that there were different patterns in oral reading errors in the data set according to language type. Specifically, the participants in the study who had experience reading languages that use the shallow Cyrillic alphabet made more nonword errors and fewer real word errors compared to the participants in the study who had experience reading Chinese. The data analyzed stem from students’ oral reading of school texts, which also highlights the fact that the differences noted here are observable in classroom contexts as part of routine classroom activities.

Previous studies suggest that readers of shallow orthographies make more nonword errors compared to readers of deep orthographies, who make more real word errors when reading in their first language (Frith et al., 1998; Landerl & Wimmer, 2000; Wimmer & Goswami, 1994). In this case, this pattern was observed in the secondlanguage writing system (English). This is interesting because English was an orthography that first- language readers were more likely to make real-word errors, according to the previous research. Yet here, we can see a difference according to first-language reading experience that results in varying amounts of real and nonword errors. The findings of this study seem to align with Li’s and Koda’s (2022) conclusion that “[t]he features of the [first language] writing system influence the formation of [second language] word formation analysis skills….[P]rior experience with a particular writing system has lasting impacts on the development of linguistic cognition” (p. 1418).

The pattern observed in these data may indicate that the readers transferred reading skills, which they had developed and relied on differently in their first languages, to reading in English. Although transfer cannot be determined empirically without measuring participants’ first language metalinguistic and reading skills, the different oral reading patterns seen here could be an indication that the participant readers’ reliance on such skills differed. Use of a sound-out strategy by Cyrillic readers is consistent with previous research findings that indicate that a sublexical approach is more common in readers of a shallow orthography (Perfetti & Dunlap, 2008). Likewise, previous research has shown that Chinese readers of English tend to rely more on orthographic information than phonological information when reading English and may use a visual whole-word strategy (Wang & Geva, 2003)

Although there is a large body of research that suggests differences in metalinguistic and reading skills across orthographies as well as transfer of first language reading skills to second language reading, it is possible that instruction and classroom experiences played a role as well.

Although there is a large body of research that suggests differences in metalinguistic and reading skills across orthographies as well as transfer of first-language reading skills to second language reading, it is possible that instruction and classroom experiences played a role as well. Instructional contexts for languages that have alphabetic writing systems may be more likely to include activities and games that build awareness of sub-syllabic units (Holm & Dodd, 1996), and phonics instruction tends to be used for shallow orthographies (Pefetti & Dunlap, 2008). Reading is not universally taught in the same way, even in the same language.

Conclusions

It is important to acknowledge that although my initial analysis suggested that Retrospective Miscue Analysis had little to no influence on the nature or number of the participants’ oral reading errors, the protocol and/or the administration procedures of the QRI5 could have influenced participants’ error patterns. If this was the case, the influence should not have been different for Chinese and Cyrillic readers, since all participants experienced similar procedures. As noted above, I also did not measure first-language reading so there are limits as to which conclusions can be drawn about the source of the oral reading differences in the data. Furthermore, the sample of oral reading errors was large, but only eight participants were included in the study. Future research could investigate whether this pattern is evident in a larger group of participants.

Although the theories about the sources of observed differences are complex, the implications are important for all teachers. This inquiry started in my classroom when I sensed that something was different about the ways my students were reading. I wanted to better understand whether that difference was quantifiable, and if it was important for my teaching and my students’ learning. I realized in conducting this research that my students brought different linguistic funds of knowledge (Moll et al., 1992) to the task of reading in English, and that using sounding-out strategies was not as universal as I had thought. This information helped me to implement teaching that bridged the orthographic differences between the writing systems they knew and English. For example, I taught Chinese students how to break polysyllabic words into syllables and use what they knew about letter sounds to pronounce the words. I also implemented word study with all students to increase their awareness of the small units of meaning found in the roots and affixes of words.

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ABOUT THE AUTHOR

Melissa Latham Keh, Ed.D., is an associate professor at Bridgewater State University, where she teaches courses on literacy development in multilingual contexts and assessment of multilingual learners. Prior to Bridgewater State University, she taught high school English Language Arts and English as a Second Language.