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Is A2 in German Better than B2 in French when Reading Danish? The Role of Prior Language Knowledge when Faced with an Unknown Language Karolina Mieszkowska and Agnieszka Otwinowska

Introduction Multilingual language acquisition (MLA), even though undeniably stemming from second language acquisition (SLA), involves a more complex interplay of factors than SLA. Learning an L3-Ln does not involve adding yet another language to our repertoire by means of a habitual and automated process. On the contrary, MLA embraces some unique effects that arise from the interactions among the many languages learnt and the processes of learning them (Cenoz and Genesee, 1998). Research shows that L3-Ln learners frequently make use of all their previously acquired languages (e.g. Cook 2009; Dewaele 2001, 2010; De Angelis 2005; Hammarberg 2001; Jessner 2006; Ringbom 2007; Rothman 2011; Otwinowska-Kasztelanic 2011). Consequently, the directional language transfer from L1 to L2 that predominates at the early stages of SLA becomes quite fuzzy. The more languages there are at the speaker’s disposal, the more complex the interactions between those languages. Additionally, such factors as language typology, individual learner differences and psychotypology come into play, blurring the sources and the directionality of influences across languages. In this chapter, we first touch upon the notion of crosslinguistic influences in language learning, and factors that might influence language activation and use in the case of a multilingual person. Then we pass on to summarizing studies on the role of prior foreign-language knowledge in multilingual language activation and inferencing. The aim of the empirical part is to examine mechanisms employed by multilingual speakers when faced with an unknown language that bears a degree of similarity to the languages they have been acquiring. We also want to find out which languages would be activated and would dominate as the source language for crosslinguistic influences, and what factors would determine the choice of the auxiliary language. Finally, we want to investigate how individual differences (language constellations and cumulative

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Crosslinguistic Influence and Crosslinguistic Interaction

language experience) may influence the process of decoding the text. To this end, we presented a group of Polish advanced users of English (L2) with a relatively difficult text in Danish, a language unknown to them. Apart from English and Polish, the students had different constellations of L3-Ln (Germanic, Romance, and Mixed) and varied cumulative L3-Ln learning experience. We asked the subjects to orally translate the text, commenting on their translations. Then we presented them with an English version of the same text and asked them to judge their translation. The translation and the comments were recorded in the form of verbal protocols. Finally, we drew conclusions concerning the assistance of the typological and psychotypological distance to the crosslinguistic influence in multilingual comprehension as well as individual factors in language activation and choice when faced with a new language to be deciphered.

1 Theoretical background 1.1 Crosslinguistic influences in MLA Since Weinreich (1953) coined the term interference, researchers have tried to describe the processes of mutual influence of languages in the speech of bilinguals and multilinguals. After a few decades, it became apparent that interference is not the best label for the phenomenon. Odlin (1989: 27) established a classic definition of transfer, calling it the influence resulting both from the ‘similarities and differences between the target language and any other language that has been previously (and perhaps imperfectly) acquired’. Odlin’s definition acknowledged the fact that influence may come from all the speaker’s languages and that it may be negative or positive, and that the learner/user of a language may be in fact multilingual, which has paved the way for the study of transfer in the acquisition of more than one language. Sharwood-Smith and Kellerman (1986) proposed the notion of crosslinguistic influence, postulating that transfer was not a satisfying term to combine the whole range of linguistic processes in bilinguals. Crosslinguistic influence (CLI) combines all language contact phenomena – not only the positive and negative transfer, but also interlanguage transfer, reverse transfer (from interlanguage back into NL), interference, borrowing, language loss or language avoidance (Sharwood-Smith and Kellerman 1986: 1). Nowadays, however, both terms are often used interchangeably in language-acquisition studies and they will also be used in this way throughout this chapter. In MLA, transfer gains yet another dimension – the linguistic influence may come from all languages involved. According to Cook’s multi-competence model (1991, 1992) and Herdina and Jessner’s (2002) dynamic model of multilingualism, all the languages of a user/learner are stored together. So, the many languages in one mind form a system whose parts are interrelated in a complex and dynamic way and influence one another. All the languages may also interact during comprehension or production processes (Cook 2009). One of the key findings supporting the fact that languages are interconnected in the mind and that access to languages is non-selective is the so-called cognate facilitation effect obtained in strictly controlled psycholinguistic experiments


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investigating reaction times. In laboratory experiments, cognates, that is, words that share form and meaning across languages, are responded to faster than languagespecific control words. The same effect has been observed in various experimental paradigms dealing with bilingual word recognition in the visual modality (e.g., Dijkstra et al. 2010; Lemhöfer and Dijkstra 2004) and in a range of recognition and production tasks performed by bilinguals, including progressive demasking (Dijkstra, Grainger and Van Heuven 1999), picture naming (Costa, Caramazza and SebastianGalles 2000) and word association (Van Hell and De Groot 1998; Van Hell and Dijkstra 2002). The cognate status of words manifests itself also in experimental research on foreign-vocabulary learning, where cognates turn out to be particularly easy to learn, are accessed faster than non-cognates and are resistant to forgetting relative to noncognate words (De Groot and Van Hell 2005). In the case of bilinguals, cognate effects indicate that during lexical access, the lexicons of both languages known to a bilingual are activated. However, there is also a growing bulk of psycholinguistic evidence for connectivity between the mental lexicons for L1, L2 and L3 (Dijkstra and Van Hell 2003; Lemhöfer, Dijkstra and Michel 2004; Szubko-Sitarek 2012; Tymczyńska 2012; Van Hell and Dijkstra 2002). The cognate facilitation effect has been obtained even when multilinguals situated in an L1 setting performed lexical decision, or wordassociation, tasks in their native language (Van Hell and Dijkstra 2002). If languages are indeed interconnected in the mind, then from the point of language acquisition the conceptualization of transfer should take into account the fact that all of the user’s languages may influence transfer. Thus, De Angelis (2007) proposes a useful new classification of CLI: one-to-one and many-to-one. The former accommodates the already mentioned influence between the source and the target language; the latter, many-to-one or combined CLI, is the simultaneous influence of more than one language upon the target language. It occurs either when two or more languages interact with one another and influence the target language together, or when one language influences another, which in turn influences the language being acquired. De Angelis (2007) concludes that it is research on combined CLI that is essential in defining mechanisms that underlie the use of multiple sources of knowledge, which will allow us to create more precise and comprehensive hypotheses about CLI.

AQ: Please confirm the shortened running head.

1.2 Factors in CLI and language activation In this chapter, we will examine the combined CLI in multilingual subjects faced with an unknown language in its written form. It is assumed that when a new language is being acquired, one or more of the languages at the learner’s disposal may serve as an auxiliary language, promoting intercomprehension (Gibson and Hufeisen 2003; Franceschini 2009). Ringbom (1987: 155) has pointed out that ‘the less the learner knows about the target language, the more he is forced to draw upon any other prior knowledge he possesses’. Proficiency in the source language may also determine the type of CLI to occur. Ringbom (2007) distinguishes between transfer of form and transfer of meaning. The former, relatively superficial in nature, does not require high levels of language proficiency and can come from languages that are less developed. However, transfer-of-form learners may fall into the trap of false friends and deceptively


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similar constructions. In contrast, transfer of meaning requires internalization and automaticity, which only comes with the native or highly proficient language. Here, we would like to find out what factors come to play in the activation of the auxiliary language(s) at the multilingual learner’s disposal. Cenoz (2003b) reports on two groups of such possible factors: first, the characteristics of the languages involved (language typology and factors related to the use of language, e.g., proficiency in the language, frequency and recency of use), then the individual and contextual factors (anxiety, metalinguistic awareness, the nature of the task, characteristics of the interlocutors, etc.). Below, we will discuss those that have been identified as playing a role in CLI. As for the characteristics of the languages involved, Williams and Hammarberg (1998) identified L2 status as a decisive factor in determining the choice of source language for CLI, especially in the case of short function words. They run a longitudinal case study of a learner of typologically related L2 and L3 and found that L2 influence was strongest in the earliest stages of the L3 acquisition but gradually diminished as the L3 acquisition progressed. According to their hypothesis, third language learners choose their L2 and not L1 as the auxiliary language for two reasons. First, learners perceive using a non-foreign language (rather than their L1) as a better strategy to acquire another foreign language (Williams and Hammarberg 1998: 323). Thus, their mother tongue, which does not sound ‘foreign’, is suppressed in the mind of a learner, and the language that is left to the L3 learner to draw upon is their L2. The second argument for the L2 status is that the mechanisms used in L3 and L2 learning are in fact similar and clearly contrast with L1 acquisition, which is innate and mostly communicative in nature. As a result, learners draw on their experience in L2 learning in order to benefit from it in what seems yet another analogous language learning. The ‘L2 status’ effect has been corroborated by other studies, which show that association of foreignness is not a deliberate strategy but rather a matter of cognitive constraint (De Angelis and Selinker 2001; De Angelis 2005). It may also be connected with degrees of language activation and language mode (Green 1986, 1998; see below). Hammarberg (2001), and Dewaele (1998) further developed the status hypothesis and drew attention to the fact that in L3 (or L4, L5, Lx) performance, there is a tendency to activate the most recently acquired language (the so called recency effect). However, it is also argued that typological factors can override the L2 effect and the recency effect, especially for languages bearing a lot of crosslinguistic similarity. Crosslinguistic similarity can be defined simply as the degree of congruence between the languages involved (Jarvis and Pavlenko 2007). On the one hand, it is connected with the typological distance between those languages and depends on linguistic genealogy, that is, the degree of genealogical relationship between languages (Comrie 1981). On the other hand, at the lexical level, languages may be close thanks to the process of extensive borrowing, which draws their lexicons close to each other and results in the presence of cognates of nongenetic origin (Jarvis 2009). Disregarding the sources of the crosslinguistic similarity, the closer the relationship, the more crosslinguistic interaction takes place. Conversely, the L2 factor proves to play a minor role in crosslinguistic consultation if languages are typologically too distant and are regarded as such by the learner/user (e.g., Cenoz 2001, 2003a; Dewaele 1998; Müller-Lancé 2003; Ó Laoire


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and Singleton 2009; Ringbom 2007). It follows that the actual language distance may be congruent or incongruent with the subjective psychotypological distance, that is, the perceived language distance individually experienced by the learner/user (Kellermann 1977, 1995). The subjective perceptions of that distance, which shape the participants’ view of the appropriate language source for crosslinguistic influence, could have a stronger impact on CLI than the objective typology. Although there is plenty of evidence in favour of interaction in the lexical processes between the different languages used by an individual, as noted by Singleton (2003: 169), ‘the very fact of this “psychotypological” dimension runs counter to the notion of straightforward total integration within the mental lexicon, because, precisely, it implies a degree of selectivity in relation to consultation of the languages represented’. Other important linguistic factors include the frequency of the item in the language which is the source of CLI, since learners tend to transfer frequency preferences from L1 to the L2 (Kellermann 1983; Jarvis and Pavlenko 2007); the markedness of the item; and the proto-typicality of form. The latter two are connected with constraints on CLI, where markedness is the extent to which a linguistic feature is special, relative to other features, and prototypicality is the extent to which a meaning of a word is considered core, or basic (Ellis 2008). Frequent, unmarked and more prototypical forms (constructions and word items) will be transferred more often and more readily than forms that are infrequent and somehow less representative of the prototypical meaning or usage (Kellerman 1995). These factors may also interact with individual psychotypology. A factor crucial for CLI and prior language activation is proficiency in L2-Ln connected with the frequency and recency of use of the languages. Probably, a certain threshold in language proficiency must be passed before a given language can be considered a source for CLI. The main question is how proficient a speaker must be in order for his or her prior linguistic knowledge to influence the production and development of a target language, but it should probably not be less than three to four semesters of study before a language could serve as a source of CLI (De Angelis 2005, 2007). In the case of the lexicon, it has been experimentally shown that L2 proficiency plays a role in language activation (see Van Hell and Tanner 2012 for an extensive overview). Due to non-selective access to the mental lexicon, words from more than one language compete for activation in production and perception. However, experimental research suggests that the magnitude of the cognate effect in word recognition depends on proficiency in L2 (Costa, Caramazza and Sebastian-Galles 2000; Brenders, Van Hell and Dijkstra 2011) and that some threshold proficiency level in L2 and L3 is needed for cognate facilitation effects to take place in bilinguals and trilinguals (e.g. Van Hell and Dijkstra 2002; Poarch and Van Hell 2012). So, there must be a minimal level of proficiency for words from a given language to play a role in the selection process, ‘i.e. their default level of activation should be high enough to make them competitive’ (De Bot 2004: 8). Consequently, proficiency in a given language must be high enough to activate that language when dealing with written stimuli or text. In research on third language acquisition and multilingual language acquisition, it is often emphasized that L3 proficiency is equally important to L2 proficiency; cumulative learning experience (Jarvis and Pavlenko 2007) helps the learner to


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employ metalinguistic awareness and crosslinguistic learning strategies. These are revealed in the form of conscious reliance on crosslinguistic similarity between languages in order to draw inferences concerning the unknown words and phrases and to learn more effectively (Berthele 2011; Gabryś-Barker and Otwinowska 2012; Lasagabaster 1998, Otwinowska-Kasztelanic 2011; Singleton and Aronin 2007). More experienced multilinguals tend to notice and use crosslinguistic similarity that aids comprehension and production of the new language. Thus, the cumulative languagelearning experience and metalinguistic awareness may be said to trigger affordances available to the learner. The notion of affordances, which stems from perceptual psychology, refers to perceived opportunities for action provided for the observer by the environment (Gibson 1977, 1979). In language learning, the affordances available to the learner when interacting with his/her linguistic environment are connected with the person’s language resources and his/her language-learning environments. Crucially, affordances are available only to those learners who notice and know how to use them (Singleton and Aronin 2012; Dewaele 2010; Singleton and Aronin 2007). As Dewaele (2010) specifies: Learners’ affordances will depend on their perception of the qualities of a new language and the amount of cross-linguistic and intralinguistic knowledge that they could mobilise when learning this new language. Just how relevant such prior linguistic knowledge is depends on the proximity of the target language (TL) and any languages known. Dewaele (2010: 106)

In conclusion, we can assume that both proficiency levels in L2 and L3-Ln together with typological factors may considerably influence language activation and CLI in the case of multilinguals. Thus, in the present chapter we will combine subjects’ proficiency in their languages, the number of languages they know and their typological relatedness into one cumulative concept of affordances available to the learner. Another issue important for language activation and CLI is the language mode the bilingual/multilingual speaker is in, that is, the relative state of activation of their languages. The concept of relative language activation stems from two models of processing. One is Green’s (1986, 1998) model of bilingual language processing, which assumes that language users can control their language processing by modifying levels of activation. The second is Grosjean’s language mode (1985, 1997, 1998, 2001) model, according to which the user’s languages are activated to a varying degree in a given situation but are never completely switched off. Grosjean’s language mode (1985, 1997, 1998, 2001) assumes that the activation of a bilingual’s two (or more) languages and language-processing mechanisms is a relative state. ‘At any given point in time and based on numerous psychosocial and linguistic factors, the bilingual has to decide, usually quite unconsciously, which language to use and how much of the other language is needed – from not at all to a lot’ (Grosjean 2001: 2). Importantly, the language mode affects the speaker’s/learner’s perception and the speed of access to one or two lexicons. In turn, the language mode itself is affected by the learner’s expectations and by language intermixing. The language mode view can be extended to multilingual processing as demonstrated by Dewaele (2001). According to him, the most highly activated language takes over, while the speaker’s other languages remain


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less activated along the language mode continuum. This activation will depend on non-linguistic and linguistic factors such as the person spoken to, the situation, the content of discourse and the function of the interaction. Finally, as for visual word recognition and reading by bilinguals and multilinguals, the issue of precisely how and to what extent the activation of languages interacts with bottom-up factors (phonetic/phonological/orthographic features, etc.) and with top-down factors (linguistic and non-linguistic context) still remains an empirical question. Dijkstra (2003) considered a number of linguistic factors that appear to help the word selection process. These include such bottom-up factors as itemrelated characteristics (neighbourhood density, language-specific cues, language distance and script type), and top-down factors having to do with linguistic context (morphological, syntactic, and language membership information). Languagespecific cues, which are visible even if two languages are closely related and use the same script, include, for instance, diacritical markers, such as accents in French, language-specific letters like ‘ą’ and ‘ę’ in Polish or letter combinations characteristic in one given language and not in another. The context of such clues may ‘deactivate’ the other languages known. According to Dijkstra (2003), in research settings topdown non-linguistic effects of context (expectation, instruction) and top-down linguistic effects of context (syntactic, lexical) can also have an impact on relative language activation.

1.3 Prior foreign language knowledge in language activation The activation of prior language knowledge and crosslinguistic consultation in multilinguals may be studied through translation and inferencing from an unknown language. Here we draw attention to three studies. Gibson and Hufeisen (2003) asked multilingual learners of English and German to translate in the written form a text from Swedish, an unknown language, into the foreign language the participants were currently studying, that is, either English or German. The subjects were of varied L1 backgrounds and had studied German and English as L3, L4 or L5. The text, accompanied by a picture, was taken from the beginner’s Swedish textbook, so the syntax consisted of simple SVO sentences. The participants were also asked to describe the types of influence, both linguistic and metalinguistic, on their attempts to translate the text. Gibson and Hufeisen (2003) report that learners strongly denied that their L1 languages helped, unless it was German as L1. However, it is the learner’s L2 that exerted a stronger influence on the following foreign languages. Multilinguals confronted with the task of translating a passage in an unknown language tended to use their lexical knowledge in German and English (i.e. languages they perceived as most similar to Swedish) and tended to browse through the mental lexicons of their languages while reading a specific target language. Translation correlated with a high degree of metalinguistic awareness in the participants’ comments, but also with successful guessing and top-down processing techniques. The main drawback of their study is the fact that the groups of learners examined were hardly homogenous in terms of language backgrounds, so methodologically the study was not rigorous enough. Secondly, the text used for translation together with the picture was quite transparent.


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Gabryś-Barker (2005) carried out a study on the role of prior-language knowledge in multilingual language activation. She asked two homogenous groups of multilingual students of German as L3 (L1 Portuguese, L2 English advanced) to translate a text either from L1, or from L2 to L3 German. The text was a short newspaper article on a topic familiar to the students. It was assumed that the relatively difficult task of translating into the weakest L3 would force the participants to ‘perform a more conscious and more elaborate lexical search using various domains of their knowledge, strategies and language awareness’ (Garbyś-Barker 2005: 105). Simultaneous introspection (thinkaloud protocols) was used to find out more about the participants’ processing of the text. The main finding was that the activation of languages strongly depended on the language of input. When translating from L1, students’ L1 and L3 were activated. However, when translating from L2, their L2 and L3 but also L1 was activated. What is more, translation from L1 seemed more automatic, but when translating from L2, students often commented on the strategies they employed. The study points to the fact that using L2 instead of L1 for the translation task may bring more insight into language processing and strategies employed in translation. The last piece of research to be mentioned here is by Berthele (2011), who studied the role of prior foreign-language knowledge in multilingual language activation and inferencing. In a series of methodologically rigorous studies, he asked multilinguals to infer meanings of cognate and non-cognate words in an unknown language, one typologically close to the languages they used (Germanic or Romance). The words were presented in various tasks, in context and out of context as vocabulary lists. Berthele (2011) found that typological proximity of the learners’ L1-Ln languages was important for inferring meaning of cognates and non-cognates in an unknown language. In lexical inferencing, the factors of proficiency in the L2-L3 languages and multilinguality proved to interact. The participants with higher self-rated proficiency in at least two of their L2-Ln languages did better than multilinguals without such knowledge (2011: 198). Berthele (2011) also demonstrated that multilinguals with high proficiency in two languages that are close to the target perform better than all other groups. As for language activation and CLI in such processing, he concluded that: The … quality of these interlingual guessing procedures depends on many factors, both concerning the multilingual subjects and the linguistic contrasts involved. Quality increases with increasingly proficient multilingual systems, and … the main process that enables multilinguals to be efficient in the tasks is a form of multilingual abduction, an inferencing process that exploits multlilinguals’ knowledge of what are likely and of what are unlikely correspondences across and within languages. Berthele (2011: 216)

2 Research on translating from an unknown language In our study we assume that multilingual speakers tend to apply CLI strategies that make use of their prior language knowledge and language learning experience in order to understand a new language on its first encounter. We aim to explore the mechanisms


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employed by Polish advanced users of English with different L3-Ln constellations (Germanic, Romance and Mixed) when faced with a text in an unknown language. For this purpose we pose the following research questions:

RQ1: Will typological proximity of the languages known substantially aid understanding of a text in an unknown target language?

RQ2: Will proficiency in L3 play a significant role in inferencing? RQ3: Do the factors of typology and proficiency combine to aid comprehension of an unknown language? We assume that multilinguals will browse through the lexicons and grammars of their various languages, especially L2 and L3-Ln, to choose a language or languages that could aid comprehension. We hypothesize that the factors of typology and proficiency in languages will significantly aid comprehension of a text in an unknown language.

2.1 Participants The participants were 40 Polish-speaking multilinguals aged between 21 and 30 (M = 23).The group included 36 females and 4 males. All were students of the Institute of English Studies at the University of Warsaw, were equally proficient in their L2 English (C1/C2 level)1, and had had training in linguistics and pedagogical grammar, so were able to read, analyse and comment on linguistic aspects of texts using English. The participants filled in a semi-structured language-learning experience questionnaire in English, where they were asked to assess their skills (i.e., reading, writing, speaking and listening) in all their L3-Ln languages on a 5-point Likert scale and to answer specific questions regarding each of their additional languages.

2.2 Instruments and procedure The participants were interviewed in a one-to-one setting by the researcher. The study consisted of two tasks. First, the subjects were presented with a short text (114 words, see Appendix A) in Danish, a Germanic language unknown to them. The text consisted of three paragraphs and was an excerpt from the Universal Declaration of Human Rights, Article 26th on Education taken from Hufeisen and Marx (2007: 355). Apart from the title reading ‘Artikel 26’ (Article 26) and the paragraph structure, the text was not aided by any accompanying extra-linguistic information. Nevertheless, the excerpt featured some easily recognizable international words (e.g., elementære, gratis, obligatorisk, religiøse grupper, respekten, tolerance), which could help in establishing the context. Using a think-aloud/verbal protocol method (Dörnyei 2007), the subjects had to translate as much as they could into English and comment on their associations and mental operations. The aim was to extract information on their cognitive processes and CLI from their impromptu responses. Secondly, in a stimulated recall task that followed, the subjects were confronted with the English translation of the same text (from Hufeisen and Marx 2007: 356, see Appendix A) and were asked to judge and comment on their original ideas. This phase allowed for further interpretation of the text and provided additional data on their awareness of crosslinguistic lexical similarity. All the interviews were recorded and transcribed.


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2.3 Method of analysis Multilinguality, proficiency and affordances in L3-Ln As shown in Figure 9.1, more than half of the subjects (23) were quadrilingual, nine were trilingual and five were quintilingual. On the basis of the L3-Ln languages known, the subjects were divided into three groups, from now on called as follows: ●

●

●

Germanic (n = 11) with users of L3 German (10 subjects) and/or Norwegian Bokmål (L3 or L4) (5 subjects) Romance (n = 12) with users of L3 French (10 subjects), and L4-Ln Spanish (6 subjects), Portuguese, Italian Mixed (n = 14) with users of both Romance and Germanic languages as L3-Ln

Three participants were excluded from the analyses due to their extremely low or extremely high motivation, which manifested in anomalous scores during the analysis stage, so the total number of participants’ answers analysed was 37. The exact language profiles of each participant within the three groups can be found in Appendix B. Due to their common background (the same L1, level of L2 English proved by internal university tests and similar linguistic training), the L1 and L2 English of participants was not taken into consideration when distinguishing between the three language groups because we assumed that these factors had an equal influence on participants’ task performance. As for the average proficiency levels for L3-Ln languages, the Mixed group was most proficient (L3-Ln around B1/B2 level), The Romance group followed, while the Germanic group was the least proficient (L3-Ln around A2/B1 level). Similarly to Dewaele (2010), we decided to award our subjects points for their particular L3-Ln language constellations. We assumed that proficiency in languages beyond L2 has an impact on additional language learning, so the subjects’ proficiency in their L3-Ln languages was marked in the following way: ●

●

L3 and L4 were assigned 1 point for levels A1-A2, 2 points for B1-B2, and 3 points for C1-C2. Proficiency in L5, L6 and L7 (usually rather low) was not promoted by additional points.

GERMANIC group trilingual

36%

MIXED group

ROMANCE group 17%

16%

trilingual

7%

quadrilingual

14%

quintilingual

quadrilingual

quadrilingual 64%

quintilingual 67%

22%

57%

sextilingual septilingual

Figure 9.1 The percentage of L3, L4, L5, L6, and L7 users in the Germanic, Romance and Mixed groups.


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We also assumed that typological factors of the L3-Ln known would influence the task performance, so the subjects’ languages were marked for typological relatedness to the target language, Danish: ●

● ● ●

Three points for Norwegian (Bokmål), which is a North Germanic language, similar to Danish and uses the same spelling conventions. Two points for German, which is a Germanic language. One point for Romance languages and other Indo-European languages. Zero points for non-Indo-European languages.

The typological relatedness of L5, L6 and L7 was marked only if it was German or Norwegian, and then, it received one or two points, respectively. The final score for each participant was a sum of points for his/her proficiency and typological relatedness of his/her L3-Ln. This allowed us to establish the variable of High versus Low affordance, a cumulative score of typological relatedness, the number of languages at subjects’ disposal and proficiency in the subjects’ L3-Ln (the cut-off score was set to 6 points, while the minimum score in the sample was 3 points, and the maximum score in the sample was 9 points). Figure 9.2 presents the distribution of High versus Low affordance scorers in each of the three language groups. The data concurred with participants’ proficiency levels: all those in the Mixed group (n = 14) were High-affordance scorers, the Romance group was balanced with an equal number of low and high scoring participants (n = 6), while the Germanic group included more low-scoring participants (n = 7) than high-scoring (n = 4), mostly due to their lower proficiency in L3-Ln.

Qualitative Analysis of Verbal Protocols The transcriptions of the verbal protocols were analysed in the following way. Whenever the subjects claimed some items to be similar to Norwegian, English, German, French or Spanish, such items were marked as either correct or false (i.e., resulting from formal similarity but different in meaning, e.g. the Danish til meaning ‘to’/‘for’ and the English ‘til’). This allowed us to analyse the possible sources of CLI for each participant. Afterwards, the number of the similarities noticed by the subjects 16 14

HIGH

LOW

12 10 8 6 4 2 0 GER

ROM

MIX

Figure. 9.2 The distribution of High and Low affordance scoring participants in Germanic, Romance, and Mixed groups.


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was divided by the number of all the similarities to be found in the text from a given language. In this way, the degree of reliance on each language was calculated. For instance, if S20 had transferred 24 of 56 items that were similar to Norwegian, her degree of reliance on Norwegian was 42.9 per cent. The transcriptions were checked for any references to the following three main categories: 1. Ability to draw inferences (recognizing international words and Danish content and function words, referred to as the total number of words decoded); maximum score of 57 points; 2. Top-down strategies (recognizing text genre, guessing meaning from context and drawing inferences from collocations, tautologies and word pairs); maximum score of 12 points; 3. Bottom-up strategies (analysing grammar and analysing morphology); maximum score of 12 points. The detailed description of the scoring procedure can be found in Appendix C.

Quantitative analysis Due to the specificity of the verbal protocol data and the number of students in each group, the methods of statistical analysis included a non-parametric Kruskal-Wallis one-way analysis of variance (ANOVA) by ranks, which was used to compare the three language groups (Germanic/Romance/Mixed) in their performance on lexical inferencing and top-down/bottom-up processing. Non-parametric Mann-Whitney U tests were further used to calculate contrasts between pairings of language groups (Germanic and Mixed, Germanic and Romance, Mixed and Romance) and to compare the performance of Low/High affordance groups. An analysis of covariance (ANCOVA with Bonferroni correction) was used to evaluate whether means of the dependant variables (total number of words recognized, top-down and bottom-up processing) are equal across the three language groups (Germanic, Romance and Mixed) while controlling for the effects of the covariate of the High/Low affordances.

3 The results of the study 3.1 The role of typological proximity of languages in comprehension of the unknown target language Qualitative analysis of text features The content and function words in the text were analysed to measure the lexical density of the Danish text, that is, the percentage of content words in the total number of words in the text. The lexical density of 52.6 per cent places it in the middle difficulty range for a written non-fiction text, whose density usually ranges between 40 and 65 per cent (Stubbs 1996). The text contained 64 types (word forms) and 114 tokens (occurrences of word-forms), while the type-token ratio equalled 56.1 per cent. The ten


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Figure 9.3 Lexical similarity of the items in the Danish text. most frequent words that occurred in the text (see Figure 9.3) included basic function words such as og (and), skal (shall, will), den (article) and the key word undervisning (education). Next, each lexical item of the Danish text was compared to its equivalents in Norwegian, German, English and Polish (the subjects’ L1). In this way, a table of language equivalents was created and the words with similar forms in all the languages were labelled as ‘international words’. There were ten of such words (e.g., obligatorisk, tolerance, respekten, nationers, gratis). For further analysis, the types were organized into 57 units (45 content, and 12 function words), some combined into phrases, for example, på grundlag af (on the basis of), religiøse grupper (religious groups). This was done because the subjects, when encountering these expressions, treated them as units. The analysis of lexical similarity of the items in the Danish text revealed that out of 57 units enumerated, 56 (98.2 per cent) were formally similar to their Norwegian equivalents (with no false cognates). This is due to the fact that Norwegian Bokmål (the dialect taught on language courses), has – in its written form – originated from Danish. The resemblance of Danish to other Germanic languages is lower: 35 (61.4 per cent) of the Danish units are formally similar to German words (including 3 false cognates), and 30 (52.6 per cent) units were similar to their English equivalents (including 3 false cognates), as shown in Figure 9.4 below. Negative CLI. Item transfer. Among the Danish items that proved to be most misleading were 8 content words and 3 high-frequency function words. It was interesting to find that most assumed incorrect translation of the misleading items came from English, the subjects’ L2. The word most frequently mistranslated was the key word undervisning (education). The word does not have a familiar equivalent in any of the languages, apart from Norwegian, and so it was only the context and the surrounding international words (elementære, gratis, obligatorisk, teknisk, højere), that could help in establishing the meaning. Other often mistranslated items were skal (shall, must), translated as ‘scale’ or ‘school’; forenede (united), translated as ‘foreign’, ‘national’ or ‘frontier’; børn (children), translated as ‘(in)born’ or ‘birth’; and freden (peace), translated as ‘friend’ and ‘freedom’. These items constitute a ‘litmus paper’ for revealing the auxiliary language chosen by our participants. Most of those


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mistranslations are instances of item transfer, a perceived similarity of form combined with an assumed similarity of meaning or function. Positive CLI. By comparing the percentages of language-based lexical similarities, we determined which language was the most active advisor in inferring the meaning

Figure 9.4a CLI sources in the Germanic group. Percentage of similarities to various languages observed by each participant.

Figure 9.4b CLI sources in the Mixed group. Percentage of similarities to various languages observed by each participant.

Figure 9.4c CLI sources in the Romance group. Percentage of similarities to various languages observed by each participant.


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of the new items. Figure 9.4a, b and c show the percentage of similarities from each language observed by the participants in the Germanic, Mixed and Romance groups. It can be seen that the participants, regardless of their group, observed most similarities from English. The Mixed group, who noticed most similarities in general, relied strongly on English and spotted on average 41.1 per cent of English-based similarities, 33.9 per cent of all German-based similarities (more than the two other groups) and 20.8 per cent of all Norwegian-based similarities. The Romance group relied strongly on English and recognized on average 44.5 per cent of English-based similarities – more than the two other groups. The Romance group also managed to extract some French- and Spanish-based similarities. However, those similarities consisted mostly of international words. We had assumed that the congruity between Norwegian and Danish might affect the results for the subjects with Norwegian as L3 (L4) to a greater extent than similarity to other languages. However, it turned out that the Germanic group as a whole recognized fewest language-based similarities: only 36.4 per cent of English-based similarities (the lowest score of all three groups) and only 24.3 per cent of the Germanbased similarities. Some students clearly failed to perform the task, for example: S11 (Germanic): Some words are just like English words, and I am wondering if it’s really Danish or maybe English combined with German or just words devised to look like German or English. Or maybe these are words from the language I know but the order of letters is changed.

Not surprisingly, within the Germanic group, the subjects who learnt Norwegian (n = 5) spotted on average 26.4 per cent of Norwegian-based similarities, which is more than any other group, and 42.6 per cent of English-based similarities, outperforming the Mixed group but not the Romance group. We also decided to compare the influence of proficiency among all the subjects that were learning Norwegian, the language typologically closest to Danish. As discussed above, Norwegian shared with Danish 98.2 per cent of the lexical units of the text. For the analysis the two groups were set apart: a Norwegian A1 level group (n = 5), and a Norwegian B1 level group (n = 3). This allowed us to qualitatively check whether the Norwegian B1 group would in fact benefit from their proficiency and observe more language-based similarities. The results presented in Figure 9.5 show that the B1 group recognized twice as many Norwegian-based similarities (41.1 per cent, M = 23, SD = 9.85) as the A1 group (21.2 per cent, M = 11.8, 80.0%

Norwegian-based similarities German-based similarities English-based similarities International words

60.0% 40.0% 20.0% 0.0%

A1 group

B1 group

Figure 9.5 Norwegian-, German-, and English-based similarities, as well as international words, recognized across Norwegian A1 and Norwegian B1 group.


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SD = 2.59). They also reported more German-based similarities (25.5 per cent, M = 8.7, SD = 10.69) as compared to the A1 group (12.9 per cent, M = 4.4, SD = 4.28), and more English-based similarities (B1 group: 50 per cent, M = 16, SD-9.54, A1 group: 37.5 per cent, M = 12, SD = 3.54). As for qualitative evidence, the A1 group focused mainly on the search for the international words and often got misled by the false cognates: S16 (Nor. A1): The first paragraph is about under [English pronounciation] vis… visning, so it’s about visas? I don’t understand this word, I know it is something ‘under’, but ‘visning’ ? I don’t know. ‘Enhver’ means ‘everywhere’ … there are some gratis things … ‘mindste’ ? I don’t know, what that is … ‘elementær’, that should mean ‘elemntary’, yeah. Grun … ‘grundlæge’ … [laughs] I don’t know what that is but ‘elmentær undervisning skal være obligatorisk’ … so ‘undervisning’ is obligatory. S18 (Nor. A1): I think that ‘undervisning’ is something useful for people, and gives them some benefits, because I think ‘gratis’ means that it’s maybe some kind of ability … you can do something and it helps you in everyday life, but I don’t know exactly what it is. And there were some words like ‘tolerance’ and ‘relig … iøus grupper’ and … hm … but I don’t know what is the connection between those.

Notably, the higher level of proficiency led to more language-based similarities not only in Norwegian but also in all Germanic languages. The subjects’ average score of Norwegian-based similarities almost doubled in comparison to the A1 group. While this is undoubtedly a result of higher proficiency, an increase in the observation of English-based similarities must have another explanation. Compared to the A1 group, the B1 subjects observed more similarities from English (on average 50 per cent, compared to A1 37.5 per cent), though the proficiency levels in the two groups were the same. The B1 subjects mentioned also more crosslinguistic similarities from German (the average score at 50 per cent), though only one subject knew German well (S21 at the B2/C1 level), and they reported on more international words. S19 (Nor B1, Ger B2): I must say I’m really surprised because I understand most of the text. … I understand it as it [education] should be possible up until higher education, something like that, because ‘højere’ is definitely ‘higher’, and the ‘undervisning’ is ‘education’, and ‘til’ is definitely *‘until’ or … yeah *‘until’. S20 (Nor B1, Ger A1/A2): ‘venskab’ …‘mellem’ … mellem can be ‘mellom’ in Norwegian, so between all nations, ‘alle nationer’ … ‘og den skal fremme Den forende … Nationers’ so … abroad … nations from another country … ‘arbejde til’ … ‘arbejde’ … so ‘arbeid’, so I have some associations from German, yeah [laughs].

The evidence from the transcribed verbal protocols showed that the B1 Norwegian subjects were altogether more successful in decoding the Danish text – they saw more language-based similarities, and their reports were more informative. The quantitative data should be approached with caution due to the very small sample of students knowing Norwegian, but they clearly hint that both typological proximity of languages and participants’ proficiency level play a role in inferencing. This issue will be analysed in greater detail in the quantitative analysis below.


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3.2 Evidence from lexical inferencing Role of typology The Mixed and the Romance groups seemed to reveal a deeper analysis of the text at hand. Even though they could not associate the key word (undervisning – education) with any other word in their languages and they did not use morphological analysis to deconstruct it, they tried to deduce its meaning from the surrounding adjectives (topdown investigation), for example: S40 (Mixed): I know the words describing this word [‘undervisninig’], which are: elementary, or maybe basic, let’s say … and then ‘obligatorisk’ which will be ‘obligatory’. I would stick to the idea that ‘undervisning’ is some kind of action. S23 (Mixed): the text relates to ‘education’, the key words ‘elementære’ ‘obligatorisk’ ‘grundlæggende’ they are instantly related to education.

The qualitative data hinted that the Mixed group was most apt to recognize and report familiarity with the international words (average 71 per cent of such words, M = 7.1 items, SD = 1.69). The Romance group followed (average 69 per cent international words recognized, M = 6.9, SD = 1.62), while the Germanic group was the worst (average 63 per cent of international words recognized, M = 6.3, SD = 1.01). However, KruskalWallis tests revealed no statistical differences across the three groups (p = 0.428). As to the words recognized in total, the Mixed group reported on average 77.4 per cent of words in the sample (M = 44.1, SD = 10.06), The Romance group recognized on average 60.3 per cent of words (M = 134.4, SD = 11.65) and the Germanic group recognized on average 57.7 per cent of words (M = 32.9 items, SD = 15.63). The main effect of the group was significant (Kruskal-Wallis score (H (2) = 7.15, p = 0.028), but the contrast was only significant for the Germanic and the Mixed group (MannWhitney U = 34.50, p = 0.021), to the effect that the Mixed group obtained significantly higher scores than the Germanic group.

Affordances: Combined role of typology and L3-Ln proficiency In order to account not only for language typology, but also for the participant’s proficiency in their L3-Ln constellations, the participants were further divided into High- and Low-affordance scorers (see Section 2.3 for details of assessment). When regrouped as Low- and High-affordance scorers, it turned out that the High group recognized more language-based lexical similarities. On average the participants from the High-affordance group decoded 76.1 per cent of crosslinguistically similar words (M = 43 items, SD = 11.68), whereas the Low-affordance group decoded 47.50 per cent of the items (M = 27 items, SD = 8.36). The Mann-Whitney U test results (U = 37.50, p = 0.000) revealed a significant difference between the two groups in the total number of words recognized. When zooming in on the participant’s performance within the two affordance levels, it was interesting to find that both the highest and the lowest mean score in decoding words belonged to the Germanic group (Figure 9.6). However, an analysis of co-variance revealed no significant effect of the group (Germanic, Romance, Mixed) on the number of words decoded after controlling for the effect of the High/Low affordance level


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Number of words decoded

60 high

low

50 40 30 20 10 0 Germanic

Mixed

Romance

Figure 9.6 Means for the number of total words decoded by the three language groups in their Low/High affordance distribution. (F (2,33) = 0.091, p = 0.914). Also the planned contrasts revealed that neither the Germanic group (p = 0.901, 95 per cent CI [8.80, 9.96]) nor the Romance group (p = 0.674 95 per cent CI [7.88, 12.03]) differed from the Mixed group in the number of words decoded. However, the covariate, the High/Low affordance level, was significantly related to the number of words decoded by a subject, (F (1,33) = 10.842, p = 0.002). Thus, we can conclude that the affordance level, that is, the typological relatedness of L3-Ln languages combined with the learner proficiency in those languages, proved to have more influence on the subjects’ lexical inferencing than their language group status.

3.3 Evidence from the top-down and bottom-up strategies Role of typology The qualitative analysis of the verbal protocols of individual subjects illustrates how the participants tried to decode the unknown language. When the Germanic group resorted to bottom-up strategies, they mostly applied morphological analysis to decode the key word undervisning (‘education’); for example: S38 (Germanic): ‘undervisning’ it has two parts: ‘under’ and ‘visning’ and ‘visning’ is like vision. S12 (Germanic): it’s all about some scales which show some result of some research, or something like that. And we’ve got at least a few examples of these scales, there’s a scale with a strange name ‘være gratis’ … different types of this ‘undervisningen’ scale. And those [scales] are ‘elementary’ and ‘obligatorisk’ whereas some other are not … and ‘børn skal’ – ‘birth rate’.

The Mixed and the Romance groups did not use bottom-up analysis in the case of the key word. Instead, they looked closely at the grammar and morphology of the whole text, showing a well-developed metalinguistic awareness; for example: S5 (Mixed): all words like ‘har’, ‘ret’ or ‘have’ may be somehow associated with perfect tense in German and in English because it looks very much the same … ‘den’ and ‘de’ stand for German ‘der’ ‘die’ ‘das’.


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7 top‐down mean

bottom‐up mean

6 5 4 3 2 1 0 GER

ROM

MIX

Figure 9.7 The average scores of the three groups in top-down and bottom-up strategies.

S40 (Mixed): there are two words that have the same ending … which is probably the same form of the word ... and … immediately, I would say these are two adjectives, but they might be some particular case and the case is marked by the ending … then this noun [undervisning] has a plural form [undervinisngen], with this genitivus, like ‘undervisningen of what’, and then ‘skal’ would be a noun connected to this. S36 (Romance): I think this word ‘være’ must be a verb … and that short words are probably articles, like ‘and’ ‘or’, I could guess what the parts of the sentences are, which one is a verb, which one is a noun, but I won’t understand it anyway. S34 (Romance): … when I look at the sentence [‘elementær undervisning skal være obligatorisk’] I just know that ‘elementary’ would be an adjective here, ‘undervisning’ would be a verb with ‘ing’ ending, which would suggest it’s actually a noun here … then the ‘obligatorisk’ also as an adverb here, so I was just wondering which one of the remaining words ‘skal’, or ‘være’, one of them has to be the verb. I suppose it’s the second one.

The transcriptions of the verbal protocols hint that the subjects used both bottom-up strategies, that is, analysing the syntax and morphology of the text; and top-down strategies, such as guessing meaning from context and drawing inferences from collocations, tautologies and word pairs. Figure 9.7 depicts the average score for the use of particular strategies by the three groups. It seems that all the groups relied more on the top-down strategies. The Mixed and the Romance groups (M = 6 out of 12 points, SD = 1.81, M = 6, SD = 2.64, respectively) outperformed the Germanic group (M = 4, SD = 2.55). The same holds for bottom-up strategies: the Mixed group’s average score was lower than that of the Romance group (M = 3, SD = 3.23, M = 4, SD = 3.73, respectively), but still both groups scored higher than the Germanic group (M = 2, SD = 1.18). However, a Kruskal-Wallis test run to compare the three groups revealed no significant differences in either top-down (H (2) = 4.564, p = 0.102), or bottom-up processing (H (2) = 1.464, p = 0.481).


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Figure 9.8 Mean scores in top-down and bottom-up processing performance by the three groups in their low/high distribution.

Affordances: Combined role of typology and L3-Ln proficiency When we regrouped all the study participants into Low/High affordance scorers, again both groups relied more on top-down than bottom-up strategies. The High-affordance group’s average score in top-down strategies was 6 points, while the Low-affordance group scored on average 5 points. As to bottom-up strategies, both groups received the same average score of 3 points (Figure 8). The U Mann-Whitney tests did not show significant differences in their use of top-down strategies (U = 119.50, p = 0.252) or bottom-up strategies (U = 133.50, p = 0.474). Again an ANCOVA was performed in order to assess whether the language groups differed on top-down and bottom-up processing after controlling for High/ Low affordance. The results show that the effect of typological group was statistically insignificant both in top-down processing (F (2,33) = 1.998, p = 0.152) and bottom-up processing (F (2,33) = 1.033, p = 0.367). Also the covariate, High/Low affordance, was not significantly related to the subjects’ top-down processing (F (1,33) = 0.355, p = 0.555) or to the subjects’ bottom-up processing (F (1,33) = 0.005, p = 0.945). On the basis of those results we may say that the effect of typological group and High/Low affordance (proficiency and typology combined) on top-down and bottom-up processing was too small to be statistically significant.

4 General discussion The present chapter set out to explore the mechanisms used by multilingual speakers with different L3-Ln constellations (Germanic, Romance and Mixed), when faced with a text in an unknown language. Due to the common background of our participants, which included the same L1 (Polish) and a similar level of L2 (English) proved by internal university tests, we disregarded the students’ L1 and L2 during the analysis, assuming that these factors had an equal influence on their performance. Instead, we focused on their multilinguality, that is, the constellations of their L3-Ln languages. Since similarity of form between lexical items is usually one of the first things noticed by learners of a new language, when giving our participants a text in Danish, we first aimed at examining their lexical inferencing, and focused on such aspects as the recognition of international words, the total number of words recognized (including


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content/function words) and negative transfer of form, that is, false cognates. We were interested to find which of the participants’ languages will be most active in the crosslinguistic comparisons. Secondly, we wanted to learn about the types of strategies employed in order to deal with reading in an unknown European language in order to investigate the possible top-down and bottom up approaches to the text. Aiming to explore the effect of typology as a factor that could aid inferencing and comprehending the Danish text, we first divided our subjects according to their L3-Ln language constellations. The typological similarity between Danish and other Germanic languages like Norwegian, German and even English suggested that the multilinguals from our Germanic group of participants would find the text easier to decode than the other two groups. We had expected that Norwegian would considerably help learners because, in fact, Norwegian Bokmål, the dialect taught on language courses, has – in its written form – originated from Danish. This is because Danish was used in Norway during the union with Denmark between 1536 and 1814. Thus, in their written form, the two languages share a lot of crosslinguistic similarity. Contrary to our expectations, our data showed that the Germanic (Norwegian + German) group was actually significantly worse than the Mixed group (German + Romance languages) in the total of the words recognized. What clearly hindered the performance of the Germanic group as a whole was their lower L3-Ln proficiency. The impact of proficiency was visible even when qualitatively comparing the verbal protocols of the less and the more proficient learners of Norwegian as L3-Ln; although the typological proximity of the languages helped, the students with higher proficiency were much better at inferencing and understanding the words, grammar and meaning of the text than the less proficient learners. It seemed that the proficiency and typological proximity of language constellations could interact when aiding comprehension. Therefore, we decided that the combined L3-Ln proficiency and typological relatedness of the language might constitute a set of affordances available to the learner; that is, they will both have an impact on how well the participant will interact with the text in the unknown language. To investigate this we established a variable of High/Low affordance, which combined proficiency in L3-Ln with the typological proximity of the languages known to the learner. The participants scored more thanks to the typological proximity of languages in their constellations and thanks to their proficiency in their language (as described in detail in Section 2.3). The Low- and High-affordance subjects proved to perform differently in the lexical inferencing. The non-parametric Kruskal-Wallis tests showed that the High-affordance participants recognized significantly more words than the Low-affordance group. The ANCOVA indicated that High/Low affordance was a significant predictor of the participant’s performance in lexical inferencing. In the qualitative analysis, those subjects who knew both Norwegian and German and knew either of the languages well (at least B1 level, classified as High Affordance group) outperformed everyone else in the recognition of Norwegian-based similarities and recognized the same number of lexical items as the best-performing Mixed group. However, the Low-affordance subjects, even though they knew some Norwegian, performed much worse. Thus, an important finding to emerge from this part of the study is that there may be less assistance of typological proximity of languages within constellations if the learner’s level of proficiency in L3-Ln languages is too low (in this case, below B1).


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Interestingly, English proved to be the main source of CLI, both positive and negative, at the lexical level. As for negative CLI, it often happens at the early stages of language learning; learners who have a limited knowledge of the target language rely strongly on form rather than on meaning and hence establish oversimplified equivalence hypotheses (Ringbom 2007). Consequently, item transfer readily reveals its source, which at the same time is the auxiliary language used to help the comprehension process. The most frequently misleading Danish items in our study revealed the auxiliary language chosen by our participants. The word most frequently mistranslated was the key word undervisning (‘education’). The word does not have a familiar equivalent in any of the languages apart from Norwegian, and so it was only the context and the surrounding international words that could help in establishing its meaning. Here, most of the assumed incorrect translations of the misleading items came from English. Also the mistranslations of function words had their sources in English, which is in accordance with Williams and Hammarberg’s (1998) L2 status hypothesis. Even the participants who learnt Norwegian and knew it well strongly relied on English. In fact, both the mixed and the High-affordance Germanic group (consisting of participants learning Norwegian) relied on English to great extent rather than on Norwegian equivalents of words like børn (Nor: ‘barn’, Eng: ‘children’), or even skal (Nor: ‘skal’, Eng: ‘shall’) and til (Nor: ‘til’, Eng: ‘to/for’). As we can see from the data on positive CLI, here also English was the strongest source of transfer. The Mixed group spotted, on average, 41.1 per cent of English-based lexical similarities and 33.9 per cent of all German-based similarities, while the highffordance Germanic group spotted 42.6 per cent of the English-based similarities and 26.4 per cent of Norwegian-based similarities. Even the subjects learning Norwegian spotted on average 42.6 per cent of English-based similarities and only 26.4 per cent of Norwegian-based similarities, which was more than any other group, but still below expectations. These results point to several possible, but not mutually exclusive, interpretations. First, proficiency in a language may render this language as a ready source of transfer in accordance with Williams and Hammarberg’s (1998) L2 status hypothesis. Our subjects were highly proficient in English, as compared with their somewhat lower proficiency in other languages. This may have influenced the choice of English as the auxiliary language. Secondly, psychotypology, the individual perception of the linguistic distance, may play a role in determining the source of linguistic transfer. Typologically, English could have been perceived as a natural choice to rely on since it is a Germanic language. On the other hand, Polish, the participants’ L1, was not active and had no overt influence on translation. This converges with the findings by Gibson and Hufeisen (2003) that L1 may not play a role in learning a language beyond L2 if it is not perceived as close enough to the target. And indeed, being a Slavic language, Polish could not have been of much help with the task. Finally, the amount of CLI from English, the subjects’ L2, can be explained by the notion of the language mode (Green 1986, 1998; Grosjean 1985, 1997, 1998, 2001). English was the language used throughout the interview, and therefore it was highly activated. The level of activation is also reported to play a major role in determining the source language for CLI.


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Unfortunately, the analysis of top-down and bottom-up processing did not reveal significant differences between the typological participant groups, and neither did reanalysing the data by dividing the subjects into Low- and High-affordance groups. However, the qualitative analysis of the results showed that subjects with lower proficiency in L3-Ln tended to use fewer strategies and sometimes failed to perform the task even though they could transfer knowledge from typologically related languages. Compared with the two other groups, the Germanic group used fewer strategies and were less successful than the Mixed group, where the subjects were at higher proficiency levels (B2 or above). The results of the Mixed group indicate that betterdeveloped metalinguistic awareness made the subjects more keen on searching for lexical similarity. Again, it follows that those in the Germanic group were hindered in their use of their linguistic knowledge, presumably because they knew fewer languages than the other groups, and their proficiency levels in the languages were lowest. Thus, their metalinguistic awareness was weaker, which prevented them from using their typological assets to the fullest. Consequently, our data hint that proficiency in a language, possibly together with language activation levels, are important in shaping participants’ strategic performance. We suggest that higher L3-Ln proficiency levels may facilitate the learners’ metalinguistic awareness and add to their confidence and overall success in the inferencing task. In our study, similarly to the findings by Berthele (2011), proficiency in L3-Ln coupled with typological factors guaranteed greater success in inferencing from an unknown language. Possibly, further research is needed to establish whether such results would be replicated on larger samples.

Conclusion The research discussed above gives evidence that MLA embraces unique and complex factors that arise from the interactions among the many languages learnt and the processes of learning them. MLA is characterized by a more complex interplay of factors connected with language typology and individual learner differences than SLA. From these factors, we have closely investigated two: typology and proficiency in L3-Ln. We have found that one may enhance the force of the other, forming a set of affordances when learning a language beyond L3. However, even though typological distance plays an important role in CLI, it was not the main factor in choosing the auxiliary language for comprehension of a text in Danish, an unknown Germanic language. Our results demonstrated that the Mixed and Romance groups, which were more proficient in L3-Ln, outperformed the lower-proficiency Germanic group in inferencing. Since the investigated group was homogenous in terms of the participants’ educational background, their L1 Polish and their highly advanced L2 English, the data clearly indicate that it is proficiency in L3-Ln languages together with cumulative language experience that matters in enhancing the inferencing strategies. Typological proximity of languages helps only if proficiency in L3-Ln is high enough. Our data suggest that the metalinguistic awareness needed to tackle challenging language


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tasks develops alongside the process of gaining proficiency in L3. It therefore follows that metalinguistic awareness is both a product of multilinguality and a trigger that stimulates additional language acquisition.

Acknowledgements We would like to thank professor Maciej Haman for consulting our statistical analyses and our anonymous reviewer for suggesting improvements to the earlier version of this paper. Many thanks to all the students who took part in our time-consuming study.


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Appendix A: The text used in the study – a fragment of the Universal Declaration of Human Rights in Danish and its translation in English (Hufeisen and Marx 2007: 355)


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S21

S19

S4

S5

GER

GER

MIX

MIX

S28

S20

GER

MIX

S16

GER

S27

S38

GER

S30

S18

GER

MIX

S7

GER

MIX

S6

GER

S8

S13

GER

S17

S12

GER

MIX

S11

GER

MIX

No

Group

high

high

high

high

high

high

high

high

high

high

high

low

low

low

low

low

low

low

Affordance level

German B2

French B2/C1

German B2

French A1/A2

German B2

German B2

French B2

German B2

German B2/C1

Norwegian B1

German A1/A2

German B1

Norwegian A1

German B1/B2

German B1/B2

German A1/A2

German A1/A2

German A1/A2

L3

Italian B2

Spanish B1

Spanish A2

Norwegian A1

Spanish A1/A2

Japanese B1/B2

German A1

Norwegian B1

Norwegian A1

German A1/A2

Norwegian A1

L4

Italian A2/B1

Italian A1

L5

Appendix B: Language profiles of the study participants (L3-Ln) L6

L7

238 Crosslinguistic Influence and Crosslinguistic Interaction

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S2

S3

S36

S37

S34

S35

S39

S9

S24

S31

ROM

ROM

ROM

ROM

ROM

ROM

ROM

ROM

S33

MIX

ROM

S25

MIX

ROM

S23

MIX

S1

S22

MIX

S15

S40

MIX

ROM

S26

MIX

ROM

S32

MIX

high

high

high

high

high

high

low

low

low

low

low

low

high

high

high

high

high

high

high

French C1

French C1/C2

French B2/C1

French B2/C1

French B2/C1

Spanish C2

Italian B2/C1

Spanish B2

French B2

French B2

French C1

French B2

French C2

French C1

Norwegian B1

German B1

German B2/C1

German B2/C1

German B2

Italian B1/B2

Spanish B2

Spanish B2/C1

Spanish B2

Italian B1/B2

Portugese A1/A2

Spanish A2

French A1

Russian A1/A2

Italian A2

Spanish B2/C1

Portuguese B2

German A2

French A2

Spanish B2

Portugese A2/B1

Spanish B1

Spanish A2

Jamaican creole A1

German A1/A2

Spanish B1

French A2

Norwegian A1

Czech A1/A2

Italian A2

German A2

Is A2 in German Better than B2 in French when Reading Danish? 239

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Appendix C: The procedure for scoring verbal protocols and simulated recall General Category Inferences

Category specified Recognizing specific words: CONTENT

Point assignment Number of words (max. 57)

Recognizing specific words: FUNCTION Recognizing international words Top-down strategies

Bottom-up strategies

Recognizing text genre: 1–2 points for identifying as law/regulation/ general idea of a formal constitution text or recognizing the text as a legal text/ part of constitution/ regulation

1–2 points for success

Guessing meaning from context

1–2 points for drawing on the knowledge of the world or drawing on the context of the text


Drawing inferences from collocations

1–2 points for e.g. if ‘respect’, then ‘strengthen respect’ or drawing from tautologies/word pairs


Grammatical analysis (bottom-up strategies)

1–2 points for looking for verbs/nouns/looking at word order, etc.


Looking at morphology

1–2 points for decomposing words into smaller units, easier to analyse


Checking inferences 1–2 points for revising against the new data previous assumptions



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Notes 1 In the present study we define L2, L3, L4 and L5 using proficiency criteria. Thus, L2 is equivalent to the best-known foreign language, L3 is the second best language and so on.

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