While experiential factors in L1 perception have been well studied, very little is known about the consequences of L2 experience for neural representations of L2 phonemes. Does experience with typical pronunciations of L2 speech sounds lead to cross-linguistically distinct memory traces for non-native phonemes? The goal of the present study is thus to investigate the effects of long-term L2 experience on the nature of phoneme categories of a second language. To this end, we measured auditory brain responses by using the Mismatch Negativity (MMN). Specifically, does language-specific experience, due to the frequency of pronunciation variants of the English voiceless interdental fricative /θ/, result in distinct MMN responses to /θ/ substitutions as a function of specific differences between Dutch and German accented speech?

### Production and Perception of English Interdental Fricatives

The English fricative /θ/ presents great difficulties in production for many learners of English, and even highly proficient L2 learners regularly substitute English /θ/ with other sounds, most often /s/, /t/, and /f/ (for an overview, see Brannen, 2002). The preferences for substitutes depend on the L1 background of L2 speakers (e.g., Brannen, 2002; Hanulíková and Weber, 2010). Hanulíková and Weber (2010) have shown that German learners of English commonly substitute /θ/ with /s/ (29%) and to a much lesser extent with /t/ (7%) or /f/ (5%), while Dutch learners prefer to use /t/ (23%) and to a much lesser extent /s/ (5%) or /f/ (3%); (Note that all three substitutes are phonemes of both Dutch and German). As a consequence, it is reasonable to assume that German learners experience /s/-substitutes (as in /sεft/ for *theft*) the most, while Dutch speakers are most often presented with /t/-substitutes (as in /tεft/ for *theft*). In the present study, we therefore focus on the perception of these two most frequent substitutes.

/θ/ and /s/ are acoustically slightly more similar than /θ/ and /t/. From an articulatory viewpoint, /θ/ and /s/ are fricatives, realized with a constriction in the oral tract that causes turbulent airflow. /t/ on the other hand is an oral stop consonant, for which the vocal tract is first blocked, stopping all airflow, before it is released with a burst. /θ/ is characterized by a relatively flat spectrum with no clearly dominating peaks, while alveolar /s/ displays an intense primary spectral peak at higher frequencies (e.g., Jongman et al., 2000). The spectrum of /t/ has a diffuse spread of energy, with peak amplitudes being larger in the high frequencies (e.g., Stevens and Blumstein, 1978). The two groups of Dutch and German L2 learners of English are particularly interesting, because they not only differ in their predominant [θ] substitutions, but also in the acoustic properties of both /s/ and /t/ in their respective L1 and from their L2 English. Dutch /s/ is less articulatorily tense and has graver friction than German or English (Mees and Collins, 1982; Rietveld and van Heuven, 2001; Hanulíková and Weber, 2010), and /t/ in initial position is aspirated in German (and in English) but unaspirated in Dutch (Lisker and Abramson, 1964; Keating, 1984).

These acoustic similarities and differences between /θ/-/s/ and /θ/-/t/ do not necessarily affect the ability to perceptually discriminate these pairs. Offline discrimination and identification tasks show that non-native listeners can distinguish between /θ/

and /s/ and /θ/ and /t/ quite well (e.g., Hancin-Bhatt, 1994; Cutler et al., 2004; Hanulíková and Weber, 2012). For example, Cutler et al. (2004) have found that Dutch L2 listeners confuse English /θ/ (in 0-db SNR) with /t/ 6.3% and with /s/ 0.4%. Hancin-Bhatt (1994) showed that German listeners in good listening conditions misidentify /θ/ as /t/ 0% and as /s/ 5%. In line with this pattern, Hanulíková and Weber (2012) showed in an AXB task that performance for both /θ/-/s/ and /θ/-/t/ contrasts was high and comparable across Dutch and German listeners (on average 89% correct for the /θ/-/s/ contrast and 90% correct for the /θ/-/t/ contrast). Although Dutch and German listeners can perceptually distinguish between /θ/-/s/ and /θ/- /t/ quite well, their productions show clear preferences toward one of the variants. While these production preferences affect lexical processing, it is less clear whether non-native phoneme perception is affected as well. This raises the question of the level at which such experiential effects arise during processing. Does the frequency of production variants in L2 speech already affect pre-attentive processing of speech sounds at a pre-lexical level? In other words, is the memory representation of /θ/ closer to /s/ for German listeners, and to /t/ for Dutch listeners?

### MMN Studies on Effects of Experience in Speech Perception

An excellent tool to investigate experience-based auditory memory traces is Mismatch Negativity, an early event-related brain potential (ERP) generated in the auditory cortex. It is a negative ERP component that occurs between 150 and 350 ms after the detection of a deviant feature in the stimulus. In a typical MMN design, the so-called standard stimulus (sound, syllable, or word) is presented 80–90% of the time while the socalled deviant stimulus (sound, syllable, or word) is presented 10–20% of the time. It is assumed that the MMN is evoked through a mismatch of the properties of a deviant stimulus and the neural traces in sensory memory consigned by the repeated presentation of a standard stimulus, irrespective of the direction of the subject's attention or task. As such, an MMN design allows the examination of amplitude differences upon the detection of a change between standard and deviant pronunciations.

Since its discovery in the 1970s (Näätänen et al., 1978), MMN has been linked to various aspects of deviant acoustic properties (for an overview, see Shtyrov and Pulvermüller, 2007) such as pitch (e.g., Näätänen and Gaillard, 1983; Jacobsen et al., 2003), stimulus duration (Paavilainen et al., 1991), and loudness (e.g., Keidel and Spreng, 1965). It has been shown that better discrimination of a native or a non-native phonetic contrast is reflected by higher MMN amplitudes (e.g., Winkler et al., 1999; Shafer et al., 2004). Näätänen et al. (1997) were among the first to observe such language-specific phoneme representations using MMN. In their study, Finnish and Estonian participants were presented with the vowel /e/ (used as standard in the MMN design), that is present in both languages, as well as with vowels /ö/, /o/, /õ/ (used as deviants in the MMN design), of which the first two are present in both languages but the last one only exists in Estonian. Näätänen et al. (1997) found that the amplitude of the MMN was influenced by the deviant's phonemic status in the respective language. There was larger MMN for vowels that were present in the participant's native language (Finnish) compared to vowels that were not present. The effect did not seem to be affected by acoustic features, since the deviant vowels were equally complex. Larger MMN occurred only when the deviant stimulus was part of the respective phoneme inventory. This result led to the suggestion that memory traces of speech sounds are language-dependent, and reflect native phoneme categories (cf. Bien and Zwitserlood, 2013). A replication of the result came from data from 12-months-old but not from 6-monthsold infants, suggesting an early development of language-specific memory traces (Cheour et al., 1998).

In the same line of research, Dehaene-Lambertz (1997) found that native French-speaking subjects display MMN when confronted with an acoustic change signaling a phonemic boundary in French but not in Hindi. Effects of experience with a L1 are also visible when experience is operationalized as the relative frequency of occurrence for a given phonological process in a given context. To examine sensitivity to frequency of phonological variants, Tavabi et al. (2009) created German bisyllables and manipulated the phonemic context in which assimilation of /n/ to /m/ occurs (e.g., *onbo* to *ombo*) as well as the frequency of assimilation (/n/ to /m/ is more frequent than /m/ to /n/). They found that both the frequency of the particular assimilation and the context in which it occurs modulate the MMN.

MMN can be used to index the perception and discrimination abilities of foreign-language phonemes as well; Winkler et al. (1999) demonstrated that Hungarian participants with no prior exposure to Finnish showed no MMN and very poor discrimination performance with the Finnish vowel contrast (/e/ – /æ/). Hungarians who were fluent in Finnish showed a MMN that was comparable to the one found in native Finnishspeaking participants. Training effects for the perception of nonnative contrasts – Germans learning moraic consonant duration in Japanese – are reflected in the emergence of an MMN (Menning et al., 2002). Interestingly, presenting a continuum of synthesized Hindi stops to English and Hindi speakers, Shafer et al. (2004) found some evidence that pre-attentive discrimination is modulated by experience with the speech sounds of a language. The observed MMN did not, however, directly correspond to the behavioral discrimination results, and some pairs of sounds that could be behaviorally discriminated did not elicit MMN. Long-term experiential factors with L2 phoneme duration were tested by Nenonen et al. (2003). They found that – despite extensive experience with the L2 and advanced L2 skills – non-native listeners did not reach native-like discrimination abilities for speech stimuli (but they were comparable with natives when tested with non-speech stimuli).

Taken together, these studies suggest that the MMN can be used as an index of long-term experience with native and non-native speech sounds, using single speech sounds, syllables, and non-words. In this study, we examine electrophysiological activity of the brain to understand the perception of English dental fricative sounds in two groups of proficient L2 listeners, which has been rarely done. Some previous research (mainly using magnetoencephalography) on fricative perception examined L1 English phonemic contrasts such as /s/ and /- / (Miller and Zhang, 2014; Lago et al., 2015) as well as responses to Polish fricatives by native and inexperienced non-native listeners (Lipski and Mathiak, 2007). It remains unclear whether experience with typical mispronunciations of L2 speech sounds lead to cross-linguistically distinct memory traces for non-native phonemes. In our study, we examined this question by using English monosyllables with no lexical status to avoid possible topdown effects (Pulvermüller and Shtyrov, 2006), and to focus on L2 memory traces for phonemes.

### Present Study

In the present study, we use MMN to look at the role of experience with common mispronunciations in a second language. Specifically, we examine whether cross-linguistically distinct experience with mispronunciations of L2 speech sounds shapes the neural organization of L2 phonemes, as reflected in the size of mismatch effects. Studying Dutch and German participants, we focus on the perception of the voiceless interdental fricative /θ/ and its substitutions /t/ and /s/, most commonly produced by these two groups of learners of English.

To examine the influence of experience with non-native accents on auditory memory traces, we compared the automatic electrophysiological responses in Dutch and German listeners to the English pseudoword *thond* and its pronunciation variants *sond* and *tond* in an oddball paradigm. Oddball paradigms are not free from lexical effects, even with attention diverted from the acoustic stimuli (cf. Pulvermüller and Shtyrov, 2006). Therefore, we used English monosyllabic pseudowords. We concentrated on the variant forms /s/ and /t/ as they represent the preferred substitute for the two learner groups respectively. If long-term experience with typical non-native variants already affects this early automatic processing level, we should find a similar accentspecific pattern of results as reported for lexical processing in Hanulíková and Weber (2012). That is, smaller mismatch effects should be found for *tond* than for *sond* for Dutch listeners, and the reverse should be found for German listeners. Alternatively, exposure-frequency effects might only arise at higher levels of lexical processing and might not affect non-native phoneme representations. In that case, the two variant forms *tond* and *sond* might either elicit comparable brain responses, or they might reflect effects of stimulus similarity, in which case *tond* should elicit a larger mismatch effect than *sond* for both Dutch and German participants.

### MATERIALS AND METHODS

#### Participants

Eighteen native speakers of Dutch (mean age: 23, *SD*: 3.3, nine male) and 17 native speakers of German (mean age: 23, *SD*: 1.6, three male) participated in the present study, after having given written, informed consent. Dutch participants were tested in the Netherlands, at the Max Planck Institute for Psycholinguistics. German participants were tested in Germany, at the University of Münster. All participants reported having normal hearing and no history of neurological problems, head injuries, or continuous medication. Participation was compensated with €12 or course credit.

Subsequent to the experiment, participants took part in an ABX discrimination test of the speech materials, and provided information on their use of and proficiency in English. All German participants had learned English in school as their second language with a mean duration of 8.4 years (*SD*: 0.8). Dutch participants had on average 7.6 years (*SD*: 0.7) of English education in school. In the Netherlands, all students in upper educational levels have to attend German language courses for at least 3 years, and German is usually their third or fourth nonnative language (after English). Thus, all Dutch participants had some knowledge of German. Dutch, on the other hand, is not mandatory in German high schools, and German participants had little or no exposure to Dutch.

This study was carried out in accordance with the recommendations for ethical guidelines of the Institute for Psychology, Westfälische Wilhelms-Universität, Münster, Germany and Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands. All participants gave written informed consent in accordance with the Declaration of Helsinki.

#### Stimuli and Design

We compared processing of the English interdental fricative /θ/ in the pseudoword *thond* with the non-native pronunciation variants *tond* and *sond*. The variant *sond* represents a typical pronunciation of *thond* for German speakers of English, who frequently substitute /θ/ with /s/, while the variant *tond* is typical for Dutch speakers of English, who frequently substitute /θ/ with /t/ (cf. Hanulíková, and Weber, 2010). The stimuli used in the experiment were therefore the English monosyllabic pseudowords *thond*, *sond*, and *tond*. To ensure a native-like pronunciation of /θ/ in *thond*, all pseudowords were produced by a native speaker of English. None of the stimuli is, or closely resembles, an existing word in Dutch or in German. In addition, pronounced as English pseudowords, *thond*, *sond*, and *tond* cannot be interpreted as Dutch or German pseudowords, due to a violation of the phonotactic constraint of syllable-final devoicing (e.g., in Dutch and in German, the pseudoword *sond* would be pronounced /sont/). The length of the initial consonants was 149 ms for *thond*, 60 ms for *tond* and 176 ms for *sond*. The length of the stimuli was 593 ms for *thond*, 499 ms for *tond,* and 609 ms for *sond*. The stimuli were cross- and identity-spliced to avoid elicitating MMN due to features other than the initial phoneme in the recorded materials (see **Figure 1** for stimuli waveforms and spectrograms after the splicing procedure). Some variation in the stimuli was re-created by changing the pitch to abstract away from specific acoustic properties of individual tokens (e.g., Bien et al., 2009). With three stimuli and five levels of pitch (+12, +6, +0, −6, and −12 Hz), the total number of tokens was 15. All stimuli served as both standards and deviants in different blocks.

The experiment consisted of four blocks, each with a different STANDARD\_deviant combination ([THOND\_tond]; [THOND\_sond]; [TOND\_thond]; [SOND\_thond]). The order of blocks was balanced across participants. Within each block, 500 stimuli were presented in random order, with a deviant

likelihood of 20% and an inter-stimulus interval of 1000 ms. Each block lasted for approximately 11 min, and there was a short break after each block. The experimenter started the next block once the participants had retaken a stable and comfortable position.

### Procedure and EEG Recording

are shown from 0 to 5 kHz on the horizontal axis.

Participants were comfortably seated in front of a computer screen in a sound-attenuated room. The stimuli were presented via loud speakers at approximately 60 dB SPL. During the electrophysiological recordings, participants watched a silent movie and were told that they could ignore the auditory stimuli.

The electroencephalography (EEG) of the German participants (GER) were recorded in sampling rates of 256 Hz, using 64-channel WaveGuard caps (ANT, Enschede, Netherlands) connected to an ANT amplifier (ANT, Enschede, NL). AFz was used as the ground electrode, and electrode impedances were kept below 5 K-. Horizontal eye movements were recorded using two bipolar electrodes with left and right canthal montage. Lateral eye movements and blinks were recorded using two bipolar electrodes placed above and below the right eye. An average mastoid reference was used.

Electroencephalography for the Dutch participants (NL) was recorded from 34 Ag–AgCl electrodes (Brain Products, MedCat, Netherlands) at standard 10–20 locations. Impedance was kept below 5 k-. All recordings were referenced to the left mastoid during recording (eye movement and blink artifacts were recorded from F9 to F10 and from Fp1 to an additional EOG electrode below the left eye), amplified with BrainAmp DC amplifiers (0.016–100 Hz band pass, digitized at 500 Hz), and rereferenced off-line to the mastoid average (e.g., Poellmann, 2013; Poellmann et al., under revision).

Data were analyzed with Advanced Source Analyses (ASA) software (ANT Software BV, Enschede, NL) and with SPSS statistics. We filtered the data offline, applying a 35 Hz low-pass filter. EEGs outside the range of −75 to +75 μV were labeled as artifacts and excluded from further analyses. This ensured the elimination of segments containing eye movement, blinking, or muscular activity. Overall, 81% of epochs were free from artifacts and used for analyses (71% for German and 91% for Dutch participants). Intact epochs were evenly distributed across conditions within each group. The remaining data were averaged in epochs of 800 ms, including a 250 ms pre-stimulus baseline interval used for epoch correction. All analyses were based on the mean amplitudes at Cz.

We analyzed the *identity* mismatch (*i*MMN) elicited by the *thond*-pronunciation deviants *tond* and *sond* in the Dutch and German participants. In order to compute the *i*MMN for *tond* and *sond*, we subtracted the respective ERPs when used as a standard next to *thond* from the ERPs when used as a deviant next to *thond*. That is, for the iMMN of *tond*, the standard-ERP elicited by *tond* in the block [TOND\_thond] was subtracted from its deviant-ERP elicited in the block [THOND\_tond]. For *sond*, the standard-ERP in block [SOND\_thond] was subtracted from its deviant-ERP elicited in block [THOND\_sond]. This *i*MMN procedure is specifically relevant when stimuli differ with respect to duration and various spectral factors, which certainly holds for fricatives and plosives. Calculating iMMN cancels out the specifics of the individual acoustic stimulus tokens (**Figure 2**).

Based on qualitative visual inspection, the time windows for the analyses of the mismatch effects were determined by the range of the deviant-N1. Note that mismatch negativity often overlaps with the N1 (cf. Schröger, 1998). The datadriven selection of the time windows was done separately for

the Dutch and German groups of listeners. Measured at Cz (**Figure 2**), where both the N1s and the mismatch effects were most prominent, the time windows were 88–140 ms (Dutch) and 68–133 ms (German) for *tond*, and 134–196 ms (Dutch) and 78– 168 msec (German) for *sond*. The use of different time windows is justified for the factor *phoneme* because of the large variance in the onset of perceivable information between the critical stimuli. Likewise, because listeners' perception is optimized for their native language, Dutch and German listeners differ with respect to the uptake of information that distinguishes between phonemes (the voice-onset times vs. prevoicing distinction for voiced plosives is a prime example). Thus, to select most objectively for the planned comparison of the identity mismatch elicited by a given stimulus, we also opted for data-driven (and thus potentially different) time windows for the factor *listener group*. Note that it is not uncommon to use datadriven solutions to the problem of latency variability (see Luck, 2005, p. 135). All analyses were based on the mean amplitudes at Cz within the specified time windows (i.e., over the whole range of the deviant-N1). We followed the suggestions by Luck (2005) to use an area amplitude measure rather than a peak amplitude measure to mitigate the reduction in amplitude caused by latency variability amplitude (see also Schröger, 1998). For the statistical analysis, we used a 2 (Deviance: sond, tond) by 2 (Group: Dutch, German) repeatedmeasures analyses of variance (ANOVA) and report Greenhouse– Geisser corrections and corrected F-values where appropriate. Additionally, we report one-way ANOVAs for Deviance for each group separately.

### Behavioral ABX-Experiment

After the EEG experiment, all participants completed a speech-sound discrimination ABX-task to test participants' discriminatory ability for the three stimuli. Stimuli /θond/, /tond/, and /sond/ were presented over speakers in 12 trials in a random order at the A and B positions, followed by a third stimulus at the X position that matched either A or B. Participants had to press the left shift button when the last presented (X) stimulus matched the first (A) stimulus, and to press the right shift button when it matched the second (B) stimulus. Stimuli were presented at ISIs of 800 ms.

The results showed that German participants distinguished /θond/ equally well from /tond/ (2,9% errors) and /sond/ (4,4% errors). For Dutch participants, it was harder to distinguish /θond/ from /sond/ (22,2% errors) than from /tond/ (8,3% errors). A closer look at the Dutch participants shows that the higher error rate is mainly due to three participants. The error rate drops to 9,3% when these participants are excluded. Note that this discrimination pattern would go against the predicted experience-based perception effect in the EEG study, according to which Dutch speakers would perceive /t/ as a closer match to /θ/ than to /s/ (as reflected in their production behavior). Moreover, previous studies reported non-significant MMN responses to L2 contrasts in L1 and L2 participants despite the presence of differences in behavioral discriminations of L2 contrasts (e.g., for the Japanese listeners' difficulties with the English /r/ and /l/; Zevin et al., 2010).

### RESULTS

Visual inspection of the data in **Figure 2** indicated that, when presented next to *thond*, both pronunciation variants *sond* and *tond* elicited mismatch effects in both groups of participants. However, against our hypothesis, the numerical differences of mismatch effects for /s/ and /t/ between the language groups show larger effects for /tond/ in Dutch listeners, and larger effects for /sond/ in German listeners.

In a first step, we tested the significance of each identity mismatch component against zero in each group of participants. Subtracting the standard-ERP of *sond*, elicited in block [SOND\_thond], from its deviant-ERP, elicited in block [THOND\_sond], the identity mismatch effect (mean amplitude in the specified time window) was −0.65 μV [*t*(1,17) = 4.51, *p* = 0.049] for Dutch participants and −0.81 μV [*t*(1,16) = 7.08, *p* = 0.017] for German participants. The difference in the *sond*-*i*MMNs between the two groups was non-significant (independent sample *t*-test [*t*(33) = 0.379, *p* = 0.707]). *Tond* elicited iMMNs of −0.93 μV [*t*(1,17) = 8.31, *p* = 0.010] in Dutch participants and −0.20 μV [*t*(1,16) = 0.44, *p* = 0.519] in German participants. The difference in the *tond*-*i*MMNs did not reach significance (independent-sample *t*-test [*t*(33) = −1.667, *p* = 0.105]).

In a second step, ANOVAs on the identity mismatch effects were carried out separately for the two groups of listeners; the factor Deviance (*sond*, *tond*) was not significant in either the Dutch [*F*(1,17) = 0.35, *p* = 0.563] or German group [*F*(1,16) = 1.88, *p* = 0.189]. An overall ANOVA with Group (Dutch, German) as the between-subjects factor and Deviance as the within-subjects factor revealed no main effect of Deviance [*F*(1,33) = 0.027, *p* = 0.609], no main effect of group [*F*(1,33) = 0.961, *p* = 0.334], and no significant interaction between Group and Deviance [*F*(1,33) = 1.88, *p* = 0.180; see **Table 1**].

To summarize, mismatch effects were seen for both deviant stimuli in both language groups (except for the iMMN for *tond* in the German group, where it was expected to be pronounced). Interestingly, the pattern of identity mismatch elicited by the *thond-*pronunciation variants *sond* and *tond* was comparable in both groups of listeners (see **Table 1**). This does not confirm

TABLE 1 | Analyses of variance on the identity mismatch effects (mean amplitudes in **μ**V) elicited by the *thond*-pronunciation variants *tond* and *sond*, computed with GROUP (Dutch, German) as a between-subject factor, and for each group separately.

an L2-accent-specific pattern of results, according to which smaller mismatch effects were expected for *tond* than for *sond* for Dutch listeners, and the reverse was expected for German listeners. What we observed instead is that the two variant forms *tond* and *sond* elicited comparable brain responses across the two listener groups and thus might reflect effects of stimulus similarity.

### DISCUSSION

The present study examined whether pre-attentive processing of pronunciation variants in non-native speech is influenced by cross-linguistically distinct experiences with such variants. If experience exerts a predominant influence on speech processing and speech-sound representation, smaller mismatch effects were expected for *tond* compared to *sond* in Dutch listeners, for whom /t/ is the common substitute for /θ/ (Hanulíková and Weber, 2010). The reverse was expected for Germans, who frequently substitute /θ/ with /s/ (Hanulíková and Weber, 2010). While there is converging evidence that experience with pronunciation variants in an L2 influences speech processing at a lexical level (e.g., Hanulíková and Weber, 2012), the present study found no evidence for an impact of experience with L2 pronunciations on L2 phoneme representations. We did not find (at least in the ANOVA analysis) the predicted differential processing between the two groups. Note that the numerical differences of mismatch effects for /s/ and /t/ between the language groups were even against the hypothesized direction, with larger effects for /tond/ in Dutch listeners, and for /sond/ in German listeners. A possible explanation is provided further below, however, given the lack of interaction, these differences should not be interpreted.

In the ERPs of Dutch and German proficient speakers of English, we compared the identity mismatch effects elicited by the pronunciation variants *sond* and tond in the context of the English pseudoword *thond*. Presented next to the pseudoword *thond*, the pronunciation variants *sond* and *tond* elicited mismatch effects in both the Dutch and German groups of listeners. This was evident when using the identity mismatch approach (presenting two blocks with switching roles of standard and deviant for each variation of interest, then subsequently comparing the ERPs elicited by the identical stimulus when presented as standard and when presented as deviant).

Due to its clearer acoustic onset, *tond* elicited a more distinct and more negative N1 than *sond*, both when presented as a standard and when presented as a deviant. This acoustic difference, however, was not confirmed in a main effect of Deviance in the iMMN. Most importantly, the mismatch effects elicited by *sond* and *tond* were statistically comparable, and there were no interactions with listener group. This result seems to reflect effects of stimulus similarity comparable across both listener groups. Note that we used English monosyllabic pseudowords (*thond, tond, sond*) and avoided lexical items because pronunciation substitutions may vary depending on the phonemic context and position in a given word. An interesting question for future research is thus whether the same result would be obtained for real words.

It should be noted, however, that while the mean latencies of the time frames were similar between the two listener groups in the *tond*-condition, they were different in the *sond*-condition. One possible reason for this difference could stem from a different uptake of acoustic cues for the English fricative between the two listener groups. Previous studies have shown that Dutch /s/ is articulatorily less tense and has graver friction than German /s/ (Mees and Collins, 1982) and therefore also differs from English to a larger extent than German (e.g., Hanulíková and Weber, 2010, 2012). Slight latency differences present in the *tond*condition could also be explained by the distinct L1 acoustic characteristics. The Dutch /t/ is less aspirated than the English /t/ and mainly uses prevoicing as a cue to voicing, while German listeners use the VOT to categorize voicing of plosives (Lisker and Abramson, 1964; Keating, 1984). This could lead to distinct /t/ categorization patterns for German compared to Dutch listeners. These differences could have perceptual consequences and this could explain why the mapping of the English /s/ and /t/ sounds onto the distinct Dutch /s/ and /t/ resulted in different latencies than mapping of the English sound onto the more similar German /s/ and /t/. Distinct uptake processes of acoustic information are very likely despite behavioral tasks suggesting that both Dutch and German listeners show comparably high discriminatory performance for both /θ/-/s/ and /θ/-/t/ contrasts (e.g., Hanulíková and Weber, 2012). Although the control ABX test run after the present EEG study showed a higher error rate for /θ/-/s/ compared to /θ/-/t/ in the group of Dutch participants, this was mainly due to three participants. It would be interesting for future research to examine the issue of how cues are weighted differently in the foreign and native languages, particularly in the two highly related languages such as German and Dutch.

Finally, the time windows for analyzing the auditory components were selected based on the grand average of the deviant-N1s. Though we selected the time windows separately for *tond* and *sond* and separately for the group of Dutch and German participants, selection was not based on the individual responses of each participant. The time spans of certain ERP components can vary greatly across individuals (e.g., Michaelewski et al., 1986). As a consequence, group average analyses can eliminate individual mismatch effects, underestimating their actual size. The observation of significant effects based on group averages can be considered a strong indicator that these effects are real. Moreover, we restricted our analysis to the first N1 elicited by the speech sound, time-locked to its onset. Another approach would be to also analyze the second N1, elicited by the acoustic change complex defined as – and time-locked to – the transition of the consonant to the following vowel (see Lipski and Mathiak, 2007; Miller and Zhang, 2014). The ERP data in both subject groups (see **Figure 2**) indicate the consistent elicitation of the negative deflection responses to fricatives. Future research might want to focus on the time-point-by-time-point ERP responses to the speech stimuli to accommodate the complexity of ERP waveforms that could arise from tracking the acoustic properties of speech stimuli in the time domain.

A number of MMN studies found language-specific effects on phoneme perception (e.g., Dehaene-Lambertz, 1997; Näätänen et al., 1997; Winkler et al., 1999; Jacobsen and Schröger, 2003; Nenonen et al., 2003). However, most of these studies examined native listeners' perception or L2 perception of familiar and unfamiliar contrasts with within- or across-category manipulation for a given language. The present study used phonemes that are frequently produced by non-native speakers of English as substitutions for interdental fricatives. The present study is thus the first to look at whether cross-linguistically distinct experience with frequent non-native pronunciations modulates phoneme representations. The results suggest that experience-based memory representations for frequent or preferred phoneme substitutions are not (or not well) established. Given previous research on differences between native and advanced learners' perception of acoustic features (e.g., Nenonen et al., 2003), the present result may not be surprising. The formation of stable language-specific memory representations in an L2 seems to require early exposure or, for late learners, frequent exposure and practice. Listeners can learn to distinguish non-native contrasts, even when they are unable to produce these (Menning et al., 2002). It would be good if learning novel L2 speech sounds would result in the formation of a new perceptual category (for /θ/, for example), even if correct production lags behind. The use of L2 pronunciation variants may facilitate lexical processing, but does not lead to an annexation of novel sounds into native categories. Indeed, cross-linguistic perception studies and models (e.g., SLM, PAM) suggest that it is more difficult to establish a new L2 phonological category when the acoustic-phonetic properties of an L2 sound are similar to an L1 sound (Flege, 1995, 2007; Best and Tyler, 2007; see Dobel et al., 2009, for evidence from the N400 component). While these models are not directly concerned with L2-accented speech, the present results could be explained on the basis of

REFERENCES

acoustic/auditory properties of the consonant pairs (/θ/ as more similar to /s/ than to /t/).

Taken together, the results suggest that long-term nonnative experience with frequent pronunciation variants in a second language does not alter memory traces of phonemes or perception of these L2 speech sounds. Instead, pre-attentive perception of non-native speech sounds may better be explained in terms of acoustic similarity to native categories.

#### ACKNOWLEDGMENTS

We wish to thank Merel van Rees Vellinga for her help during the experiment set-up and data collection in the Netherlands, and Katharina Dohm and Sophia Thrun for her assistance with data collection in Germany. We thank both reviewers for their helpful and constructive comments on a previous version of this paper. This research was funded by the Max-Planck Society, Germany.

### FUNDING

The article processing charge was funded by the open access publication fund of the Albert Ludwigs University Freiburg.

### AUTHOR CONTRIBUTIONS

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

*Electroencephalogr. Clin. Neurophysiol.* 78, 466–479. doi: 10.1016/0013- 4694(91)90064-B

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2016 Bien, Hanulíková, Weber and Zwitserlood. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Processing Preference Toward Object-Extracted Relative Clauses in Mandarin Chinese by L1 and L2 Speakers: An Eye-Tracking Study

Yao-Ting Sung1, 2, Jung-Yueh Tu<sup>3</sup> \*, Jih-Ho Cha<sup>2</sup> and Ming-Da Wu<sup>2</sup>

*<sup>1</sup> Department of Educational Psychology and Counseling, National Taiwan Normal University, Taipei, Taiwan, <sup>2</sup> Center of Learning Technology for Chinese, National Taiwan Normal University, Taipei, Taiwan, <sup>3</sup> International Chinese Education Center, School of Humanities, Shanghai Jiao Tong University, Shanghai, China*

The current study employed an eye-movement technique with an attempt to explore the reading patterns for the two types of Chinese relative clauses, subject-extracted relative clauses (SRCs) and object-extracted relative clauses (ORCs), by native speakers (L1), and Japanese learners (L2) of Chinese. The data were analyzed in terms of gaze duration, regression path duration, and regression rate on the two critical regions, head noun, and embedded verb. The results indicated that both the L1 and L2 participants spent less time on the head nouns in ORCs than in SRCs. Also, the L2 participants spent less time on the embedded verbs in ORCs than in SRCs and their regression rate for embedded verbs was generally lower in ORCs than in SRC. The findings showed that the participants experienced less processing difficulty in ORCs than SRCs. These results suggest an ORC preference in L1 and L2 speakers of Chinese, which provides evidence in support of linear distance hypothesis and implies that the syntactic nature of Chinese is at play in the RC processing.

Keywords: relative clauses, Mandarin Chinese, L2 sentence processing, eye-movements, Japanese CSL learners

## INTRODUCTION

Relative clauses (RCs) have received considerable attention in psycholinguistic and linguistic research over the past few decades. An RC is a subordinate clause that modifies a noun and is embedded within a noun phrase. There are two major types of RCs: subject-extracted relative clauses (SRCs) and object-extracted relative clauses (ORCs). Examples of an SRC and an ORC in English are given in (1a) and (1b), respectively.

#### Edited by:

*Shelia Kennison, Oklahoma State University, USA*

#### Reviewed by:

*Erich David Jarvis, Duke University Medical Center, USA Julie E. Boland, University of Michigan, USA*

\*Correspondence:

*Jung-Yueh Tu<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Language Sciences, a section of the journal Frontiers in Psychology*

Received: *15 July 2015* Accepted: *03 January 2016* Published: *21 January 2016*

#### Citation:

*Sung Y-T, Tu J-Y, Cha J-H and Wu M-D (2016) Processing Preference Toward Object-Extracted Relative Clauses in Mandarin Chinese by L1 and L2 Speakers: An Eye-Tracking Study. Front. Psychol. 7:4. doi: 10.3389/fpsyg.2016.00004*

In (1), "the principal" is extracted from the clause and leaves an empty position, which is called a gap. The relative pronoun "who" introduces the RC. The extracted noun phrase "the principal" is coindexed with the gap and is called the filler, because it should fill the gap. The two types of RCs only contrast each other with respect to the location of the gap. Hence, comprehending and integrating RCs requires dependency between the filler and gap to be developed in harmony.

SRCs are considered easier to process than ORCs, with the evidence coming from observations of RC processing by native speakers (L1) of head-initial languages (e.g., for English, see Gordon et al., 2006; for Dutch, see Frazier, 1987; for French, see Holmes and O'Regan, 1981; for German, see Schriefers et al., 1995). The SRC preference is also evident in head-final languages (e.g., for Japanese, see Ueno and Garnsey, 2008; for Korean, see Kwon et al., 2010). In addition, it is reported in studies on second language (L2) comprehension (Gass, 1979; Doughty, 1991; Hamilton, 1994). The findings of these studies have led to the conclusion that SRCs are easier to process cross-linguistically than ORCs both in L1 and L2 sentence processing. However, conflicting results have been reported on the processing-difficulty contrast between SRCs and ORCs in Mandarin Chinese (Chinese, hereafter; Chen et al., 2012). Reports of the ORC processing preference in Chinese<sup>1</sup> (e.g., Hsiao and Gibson, 2003; Hsu and Chen, 2007; Lin and Garnsey, 2011; Gibson and Wu, 2013; Sung et al., 2015) have posited a challenge to the presence of a universal SRC processing preference.

Previous studies (e.g., Hsiao and Gibson, 2003; Gibson and Wu, 2013) were conducted using self-paced reading tasks. This method usually requires readers to press the button for the occurrence of each word, which causes repeated interruptions in reading. The self-paced reading task cannot completely record or reflect the normal reading process, wherein readers can move back and forth within a sentence, such as using regression or saccades. It also limits the scope of research and lacks certain online processing information. In particular, reading RC sentences requires dependency between the gap and filler so readers may read back and forth for integration and comprehension, which can be obtained with an eye-tracking device.

The goal of this study is to re-examine the L1 processing of Chinese RCs and further expand it to L2 RC processing. Since Chinese is a head-initial language with a head-final RC pattern while Japanese is a head-final language and the two languages share some syntactic similarities, such as RC location (both prenominal) and gap position (both prenominal), it would be interesting to see how the Japanese speakers, whose language has a typologically different RC structure, process Chinese RCs. Specifically, the study intends to see whether the Chinese syntactic nature or the universal SRC preference plays a more crucial role in the L2 RC processing by Japanese speakers. The native speakers of Chinese were also manipulated in the experiment. This study would like to serve as a pioneer eye-tracking research on L2 RC processing, which invites further studies on L2 learners with different language profiles.

#### Aspects of Chinese and Japanese RC Chinese RC Structure and its Processing

The structure of a Chinese RC is different from that of an English RC. In Chinese, an RC precedes the noun to which it is attached and is transformed by adding an RC relativization marker, de, instead of a relative pronoun in an English RC. The extracted object or subject falls in the clause-final position. Examples and structural representations of Chinese RCs are given in (2)<sup>2</sup> .

(2a) Chinese SRC

<sup>1</sup> Some studies on the processing of Basque RCs also showed an ORC preference (e.g., Carreiras et al., 2010), against the universal SRC preference.

<sup>2</sup> In (2), S, VP, CP, IP, C, and V are the subject, verb phrase, complementizer phrase, inflection phrase, complementizer, and verb, respectively.

In (2a), the noun xiaozhang "principal," extracted from the subject position of the embedded verb jieshao "introduce," serves as the head noun of the RC introduced by the relativizer de. De is treated as a relativization marker and is considered as a complementizer in phrasal structure (Aoun and Li, 2003). The extracted noun xiaozhang is coindexed with the gap and fills that gap. In (2b), the noun laoshi "teacher" is extracted from the object position and therefore, forms an ORC. It is noted that Chinese RCs are prenominal, which means they precede head nouns.

The processing of Chinese RCs has been intensively investigated over the past few years. Finding both preference types in Chinese indicates that the universal SRC preference is not consistent across languages. Therefore, the presence of processing asymmetry in Chinese RCs raises the issues of whether the processing pattern of Chinese RCs is language-specific, and whether discordant findings are related to the syntactically mixed patterns in Chinese RCs.

The processing of Chinese RCs has been intensively investigated using different methods. Among these studies, SRC preference has been reported in self-paced reading tasks (e.g., Lin and Bever, 2006a,b, 2007, 2011), in computational modeling (Chen et al., 2012), and in the relative frequency of occurrence in the corpus (Vasishth et al., 2013). Among those studies supporting a universal SRC preference, Lin and Bever (2006a,b, 2007, 2011) demonstrated that SRCs are easier than ORCs in Chinese. They examined how readers process RCs from two perspectives: RC modification (subject-modifying RC vs. objectmodifying RC) and RC embeddedness (singly embedded RCs vs. doubly embedded RCs). They found that the reading times on both the relativizer and the head noun were significantly shorter for SRCs than for ORCs, irrespective of whether the RC modifies the subject or the object of the main clause. Their results suggest an SRC preference in Chinese, which is in line with the findings across languages.

However, the finding that SRCs are easier to process in Chinese has been challenged by other reports of an ORC preference (e.g., in self-paced reading tasks, see Hsiao and Gibson, 2003; Hsu and Chen, 2007; Chen et al., 2008; Lin and Garnsey, 2011; Gibson and Wu, 2013; for a Mandarinspeaking aphasia case study, see Su et al., 2007). Among these works, the most often discussed is that of Hsiao and Gibson (2003). Those authors conducted a self-paced reading task with singly embedded and doubly embedded RCs, and with an RCmodifying subject of the main clauses. They found that in doubly embedded RCs, the reading times on the head noun and the embedded verb were shorter for ORCs than for SRCs. They demonstrated a preference for ORC in Chinese, implying that the processing of RCs in Chinese is language-specific.

#### Japanese RC Structure and Processing

Like Chinese RCs, Japanese RCs come before the head nouns they modify, and therefore Japanese exhibits a prenominal RC pattern. Examples of Japanese RCs are given in (3).

Japanese employs a different strategy to construct RCs, called the case-marking system, using case makers o and ga to indicate the syntactic function of the noun modified by the RC. Japanese does not have an overt relativizer, whereas Chinese has the relativizer de in RC.

Unlike reports of Chinese RCs having either an SRC and ORC preference, most research on the processing of Japanese RCs has demonstrated a preference for SRCs by native Japanese speakers (Miyamoto and Nakamura, 2003; Ueno and Garnsey, 2008).

#### Comparison of Chinese and Japanese Structures

L2 sentence processing involves the syntactic structures of both L1 and L2. To understand and isolate the factors that potentially influence the processing of Chinese RCs by Japanese CSL learners, it is necessary to compare the structural properties of both involved languages. The structures of RC in Japanese and Chinese vary in several ways, as summarized in **Table 1**.

Due to the syntactic divergence between the two languages, it is expected that the different head positions between Chinese and Japanese may have certain effects on the L2 processing of Chinese, and therefore the two groups are hypothesized to show different processing patterns. Otherwise, if the two groups show similar processing patterns, then it would imply that the unique pattern of Chinese RCs may play a more crucial role.

### Theoretical Accounts on L2 Sentence Processing

Regarding L2 sentence processing, three theoretical accounts have been proposed to explain the difference in processing patterns between SRCs and ORCs: Noun Phrase Accessibility Hierarchy (NPAH, Keenan and Comrie, 1977), Structural Distance Hypothesis (SDH), and Linear Distance Hypothesis (LDH).

#### Noun Phrase Accessibility Hierarchy

Keenan and Comrie (1977) proposed a universal tendency, called the NPAH, which was derived from the observations of syntactic forms in a large number of languages. The NPAH ranks the accessibility of the syntactic positions in a sentence as follows: subject, direct object, indirect object, oblique object, possessor, and object of comparison. Accordingly, a language that can relativize a given position in the hierarchy can also relativize all of its antecedent positions. Some studies suggest that the difficulty processing RCs experienced by L2 learners is associated with the NPAH (Gass, 1979, 1982; Pavesi, 1986; Doughty, 1988, 1991; Eckman et al., 1988; Wolfe-Quintero, 1992; Izumi, 2003). The findings in those studies parallel the typological implications captured by the NPAH. The NPAH hypothesizes that the degree of accessibility to RC formation across languages, and such a universal tendency, implies that SRCs make sentence processing easier than ORCs.

#### Frontiers in Psychology | www.frontiersin.org January 2016 | Volume 7 | Article 4 |

#### Structural Distance Hypothesis

The SDH (Collins, 1994; Hamilton, 1995; O'Grady, 1997, 2001; O'Grady et al., 2003) states that the difficulty of an RC is determined by the depth of the gap corresponding to the relativized elements, and it is measured by counting the nodes between the gap and the filler of the RC.

In SRCs (e.g., 1a) the gap contains two phrasal nodes (IP and CP), while in ORCs (1b) the gap contains three phrasal nodes (VP, IP, and CP). Thus, the structural distance between the gap and its filler is greater in ORCs (1b) than in SRCs (1a).

#### Linear Distance Hypothesis

The LDH (Tarallo and Myhill, 1983; Hawkins, 1989; O'Grady, 2001) presents a more straightforward measurement for the gap-filler distance: counting the intervening elements (words or words with discourse referents) between the gap and filler. In SRCs (e.g., 1a), there are three words and one discourse referent intervening between the gap and its filler, and in ORCs (e.g., 1b) there is only one word along the same path. Hence, the linear distance between gap and filler is greater in SRCs (1a) than in ORCs (1b).

### L2 Processing of RC

Regarding the processing of RCs by L2 learners, a great deal of previous studies have shown that L2 performance correlated with the prediction of NPAH (Gass, 1979, 1980, 1982; Hyltenstam, 1984; Pavesi, 1986; Doughty, 1988, 1991; Eckman et al., 1988; Wolfe-Quintero, 1992 among others). Those studies tested L2 learners with different L1 backgrounds through various tasks, including written sentence combination (Gass, 1979, 1980, 1982; Eckman et al., 1988), oral picture-cued production task (Pavesi, 1986), and guided oral production task (Wolfe-Quintero, 1992). The findings demonstrated that the participants performed better in SRCs than ORCs, implying that NPAH may still hold for the L2 sentence processing. Research on L2 processing in East Asian RCs, however, has arisen controversy to the acquisition difficulties across RC types (e.g., O'Grady et al., 2003; Jeon and Kim, 2007; Ozeki and Shirai, 2007; Yip and Matthews, 2007; Packard, 2008; Cui, 2013; Xu, 2014).

Several studies on the L2 processing of Chinese RC has reported inconsistent results with the acquisition difficulty/hierarchy made by NPAH. The results from those studies suggested that no clear processing asymmetry has been settled yet. First, Packard (2008) employed a self-paced reading task with both subject- and object-modifying SRCs and ORCs. He found that the participants read ORCs more quickly than SRCs. Moreover, Cui (2013) used a questionnaire and an online self-paced reading task to compare Chinese RC processing by L1 and L2 speakers. In her study, 24 native speakers of Chinese and 33 Chinese L2 learners (17 from head-initial L1 backgrounds and 16 from head-final L1 backgrounds) were recruited. The results of the questionnaire indicated that both L1 and L2 speakers found ORCs easier than SRCs. The data from the reading task showed that for L1 speakers, ORCs were read more quickly than SRCs only in subject-modifying RCs; for L2 speakers, no preference was found in the overall results, but an SRC preference was in the head-initial group. In addition, Xu (2014) conducted a written sentence combination task, testing 45 native English-speaking learners of Chinese on the production difficulty of four RC types: SRC, direct ORC, indirect ORC, object of preposition RC. She concluded that the participants' production difficulty fully follows the accessibility order of NPAH.

In a nutshell, the NPAH is typologically-driven and wellattested in many studies on L2 RC processing but it is still disputed for Chinese RCs. One may wonder if RC processing asymmetry is language- universal or specific in Chinese.

## THE CURRENT STUDY

This study focused on three major questions related to the conflicting research findings regarding processing of the two kinds of RCs:

An eye-movement monitoring paradigm was employed to explore the reading patterns of Chinese RCs by Japanese CSL learners. The eye-movement technique enables us to obtain online information of consecutive reading as well as regression crucially relevant to RC processing. The eye-tracking indicators can be used to exam processing preference since fixation duration and the frequency of regressions increase as sentence becomes conceptually more difficult (Rayner, 1998).

### Interest Areas and Hypotheses

The interest areas, based on previous research, included the head noun and the embedded verb. These areas were examined in order to identify which type of RC is easier to process and where the processing difficulties (if any) arise. The head noun is of interest because it is the element that is extracted from the clause that later is transformed into an RC by adding the RC marker DE. In addition, head noun contrasts in the two RC types in terms of the syntactic functions (subject vs. object). The embedded verb was examined for two reasons: (1) the embedded verb syntactically governs the head noun of the RC, and (2) since Japanese is a head-final language, readers may pay special attention to the embedded verb, which may lead to different reading patterns from those of Chinese speakers.

The predictions of different theories regarding RCs, the head noun, and the embedded verb vary according to the factors emphasized, as follows:

1. The NPAH would predict an SRC preference because the subject is universally easier to relativize than the object, and participants would spend less time on the head noun of an SRC than of an ORC. That is, the processing time for an head noun would be shorter for an SRC than for an ORC. Although in the current study, all RCs modify the subjects of main clauses (subject-modifying RCs), within the RC structure, we compared the processing difference between SRCs and ORCs. Then, NPAH would favor SRCs. The NPAH assumption would lead to another prediction: that L1 syntax does not influence L2 sentence processing.

The NPAH and SDH make the same prediction in Chinese RCs in terms of processing asymmetry. However, it should be noted that two accounts were based on different theoretical implications, the former came from observations of typologically different languages while the latter was built upon syntactic structures.

## METHOD

### Participants

Thirty-six native Japanese speakers were recruited at the Mandarin Training Center at National Taiwan Normal University. These participants had learned Chinese for a mean of 2.1 years, and their level of proficiency in the language corresponded to A1-B1 level according to their learning materials associated with the standard of the Common European Framework of Reference for Languages (CEFR). They came from classes of the same proficiency level. Thirty-eight native speakers of Mandarin Chinese who were college students were also recruited. The data of participants with a comprehension accuracy of <70% in the reading comprehension test were removed from the analysis. Based on the inclusion criteria, 33 native Japanese speakers and 38 native Chinese speakers were considered to be valid samples (11 male and 22 female Japanese, and 7 male, and 31 female Chinese). The native Japanese and Chinese speakers ranged in age from 21 to 50 years (M = 28.76 years) and 20 to 49 years (M = 22.42 years), respectively. All had normal or corrected-to-normal vision.

### Apparatus

The sentences were presented in black against a light-gray background on a 19-inch CHIMEI CMV A902 LCD monitor (1024 × 768-pixel resolution). Eye movements were recorded with an EyeLink 1000 eye tracker (SR Research, Canada). The sampling rate was set to 1000 Hz. The equipment comprised two personal computers (PCs) with Intel Core i5 3.2-GHz processors: one was a display PC that was responsible for presenting stimuli and controlling the experiment, and the other was a host PC that was responsible for monitoring and collecting eye-movement data. Participants were instructed to rest their head on a chinrest to minimize head movements. Although, viewing was performed binocularly, only data for the left eye were recorded. The programming was conducted using Experiment Builder 1.10.1 (SR Research Ltd. 2004–2010), and data were analyzed using Data Viewer 1.11.1 (SR Research Ltd. 2002–2011) and SPSS 18.

### Materials and Design

The experiment had a 2 × 2 within-subject design. The independent variables were clause type (SRC vs. ORC) and distance (long vs. short), where distance was defined as the length between the gap and the head noun with which it was associated (long distance: 6–10 characters; short distance: 1–5 characters). The distance between the two syntactic dependents was manipulated by the additional modifiers preceding the head noun. The dependent variables were the accuracy rate in the reading comprehension test, reading time, gaze duration, regression-path duration, and regression rate.

The eye-movement task comprised 120 sentences: 60 experimental sentences (sentences with RCs) and 60 fillers (sentences without RCs). The experimental sentences comprised 30 SRCs and 30 ORCs, with 15 long-distance and 15 shortdistance sentences in each. The frequencies of words in the experimental sentences were calculated based on the frequency list of 8000 Chinese words compiled by the Steering Committee for the Test of Proficiency (SC-TOP) in Huayu, Taiwan, to ensure that (a) reading could be performed without vocabulary difficulties and (b) all the experimental sentences comprised phrases with similar difficulties for L2 learners, with only the complexities in the RCs varying. The average frequency of head nouns in SRCs was 0.014 (SD = 0.015) and that in ORCs was 0.019 (SD = 0.029). The difference between average frequencies of head nouns in SRCs and ORCs was not significant [t(14) = 1.03, p = 0.32]. The words used in the experimental sentences included the vocabulary at Level 1, 2, and 3 (corresponding to A1, A2, and B1 under CEFR) in Chinese 8000 words (SC-TOP). Sample stimuli are given in (4), where the head nouns and embedded verbs are bolded.

All experimental sentences and fillers were displayed in a single line in the middle of an LCD screen. The lengths of the sentences ranged from 12 to 21 characters, and the size of the characters was 36×36 pixels, with intercharacter spaces of 10×36 pixels. Each of the sentences was presented horizontally from left to right on the screen. The fillers covered various sentence structures, such as ba-construction and bei-construction. The fillers varied in length since the critical sentences included longdistance and short-distance sentences.

### Data Analysis

The data analysis included the accuracy of the reading comprehension test, reading time of full sentences, and eyemovement data. The eye-movement data were measured according to the gaze duration, regression-path duration, and regression rate. The gaze duration is the sum of all first-pass fixations on a region before the eyes move out of the region to either the right or left (Rayner, 1998). The regression-path duration is the total time spent fixating on all of the target and pretarget regions, from the first fixation on a target region to fixation to the right of the target region (Rayner and Duffy, 1986; Liversedge et al., 1998). The regression rate is corresponding to the probability of rereading the target (Yen et al., 2008), i.e., the probability of regressions back into the target region after it has already been read. Fixations of <80 or >1200 ms (representing 4.15 and 5.00% of Japanese and Chinese language groups, respectively) were eliminated from the analyses (Liversedge et al., 2004; Drieghe et al., 2008; White, 2008; Slattery et al., 2013; Stites et al., 2013). Two-way repeated-measures ANOVAs were conducted for participants (F1) and items (F2). The analysis of eye-movement data was based on the trials in which no errors were made in the reading comprehension test.

#### Procedure

This study was approved by National Science council in Taiwan with written informed consent from all participants. The participants were asked to provide background information before they proceeded to begin doing the experiment. The eyemovement task, which took about 25 min for L1 participants and 40 min for L2 participants to complete, was then conducted.  At this viewing distance, each character subtended a visual angle of 1.06◦ . The task began with a 13-point calibration, followed by five practice trials. The practice trials were in the same format as the experimental trials. For drift correction, the participants were instructed to look at a dot positioned at the location of the first character of the sentence. After the participants fixated on the dot, the experimenter pressed a button and the sentence appeared on the screen. The participants viewed each complete sentence on the screen one at a time, and were instructed to read each sentence at their own pace. Their eye movements were tracked while reading the sentence. When the participants were finished reading, they were asked to answer a true-or-false reading comprehension question to ensure that they had understood the sentence. Once the reading comprehension question was presented, the subjects were unable to go back to the test sentence. There were 120 questions in total, with a 5-min break every 40 trials. The 13-point calibration was readministered after each break. The sentences were presented in a randomized order, meaning that each participant viewed them in a different order.

#### RESULTS

### Accuracy of the Reading Comprehension Test

The means and standard deviations for accuracy of the comprehension test are given in **Table 2**.

For native Chinese speakers, the main effect of clause type on accuracy was marginally significant [F1(1, 37) = 3.91, MSE = 0.001, p = 0.055, partial eta squared (η 2 ) = 0.10; F2(1, 14) = 0.96, MSE = 0.002, p = 0.34, η <sup>2</sup> = 0.08]. The accuracy was higher for SRCs (M = 0.980, SD = 0.055) than for ORCs (M = 0.969, SD = 0.056). However, there was no significant main effect of distance or significant interaction of clause type and distance (all ps > 0.50).

For Japanese speakers, the main effect of distance on accuracy was significant in the analysis by participants [F1(1, 32) = 4.15, MSE = 0.006, p < 0.05, η <sup>2</sup> = 0.11; F2(1, 14) = 0.05, MSE = 0.019, p = 0.83, η <sup>2</sup> = 0.00]. The accuracy was higher for shortdistance sentences (M = 0.905, SD = 0.126) than for longdistance sentences (M = 0.877, SD = 0.137). However, there was no significant main effect of clause type or significant interaction of clause type and distance (all p > 0.10).

#### Reading Time of Full Sentences

The means and standard deviations for reading time of full sentences are given in **Table 3**.

For native Chinese speakers, the main effect of clause type on reading time was significant [F1(1, 37) = 16.50, MSE = 0.233, p < 0.001, η <sup>2</sup> = 0.31; F2(1, 14) = 11.61, MSE = 0.136, p < 0.01, η <sup>2</sup> = 0.45]. The reading time was significantly longer for full sentences in SRCs (M = 4.05 s, SD = 1.36 s) than for those in ORCs (M = 3.74 s, SD = 1.29 s). The main effect of distance on reading time was significant [F1(1, 37) = 181.89, MSE = 0.507, p < 0.001, η <sup>2</sup> = 0.83; F2(1, 14) = 449.28, MSE = 0.077, p < 0.001, η <sup>2</sup> = 0.97]. The reading time was significantly longer for long-distance sentences (M = 4.67 s, SD = 1.31 s) than for short-distance sentences (M = 3.12 s, SD = 0.80 s). The interaction between clause type and distance was also significant [F1(1, 37) = 10.41, MSE = 0.298, p < 0.01, η <sup>2</sup> = 0.22; F2(1, 14) = 12.00, MSE = 0.120, p < 0.01, η 2 =

TABLE 2 | Mean (M) and standard deviation (SD) values for the accuracy of the post-stimulus reading comprehension test.

*Long and short refer to the distance between the gap and the HN.*

TABLE 3 | Mean (M) and standard deviation (SD) values for Reading time of full sentences (sec).

*Long and short refer to the distance between the gap and the HN.*

Sung et al. Chinese RC Processing

0.46]. A simple main effect test showed that the reading time was significantly longer for full sentences in long-distance SRCs (M = 4.94 ms, SD = 0.64 s) than for those in long-distance ORCs (M = 4.31 s, SD = 0.33 ms) [F1(1, 74) = 26.08, MSE = 0.265, p < 0.001, η <sup>2</sup> = 0.26; F2(1, 28) = 23.58, MSE = 0.128, p < 0.001, η <sup>2</sup> = 0.46]. Regardless of clause type, the reading time was significantly longer for long-distance sentences than for short-distance sentences (all ps < 0.001; see **Figure 1**).

For Japanese speakers, the main effect of clause type on reading time was significant [F1(1, 32) = 41.54, MSE = 0.481, p < 0.001, η <sup>2</sup> = 0.56; F2(1, 14) = 24.59, MSE = 0.399, p < 0.001, η <sup>2</sup> = 0.64]. The reading time was significantly longer for sentences in SRCs (M = 7.64 s, SD = 2.13 s) than for those in

ORCs (M = 6.86 s, SD = 1.77 s). The main effect of distance on reading time was significant [F1(1, 32) = 203.67, MSE = 1.244, p < 0.001, η <sup>2</sup> = 0.86; F2(1, 14) = 324.52, MSE = 0.370, p < 0.001, η <sup>2</sup> = 0.96]. The reading time was significantly longer for long-distance sentences (M = 8.63 s, SD = 1.70 s) than for short-distance sentences (M = 5.86 s, SD = 1.13 s). However, there was no significant interaction of clause type and distance (both ps > 0.06).

#### Eye-Movement Data

**Table 4** lists the descriptive statistics for the gaze duration, regression-path duration, and regression rate. These indices are discussed in detail below.

#### Chinese Speakers

#### **Head nouns**

Head nouns were measured using gaze duration, regression-path duration, and regression rate.

Gaze duration. The main effect of clause type on gaze duration was significant [F1(1, 37) = 16.75, MSE = 744, p < 0.001, η <sup>2</sup> = 0.31; F2(1, 14) = 12.08, MSE = 390, p < 0.01, η <sup>2</sup> = 0.46]. The gaze duration was significantly longer for head nouns in SRCs (M = 238 ms, SD = 41 ms) than for those in ORCs (M = 220 ms, SD = 31 ms). The main effect of distance was not significant (both ps > 0.90). The interaction between clause type and distance was also significant in the analysis by participants [F1(1, 37) = 5.64, MSE = 570, p < 0.05, η <sup>2</sup> = 0.13; F2(1, 14) = 3.59, MSE = 306, p = 0.08, η <sup>2</sup> = 0.20]. A simple main effect test showed that the gaze duration was significantly longer for Head nouns in long-distance SRCs (M = 243 ms, SD = 39 ms) than for those in long-distance ORCs (M = 215 ms, SD = 26 ms)

*L, long distance between the gap and the HN; S, short distance between the gap and the HN; N/A, not acquired.*

[F1(1, 74) = 21.56, MSE = 657, p < 0.001, η <sup>2</sup> = 0.23; F2(1, 28) = 14.88, MSE = 348, p < 0.001, η <sup>2</sup> = 0.35; see **Figure 2**].

Regression-path duration. The main effect of clause type on regression-path duration was significant [F1(1, 37) = 69.01, MSE = 14, 662, p < 0.001, η <sup>2</sup> = 0.65; F2(1, 14) = 56.97, MSE = 6828, p < 0.001, η <sup>2</sup> = 0.80]. The regression-path duration was significantly longer for head nouns in SRCs (M = 503 ms, SD = 164 ms) than for those in ORCs (M = 340 ms, SD = 101 ms). The main effect of distance was not significant (both ps > 0.30). The interaction between clause type and distance was also significant [F1(1, 37) = 21.85, MSE = 10, 461, p < 0.001, η <sup>2</sup> = 0.37; F2(1, 14) = 38.42, MSE = 2629, p < 0.001, η <sup>2</sup> = 0.73]. A simple main effect test showed that the regressionpath duration was significantly longer for head nouns in longdistance SRCs (M = 535 ms, SD = 184 ms) than for those in long-distance ORCs (M = 294 ms, SD = 72 ms) [F1(1, 74) = 87.66, MSE = 12, 561, p < 0.001, η <sup>2</sup> = 0.54; F2(1, 28) = 93.73, MSE = 4728, p < 0.001, η <sup>2</sup> = 0.77]. The regressionpath duration was significantly longer for head nouns in shortdistance SRCs (M = 472 ms, SD = 134 ms) than for those in short-distance ORCs (M = 387 ms, SD = 105 ms) [F1(1, 74) = 11.09, MSE = 12, 561, p < 0.01, η <sup>2</sup> = 0.13; F2(1, 28) = 9.90, MSE = 4728, p < 0.01, η <sup>2</sup> = 0.26]. The regression-path duration was significantly longer for head nouns in long-distance SRCs (M = 535 ms, SD = 184 ms) than for those in short-distance SRCs by items (M = 472 ms, SD = 134 ms) [F1(1, 74) = 5.15, MSE = 14, 339, p = 0.03, η <sup>2</sup> = 0.07; F2(1, 28) = 10.35, MSE = 3328, p < 0.01, η <sup>2</sup> = 0.27]. The regressionpath duration was significantly longer for head nouns in shortdistance ORCs (M = 387 ms, SD = 105 ms) than for those in long-distance ORCs (M = 294 ms, SD = 72 ms) [F1(1, 74) = 11.41, MSE = 14, 339, p < 0.01, η <sup>2</sup> = 0.13; F2(1, 28) = 20.92, MSE = 3328, p < 0.001, η <sup>2</sup> = 0.43] Regardless of the sentence distance, the regression-path duration was significantly longer for head nouns in SRCs than for those in ORCs (all ps < 0.01; see **Figure 3**).

Regression rate. The main effect of clause type on regression rate was not significant (both ps > 0.10), as were the main effect of distance (both ps > 0.05) and the interaction between clause type and distance (both ps > 0.80).

The results for head nouns showed that gaze duration and regression-path duration on SRCs were longer than those on ORCs. Hence, the results generally suggested an ORC preference for Chinese speakers.

#### **Embedded verbs**

Embedded verbs were measured using gaze duration and regression rate. Note that the measure of regression-path duration was not used since the positions of the embedded verbs in the two types of RCs are different. In particular, the embedded verb of SRC is in sentence-initial position so that its regression time may be underestimated. Thus, the indicator regression-path duration involving regression time was excluded for the analysis of embedded verbs.

Gaze duration. The main effect of clause type on gaze duration was significant [F1(1, 37) = 19.98, MSE = 2819, p < 0.001, η <sup>2</sup> = 0.35; F2(1, 14) = 84.35, MSE = 202, p < 0.001, η <sup>2</sup> = 0.86]. The gaze duration was significantly longer for embedded verbs in ORCs (M = 274 ms, SD = 51 ms) than for those in SRCs (M = 236 ms, SD = 55 ms). However, there was no significant main effect of distance or significant interaction of clause type and distance (all ps > 0.10).

Regression rate. The main effect of clause type on regression rate was not significant (both ps > 0.10), as was the main effect of distance (both ps > 0.30). However, the interaction between clause type and distance was significant [F1(1, 37) = 6.75, MSE = 0.018, p < 0.05, η <sup>2</sup> = 0.15; F2(1, 14) = 4.59, MSE = 0.005, p = 0.05, η <sup>2</sup> = 0.25]. A simple main effect test showed that the regression rate was marginally significantly longer for embedded verbs in long-distance SRCs (M = 0.70, SD = 0.28) than for those in short-distance SRCs in the analysis by participants (M = 0.62, SD = 0.30) [F1(1, 74) = 5.54, MSE = 0.021, p = 0.02, η <sup>2</sup> = 0.07; F2(1, 28) = 1.03, MSE = 0.011, p = 0.32, η <sup>2</sup> = 0.04; see **Figure 4**].

The results for embedded verbs showed that gaze duration on ORCs was longer than that on SRCs. The interpretation of such finding will be particularly discussed in Section ORC Processing Preference.

#### Japanese Speakers

#### **Head nouns**

Head nouns were measured using gaze duration, regression-path duration, and regression rate.

Gaze duration. The main effect of clause type on gaze duration was not significant (both ps > 0.20), as was the main effect of distance (both ps > 0.05). However, the interaction between clause type and distance was significant [F1(1, 32) = 4.56, MSE = 2393, p < 0.05, η <sup>2</sup> = 0.13; F2(1, 14) = 7.69, MSE = 605, p < 0.05, η <sup>2</sup> = 0.35]. A simple main effect test showed that the gaze duration was significantly longer for head nouns in long-distance SRCs (M = 370 ms, SD = 70 ms) than for those in long-distance ORCs (M = 341 ms, SD = 65 ms) [F1(1, 64) = 5.86, MSE = 2401, p < 0.05, η <sup>2</sup> = 0.08; F2(1, 28) = 5.29, MSE = 1516, p < 0.05, η <sup>2</sup> = 0.16]. The gaze duration was significantly longer for head nouns in short-distance ORCs (M = 371 ms, SD = 76 ms) than for those in long-distance ORCs [F1(1, 64) = 7.26, MSE = 2033, p < 0.01, η <sup>2</sup> = 0.10; F2(1, 28) = 10.94, MSE = 568, p < 0.01, η <sup>2</sup> = 0.28; see **Figure 5**].

Regression-path duration . The main effect of clause type on regression-path duration was significant [F1(1, 32) = 20.14, MSE = 27, 567, p < 0.001, η <sup>2</sup> = 0.39; F2(1, 14) = 20.43, MSE = 14, 430, p < 0.001, η <sup>2</sup> = 0.59]. The regression-path duration was significantly longer for head nouns in SRCs (M = 603 ms, SD = 253 ms) than for those in ORCs (M = 473 ms, SD = 152 ms). The main effect of distance was not significant (both ps > 0.90). The interaction between clause type and distance was also significant [F1(1, 32) = 8.10, MSE = 24, 939, p < 0.01, η <sup>2</sup> = 0.20; F2(1, 14) = 12.80, MSE = 7446, p < 0.01, η 2 = 0.48]. A simple main effect test showed that the regression-path

duration was significantly longer for head nouns in long-distance SRCs (M = 642 ms, SD = 293 ms) than for those in longdistance ORCs (M = 434 ms, SD = 133 ms; [F1(1, 64) = 27.17, MSE = 26, 253, p < 0.001, η <sup>2</sup> = 0.30; F2(1, 28) = 33.15, MSE = 10, 938, p < 0.001, η <sup>2</sup> = 0.54; see **Figure 6**].

Regression rate. The main effect of clause type on regression rate was not significant (both ps > 0.05), as were the main effect of distance (both ps > 0.60) and the interaction between clause type and distance (both ps > 0.10).

The results for head nouns showed that gaze duration and regression-path duration on SRCs were longer than those on ORCs. The results generally suggested an ORC preference for Japanese speakers.

\*\**p* < 0.01.

\*\*\**p* < 0.001.

#### **Embedded verbs**

Embedded verbs were measured using gaze duration and regression rate.

Gaze duration. The main effect of clause type on gaze duration was significant [F1(1, 32) = 8.23, MSE = 14, 339, p < 0.01, η <sup>2</sup> = 0.20; F2(1, 14) = 15.87, MSE = 2754, p < 0.01, η <sup>2</sup> = 0.53]. The gaze duration was significantly longer for embedded verbs in SRCs (M = 406 ms, SD = 132 ms) than for those in ORCs (M = 346 ms, SD = 73 ms). However, there was no significant main effect of distance or significant interaction between clause type and distance (all ps > 0.30).

Regression rate. The main effect of clause type on regression rate was significant [F1(1, 32) = 6.80, MSE = 0.033, p < 0.05, η <sup>2</sup> = 0.18; F2(1, 14) = 42.31, MSE = 0.002, p < 0.001, η 2 = 0.75]. The regression rate was significantly higher for embedded verbs in SRCs (M = 0.78, SD = 0.18) than for those in ORCs (M = 0.70, SD = 0.19). However, there was no significant main effect of distance or significant interaction between clause type and distance (all ps > 0.20).

The results for embedded verbs showed that gaze duration on SRCs was longer than that on ORCs and regression rate for SRCs was higher than that for ORCs. The results generally suggested an ORC preference for Japanese speakers.

Taken together, the results comparing (1) SRC and ORC processing in the long-distance conditions and (2) SRC and ORC processing in the short-distance conditions are summarized in **Table 5**.

The overall results, as shown by the indicators in **Table 4**, suggested that the Japanese group revealed an ORC preference. Similarly, the Chinese group demonstrated an ORC preference, except for the gaze duration of embedded verbs, which will be discussed in next section.

#### DISCUSSION

In this study we used an eye-tracking technique to explore the difficulty experienced by Japanese learners when they are processing Chinese RCs. Overall, the results showed that ORCs were easier to process for Japanese CSL learners, which is similar to the pattern exhibited by Chinese speakers in terms of processing asymmetry. Our findings were consistent with the predictions of accounts based on the LDH, but not those of the NPAH and SDH. In this section we discuss the findings under the theoretical framework of RC processing in order to address our research questions, and then consider the implications for L2 sentence comprehension.

#### ORC Processing Preference

The results generally suggest an ORC preference for both the Chinese speakers and Japanese CSL learners. For the Chinese speakers, an ORC preference was evident from the following three results: (1) the gaze duration for head nouns in ORCs was shorter than that in SRCs, (2) the gaze duration for head nouns in long-distance ORCs was shorter than that in long-distance SRCs, and (3) the regression-path duration for head nouns in ORCs was shorter than for those in SRCs. The two indicators—gaze duration and regression-path duration—can reflect the initial and later stages of sentence processing, respectively. On the other hand, although the gaze duration for embedded verbs in ORCs was longer than for those in SRCs, we noticed that the Chinese speakers skipped around 63.3% of the embedded verbs in SRCs. It seems that the components in the sentence-initial position tend to be skipped. The finding that the gaze duration for embedded verbs in ORCs was longer than for those in SRCs may be due to the skipping rate being higher for the sentence-initial embedded verbs in SRCs. Hence, the overall results of the eye-movement data from Chinese speakers indicate that ORCs were easier to process than SRCs.

As for the Japanese CSL learners, their processing pattern also demonstrated an ORC preference, which can be observed from the following five findings: (1) the gaze duration for head nouns in long-distance ORCs was shorter than that in long-distance SRCs, (2) the regression-path duration for head nouns in ORCs was shorter than for those in SRCs, (3) the regression-path duration for head nouns in long-distance ORCs was shorter than for those in long-distance SRCs, (4) the gaze duration for embedded verbs in ORCs was shorter than for those in SRCs, and (5) the regression rate for embedded verbs in ORCs was lower than for those in SRCs. These results showed that Japanese CSL learners spent a shorter time on head nouns in ORCs in the initial reading (as reflected by the shorter gaze duration) and regression process (as reflected by the shorter regression-path duration), and they spent a shorter time on embedded verbs in ORCs in the initial reading process (as reflected by the shorter gaze duration) as well as in the regression process (as reflected by the lower regression rate). Thus, these results suggest an ORC preference for the Japanese CSL learners.

#### TABLE 5 | Summary Table: results of clause type, and clause type × distance.

*The results comparing (1) short-distance and long-distance SRC processing and (2) short-distance and long-distance ORC processing are NOT presented here. The symbol ## indicates that the significant result here (SRC-L* > *SRC- S) is not relevant to the discussion on the interaction between clause type and distance.*

In summary, the overall results from the two language groups suggest that the two groups exhibited a similar pattern in terms of processing asymmetry; that is, a tendency toward ORC preference. The finding of an ORC preference was inconsistent with the prediction of the NPAH, which proposes that it is easier to relativize the subject than the object across languages. Chinese RC processing seems to be language-specific. In addition, consider the two hypotheses (LDH and SDH), which focus on gap–filler dependencies in RCs. Specifically, the LDH proposes that the distance between a filler and its gap is determined by the linear/temporal distance, while the SDH emphasizes the role of the hierarchical phrase-structural distance between the filler and the gap. The predictions of the two hypotheses diverge in the processing asymmetry of Chinese RCs since the LDH and SDH use different methods to calculate the gap–filler distance. In other words, in the case of Chinese RC processing, the LDH would predict an ORC reference while the SDH would predict an SRC preference. Thus, our results provide solid evidence in support of the LDH.

### L1 and L2 Processing of Chinese RCs

In an attempt to further understand the relationship between L1 and L2 processing of Chinese RCs, we compared the processing patterns of Chinese speakers and Japanese CSL learners. In terms of processing asymmetry, both the Chinese and Japanese groups generally exhibited an ORC preference. This ORC preference in both the L1 and L2 groups supports the LDH, which indicates that the syntactic structure of Chinese plays a crucial role. On the one hand, the Chinese group exhibited an ORC preference, which can probably be attributed to the syntactic structure of RCs in Chinese, which is a head-initial language with a headfinal RC construction. The tendency toward ORCs being easier to process implies that the processing difficulty can be reflected by the linear distance between the gap and the filler. In the structure of a Chinese RC, the linear distance between the gap and the filler is shorter in ORCs than in SRCs, and therefore the tendency toward an ORC preference suggests an apparent effect of linear distance on Chinese RC processing asymmetry. Our finding of an ORC preference for Chinese speakers concurs with those of previous studies (Hsiao and Gibson, 2003; Hsu and Chen, 2007; Lin and Garnsey, 2011; Gibson and Wu, 2013). On the other hand, our finding that the Japanese group also exhibited an ORC preference indicated that the syntactic structure of the target language (i.e., Chinese) was a determining factor in the RC processing. Recall that an SRC preference appears in the L1 processing of Japanese RC (Ueno and Garnsey, 2008), whereas an ORC preference was found in the L2 processing of Chinese RCs in the current study. If the NPAH—which proposes that the subject is easier to relativize than the object—holds in the RC processing of CSL, then Japanese learners will exhibit an SRC preference. Also, the SDH predicts that Japanese CSL learners will show an SRC preference since the structural distance between the gap and the filler in SRCs is shorter than in ORCs. However, the current results showed that Japanese CSL learners demonstrated an ORC preference in the processing of Chinese RCs, as did the Chinese speakers. The processing asymmetry exhibited by Japanese CSL learners was similar to that of Chinese speakers. Thus, we argue that it is the syntactic structure of the target language (i.e., Chinese) that influences how RCs are processed by Japanese CSL learners.

### The Effect of Modifiers

It is worth mentioning the interesting finding that both the L1 and L2 groups spent less time on the head nouns in the longdistance ORCs than on those in the short-distance ORCs. For the L1 group, the regression-path duration for the head nouns in long-distance ORCs was shorter than for those in shortdistance ORCs. Also, for the L2 group, the gaze duration for the head nouns in long-distance ORCs were shorter than for those in short-distance ORCs. Together these results indicate that it was easier to process the head nouns in long-distance ORCs than those in short-distance ORCs. This finding contrasts with our expectation that the head noun in a long sentence would take a longer time to process than that in a short sentence, because in the long-distance sentence there are more antecedent elements before the head noun, which is assumed to consume more cognitive resources. Counterintuitively, it was found that the head noun in the long-distance ORCs had a shorter processing time, and we speculate that this is because the modifiers for the head nouns in long-distance ORCs can provide information to help readers predict the upcoming head nouns. The modifiers of head nouns in long-distance ORCs seem to better facilitate the processing of head nouns. This finding therefore, suggests how modifiers influence sentence processing.

### CONCLUDING REMARKS

Most of the previous studies on Chinese RCs have focused on processing by L1 speakers, and few have considered the syntactic comprehension of L2 speakers. The current study employed an eye-movement technique to investigate the RC processing by Japanese CSL learners. The eye-movement data reflecting both gaze duration and regression patterns—revealed that Japanese CSL learners and Chinese speakers have a tendency toward ORC preference. From a theoretical perspective, this ORC preference in processing Chinese RCs supports the prediction of the LDH that the key determinant of RC difficulty is the length of the gap from the head noun with which it is associated; that is, the linear distance between the gap and the filler. From an empirical perspective, these findings indicate that L1 and L2 speakers both demonstrate a tendency toward ORC preference, which suggests that the syntactic structure of RCs in Chinese is a dominating factor. The processing of Chinese RCs is language-specific in that it has a mixed pattern of a head-initial language with a head-final RC structure, constructing a shorter filler-gap distance in ORCs than that in SRCs, which perhaps makes ORCs easier to process than SRCs. In conclusion, this research expands our understanding of RC processing from L1 speakers to L2 learners of Chinese, and should provide a useful basis for further studies on the L2 processing of Chinese RCs with evidence from typologically different languages.

### ACKNOWLEDGMENTS

This research is partially supported by the "Aim for the Top University Project" and "Center of Learning Technology for Chinese" of National Taiwan Normal University (NTNU),

### REFERENCES

sponsored by the Ministry of Education, Taiwan, R.O.C. and the "International Research-Intensive Center of Excellence Program" of NTNU and Ministry of Science and Technology, Taiwan, R.O.C. under MOST 104-2511-S-003 -012 -MY3; MOST 104- 2511-S-003 -018 -MY3.

from eye-movement data. J. Psychol. Res. doi: 10.1007/s10936-015-9394-y. [Epub ahead of print].

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Sung, Tu, Cha and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Early literacy experiences constrain L1 and L2 reading procedures

#### *Adeetee Bhide\**

*Department of Psychology, Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA*

Computational models of reading posit that there are two pathways to word recognition, using sublexical phonology or morphological/orthographic information. They further theorize that everyone uses both pathways to some extent, but the division of labor between the pathways can vary. This review argues that the first language one was taught to read, and the instructional method by which one was taught, can have profound and long-lasting effects on how one reads, not only in one's first language, but also in one's second language. Readers who first learn a transparent orthography rely more heavily on the sublexical phonology pathway, and this seems relatively impervious to instruction. Readers who first learn a more opaque orthography rely more on morphological/orthographic information, but the degree to which they do so can be modulated by instructional method. Finally, readers who first learned to read a highly opaque morphosyllabic orthography use less sublexical phonology while reading in their second language than do other second language learners and this effect may be heightened if they were not also exposed to an orthography that codes for phonological units during early literacy acquisition. These effects of early literacy experiences on reading procedure are persistent despite increases in reading ability.

#### *Edited by:*

*Shelia Kennison, Oklahoma State University, USA*

#### *Reviewed by:*

*Rachel Helen Messer, Oklahoma State University, USA Ramesh Kaipa, Oklahoma State University, USA*

#### *\*Correspondence:*

*Adeetee Bhide, Office 649, Learning Research and Development Center, 3939 O'Hara Street, Pittsburgh, PA, USA<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Language Sciences, a section of the journal Frontiers in Psychology*

*Received: 02 April 2015 Accepted: 10 September 2015 Published: 02 October 2015*

#### *Citation:*

*Bhide A (2015) Early literacy experiences constrain L1 and L2 reading procedures. Front. Psychol. 6:1446. doi: 10.3389/fpsyg.2015.01446* Keywords: orthographic depth hypothesis, whole word, phonics, ESL, word recognition

### Introduction

Models of word reading have broadly identified two pathways to word recognition: first accessing pronunciation or first accessing meaning. Everyone uses both pathways to some extent while reading, but the division of labor between them (i.e., *reading procedure*) can vary depending on the word type, context (Besner and Smith, 1992), the early literacy experiences of the individual, etc. In this review, I demonstrate that early literacy experiences have a profound effect on reading procedure. I begin by briefly reviewing differences between orthographies and models of word recognition. I then demonstrate the first language (L1) persistency effect, that effects of L1 orthographic transparency and instructional method are measureable, not only in beginning readers, but also in highly skilled adult readers. Finally, I demonstrate the L2 persistency effect, that that early literacy experiences are able to exert an effect even while one is learning to read a second language, and that these effects remain with increasing L2 proficiency. Although much work has been done on the effect of instructional method on reading procedure (Connelly et al., 2009) and on the effect of L1 transparency on both L1 (Katz and Frost, 1992) and L2 reading procedure, this review is unique in that it brings together these three lines of research into one integrated framework.

#### Transparency

Writing systems are defined by the phonological grain size that each graph represents (see **Table 1**). Alphabetic orthographies, such as English, Serbo-Croatian, Korean1 , Russian, German, and French, have graphs that code for phonemes. Alphasyllabic orthographies, such as Hindi, Marathi, and Thai, have graphs that code for syllables but subcomponents of the graphs code for phonemes. Abjads (e.g., Hebrew, Persian, and Arabic) are similar to alphasyllabaries but some2 vowel subcomponents are typically excluded in text. Syllabic orthographies, such as Japanese hiragana and katakana (collectively called kana), have graphs that code for syllables. Finally, morphosyllabic orthographies, such as Chinese and Japanese kanji3 , have graphs that code for morphemes.

3Note that Japanese kanji is not, strictly speaking, morphosyllabic. Most kanji characters have two readings, on and kun. The on-reading is the Chinese pronunciation whereas the kun-reading is the Japanese pronunciation. Although the on-reading is monosyllabic, the kun-reading may be multisyllabic. Furthermore, because kanji graphs have multiple pronunciations, there is low character-phonological unit consistency (unlike Chinese).

Phonological transparency refers to how systematically a given graph maps onto a given phonological unit and vice versa (see **Table 1**). Although languages with the same writing system can vary in terms of transparency, transparency is not independent of writing system. Alphabets range from highly transparent (e.g., Serbo-Croatian) to moderately opaque (e.g., English). Note that grapheme-phoneme and phoneme-grapheme consistencies are not necessarily equivalent; for example, French and German have higher grapheme-phoneme consistency than phonemegrapheme consistency (Deacon et al., in press; Landerl, in press).

Alphasyllabaries have high graphemic subcomponentphoneme consistency; graphemic subcomponents typically map onto only one phoneme. There is less phoneme-graphemic subcomponent consistency because the schwa vowel is inconsistently represented (Bhide et al., 2013). Furthermore, the visual form of a graphemic subcomponent may change depending on other subcomponents in the graph. Syllabaries tend to be highly transparent. The vowelized versions of abjads are highly transparent. In the unvowelized form, the grapheme-phoneme correspondences are highly transparent4 . However, some vowel phonemes are not orthographically represented, so the phoneme-grapheme correspondences are

TABLE 1 | The trade-off between phonology and morphology for the word "money" in various orthographies.

<sup>1</sup>Unlike other alphabets, Korean uses a non-linear graph arrangement. Also, note that although Korean Hangul is alphabetic, Korean occasionally uses some Chinese characters as well (Taylor and Taylor, 1995).

<sup>2</sup>In unvowelized Hebrew, almost all vowels are orthographically unexpressed. Two graphs can, in certain contexts, express vowels, however, these graphs also express consonants (Frost, 2012). In unvowelized Arabic, long vowels are orthographically expressed but short vowels are not (Fender, 2008a).

<sup>4</sup>In Hebrew, some diacritical marks are used to distinguish consonants. These diacritical marks are excluded in the unvowelized form, making the consonants slightly ambiguous (Frost and Bentin, 1992).

highly opaque. Furthermore, the visual forms of graphs can change based on word position (Saiegh-haddad, in press).

In Chinese, a morphosyllabary, 80–90% of characters are made up of two components, a phonetic and semantic radical, which provide a cue to the character's pronunciation and meaning, respectively (Kang, 1993 as cited in Li and McBride-Chang, 2014) (see **Figure 1**). However, a given phonetic radical can cue for multiple pronunciations and the same syllable can be cued by multiple phonetic radicals. Therefore, at the character level, morphosyllabaries are so highly opaque that they are considered an outlier orthography. However, multi-character, multi-syllabic words are highly transparent; each character typically has one pronunciation and represents one syllable in the word.

Opacity can stem from multiple sources: some phonemes may not be represented in the text (in the case of Hebrew) or multiple graphemes may correspond to the same syllable (in the case of Chinese). Readers of Hebrew must rely heavily on context to disambiguate the many homographs whereas readers of Chinese must have highly specified orthographic knowledge to distinguish between homophonic characters.

Opacity does not necessarily make an orthography more difficult to read. There is a trade-off between accurately representing phonological and morphological information and opacity often results from the inclusion of more morphological information at the expense of phonology [Perfetti and Harris (2013); see **Table 1**]. For example, the vowel digraph "ea" is pronounced differently in the words "heal" and "health," making the words opaque. However, this phonological ambiguity makes the semantic similarity more apparent. The opacity also allows English to distinguish between homophones such as "heal" and "heel". In abjads, such as Arabic, sequences of three consonants are used to form roots, which can be combined with a variety of vowels to form families of semantically related words. For example, the root k-t-b is found in the words ketaab (book), kataba (he wrote), and maktaba (library).

These 3-letter roots are more apparent in the unvowelized versions (Ryan and Meara, 1991), another example of how phonological opacity allows for more morphological clarity. In morphosyllabaries, the characters are highly opaque, but provide a great deal of semantic information via the semantic radical. The character system also allows for the disambiguation of the many homophones in Chinese and Japanese.

#### Models of Word Reading

This basic division of labor can be simulated by computational models of word reading. The DRC model (Coltheart et al., 2001) models word naming and posits that there are two possible pathways: (1) the sublexical phonological route that uses lettersound correspondence rules to sound out words and (2) a lexical route that maps the orthographic form onto a stored whole-word phonological representation. The pathways share a common speech output (phoneme) system called the response buffer5 . If both pathways activate the correct phonemic sequence, the response is faster than if the pathways are in competition.

A connectionist alternative to the dual-route model is the triangle model (Seidenberg and McClelland, 1989). The triangle model was initially developed to model word naming, and also claimed that there are two pathways. The first pathway uses statistical regularities of sublexical constituents to activate phonological features, whereas the second maps the orthographic form onto its semantic features, and from there accesses the phonological features. Later, the triangle model was applied to examine how word meaning is computed (Harm and Seidenberg, 2004). Although there are differences between the models, both models posit that words can be read using either sublexical phonological information or morphological information derived from analyzing morphemes as orthographic wholes. This review examines the division of labor between the two pathways.

#### Assessing the Division of Labor

Although many different experimental manipulations can be used to examine reading procedure, there are seven *signature manipulations* that have been used in many studies. These *signature manipulations*, as well as other experimental manipulations/paradigms, are used throughout the review to examine reading procedure.

If the pattern of results outlined below are found in studies, it would suggest that people are heavily relying on the sublexical phonological pathway:

<sup>5</sup>Note that there are other dual route models which posit that all stimuli are processed by either the lexical or sublexical pathway and the pathways do not interact (see Norris and Brown, 1985) but there is considerable evidence against those models (Coltheart et al., 2001).

<sup>6</sup>In linear alphabets that are read from the left to the right.

down the lexical pathway or produce regularization errors (Coltheart et al., 2001). According to the triangle model, the sublexical phonological pathway is slower and less accurate at naming exception words7 (Seidenberg and McClelland, 1989).

(4) *If homophone/pseudohomophone effects are seen.* According to the triangle model, the phonological pathway cannot distinguish between homophones, pseudohomophones, and exemplars (Harm and Seidenberg, 2004). Note that studies employing homophones and pseudohomophones use various paradigms (e.g., lexical decision, backward masking, text reading, definition selection, naming, semantic judgment, spelling recognition, etc.), but share an underlying theoretical logic.

In contrast, if the pattern of results outlined below is found in studies, it would suggest that people are largely using morphological/orthographic information:

It is important to note that reading procedure is different than reading ability. Different reading procedures entail differing emphases on the two reading pathways. In contrast, reading ability refers to overall differences in reading accuracy and/or speed. This review focuses on reading procedure and hence does not examine whether particular orthographies or teaching methods are associated with higher reading ability. Rather, it examines whether particular orthographies or teaching methods are associated with different reading procedures, and to get a more pure measure of reading procedure, it primarily focuses on studies in which the samples are matched for overall reading ability. For example, differences in non-word reading accuracy are only meaningful when the groups are matched for word reading accuracy. Other measures of reading procedure, such as error type analysis, can give us some information about reading procedure even when reading ability is not matched, but the results should always be interpreted with caution.

### Reading in the L1

#### Transparency of the L1 Orthography

Previous studies suggest that people whose L1s have transparent orthographies use more sublexical phonology while reading than do people whose L1s have opaque orthographies, and that this is true for both beginning and skilled readers. The studies have compared English to more transparent orthographies (e.g., Serbo-Croatian, German, Albanian, Greek, Japanese hiragana, Welsh) or to more opaque orthographies (e.g., Hebrew, Chinese, Japanese kanji). They used signature manipulations, such as lexicality, homophonic/pseudohomophonic status, length, frequency, and semantic priming, to examine reading procedure.

#### Beginning Readers

A comparison between 7 and 9 years old children learning German and English, matched for word reading skill, found that English-speaking children struggled more with reading nonwords aloud than did German-speaking children. Because the children were also matched for years of schooling, this introduced age as a possible confounding factor (Wimmer and Goswami, 1994). However, the results are robust as another study was able to find the same effect using a different paradigm and without the age confound; Goswami et al. (2001) found that Germanspeaking children showed more pseudohomophonic interference and a greater length effect on a lexical decision task than did English-speaking children (matched for reading and spelling).

Other studies using larger age ranges (5–15 years old) and more diverse language groups (Welsh, Albanian, Greek, Japanese, and English) have corroborated the general pattern of results described above. These studies did not match the participants as well as the Goswami studies did, making the results of each individual study less convincing. However, taken as a whole, the research does suggest an effect of orthographic transparency on reading procedure. The studies found a stronger relationship between word length and naming time in readers of transparent as compared to opaque orthographies (Ellis and Hooper, 2001; Ellis et al., 2004). Furthermore, error types vary by orthography. Children reading transparent orthographies were more likely to make mispronunciations that result in non-words (e.g., saying "polical" for "political"), which is consistent with a phonological assembly strategy. In contrast, children reading opaque orthographies were more likely to make whole word substitution errors (e.g., saying "computer" for "complete"), which is consistent with a reading strategy that attempts to map the whole visual form onto a lexical entry (Ellis and Hooper, 2001; Spencer and Hanley, 2003; Ellis et al., 2004). However, as mentioned above, there are some problems with matching participants. Primarily, the participants in these studies were not matched for reading ability; children reading transparent orthographies had higher word reading scores than those reading more opaque orthographies. Hence, it is possible that these differences in reading procedures would diminish when using ability-matched samples. Furthermore, although the participants in the Ellis and Hooper (2001) and Spencer and Hanley (2003) studies comparing English and Welsh speaking students were relatively well matched demographically8 , the participants in the

<sup>7</sup>Especially low frequency exception words.

<sup>8</sup>Ellis and Hooper (2001) matching criteria: the students all lived in the Wrexham area of Wales, their schools were all in similar in terms of catchment area, classroom size and teaching method, the students were all in Year 2, the students were matched in terms of math ability. Spencer and Hanley (2003) matching criteria: the students were in local education authority schools in Denbighshire, North Wales, the students were all in Year 2, the schools used phonics to teach literacy.

Ellis et al. (2004) study comparing English, Japanese, Greek, and Albanian speaking students were not well matched in terms of recruiting and testing procedures as well as cognitive abilities.

#### Skilled Readers

In addition to the effects of orthographic transparency on beginning readers, as detailed above, effects of orthographic transparency have also been found among skilled readers, providing evidence for the L1 persistency effect. Readers of more transparent orthographies tend to read non-words more accurately and are less affected by lexicality on their naming reaction times (RTs) than are readers of more opaque orthographies. Furthermore, semantic primes during naming tasks benefit readers of more opaque orthographies to a greater degree than readers of transparent orthographies (Katz and Feldman, 1983; Frost et al., 1987).

Another way of measuring reading procedure is by forcing strategy changes. Frost et al. (1987) had undergraduate students perform a naming task with priming. In Hebrew, naming was significantly slowed when the prime was a non-word. A smaller effect in the same direction was found for English, but no effect was found for Serbo-Croatian. In another experiment, participants were asked to name words and non-words as quickly as possible. The authors varied the proportion of non-words within the lists. Hebrew speakers were significantly less accurate when there was a high proportion of non-words in the list, a trend in the same direction was seen with English speakers, whereas no effect was seen for Serbo-Croatian speakers. Nonword primes and high proportions of non-words force people to use the sublexical phonological pathway. Hebrew readers are accustomed to using the morphological pathway, and the forced strategy change slows them down. In contrast, Serbo-Croatian readers typically use phonological information, so no strategy change is needed.

The Frost et al. (1987) study demonstrated that readers of shallow orthographies use phonology to identify a word, whereas readers of opaque orthographies access phonology once a word is identified. Studies testing English and Chinese participants using a backward masking paradigm came to the same conclusion (Perfetti and Bell, 1991; Perfetti and Zhang, 1991; Perfetti et al., 1992). In the paradigm, a word target is briefly shown, followed by a brief prime, and then a pattern mask. The English-speaking participants were more accurate at identifying the word target when the prime was a pseudohomophone of the word than an orthographic control (e.g., more accurate at identifying "rate" in the condition rate-RAIT-XXXX than in the condition rate-RALT-XXXX). In contrast, priming the target character with a homophonic character did not improve the accuracy of the Chinese participants. The interpretation of these findings is that, in English, the partial products of target identification include pre-lexical phonology, so phonological primes are able to reinstate the partial products. In Chinese, there is no pre-lexical activation of phonology, so there is no effect of the phonological prime.

One possible problem with comparing the aforementioned English and Chinese studies is that the English speaking participants were on average younger (all undergraduates) than the Chinese speaking participants (mostly graduate students). Furthermore, the English tasks used pseudohomophone primes whereas the Chinese tasks used homophone primes. Another English-Chinese comparison used tighter age controls (all undergraduates) and homophones for both languages and also found that English speakers use phonology during word identification whereas Chinese speakers access phonology after word identification. However, in contrast to the studies cited about, this study looked at participants reading texts, rather than individual words. Feng et al. (2001) measured eye movements while participants read texts in which some words were either retained or replaced either by their homophone or an orthographic control (e.g., "creek" was replaced either by "creak" or "creed"). For the English texts, distributional analyses revealed that, for first fixations less than 200 ms, homophones were indistinguishable from the targets, both of which differed significantly from the orthographic controls. This was especially true if the homophone and the original word had a high degree of orthographic overlap and if the target was highly predictable from context. In contrast, when reading Chinese texts, participants had longer first fixation durations for all orthographic mismatches. This difference suggests that, while reading English, participants use phonology, orthography, and context to identify words. In contrast, while reading Chinese, people mainly use orthography.

#### Instructional Method

In addition to orthographic transparency, instructional method can also influence reading procedure. There are numerous instructional philosophies for teaching literacy. Broadly, the instructional methods cluster into two groups; phonology-based methods (such as phonics) and semantics-based methods (such as the whole word method). Phonology-based methods all focus on sounding out words, although the grain size of focus can vary (see Brown and Deavers, 1999; Ziegler and Goswami, 2006; Asfaha et al., 2009; Nag, 2011; Kyle et al., 2013). In contrast, semantics-based methods focus on recognizing whole words and deriving meaning from text. The goal of this section is to compare phonology and semantics based methods to determine if they are associated with different reading procedures. I chose not to compare phonological methods that focus on different grain sizes on the assumption that they all foster a reading procedure that is more dependent on the phonological pathway. However, there is some preliminary evidence from an artificial orthography study that phonological methods focusing on larger grain sizes may foster reading procedures that rely more heavily on the morphological pathway as compared to phonological methods focusing on smaller grain sizes (Hirshorn et al., 2015). There is not enough current research to examine the effect of teaching phonology at different grain sizes on reading procedure in the present review, but it is an interesting area of further inquiry.

Almost all of the studies focusing on reading procedure as an outcome have compared the phonics and whole word instructional methods, so I discuss those in detail. In the phonics method, letter-sound correspondences are introduced in a systematic manner. The whole word method (or book experience in New Zealand), emphasizes communication and comprehension. Words are often memorized from texts proposed by students and letter-sound correspondences are not taught systematically. The majority of studies has been done with English, so I focus on English in this section and then examine how generalizable the conclusions are to other languages further on.

Studies were included in this section only if they compared people who learned English via the phonics and whole word methods and used signature manipulations to examine reading procedure. The signature manipulations used include lexicality, regularity, length, frequency, pseudohomophonic/homophonic status, and imageability manipulations. Many of these studies (see Connelly et al., 2009 for review) compared students from Scotland, whose curriculum stresses phonics instruction, and New Zealand, whose curriculum stresses book experience. Although these studies use a cross-national sample, Scotland and New Zealand have close cultural ties and their educational systems share a common history and educational culture. Therefore, differences found between the samples are likely due to instructional differences. In the systematic phonics approach in Scotland, individual letter-sound correspondences are explicitly taught and students are encouraged to use sequences of such correspondences to sound out unfamiliar words. In New Zealand, almost all of the literacy instruction centers on story texts. Teachers help students understand the meaning of the story, and teach them to recognize words using context cues, initial letters/letter clusters, and analogies to other words. However, they are never taught to sound out successive letters.

#### Beginning Readers

Studies with 6–8 years old children have shown that students taught with a phonics focus typically outperform students taught with a book experience focus on *non-word* reading tasks, even while controlling for word reading ability and various demographic factors such as age, years of schooling, socioeconomic status (SES), word recognition, aural vocabulary, spelling ability, and short term memory (Thompson and Johnston, 2000; Connelly et al., 2001; Thompson et al., 2008). In addition to finding differences in non-word reading accuracy, Connelly et al. (2001) also found differences for *word* reading accuracy. Specifically, children taught with a phonics focus named regular words more accurately, but children taught with a book experience focus named exception words more accurately. The authors also compared the children on their ability to name highly familiar words which they encounter daily (e.g., "the," "he"). The children with phonics instruction read the words significantly slower than the children with the book experience instruction, suggesting that they were less successful at incorporating these words into their sight vocabularies. Connelly (unpublished thesis, as cited in Connelly et al., 2009) found a length effect in naming words with 5–6 years old children from Scotland but not from New Zealand (the children were matched for overall reading accuracy), again suggesting that children with explicit phonics instructions use more phonological recoding while reading.

Johnston and Thompson (1989) compared the performance of 7–8 years old children from Scotland and New Zealand (matched for age and reading ability, differences in vocabulary size were statistically controlled for) on a lexical decision task containing words, pseudohomophones, and non-words. The New Zealand children were equally accurate at rejecting the non-words and pseudohomophones, whereas the Scottish children were more accurate at rejecting the non-words than the pseudohomophones.

Finally, Connelly et al. (2001) found that children taught with a phonics focus are more likely to attempt to sound out unfamiliar words than are children taught with a book experience focus. The 6–7 years old children from Scotland were more likely to produce non-word errors or contextually appropriate errors that retained the pronunciation of at least two of the letters in the original word than were the children from New Zealand.

All of the English studies cited above used a cross-national sample to examine the effect of instructional method, so it is possible that there were some socio-cultural confounds. Two studies were able to minimize confounding factors by comparing instructional method within the same country. Foorman et al. (1991) compared first graders in the U. S. receiving either more or less letter-sound instruction in their school curriculums. The students were matched for reading ability, vocabulary, SES, and ethnic diversity. However, there were a couple of notable differences: the students receiving less letter-sound instruction were drawn from public schools and were on average 2 months older than the students receiving more letter-sound instruction, who were drawn from parochial schools. The authors found that the students receiving more letter-sound instruction showed larger regularity effects while reading aloud.

Whereas Foorman et al. (1991) compared students in the U. S., Landerl (2000) compared students living in England. The study was designed as a follow-up to the Wimmer and Goswami (1994) study cited previously. In the original study, children learning German were compared to children learning English to look for an effect of orthographic transparency. However, the children learning English were taught using a blend of the whole-word and phonics methods, whereas the children learning German were primarily taught using the phonics method. In the followup study, two groups of English-speaking children were used, one that received a mix of whole word and phonics instruction and one that received primarily phonics based instruction. They were compared to German-speaking children who received phonics based instruction. The three groups were equivalent in terms of their word reading. However, for non-word reading, the German-speaking children performed the best, followed by the English-speaking children receiving the phonics based instruction, whereas the English-speaking children receiving the mixed instruction performed the worst.

#### Skilled Readers

The studies cited above demonstrate that instructional method affects the reading procedure of children just beginning to read (5–8 years old), even while controlling for various confounding factors. However, the question that remains is, are these differences in reading procedure stable over time (i.e., can we demonstrate the L1 persistency effect)? It is possible that as reading skill increases, more words are added to sight vocabulary, reducing the need for sublexical phonology. Furthermore, as reading skill increases, all adults, despite how they were taught to read, may settle on the same "optimal" reading procedure. The research (reviewed below) suggests that this is not the case. The ability of specific tasks to detect differences in reading procedure fluctuates with age, but some effect of instructional method on reading procedure is measurable in both adolescence and adulthood.

Johnston et al. (1995) examined whether differences in reading procedure remain constant across adolescence. The participants included both 8 and 11 year-old children from Scotland and New Zealand who were matched on reading ability, vocabulary, chronological age, and ethnicity. They were tested on a lexical decision task that included words, pseudohomophones, and non-words. Unlike the 8 year-olds taught with the book experience method, the 8 year-old children taught with the phonics instruction were less accurate at correctly rejecting the pseudohomophones than the non-words. Both groups of 11-year olds were equally accurate at rejecting pseudohomophones and non-words. Therefore, for this task, the effect of instructional method diminishes with reading experience. The participants also completed a pseudohomophone sentence evaluation task, where they have to judge whether or not a sentence is orthographically correct. The incorrect sentences had one word replaced by either a pseudohomophone (e.g., Can you poast this letter?) or by a control non-word (e.g., She has loast her bag.). Both groups of 8 year-olds were less accurate at evaluating the sentences with a pseudohomophone than the sentences with a control non-word. The 11 year-olds taught with the phonics method (but not the 11 year-olds taught with the book experience method) were also less accurate at evaluating the sentences with a pseudohomophone. Therefore, for this task, the effect of instructional method becomes more apparent with age. Reading instruction also had an effect on the participants' accuracy in a word-meaning task, where participants had to choose the correct definition for presented words. Some of the stimuli were homophonic (e.g., son) and their definition (e.g., child) and the definition of their homophone (e.g., light) were among the choices. Children taught with the phonics method made more errors when choosing the correct definition for the homophonic stimuli than did the children taught using the book experience method. Therefore, on this task, the effects of teaching methodology seem relatively stable during early adolescence.

Thompson et al. (2009) were able to find effects of instructional method even among skilled adults. They compared university students (matched for age and vocabulary) who had learned to read in Scotland and New Zealand on non-word reading. The non-words included irregular, body-consistent stimuli (e.g., thild) where two responses are legitimate, the regular response that is inconsistent with the bodies of all real words and the pronunciation that is consistent with the bodies of words such as "mild". Although the two groups were equally accurate, the Scottish adults were more likely to give regular responses and less likely to give irregular responses than were the New Zealand adults. These results are easiest to explain using the DRC model. The sublexical route uses grapheme-phoneme correspondence rules to sound out a word, without taking into account the greater orthographic context. So, for "thild," the sublexical route would read it as /θIld/. In contrast, the lexical route would activate orthographically similar words, such as "child," "mild," "thick," and "third". These lexical representations would activate their phonological representations which would then activate the phonemes within them. Therefore, /aIld/ and /θ/ would be highly active, producing /θaIld/. Therefore, greater dependence on the sublexical phonological route produces the regular response, whereas greater dependence on the lexical route produces the irregular response. These data are harder to explain with the triangle model because the sublexical route uses statistical regularities that are sensitive to orthographic context. Therefore, the triangle model is more likely to produce irregular responses.

Another result from the same study allows us to more easily interpret reading procedure using both computational models. The participants were asked to name words that varied in terms of both frequency and imageability. The Scottish adults were more likely to make regularization errors while reading low frequency, low imageability words than were the New Zealand adults. These results suggest that, for Scottish adults, the word types that engage the lexical/semantic pathways to the smallest degree were unable to elicit enough support from the lexical/semantic pathways to avoid regularization errors.

#### Summary and Extension to Other Languages

Overall, the research suggests that readers of transparent orthographies (at all levels of reading skill) heavily weight the sublexical pathway while reading. In contrast, readers of more opaque orthographies rely more on morphological/orthographic information. The research on this topic has compared English to more transparent alphabets and syllabaries (German, Serbo-Croatian, Welsh, Albanian, Greek, and Japanese hiragana) and to more opaque abjads and morphosyllabaries (Hebrew, Chinese, and Japanese kanji), and found that the general conclusion held for all of those orthographies. There appear to be no studies using alphasyllabaries, but we can predict that readers of alphasyllabaries heavily weight the sublexical phonology pathway because they are transparent.

Studies of English have suggested that, in addition to transparency, instructional method can also influence reading procedure. Students taught with a phonics-based focus more heavily weight the sublexical phonology pathway, whereas students taught with a book-experience or whole-word focus weight the morphological pathway more heavily. The question that remains is, is this conclusion generalizable to other languages, or is it English specific? The evidence reviewed below suggests that the conclusion is applicable to other opaque orthographies such as Chinese, but not to more transparent orthographies such as French.

Leybaert and Content (1995) compared two French-speaking schools in Belgium (matched for SES) that used different teaching methods and examined which pathway (sublexical phonological or morphological) was more heavily weighted in their students. The authors compared age and ability-matched samples in separate analyses to control for reading experience and reading skill, respectively. Four different reading tests were administered in which different variables were manipulated to tease apart the weightings given to different pathways. The first test manipulated word regularity9 , the second test manipulated both complexity of the grapho-phonological correspondences10 and lexicality, the third test varied the frequency of words and the length of words and pseudowords, and the final test contained words, and homophonic and non-homophonic pseudowords. For all the reading tests, participants had to read the items aloud as quickly as possible.