Volume 6 (2015) Issue 1 - Article Byrne
JLLT 6 Volume (2015) Issue 1.pdf

Journal of Linguistics and Language Teaching

Volume 6 (2015) Issue 1 (PDF)

Examining Successful Language Use at C1 Level: A Learner Corpus Study into the Vocabulary and Abilities Demonstrated by Successful Speaking Exam Candidates

Shelley Byrne (Preston (Lancashire), United Kingdom)

Abstract

This study situates itself amongst research into spoken English grammars, learner success and descriptions of linguistic progression within the Common European Framework of Reference for Languages (CEFR) (Council of Europe, 2001). It follows previous corpus research which has sought to document the language required by learners if they are to progress through levels and ultimately ‘succeed’ when operating in English. In the field of language testing, for which the CEFR has been a valuable tool, qualitative descriptions of learner competence and abilities may not provide sufficient detail for students, assessors and test designers alike to know which language is required and used by learners at different levels. This particular study therefore aims to identify the language and abilities demonstrated by successful C1 candidates taking the University of Central Lancashire’s English Speaking Board [UCLanESB] speaking exams. Using a learner corpus of C1 exam performance (26,620 words), examinations of vocabulary profiles, word frequencies, keywords, lexical chunks and can-do occurrence were conducted to identify the lexico-grammar required for C1 students to obtain solid pass scores. It was found that vocabulary belonged largely to the first two thousand most frequent words in English, lexis and chunks displayed some parallels with native-speakers, and language relating to can-do occurrence performed a more productive than interactive or strategic purpose.

Key words: Learner corpora, spoken grammar, language testing

1 Introduction

Success in second language acquisition has been subject to various avenues of investigation. From the examination of individual cognitive and affective characteristics (Cook 2008; Dornyei & Skehan 2003; Ellis 2008; Gardner & MacIntyre 1992; Robinson 2002; Rubin 1975) to the application of learner models or “yardstick[s]” (House 2003: 557), researchers and practitioners have aimed to demystify what makes language learners successful. Another approach in this pursuit has been to explore more deeply the features that language comprises using corpus linguistics, a technique which has often been used to explicate how lexico-grammatical forms differ or correspond in spoken and written discourse (Biber, Johansson, Leech, Conrad & Finegan 1999, Leech 2000, Conrad 2000, McCarthy & Carter 1995). The compilation of descriptive grammars and various corpora (Biber et al. 1999, Carter & McCarthy 2006, Cambridge English Corpus (CEC) 2012, the British National Corpus (BNC) 2004, and the Cambridge and Nottingham Corpus of Discourse in English (CANCODE) 2012), has resulted in enhanced knowledge of spoken and written English features that has not only aided comparison, but has simultaneously provided a source of knowledge for learners.

However, the native-speaker (NS) foundations upon which such grammars and corpora are assembled have generated debate and criticism. Despite some learners’ aspirations to conform to native speaker models (Timmis 2002), questions have arisen regarding the applicability of a linguistic model potentially inappropriate, unachievable, conflicting or irrelevant in a world where English as a lingua franca is used often beyond native-speaker contexts (Alpetkin 2002, Canagarajah 2007, Cook 1999, Cook 2008, Kramsch 2003, Norton 1997, Phillipson 1992, Piller 2002, Prodromou 2008, Stern 1983, Widdowson 1994). Research into successful spoken and written language use has therefore begun to place emphasis on learner corpus research centring on language use by non-native speakers who operate and function as “successful users of English” (Prodromou 2008: xiv) (International Corpus of Learner English (ICLE) (Granger, Dagneaux, Meunier, & Paquot 2009), the Vienna-Oxford Corpus of International English (VOICE 2013), and Cambridge English Profile Corpus (CEPC n.d.)).

Within the European language provision context, research is also delineating learner success and language use in terms of the proficiency descriptors provided by the Common European Framework of Reference for Languages (CEFR) (Council of Europe [CoE] 2001), a document outlining the wide-ranging competencies of language learners in a variety of language learning settings. In a bid to satisfy its aims of providing a non-prescriptive, adaptable guide for language provision, no illustration is given as to the actual language to be evidenced at different levels (Alderson 2007, Weir 2005). Put simply, while readers can discover what learners should be able to do with their language, less guidance is offered for what language should be used in order to do it. It is this intentional limitation which has stimulated this study focusing on a particular set of speaking exams. As the uptake of CEFR levels and proficiency scales was considerable in the field of language assessment (Little 2007), this study aims to reveal what language is required by speaking test candidates if they are to be successful in C1 level exams. Building upon the findings of a B2 study conducted by Jones, Waller & Golebiewska (2013), it reports on data from a spoken C1 test corpus of learner language in order to answer the following research questions:

RQ1 What percentage of the words used by C1 learners come from the first thousand and second thousand most frequent words in the BNC?

RQ2a What were the twenty most frequent words used by successful learners at C1 level?

RQ2b What were the important keywords at C1 level?

RQ2c What were the most frequent three- and four-word chunks used by these learners?

RQ3 What C1 CEFR indicators are present in terms of spoken interaction, spoken production and strategies?


2 Literature Review

The impetus for identifying a spoken grammar of English arose from criticisms towards traditional grammars heavily influenced by the written word and their applicability to the diverse, wide-ranging speakers and contexts encompassed by the medium of informal conversation. Ensuing research, facilitated by developments and findings in corpus linguistics techniques (Leech 2000), prompted the compilation of large spoken corpora including the CEC, BNC and CANCODE. In addition to providing real examples of language for practitioners and learners, such corpora have done much to expand knowledge of written and spoken lexico-grammars and their distinctions. With knowledge of the target language system being integral to success in language learning (Griffiths 2004), an increased knowledge of grammar is believed to do much to raise learners’ potentials to “operate flexibly in a range of spoken and written contexts” (McCarthy & Carter 1995: 207).

One area of lexico-grammatical knowledge broadened by corpus linguistics relates to vocabulary, in particular the use of lexical chunks. Vocabulary, learned for its communicative purpose (Laufer & Nation 1995) aids the construction and comprehension of meaning, enhances the acquisition of new vocabulary, extends the knowledge of the world and is fundamental to student performance (Chujo 2004). In terms of success and language learning, it seems crucial that research should aim to identify what and how much vocabulary is needed to achieve a particular purpose (Adolphs & Schmitt 2004). Studies based on the NS corpora above have, however, demonstrated that vocabulary is rarely used in isolation. It is often combined to form prefabricated chunks (Wray 2002), formulaic expressions (Schmitt 2004) or “standardised multiword expressions” (Boers, Eyckmans, Kappel, Stengers & Demecheleer 2006: 246) which can fulfil various linguistic functions including collocations, fillers in speech and idiomatic expressions. Constituting varying proportions of total language use (Erman & Warren 2000, Foster 2001), lexical chunks not only influence the assessment of learner proficiency and success, but they also facilitate spoken production. They reduce memory constraints, they can make students sound more native-like, they can maintain accuracy and they can act as “zones of safety” (Boers et al. 2006: 247; also Wray 2002 and Skehan 1998). With estimations asserting that chunks comprise 32.3% and 58.6% of NS spoken discourse, investigations of learner success should indeed take them into account to ascertain whether they are used and whether lexical chunk instruction may be of benefit to learners.

Returning to the notion of learner success, corpus findings and spoken grammars based on the NS may seem somewhat paradoxical in the pursuit of a “natural spoken output” in the classroom (McCarthy & Carter 2001: 51). Questions have been raised as to whether NS findings can indeed provide appropriate grammatical insights beneficial to the development of ‘natural’ non-native speech. Although many teachers and learners may endeavour to achieve a native-like standard in English (Timmis 2002), the NS model for many learners can be deemed “utopian, unrealistic, and constraining” (Alptekin 2002: 57) and at times unconducive to the goals of individuals who may operate in English beyond traditional, inner-circle NS contexts (Andreou & Galantomos 2009, Kachru 1992). Recent years have therefore seen an increase in the application of learner corpora to obtain greater insight into proficiency and linguistic achievement during second language learning (e.g. ICLE, VOICE, and CEC). By exposing learners to examples from successful learners of English rather than those of native speakers, it is thought they will be able to consult a model which is more realistic, appropriate and, ultimately, within reach.

A further branch bridging the discussion of successful language use and corpus linguistics concerns associations with learner competency descriptors within the CEFR (CoE 2001). In addition to detailing extensively the skills learners possess and cultivate across a wide range of social and educational contexts, the CEFR comprehensively describes communicative language activities and competences. Specifically, in relation to the focus of this study, its six Common Reference Levels and can-do statements outline the abilities of language learners at different stages. However, despite its intentional, non-exhaustive nature (CoE 2001, Coste 2007, North 2006, Weir 2005), it has faced criticism. While some highlight its misuse, its lack of support from second language acquisition theory and its sometimes problematic application caused by vague definitions and vocabulary, others have stressed the absence of actual language use to enhance the understanding of its competency descriptors (Alderson 2007, Fulcher 2004, Figueras 2012, Hulstijn 2007;,Weir 2005). In short, the detailed guidance offered in describing abilities at each of the six levels is not replicated in the form of illustrative linguistic structures and vocabulary to be encountered or mastered by learners. One large-scale study, the CEPC (n.d.) has begun to tackle these issues. Via the compilation of an intended 10 million word (20% spoken, 80% written) learner corpus covering levels A1-C2, the CEPC intends to document the language required by learners to satisfy descriptors at each level.

While the present, much smaller study may seem to share aims similar to the CEPC, its context is more focussed. While the CEPC incorporates general and specific written and spoken English language use by learners from across the world, the lexico-grammatical findings in this study will relate only to successful spoken language use in C1 speaking examinations produced by UCLanESB so that test writers, assessors, teachers and students can all be made aware of how language can be used to fulfil CEFR criteria.

3 Methodology

A learner corpus of 26,620 words was constructed, using sample language from the UCLanESB spoken tests at C1 level. Samples were taken from 31 adult candidates (16 males, 15 females) of mixed nationalities who achieved a solid pass score on the test each. Following completion of the speaking tests, conducted in groups of two or three candidates, speakers were given a mark of 0-5 for vocabulary, grammar, discourse management, interactive ability, and pronunciation; a global score was then calculated. It was this global score which was used as a measure for success. As a score of 2.5 equates to a pass, only exams in which both or all candidates achieved a score of 3.5 or 4 were incorporated into the corpus. Students attaining a mark outside this score bracket may not have displayed a solid, successful performance at C1 level and would therefore not assist the aims of the research. Steps were also taken to verify the global scores of exams incorporated into the corpus: all exam assessors had completed UCLanESB standardisation, all exams had been second-marked and the researcher did not take part in any exam, neither as an assessor nor as an interlocutor.

To correspond with other general English tests, and to assess an array of speaking skills (O’Sullivan Weir & Saville 2002), the test was divided into three scripted parts (the format description being taken from Jones, Waller & Golebiewska 2013: 32):

Part A: The interlocutor asks for mainly general personal information about the candidates (question-answer form). Candidates answer in turn. This stage lasts for approximately two minutes.

Part B: Candidates engage in an interactive discussion based on two written statements. The interlocutor does not take part. This stage lasts for approximately four minutes.

Part C: Candidates discuss questions related to the topic in Part B both together and with the examiner. This stage lasts for approximately four minutes.

The C1 tests were transcribed using the CANCODE transcription conventions (Adolphs 2008) to facilitate analysis. Accessible to prospective readers, and still precise and reliable for illustrating interactions between the candidates and interlocutors, they were conducive to analysis during explorations of data which often involved the omission of interlocutor data. Once transcribed, data were subjected to various analyses. A lexical profile (Laufer & Nation 1995) was first created, using the Compleat Lexical Tutor (Cobb 2014) to identify the percentage of words used, belonging to the first and second thousand most frequent words in the spoken BNC (Leech, Rayson & Wilson 2001) alongside calculations of token-type ratios to allow for preliminary comparisons of lexical repetition. Wordsmith Tools (Scott 2014) software was utilised to calculate word frequency and keyword lists which employed a keyness ratio of 1:50 (Chung & Nation 2004) and the spoken BNC as a reference. To answer the final part of the second research question, three- and four-word lexical chunks were then sorted according to their frequency via Anthony’s (2014) Antconc software. The final stage involved a qualitative analysis of learner language, using NVIVO software (QSR 2012). This helped to determine the occurrence of relevant, spoken C1 can-do descriptors and the language used to realise them. Relevant speaking descriptors were taken from the production, interaction and strategy use sections of the CEFR (CoE 2001: 58-87).

4. Results and Discussion

4.1 Research Question 1 (RQ1)

Research Question 1 was the following one:

What percentage of the words used by C1 learners come from the first thousand and second thousand most frequent words in the spoken BNC?

The percentage of words from the first thousand (K-1) and second thousand (K-2) most frequent words in English are shown in Table 1 below:

Tab. 1: Percentage of words from the first and second thousand most frequent English

words

As can be seen, a cumulative majority of words, 96.91%, originated from the first 2000 most frequent words in English. Although this majority is dominated by words from the K-1 band, in sum, the data still demonstrate that less than one in every twenty words belonged to bands beyond the 2000 word limit. For students to be successful at C1 level, therefore, it is crucial that candidates have knowledge of words originating from the K-1 and K-2 bands, an assertion supported by several writers (McCarthy 1999, O’Keefe, McCarthy & Carter 2007).

Further insights into C1 success can also be obtained by examining the coverage provided by word families: groups consisting of headwords, their inflections and derivations (Nation 2001, Nagy et al, 1989). Whilst it is acknowledged that learners require a wide-ranging vocabulary in order to satisfy long-term learning goals (Nation 2001), much research recognises the need for students to make use of a limited, useful vocabulary, a vocabulary which is continually repeated and recycled in order to satisfy a range of spoken and written functions (Nation 2001, Nation & Waring 1997, Cobb n.d.). Such a useful vocabulary in English is said to mostly comprise the first 2000 word families: in written texts, this figure provides a coverage of approximately 80% (Francis & Kucera 1982, Cobb n.d., Nation & Waring 1997, Nation 2001), whilst in unscripted spoken texts, the percentage coverage rises to 96% (Adolphs & Schmitt 2004) or 97% (Schonell et al, 1956, cited in Adolphs & Schmitt 2004). The data in Table 1 indicate that K-1 word families (58.48%) and K-2 word families (22.74%) only supplied a combined coverage of 81%. This figure, greatly reduced in comparison with the estimations of Schonell et al. (1956) and Adolphs & Schmitt (2004), is, however, somewhat anticipated. C1 learners will not have a vocabulary breadth comparable to that of native speakers, nor will they be able to draw on an equal, or readily available, knowledge of the inflections or derivations belonging to a particular headword.

The above deduction could therefore have implications for the expectations placed upon successful C1 learners in relation to CEFR descriptors. With C1 encompassed by the proficient user label in the CEFR (CoE, 2001: 23), it may be easy to assume candidates to be able to employ more advanced lexis. However, with such a high proportion of K-1 and K-2 words and a type-token ratio of 14, which suggests a certain degree of repetition at this level, emphasis might not be placed on the advanced nature of vocabulary, but on the flexibility and frequency with which the first 2000 words can be used as per the C1 level descriptor presented earlier. For instance, although example statements such as the excerpt below do not seem impressive in terms of lexical difficulty (bold type represents words beyond K-2), they do contain vocabulary which i) meets the demands of the task and ii) can be reproduced for use in other parts of the test[1]:

Example:

<$3M> Okay can I go first? Okay erm tourism in my country is not really important why because erm my country has a lot of problems like erm there are a lot of things that er need to be atte= attended to before tourism so basically what they are focussing on is not tourism at all they are trying to focus on agriculture and the production the industries and the rest so like tourism is like neglected in my country.

4.2 Research Question 2a:

What were the twenty most frequent words used by successful learners at C1 level?

Tab. 2: Most frequent words used by successful C1 learners

Upon initial inspection, these word frequency results may seem rather unsurprising. When compared with frequency lists for the spoken BNC (Leech, Rayson & Wilson 2001) and the Cambridge and Nottingham Corpus of Discourse in English [CANCODE] (2012), there are many parallels; the C1 list seems typical of what is expected in native spoken language. Discussion here will focus on those entries which are absent in the spoken BNC and CANCODE most frequent 20 words, namely ‘erm’, ‘think’, ‘so’ and ‘because’.

Firstly, the CEFR C1 descriptor clearly states its position regarding hesitancy: fluent expression should be executed “without much obvious searching” (CoE 2001: 27). The fillers er and erm, nevertheless, occupy the second and the sixth position, respectively, in the C1 frequency list. This, too, is rather predictable in that of a variety of “performance additions” such as fillers, discourse markers and delays, er and erm are regarded as the most common (Clark & Foxtree 2002: 74). They can also be used to cope with memory demands which can cause uncertainty, delay or inability when answering questions (Smith & Clark 1993), and it can be assumed that learners will have to exploit a much narrower vocabulary to fulfil their linguistic needs, a task potentially increasing the occurrence of pauses. While delaying expressions such as well, what do you call it and how will I put it are found in the C1 data, they are not as flexible as er and erm; arguably, they may neither seem as natural. Ultimately, despite the C1 descriptor, it should be expected that successful C1 students will still use er and erm frequently.

Developing from hesitation, it is relevant to discuss how word frequency may be influenced by the nature of the C1 exam and the task demands placed upon candidates. For instance, words such as think, so and because would be expected in an exam which frequently elicits opinions and reasonings in order to assess abilities to “formulate ideas and opinions with precision” (CoE 2001: 27). In the case of think (38th position in CANCODE; 46th position in the spoken BNC), the data and the aims of some vocabulary instruction for giving opinions may conflict. Some exercises make an effort to present learners with alternatives to I think which represented 260 occurrences in the C1 data, such as in my opinion (ten occurrences), I believe (seven occurrences), from my point of view (one occurrence) and as far as I’m concerned or if you asked me (zero occurrences). In the C1 data, these other forms were heavily eclipsed in terms of frequency. This finding raises the question as to whether students should be expected to use these alternative phrases when I think delivers success at C1. It may seem basic, but it is efficient and more target-like when compared with NS corpus data.

C1 descriptors also require learners to provide sufficient conclusions to their utterances. A productive can-do statement looks for evidence that C1 learners are able to supply an “appropriate conclusion” to “round-off” their arguments (CoE 2001: 27). In relation to task demands, this can offer some explanation as to why the conjunction so appears frequently in the C1 corpus (in the spoken BNC, this function occupied 274th position). Corresponding to word usage for expressing purpose, as documented in Carter & McCarthy’s Cambridge Grammar of English (2006: 143), a high majority of occurrences of so did involve its use as a subordinating conjunction to introduce “result, consequence and purpose”. Whilst this contrasts greatly from Carter & McCarthy’s (2006) observation that so in NS spoken English is used most frequently as a discourse marker (e.g. so what are we supposed to be doing?), the C1 data show that not only is this usage very frequent, but that this could be a direct result of the demands placed upon students by the exam tasks. Similarly, the high frequency of because in the C1 data should have been foreseeable; students are repeatedly asked for explanations for their opinions. Also, although cos does appear in the C1 frequency data (76th position) and its use is expected in informal speech (Carter & McCarthy 2006), because is used more often to give reasons and extra information in support of opinions in the main clause, as in the following example (words in bold have been discussed in this section):

Examples:

<$11F> I think if you er put a bins and it er has a labels or er write about which one is er for recycling mm people will do right so I think it's a good way to protect the environment. How about you?

<$12F> Okay I take your point but erm this is some problem about the bins because erm I often see a lot of people they can't recognise the symbol on the bins because erm they sometimes they walking on the road they just erm keep they eyesight in the street so they can't erm remember the symbol on the bins.

A final finding to be highlighted here refers to a notable difference in the C1 data which contrasts the findings of Jones, Waller and Golebiewska’s (2013) study into UCLanESB’s B2 spoken test data. Despite the arguable value of teaching students high frequency verbs such as go, have and do (Willis 1990) for use as full, auxiliary and delexicalized verbs (Lewis 1993, 1997), such verbs did not appear in the most frequent C1 words seen in Table 2. In fact, go, although still much more frequently used than have and do in the B2 data, only appears in 49th position. Such a finding may initially suggest that C1 students have a greater repertoire of vocabulary that can satisfy similar meanings or functions. Although this would require greater exploration, this conclusion may appear valid in the C1 data, especially when the low occurrence of circumlocution and paraphrase (see RQ3; findings) is considered. The successful C1 students in this study may, therefore, have demonstrated the necessary “good command” of vocabulary to satisfy the CoE’s (2001: 28) C1 descriptor of range.

4.3 Research Question 2b

What were the important keywords at C1 level?

Tab. 3: Top 20 keywords used by successful C1 learners

Preliminary observation seems to corroborate conclusions from the examination of the frequency lists. Not only do words such as er, erm, think, like, so and because appear much more highly in the C1 frequency lists when compared to the reference corpora lists used, but they also seem to be of particular significance to the success of C1 test candidates. Once again, the implied importance of these words could be a product of test design and the task demands placed on students. It could also be assumed that the keyword ranking of this lexis could be due to their fluctuating usage: their high frequency and usefulness not only corresponds to the nature of the C1 exam, but also to the valuable range of functions the words fulfil for successful candidates.

For instance, the cases of think and like may demonstrate the variety afforded, a variety which may help to satisfy criteria relating to C1 expectations of students to be able to use language “flexibly and effectively” (CoE 2001: 27). When exploring Key Word In Context (KWIC) concordance data to discover the way in which these words were used, think and like varied. Unsurprisingly, think was used to give and obtain opinions throughout the exam (the most frequent question asked by students was What do you think?). As the examples below demonstrate, it also was utilised to create hedging phrases, expressions of uncertainty, and it was occasionally modified to add emphasis:

Examples:

<$7F> Yeah it will help the environment environment I think.

<$2M> Erm I really think that this is the most important bit about the hotel er the place where I would spend the night if it's er I really think that if erm the room's totally quiet like the walls are too thick that the sound can't pass over them <$O2> it's perfect for me </$O2>

In relation to like, it became increasingly apparent, when scrutinising the KWIC data that its use not only altered according to its word class, but also according to the exam section. The data showed that like was used as a lexical verb, a preposition, and as a filler (as shown below):

Examples:

<$19M> Er usually I like [verb] light music and pop music. The light music er especially for before I go to bed and pop music for example when I travelling somewhere I usually use my headphones to listen it.

<$29M> Well first of all I live in Qatar it's a sm= small country and my neighbourhood is actually in <$G3> it's in Doha so it's like [preposition] any normal neighbourhood in the world

<$24M> But for me like [filler] all these are related like [preposition] stress rent smoking and maybe you you have stress because you don't sleep enough.

Like allowed students to provide examples and analogies and it also acted as a filler during voiced pauses (Carter & McCarthy 2006). Although it was predominantly used as a lexical verb in Part A of the exam, its usage in parts B and C changed when it began to be used more as a filler, similar to the way young native speakers use it today (Carter & McCarthy 2006). Since Part B removes the interlocutor’s support and Part C “aims to push candidates towards their linguistic ceiling” (Jones, Waller & Golebiewska 2013: 33), it is anticipated that the occurrence of pauses will increase. However, at C1, perhaps the use of like in this way evidences a mastering or attempts by learners to employ NS filler lexis.

4.4 Research Question 2c

What were the most frequent three- and four-word chunks used by these learners?

Table 4 presents the most frequent three- and four-word chunks used by successful C1 students. The chunks in bold also appeared in the top 20 in the spoken BNC’s chunk data (Adolphs & Carter 2013):

Tab. 4: Most frequent three- and four-word chunks

An initial comparison of the C1 results above and the 20 most frequent chunks in the BNC (Adolphs & Carter 2013) and CANCODE (McCarthy 2006) reveal that whilst chunk frequency was relatively low in the C1 data, there is evidence that successful candidates replicate some of the most common chunks typical of NS speech.

With regards to the composition of the C1 chunks, the data suggest that they represent another way in which knowledge of the K-1 and K-2 word families can be exploited. A profile using the Compleat Lexical Tutor revealed that 94% of three- and four-word chunk lexis originated from the K-1 band, task-related lexis from the K-2 (e.g. location and hotel) constituted 4%, and erm (2%) was considered off-list. A similar analysis of the BNC’s most frequent three- and four-word chunk lexis determined that 100% of the words came from the K-1 band. To make use of chunks, therefore, no complex, less-familiar vocabulary is needed; although NS chunks may prove problematic for learners to “identify and master” (Wray 2000: 176), the lexis they comprise should correspond to the vocabulary that C1 students already possess.

Lexical chunks are also deemed advantageous for their impact on fluency, memory and, particularly, listener perceptions of proficiency (Schmitt 2000, Boers et al. 2006, Wray 2000). Chunks are believed to be stored holistically, their availability demands less cognitive capacity and they can “transform” perceptions even of low-level learners’ fluency (O’Keefe, McCarthy & Carter 2007: 77). The fact that they appear in C1 speech, although less frequently than in B2 speech (Jones, Waller & Golebiewska 2013) may show that they could be a component of successful C1 candidates being judged to be fluent and spontaneous (CoE 2001). Furthermore, they are flexible and perform a range of lexical and functional roles (see RQ 3) and they can, at C1, include fillers. Although lexical chunks are usually identified through a lack of hesitation (Ellis & Sinclair 1996), C1 students may be able to give the impression of fluency despite the use of vocalised fillers. Ultimately, students who are able to incorporate chunks into their production will be seen as more proficient and more successful to those who cannot (Boers et al. 2006).

4.5 Research Question 3

What C1 CEFR indicators are present in terms of spoken interaction, spoken production and strategies?

A qualitative analysis of the C1 test data aimed to establish which speaking can-do statements were demonstrated for production, interaction and strategy use. Although students received solid pass grades which denoted a certain degree of achievement, it was necessary to see how their exam performance corresponded to CEFR descriptors. The corpus data have already identified the lexis contained in their language, but success also involves learning what the C1 students actually did with their language.

Fig. 1: C1 can-do occurrence across all parts of the exam

Of 660 can-do instances, approximately 45% related to production. Although the nature of the test did influence this category (there was less evidence of sub-theme integrations, conclusions, speculation and outlining of issues in the shorter, less demanding section, Part A), the data suggest that C1 candidates should develop and lengthen their answers to demonstrate productive abilities if they are to be considered successful. Although the CEFR does not specify for which ‘complex subjects’ this should be done, the example statement below does illustrate how this could be achieved.

Example:

<$3M> Okay erm immediate transport problems in my country would be the fact that <$=> erm the erm <$G?> </$=> it would be er like the transportation agency or should I say like erm the people er like that handle transport are not very strict. Erm young people like er people like four years older younger than me like sixteen years olds or fifteen year olds are allowed to drive. Basically it's not allowed in the er law in my country but even if you're fifteen or thirteen they could drive around in a car and if like a policeman should stop you or a road safety person should stop you you could bribe them like really low amounts like anybody could afford it and they will let you go.

It was also pertinent to note that interactive and strategic can-do language occasionally appeared similar across some learners in the sample. For instance, some candidates employed the same lexical chunks, although somewhat low in terms of frequency, to satisfy the demands placed upon them. In order to develop the progress of the exam and invite responses (interaction) the chunk what do you (20 occurrences) was combined with think, admire, feel and reckon. This particular chunk may afford the students a greater degree of fluency and flexibility; it may not require additional processing and it is a chunk which may be adapted via the inclusion of a “slot” or space for numerous words depending on the desired meaning (Schmitt 2000: 400). Students also showed similarity in the way they used language to gain time during the exam. The chunk I agree with (22 occurrences) was judged to be a stalling technique on eleven occasions and a quarter of instances of er I think, erm I think, and I think erm were used as a delaying tactic. Although phrases like let’s say…, what do you call it and how will I put it were found. Perhaps this final finding may support claims that the teaching of chunks should concentrate on multifunctional phrases which can be of maximum benefit and of maximum flexibility at C1. Furthermore, chunks which appear to be lexically important but which additionally have a functional capacity could also be a feature for instruction since chunks offer a degree of efficiency, relevance and familiarity which may help to develop pragmatic competence (Schmitt 2000).

5 Conclusion

The findings outlined here have various implications for language pedagogy and success in learning English. Vocabulary used by the C1 learners stemmed mostly from the first thousand words of the BNC. Being successful in speech seems to advocate a fundamental need for students to learn these words. It may also justify Nation’s (2001: 16) claim that such lexis should receive “considerable” attention since words beyond K-2 do not yield great profit in terms of occurrence. Pedagogy could therefore supplement learners in two ways:

· Firstly, as per Nation’s advice, classroom time could be maximised by exposing students to more frequent vocabulary.

· Secondly, teachers and successful language learners could impart their knowledge of language learning strategies. These readily available tools for language learning may help learners exploit their target language knowledge, they can extend learning in and out of the classroom and they are themselves believed to be a sign of a successful language learner (Griffiths 2004, Oxford 1994, Oxford & Nyikos 1989). Specific strategies related to guessing word meaning from context, remembering words and using materials such as dictionaries and wordlists may result in greater efficiency for teaching and learning low-frequency vocabulary.

Another implication relates to the treatment of vocabulary by learners. Since many learners “rely far more on word-by-word processing” (Foster, Tonkyn & Wigglesworth 2000: 356), pedagogy could make students more aware of the value of learning vocabulary in chunks instead of on an individual basis (Boers et al. 2006). Successful C1 students were able to employ some lexical chunks in their speech. Not only did most of these chunks employ lexis from the K-1 category, but they also assisted in the realisation of some CEFR can-do statements and they may have given the assessor a greater impression of fluency and proficiency. Introducing learners to chunks used frequently by native speakers and successful learners in speech may allow them to take full advantage of their positive effects. If attention is also paid to the way in which chunks can be multifunctional, students once again could apprehend and reach the full potential of their English vocabulary.

With regards exam performance, this study could offer C1 learners some valuable advice. Although some students, teachers and indeed some assessors may discourage and disapprove of hesitation, it was found that successful candidates did still exercise delaying techniques. Er and erm were amongst the most frequent words used; phrases such as I think and I agree with you were also used to fill pauses. Although the CEFR places importance on spontaneous and fluent speech at C1, candidates can still pass and be successful despite some hesitation. With regards to the occurrence of can-do descriptors, successful C1 learners evidenced their productive abilities more frequently than interactive and strategic criteria. It is the author’s experience that learners are taught not to give one-word answers; it could also be suggested that practitioners should go beyond this and provide students with relevant examples from learner or native corpora as to how more detailed answers could be achieved. For instance, students may assume that greater complexity is needed to develop ideas. The data, however, demonstrated that productive language often involved the use of simple contractions such as because and so to connect ideas.

Finally, it remains to be acknowledged that this study involved a rather small corpus. Additional research with an increased corpus size is needed. A comparison of C1 data with other levels in the CEFR is also required so that speaking exam success at different stages can be examined and then compared to identify areas of similarity and contrast. Such research could also provide a platform for subsequent investigations which would reveal more about exam performance for the benefit of teachers, researchers, course developers and, of course, students.

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Author:

Shelley Byrne

Associate lecturer

University of Central Lancashire

E-mail: sbyrne@uclan.ac.uk

[1] Key for samples: $0 = interlocutor, $2M/$3M etc = male candidate, $2F/$3F = female candidate.