5.1 Preliminary considerations
5.1.3 Target language use and related concepts
160 production (Gilquin & Granger 2015: 430; Granger 2015: 12). The more informative the metadata, the more informative can be the analysis and the comparison of different learner groups; with the help of statistical measures and approaches, we can determine how this background information affect the language production (Gilquin & Granger 2015: 430).
Possible background information in learner corpus research could be the L1, or further previously acquired languages, age, gender, country of origin, country of current stay, proficiency level, and socio-economic-background, to name just a few.
In summary, with the help of learner corpora, it is possible to understand language acquisition processes. Learner corpus research combines second language acquisition research, corpus linguistics, and also a more applied perspective, i.e. foreign language teaching (Gilquin
& Granger 2015: 428). It is therefore the ideal approach to investigate the current research questions. The reason for all the earlier mentioned biases and limitations that we can currently find in LCR is the still young age of learner corpus research (Gilquin & Granger 2015: 427-429). Therefore, the current study can add to this new research area by investigating the use of tense and aspect in a small learner corpus that includes written and spoken English production data of intermediate second and third language learners.
161 by defining a native speaker and by making claims about the language production of a native speaker, we touch upon another diffuse but at the same time indispensable term, and that is standard. A standard is somehow understood as being the norm, as something accepted, and in this sense, it is the average or the sum of all native speakers’ idiolects (McKay & Brown 2016:
xiv). This definition of a standard is only a superficial one and it will not be looked at in more detail here. The reason why it had to be briefly introduced is that when learner English of a particular group is compared to another group of learners, we make reference to which of the learners behaves more target-like. Hence, we have a certain standard, a certain idealized setting, in mind, which we understand as the preferred realization. Against this background, we compare the performance of the participants with each other.
Apart from the aforementioned obstacles, another critical comment also from McKay and Brown is that “the idealized native speaker standard is impossible for most learners around the world to achieve” (2016: xiv). They explain that more or less everywhere around the world, we find curricula that school children cannot completely fulfill and which, as a result, frustrates teachers and students equally (McKay & Brown 2016: xv). The topic whether it is desirable or even possible to aim at native speaker competence for learners of a foreign language has been and is still currently a matter of debate (McKay & Brown 2016; Seidlhofer 2004). According to Cook, only few learners (if at all) of a foreign language will ever reach a native like status;
thus, we should regard the language of foreign language learners as a distinct system (Cook 1999: 189). Yet, it seems to be the goal in foreign language teaching to aim at making the learners achieve native language competence, which therefore ultimately results in a failure in most of the cases (Cook 1999: 189-199). McKay and Brown (2016) propose a solution to overcome this obstacle; yet, so far, the school systems adhere to the former native speaker target standard that all learners need to achieve.23
Due to the lack of an alternative system, the approach of this study is the following: the texts of the learners of English will be compared to the texts written by native speakers of English. The aim is not to judge or to present the learner English as a deficient variety; yet, we regard native speaker English as a useful source for a comparison. Not only one native speaker but several native speakers performed the task. This way, we make up for a variety of idiolects, which are meant to represent native speaker English in this study. In addition, we did not use expert native speakers, i.e. we did not use educated adults that possess a university degree or even have linguistic expertise. Instead, we rely on English native speakers who are still in the
23 For a detailed discussion about English as an International Language (EIL) see McKay and Brown (2016) and for a perspective on teaching world Englishes and English as a Lingua Franca see Jenkins (2006).
162 process of (formally) acquiring their native language English. They are the same age as the other participants of the study. We briefly come back to this issue in Chapter 6.1.2, when we discuss the participants of this study in more detail. In addition, we rely on the reference grammars Biber et al. (2000), Huddleston and Pullum (2002), and Quirk et al. (1985) as a basis for the analysis and the coding of the learner corpus.
Another crucial choice that had to be made is which variety of English will be chosen as the standard of this study. In general, one could assume that the most widely accepted varieties must be Standard British English and Standard American English. Yet, which standard is the one that is aimed at in the foreign language classroom in school? There is a so-called competition between British English on the one hand and American English on the other hand.
Berns made a claim in 1995, which was reprinted in an edited volume in 2006 (Bolton & Kachru 2006) and could therefore be regarded as being relevant not only in the 1990s but also in the 21st century: “[u]sually English is thought of only as a foreign language – one needed to understand and communicate with the native speakers of that language, e.g. British or American; the instructional goal is to learn British or American English” (1995: 24). Hoffmann explains that in Europe, it was conventionally the Standard British English variety that was seen as the target language and this resulted in teaching material being mostly based on British English (2000: 7). Yet, Hoffman also stresses that Standard American English, due to its omnipresence, is the one that has gained importance and that it is the variety that mostly influences other languages and other English varieties (2000: 7).
This observation accords with what Mair (2013) proposes in his recent model of varieties of English. He classifies standard Englishes into four groups: (i) hyper-central variety (American English), (ii) super-central varieties (British English, Australian English, among others), (iii) central varieties (Irish English, Jamaican English, among others), and (iv) peripheral varieties (Maltese English, Papua New Guinea English, among others) (Mair 2013:
261). There is only one hyper-central variety, namely American English, which is claimed to potentially influence all other varieties (Mair 2013: 261). He specifically stresses that lexical borrowings are predominantly “downward” (i.e. from (i) to (iv)) and that upward borrowings, though possible, are less frequent (Mair 20113: 261-262).
In general, we can assume that a lot of the course materials in schools are based on British and American English and that at the same time, the students are influenced by American English via the internet, music, films, etc. Therefore, both standard varieties will be accepted here. If we considered another learning context, such as university classrooms, the picture could be different. At a university in Berlin, Germany, it was observed that the use of
163 English and the need for using English has changed, due to spending a certain amount of time abroad, traveling, and the increasing use of the internet, among others (Erling 2002: 10).
Students meet situations in which they have to use English quite regularly in their daily lives (Erling 2002: 10). Erling noticed that here, the standard and the use of English is not limited to British or American English but that influences from a wide range of English varieties can be found (2002: 12). Nevertheless, the current study is limited to secondary-school children and it can be assumed that their English performance is mainly affected by British and American English due to the school curriculum. In how far this is changing in the (near) future is not relevant here.
Let us now turn to an even more difficult concept and that is language proficiency. We have already discussed it in Chapter 3.2, mainly from the perspective of balanced or unbalanced proficiency of two languages. In this study, in addition to discussing the status of the two previously acquired languages, we are primarily interested in the proficiency of the foreign language that is currently acquired. Hence, we look at the performance of the students in English and how proficient they are in completing a written and oral assignment. We now combine target-like or standard use with proficiency. This should give us some indication about language acquisition. As was explained earlier, it is not easy to measure acquisition per se; we can only analyze the results of the acquisition process, i.e. their actual performance.
One basic proficiency measure is simply the number of words that are produced (either in written or in oral performance). Vermeer argues that the number of sentences and words increases with increasing competence of that language (2000: 78). Furthermore, lexical diversity increases; hence, we find more infrequent words and more overall lexical variety in language use with increasing competence or proficiency (see for example Milton 2009: 126).
This may not be a perfect measure, yet it qualifies as an approximation. By looking at the number of words produced and by including the token frequency, we have one point of reference when comparing the students. This suffices as a first overview, without regarding grammatical correctness, style, cohesion, and the like. These are of course relevant later on, and we will come back to additional grammatical variables in Chapter 5.3, when we discuss the annotation of the learner corpus.
Moreover, the design of the current study is a cross-sectional approach (see Jarvis &
Pavlenko 2008: 32). This means that two different cohorts, students at the age of 12 and students at the age of 16, performed the same tasks. The language production in these tasks is the basis for the learner corpus. This corpus is not based on production data of one and the same student at measure point A and measure point B. Instead, we rely on an entirely different learner group
164 to estimate progress in language acquisition. It is not a longitudinal study that investigates the actual development of the individual participants; yet, this cross-sectional design, or
“pseudolongitudinal design” allows analyzing learner English at two different points in time and it is possible to refer to a quasi-process (Jarvis & Pavlenko 2008: 37). When it comes to language acquisition, age, or more precisely the time of exposure to that particular language, is a variable that is highly correlated with proficiency (see for example Milton 2009 on proficiency measured with vocabulary size and linguistic diversity). We are interested in the process of language acquisition and the differences between students with differing language backgrounds, and therefore, we need participants that are at varying points in time, i.e. with different proficiency levels. Within this cross-sectional design, we do not only have a particular group of learners, i.e. bilingual learners of English, at two developmental points in time, but we complement this by several monolingual control groups. Hence, we can assess developmental differences between different monolingual learners of English, between three distinct bilingual learners of English, between bilingual and monolingual learners, and we also have access to a native speaker control group. Nonetheless, we are aware that a cross-sectional design is only an approximation and we need to carefully interpret the results and keep in mind that “cross-sectional research tends to be intersubjective” (Jarvis & Pavlenko 2008: 32).
We finish this section by turning our attention to cross-linguistic influence again, more specifically to the identification of cross-linguistic influence. This entire study is centered on cross-linguistic influence and on the identification of the language or languages that act as the source for cross-linguistic influence in additional language acquisition. We follow Jarvis (2000) and Jarvis and Pavlenko (2008) who identified three essential types of evidence that are needed to determine cross-linguistic influence (see Table 13).
Intragroup homogeneity Evidence that the behavior in question is not an isolated incident, but is instead a common tendency of individuals who know the same combination of languages.
Intergroup heterogeneity Evidence that the behavior in question is not something that all language users do regardless of the combinations of L1s and L2 that they know.
Crosslinguistic performance congruity Evidence that a language user’s behavior in one language is motivated by her use (i.e., the way she demonstrates her knowledge) of another language.
Table 13: Evidence for cross-linguistic influence (taken from Jarvis & Pavlenko 2008: 35)
With the current study design, we are able to address all three types described by Jarvis and Pavlenko (2008). First, intragroup homogeneity can be based on features that are specific to one or more language groups in the current learner corpus, yet not for all. We clearly do not say for only one language group, because each group is at least partly overlapping with one other
165 language group and may potentially share certain features with the other group. Hence, identifying homogeneity between two or more groups would not automatically negate cross-linguistic influence. It depends, however, on the combination. Let us consider an example: the Vietnamese-German bilinguals share features with two groups, with the German monolinguals on the one hand, and with the Vietnamese monolinguals on the other hand. Thus, we may detect features that are shared by two of the three groups. One note of caution, we clearly do not want to equate bilinguals with the sum of two monolinguals, and we acknowledge that bilinguals are individuals with an independent language competence (see Franceschini 2016: 100).
Nevertheless, we are convinced that bilingual speakers share at least some language specific properties and concepts with the monolingual speakers of the respective languages. We could then find similarities between the Vietnamese-German bilinguals and the Vietnamese monolinguals or between the Vietnamese-German bilinguals and the German monolinguals. In the latter case, we would expect to find the same pattern also in the other two bilingual groups, because we would then identify German transfer.
Second, intergroup heterogeneity can be assessed, because we have in total seven different groups of learners of English presented in this corpus. This means that the features that we identified as particular for one or more language groups should not be shared by the other language groups. This way we can assure that it is not something that is typical for all learners of English. The large variety of languages involved may help us to draw multiple comparisons to exclude features that are common for all learners of English.
Third, cross-linguistic performance congruity can be demonstrated with features that have a counterpart in one (or more) of the other languages. This would be most clearly visible in a grammatical structure found in the English corpus that is not target-like in English but in one of the other languages. The reverse may also be possible, albeit less clearly identifiable: a structure that works similar in English and another language may also be transferred to English.
However, the existence of such a structure does not necessarily mean that is an instance of cross-linguistic influence. It could also simply mean that the student has successfully acquired this grammatical concept. Hence, it is easier to identify negative transfer (the former) than positive transfer (the latter). To make this a bit more understandable, let us come back to the example from above. This time, we would need to find a property that is shared by the Vietnamese monolinguals and the Vietnamese-German bilinguals but not by any other group.
Remember, this could be either an ungrammatical or non-target-like structure in English, or a structure that these two groups use more frequently in a target-like way, in comparison to the other groups. Hence, we would then have evidence that this feature is related to cross-linguistic
166 influence from Vietnamese and that it is not a general learning step that all learners of English undergo. If, however, the feature is shared by all learners with access to German, we would then argue for transfer coming from German.
Figure 9 represents what has just been explained: it maps out the relations between the individual groups of learners of English. It connects the bilingual participants with two monolingual learner groups and the German monolinguals are in the center, connected to the three bilingual groups.
Figure 9: Interconnectedness of language groups
Furthermore, we once again come back to the claim that bilinguals are not the sum of two monolingual speakers and briefly discuss an important remark by Puig-Mayenco et al. (2018).
When discussing the potential source(s) of transfer in L3 acquisition, the authors state that “we simply cannot take for granted that all L3 learners have acquired all domains of the L2 and thus actually have multiple sources from which transfer selection can obtain” (Puig-Mayenco et al.
2018: 20). This is a crucial point, and this is equally relevant for the current study. In their discussion, Puig-Mayenco et al. (2018) refer to second language learners that acquire this L2 as a foreign language. In our case, both languages of the bilingual heritage speakers can be seen as native languages. Nevertheless, this warning does also apply here, because we cannot be sure either that all grammatical categories of the heritage language are developed in these bilingual speakers. This means that certain properties of the heritage language may not be transferred to English, because the students do not know these grammatical concepts in Russian, Turkish, or Vietnamese. We assured that all participants have at least some knowledge of their heritage language (this was a pre-requisite for being a participant in this study) and the majority indicates
167 to use the heritage language at home with their parents (see more about this in Chapter 6.1.3).
However, we also stressed that one property of heritage speakers is that the heritage language is less developed and less dominant than the language of the environment, in our case German.
We need to keep this in mind when interpreting the results.
As a last point when discussing the identification of cross-linguistic influence on the basis of a learner corpus, we want to refer to an important claim, made by Kortmann (2005:
158-159), that was already briefly discussed in Chapter 4.8. When analyzing learner language, not every mistake or error can be explained with transfer (Kortmann 2005: 158-159). Hence, contrastive analysis, as a way of identifying cross-linguistic influence, is still a useful
“diagnostic tool” which can help to explain errors and language production, but there are numerous other factors that must be taken into account as well (Kortmann 2005: 159).
Nevertheless, we aim at identifying patterns across language groups that account for both positive and negative effects of cross-linguistic influence. We understand here transfer as both positive transfer (i.e. target-like production due to similarities to a previously acquired language) and negative transfer (i.e. non-target-like production due to a property found in a previously acquired language that has a different representation in the target language and is therefore misused in the target language), as was explained above. With the inclusion of additional variables, i.e. background information of the participants, we have further points of reference when analyzing the data (see more in Chapter 6.1). Yet, Jarvis and Pavlenko (2008:
13) rightly stress “that CLI is a highly complex cognitive phenomenon that is often affected by language user’s perceptions, conceptualizations, mental associations, and individual choices”.
What this assumes is that learners are not homogenous (even if they belong to one group and even if they have similar background variables) and that cross-linguistic influence is not the same for every learner in every situation.
After having discussed a number of relevant concepts that will be taken up in the remainder of this study, we now turn our attention to the E-LiPS project. In this next section, we introduce the setting of the study and we discuss already published studies that are based on subsamples of the current data set.
168 5.1.4 E-LiPS project
General comments about the E-LiPS Project
The current study uses data from E-LiPS, a subproject of the Linguistic Diversity Management in Urban Areas (LiMA) Panel Study (LiPS) that was conducted at the University of Hamburg from 2009 until 2013 (Linguistic Diversity Management in Urban Areas, 2009-2013, directed by Peter Siemund and Ingrid Gogolin). The goal of LiPS was to document the linguistic development of multilingual children with a Russian-German, Turkish-German, and Vietnamese-German background. The study focused on the proficiency in the heritage languages and the proficiency in German, the language of the environment and language of instruction in school. E-LiPS was the extension of the study and focused additionally on foreign language acquisition. The hypothesis that led to this investigation was the assumption that the acquisition of a(n) (additional) foreign language is different for monolingual speakers than it is for bilingual speakers. As was outlined in Chapter 2 and in Chapter 3, bilingual speakers can, on the one hand, theoretically resort to more than one language as a source for transfer as opposed to monolingual speakers. On the other hand, bilingual speakers are said to possess more metalinguistic knowledge or to have a greater metalinguistic awareness than monolingual speakers, which should have a positive influence on the acquisition of languages in general.
Different case studies were conducted with the E-LiPS data, to verify these assumptions (Siemund 2019a). The current project also uses the E-LiPS data, yet not only parts of it but the entire data set plus an extension, and it focuses on tense and aspect. The overall aim is, again, to find substantial support for or counterevidence against the aforementioned assumptions.
The E-LiPS project consisted of several different tasks. Each participating student wrote an English text, a narrative, and the older participants wrote in addition to this narrative another text type, namely an instruction for building a boomerang. Apart from participating in this written task, they also took part in an oral exercise; their performance was recorded and transcribed. A learner corpus that is based on these two individual parts, the written narrative and the oral task, was built. A more detailed documentation of the methodology can be found in Chapter 5.2.
Before we turn to the analysis, certain challenges which are known to be challenges in corpus linguistics in general need to be addressed as preliminary considerations before the actual study can be conducted. Gast discusses the issue of classifying semantic categories and
169 acknowledges that often, these coding decisions are based on the subjective interpretation of the researcher which ultimately leads to the negative consequence that “objectivity is compromised” (Gast 2006: 116). Yet, very often, it seems inevitable to make certain decisions in order to answer the research questions and in order to generate a productive outcome (Gast 2006: 116). Then again, one advantage that this study has, in comparison with other corpus analyses, is the fact that the analysis does not consist of the inspection of random texts with an unknown context, but that the students were presented with two carefully chosen picture sequences to which they should write or tell a story. Based on the pictures, it may be at least partially easier to make semantic classifications. Nevertheless, there remain controversial cases that will be discussed in more detail in the following chapters and that must be kept in mind when drawing conclusions.
A further limitation is that information about proficiency in English can only be drawn from two tasks – no additional C-test or similar test to evaluate the language level was conducted. Many comparable studies use testing instruments to evaluate the level of proficiency of their participants according to the Common European Framework of Reference for Languages (CEF or CEFR) (see for example Brehmer & Mehlhorn 2015; Gogolin et al. 2017).
Yet, the goal of this study is not to compare the proficiency levels of the participants but to compare their usage of tense and aspect in a written and an oral task. It could be argued that it is relevant to assess the level of English to compare these texts. Yet, all participants study English in a school setting and it was possible to obtain their school grades (for English, German, and Mathematics). This will be used as a comparative figure.
Some further preliminary considerations concern four studies that analyzed a subset of the entire E-LiPS data set. Based on what Lechner and Siemund (2014a), Siemund and Lechner (2015), Lechner (2016), and Siemund et al. (2018) present, we extended the data set and conducted a more detailed study that looked at the use of tense and aspect. Before we present the details of the current study, we briefly outline what the aforementioned studies reported.
Siemund and Lechner (2014a)
The most relevant of the studies is without doubt Lechner and Siemund (2014a). Their qualitative study investigates the use of tense and aspect marking as well as subject-verb-agreement in a subsample consisting of five 16-year-old students of four different language groups (German monolinguals; Turkish-German, Russian-German, and Vietnamese-German bilinguals). In addition to language background, they include language external factors such as
170 gender, school type,24 and the educational and socio-economic background of the family to investigate in how far these also play a role in the success of acquiring a foreign language or if bilingualism versus monolingualism is a stronger indicator for target-like versus non-target-like use of a foreign language (Lechner & Siemund 2014a: 334). School performance assessment studies, such as PISA in Germany, report a strong correlation between not speaking German at home, but conversing in the heritage language of the family instead, and low performance in school (Lechner & Siemund 2014a: 320). These assumptions are the foundation of their investigation.
First, they coded the data for target-like and non-target-like subject-verb-agreement. In all four groups they found the omission of the third person singular {-s} to be the most typical error (Lechner & Siemund 2014a: 327). They could not detect a statistically significant difference between the groups; this seems to be a problem area among all these learners of English (Lechner & Siemund 2014a: 327). Their expectation that the Vietnamese-German bilinguals perform worst was not met; even though Vietnamese is an isolation language and does not show subject-verb-agreement, no negative transfer in English was visible in the bilingual group (Lechner & Siemund 2014a: 327-328).
In general, they report coding difficulties, because some of the participants used the present tense and others the past tense in their writings. Since in English, subject-verb-agreement is only visible in the third person singular in present tense and in auxiliary verbs and the copula verb be, the interpretation of the data is slightly blurred (Lechner & Siemund 2014a:
238-239). Second, they concentrated on tense morphology and coded again for target-like and non-target-like occurrences (Lechner & Siemund 2014a: 329) and they also counted incorrect tense-switches (Lechner & Siemund 2014a: 330). These turned out to be better indicators, because other than with subject-verb-agreement, both are equally relevant in present and past tenses (Lechner & Siemund 2014a: 331-332). However, no statistically significant differences could be found, only tendencies. Finally, they calculated attainment scores for each participant.
This score was based on textual complexity, lexical richness, overall correctness and length of the text (Lechner & Siemund 2014a: 332-333). Here, the Turkish-German group is clearly at the lowest end of the scale (Lechner & Siemund 2014a: 334).
In the following analysis, they included gender, age of onset for German, the socio-economic index, and the type of school. Interestingly, age of onset had little to no impact; yet
24 There are several distinctive types of high schools in Germany, the university-bound secondary-school track, called ‘Gymnasium’, and the vocational tracks ‘Realschule’, ‘Stadtteilschule’, ‘Gesamtschule’. More on this distinction and its relevance can be found in Chapter 6.1.