Discussion Experiment 2

The present experiment investigated L1 gender transfer effects in a sentence processing task, measuring error rates and ERPs. ERPs can give information on the time course of information integration and parsing during language processing. Experiment 1 (cf. chapter 4) showed that, different from the research focus in the present literature, it was not only L1 characteristics that impact transfer processes but that also L2 characteristics, such as gender transparency, play a role.

Therefore, the presence or absence of certain L1 features in the L2 might be important. The central question in this second experiment was whether L1 gender transfer would also be possible into an L2

5.5 Discussion Experiment 2

lacking gender, namely, English. Subjects were native speakers of German who were very low-proficient in their L2 English.

It was hypothesized that gender transfer effects would become apparent in the error rates. The highest error rates were predicted for the pseudocongruent condition, lower error rates were predicted for the correct condition, and the lowest error rates were predicted for the incongruent condition. Regarding ERP components, the focus was on the P600 component as an indicator of the detection of syntactic and morphosyntactic violations (cf. sections 1.3.2 and 1.5.1). The weakest P600 was expected for the correct condition, as this condition was correct in the L2 and should therefore not give rise to any syntactic re-analysis processes. The P600 in response to the pseudocongruent condition was expected to lie in between the correct and incongruent condition, as it was hypothesized to be perceived as somewhat correct due to L1 gender transfer. If gender transfer occurs, the pseudocongruent condition should be processed significantly different from the incongruent condition. If there was no gender transfer, the pseudocongruent condition should be processed similarly to the incongruent condition.

One of the most important findings in the present experiment was that clear L1 transfer effects were obtained in the error rates. As predicted, significantly more grammatical judgment errors were made in the pseudocongruent condition than in the two other conditions. This showed that L1 gender transfer can even take place when the L2 lacks gender. Furthermore, as hypothesized, less errors were observed in the incongruent condition than in the correct condition. This was probably due to the fact that only the incongruent condition can be thought of as free of L1 gender transfer, as only in this condition the second sentence would have been incorrect in both L1 and L2. Surprisingly, however, despite the pattern in the error rates providing such strong evidence for L1 gender transfer, these transfer effects in the error rates were not observed in the ERP patterns. On the contrary, in the P600 component, processing differences were observed between the correct and the two incorrect conditions. No difference between the pseudocongruent and incongruent condition was observed. This effect would have been expected in the case of absence of L1 gender transfer or for a native control group. The P600 seemed “native-like” in distribution, latency and amplitude.

Nevertheless, it is difficult to estimate if this was really a completely “native-like” P600 as it could not be directly compared to a native control group. Furthermore, as predicted for these low-proficient speakers, no LAN was obtained. Since in early stages of language learning L2 speakers sometimes exhibited an N400 instead of a P600, it was speculated that also an N400 could be observed.

However, this was not the case.

As a result, gender transfer was manifested in the error rates but did not become manifest in the ERPs. To shed light on these seemingly contradictory results and in order to investigate proficiency effects, subjects were divided into two groups according to whether they had shown L1 transfer in the error rates or not: the “L1 transfer group” and the “no L1 transfer group”. It was thought that the

“L1 transfer group” would potentially exhibit the hypothesized pattern also in the ERP results.

However, surprisingly, the lower-proficient “L1 transfer group” showed no sensitivity to L2 grammatical violations at all, as no P600 became evident for any of the conditions. The “no L1 transfer group”, on the other hand, showed the same pattern that appeared in the overall analysis, that is, an equally pronounced P600 for the two incorrect conditions. Besides this, no other effects of proficiency were observed. When subjects were divided into two proficiency groups according to their C-test scores, no differences between the two groups were found.

Furthermore, the P600 processing pattern was mirrored in two other components, which are not typically reported for grammatical violations, namely, the P200 and a (sustained) negativity component in response to the verb is, following the critical pronoun. The P200 does not belong to the well-established components in the processing of semantic or syntactic violations, like the N400, P600, LAN, and ELAN. However, in studies investigating perception and memory the P200 seemed to indicate some kind of matching process that compares features of the encountered stimulus with the features of a target stimulus stored in memory. Therefore, it seems reasonable to assume that it could also be sensitive to the matching of an anaphor with its antecedent. However, in studies investigating expectancy and predictability effects the amplitude pattern for the P200 was opposite to the pattern found for the present conditions (Federmeier & Kutas, 2002; Federmeier et al., 2005;

Holcomb et al., 1992). Another possibility is that the more pronounced P200 in response to the incorrect pronouns reflects frequency effects, as stronger P200s are also found for low-frequent words than for high-frequent words (Dambacher et al., 2006; Hauk & Pulvermüller, 2004; Rugg, 1990;

Van Petten & Kutas, 1990) and the pronouns he and she are less frequent in English than the pronoun it. The comparison with ERP patterns of the people filler pronouns renders this interpretation more likely. Yet another possibility is that a combination of congruency and frequency effects is at work here. Regarding proficiency effects, it is important to point out that for the P200 component, the “L1 transfer” and “no L1 transfer group” showed the same processing pattern, that is, the overall pattern found. This demonstrates that even low-proficient subjects, who exhibited L1 transfer in the error rates and no sensitivity to L2 violations in the P600 time window, are possibly sensitive to frequency effects.

Also the occurrence of a negativity in response to the verb is, following the critical pronoun, was not completely clear. The negativity occurred in the time window of 350 - 650 ms after the verb is, which is equal to 950 - 1250 ms after pronoun onset, in response to the two incorrect conditions, compared to the correct condition. In principle, it could be a late manifestation of an N400 component, which appears to be not unusual in the L2 processing literature (Morgan-Short et al., 2010). This seems especially plausible considering the results of Hammer, Jansma, Lamers, and Münte (2005). These authors found a late N400 in response to pronoun violations when the antecedent was a thing, as it was also the case in the present experiment. Furthermore, prior to this late N400, also a P600 had emerged, just as in the present experiment. Taken together with the interpretation of other late or

“sustained” negativities(Gillon Dowens et al., 2010; Jiang et al., 2009; Sabourin & Stowe, 2004, 2008), this negativity could reflect an increased attempt to somehow integrate the encountered incorrect stimulus word or the working memory load associated with it. Most importantly for the present discussion, this late negativity basically reflects the results found for the P600: The incorrect conditions are processed differently from the correct condition, which was observed in the overall analysis as well as in the analysis of the “no L1 transfer group”. Only the lower-proficient “L1 transfer group” showed no difference between the correct and incorrect conditions, just as in the P600 analysis.

Overall, regarding the ERP results, the predictions were not borne out. The pseudocongruent condition was not processed differently from the incongruent condition in any of the observed components. On the contrary, the pseudocongruent condition was processed very similarly to the incongruent condition, but significantly different from the correct condition. As mentioned before, this is the processing pattern that is expected in the absence of L1 gender transfer. Yet, as shown in the error rates, L1 gender transfer did occur. The error patterns were used as a basis for creating two groups, the “L1 transfer group” and the “no L1 transfer group” in order to clarify why the gender

5.5 Discussion Experiment 2

transfer in the error rates did not become apparent in the ERPs and with the addition goal of investigating proficiency effects. In the ERPs, the more proficient “no L1 transfer group” showed a native-like processing pattern across all three components. The “L1 transfer group”, on the other hand, showed no sensitivity to L2 grammatical violations regarding the P600 and late negative component. Here, all conditions were processed in the same way. It seems that some of my low-proficient participants had already developed a sensitivity for this kind of syntactic violations, whereas others still had not. My data suggest that low-proficient speakers go through different phases in the language acquisition process. At least in some cases, L1 gender transfer can be minimized and native-like sensitivity for L2 gender violations can be developed even at a low proficiency level. Regarding the P200 component, however, the same processing differences were observed in the “L1 transfer group” and in the more proficient “no L1 transfer group”, that is, the incorrect conditions (including the less frequent pronouns) were processed differently from the correct condition. This probably shows that even low-proficient speakers exhibit sensitivity to word frequency. Furthermore, when proficiency effects were investigated using C-test scores, no effects were found, neither in the behavioral, nor in the ERP data. So it seemed that using behavioral data as a basis for creating proficiency groups can be a fruitful approach (cf. also Osterhout, McLaughlin, Pitkänen, Frenck-Mestre, & Molinaro, 2006).

Nevertheless, it remains puzzling why no evidence for gender transfer became apparent in the ERPs of the “L1 transfer group” as an online processing measure but only in the behavioral accuracy measure. This seems especially strange because, evidently, the behavioral output is a result of the preceding processing effort. In addition, as stated before, ERPs are thought to be more sensitive than behavioral measures (Luck, 2005; McLaughlin et al., 2004; Tokowicz & MacWhinney, 2005) as they give insights into processing as it unfolds in the brain. Behavioral measures, on the other hand, can only give information on the “end product” of such processing so that what happens prior to the output remains a “black box”. Therefore, since behavioral output was a result of online processing which was measured by ERPs, transfer effects that became apparent in the error rates should also have manifested themselves in the ERPs.

Yet, by and large, the present results are in line with the results of McLaughlin, Tanner, Frenck-Mestre, Valentine, and Osterhout (2010). They found that L2 speakers´ behavioral sensitivity correlated with the P600 amplitude, that is, L2 learners with stronger behavioral sensitivity showed a more robust P600 than those with less behavioral sensitivity, who showed only a small or no P600 (p.

126). Aside from L1 transfer, this is more or less in agreement with the present results: Lower error rates (“no L1 transfer group”) also correlated with a more pronounced P600, while the “L1 transfer group”, exhibiting higher error rates, showed no P600. However, contrary to McLaughlin et al.

(2004), in the present experiment no intermediate stage between no L2 sensitivity and grammaticalization was found. Furthermore, the present results are also in line with the findings of Foucart and Frenck-Mestre (2011, experiment 1), who found that only a part of the native German speakers was sensitive to gender violations in L2 French when nouns had different gender values across languages, while all L2 learners were sensitive to gender agreement violations in the case of gender-congruent nouns (p. 387). In the present experiment, all nouns were gender-incongruent. In addition, Foucart and Frenck-Mestre (2011) concluded that even L2 learners who appear relatively homogeneous in proficiency and other factors might show different learning rates for a specific grammatical structure (p. 388). This is consistent with the results by McLaughlin et al. who state that

“We also show that although learners’ brain responses are quite variable, this variability is highly systematic and can be used to identify meaningful subgroups of learners.” (p. 124). The fact that

individual differences can arise even in groups of homogeneous proficiency is less surprising when one considers that ERP patterns can rapidly change for various reasons, potentially yielding individual differences. For example, as discussed in section 1.4.2, changes in ERPs are possible after only short periods of training, even regarding such difficult structures as grammatical gender (Davidson &

Indefrey, 2009). Furthermore, it has also been found that ERP patterns can suddenly become native-like after a certain time of non-exposure (Morgan-Short, Finger, Grey, & Ullman, 2012). In addition, subtle factors such as the type of instruction (implicit vs. explicit) can have an influence on the native-likeness of ERP patterns (Morgan-Short et al., 2010). In view of all these factors that can affect ERP patterns in L2 processing, it becomes clear that most groups of L2 learners will probably display individual differences in ERPs, no matter how homogeneous they seem to be according to collected metadata.

What do the present results mean in light of the literature discussed in the introduction of the present experiment? Different from Barto-Sisamout, Nicol, Witzel, and Witzel (2009), in the present experiment clear evidence was provided that L1 influences even arise in cases where an L1 morphosyntactic feature is absent in L2. Barto-Sisamout et al. had only obtained a trend towards slower reading times in a comparable condition, that is, a “condition in which morphological marking is required in the L1 but not in the L2” (p. 1) but no significant result. Similar to the results of the pronoun production task conducted by Antón-Méndez (2010), it was shown that L2 speakers can have difficulties with L2 pronoun processing and that L2 pronoun processing was biased by L1.

Consistent with the results of the eye-tracking task by Conklin, Dijkstra, and van Heuven (2007), I also found evidence for gender transfer effects from a gendered language into an ungendered language in a pronoun resolution context. However, contrary to the earlier discussed studies providing evidence for L1 influences in gender processing in ERPs (Foucart & Mestre, 2011; Frenck-Mestre et al., 2009) and evidence for L1 gender transfer in L2 processing (Ganushchak et al., 2011;

Midgley et al., 2007), the present experiment failed to show evidence of L1 gender transfer in an ERP component. Nonetheless, the situation in the experiments of Foucart and Frenck-Mestre (2011, experiments 2 and 3) and Frenck-Mestre et al., (2009) might have been a little different: Only general L1 influences in L2 gender processing instead of congruency effects were observed, as native German speakers proved to be insensitive to L2 gender violations only when these involved plural forms – probably because German lacks gender agreement for plural but not singular forms. Furthermore, similar to the present result, in the study by Ganushchak et al. (2011) also a transfer effect in the error rates was obtained. But here, subjects were in a language-mixing context and put in response conflict, which probably favored the rise of interference effects. In addition, a different ERP component than in the present experiment was investigated. The stimuli used by Midgley et al.

(2007), on the other hand, probably most closely resembled the stimuli used in the present experiment, as also pronouns were used as critical items. However, since participants read for comprehension, error rates did not give insights on possible gender interference processes. A difference between conditions in the P600 time window was found, but the P600 had an unusual anterior distribution. Hence, the results of the present experiment only partly fit into the literature discussed in the introduction. In light of the literature, it is uncertain why the present experiment showed L1 transfer effects in the error rates but not in the ERPs. In each case, one possible explanation, namely, that the participants in the present experiment might have been too high-proficient for L1 transfer effects to arise can be ruled out, since regarding the ERP results, two proficiency groups could be identified: a lower-proficient group showing no sensitivity to L2 gender violations and a higher-proficient group showing a native-like processing pattern. If there was an

5.5 Discussion Experiment 2

intermediate stage using the L1 as a processing basis, it should have become apparent in the ERP data.

Regarding the models discussed in section 1.5, the Declarative/Procedural Model (DP Model) and the Competition Model, only some of their predictions are supported. As explained in section 1.5.1, according to the DP Model, contrary to native speakers, late L2 learners tend to rely on declarative structures instead of procedural structures when processing L2 grammar. The N400 has been hypothesized to indicate the usage of declarative structures, while the LAN has been hypothesized to indicate more automatized processing and the usage of procedural structures (Morgan-Short et al., 2010), depending on left-frontal structures. As mentioned in section 1.3.2, the P600 seems to indicate more controlled processing and structural reanalysis. In the present experiment, no N400 indicating reliance on declarative structures has been obtained, different from experiments showing that in the beginning, learners might tend to rely on declarative structures instead of procedural structures (Guo et al., 2009; McLaughlin et al., 2010; Morgan-Short, Steinhauer, Sanz, & Ullman, 2012; Osterhout, McLaughlin, Pitkänen, Frenck-Mestre, & Molinaro, 2006; Steinhauer, White, &

Drury, 2009; cf. sections 1.3.2 and 1.4.2. Furthermore, no LAN, which is sometimes observed in response to morphosyntactic violations in native speakers and indicates clear reliance on procedural structures, has been observed, either. Since no native control group has been tested, it is not clear whether a LAN would have been observed in native processing. The (possibly) native-like P600 found in the present experiment indicates reliance on L1 neurocognitive processing systems (Morgan-Short et al., 2010) but contrary to the LAN, it does not necessarily indicate reliance on procedural memory (Newman, Ullman, Pancheva, Waligura, & Neville, 2007; Ullman, 2004). Other, previously cited behavioral studies investigating gender agreement had found that late L2 learners were not able to rely on procedural structures (Blom, Polisenska, & Weerman, 2008; Kempe, Brooks, & Kharkhurin, 2010; Sabourin, Stowe, & de Haan, 2006; cf. section 1.5.1). However, in the case of the present data, the conclusion regarding the usage of the declarative vs. procedural memory system remains uncertain. Moreover, the studies conducted by Blom et al. (2008) and Sabourin et al. (2006) are in line with the earlier discussed finding that L2 performance deteriorates with greater agreement distance (cf. section 2.2). Also, Morgan-Short et al., (2010) found a more reliable N400 for local dependencies than for non-local dependencies, which was in line with the DP model stating that local dependencies should be easier to learn in declarative memory than non-local dependencies (p. 182).

In the present study, however, a non-local dependency was tested and a possible native-like P600 was found. Hence, the results of the present experiment suggest that L2 performance does not necessarily have to be worse than native-like at greater agreement distances, even at beginning stages. At least for one subgroup of the participants, performance in behavioral and ERP measures was (almost) native-like. Hence, it might be the case that, when the L2 structure is sufficiently simple, native-like processing is possible, even at low proficiency levels, for L2 grammatical gender and at greater agreement distances.

As stated in the introduction of the present experiment, the Competition Model would predict the most pronounced P600 in the case where a structure is grammatically incorrect in both L1 and L2, as

As stated in the introduction of the present experiment, the Competition Model would predict the most pronounced P600 in the case where a structure is grammatically incorrect in both L1 and L2, as