Mastering academic writing is not an easy task for learners, especially when the language they have to use is not their mother tongue. Not only do they have to acquire a specialised vocabulary, but they also have to find an appropriate voice, one that will be accepted by the academic community as a whole. It has been suggested in the literature that one of the problems non-native speakers experience in this latter respect is their lack of register awareness (see e.g. Altenberg 1998, Granger & Rayson 1998). This issue will be investigated here through the study of language functions particularly prominent in academic writing, such as expressing one's own opinion, quoting other people's work or concluding a piece of writing. More precisely, non-native learner writing will be examined with respect to medium variation, comparing data from the International Corpus of Learner English (Granger et al. 2002) with native academic writing and spoken interaction from the British National Corpus. The analysis reveals a clear tendency among non-native learners to produce words and structures that are more typical of speech than of academic writing. To give but a couple of examples, they often use 'say' as a reporting verb and prefer amplifying to downtoning adverbs, thereby constructing an inappropriately informal voice. While this tendency can partly be explained by non-native learners' lack of intuition regarding the distinction between casual speech and formal writing (see Lorenz 1999), we argue on the basis of data from the LOCNESS (Louvain Corpus of Native English Essays) that it is also characteristic of novice writers, whether native or non-native, and that this is part of the process of acquiring an academic voice and becoming expert writers. We suggest that one way of helping learners to find their voice in academic writing is to show them how to lose it, that is how to turn their 'voice' (spoken word) into academic 'writing'. To this end, their attention should be drawn to medium variation and in particular to the differences that exist between academic writing and spoken interaction. Some consciousness-raising activities will be proposed that aim to achieve this purpose.
Writing idiomatic academic texts in English is a challenge faced by an increasing number of international students and scholars. In this article, we present a web-based dictionary-cum-writing aid tool, the Louvain English for Academic Purposes Dictionary, which aims to address the attested needs of non-native writers of English, with a particular focus on the phraseological patterning of academic words. First, we present the general design of the dictionary, highlighting four of its main features, i.e. the fact that it is corpus-based, production-oriented, hybrid and customizable. We then describe key aspects of the macro- and microstructure and highlight innovative features of the access structure, such as direct access to discipline-specific corpora. The conclusion outlines some important priorities for the future, in particular the need for validation and the desirability of integrating the dictionary into a wider learning environment.
Learner errors have typically been traced back to the learner’s first language (i.e., interlingual errors) or to more general learning processes and pathways (i.e., intralingual errors). The entry first provides some historical background and shows how the understanding of learner errors has evolved with time and theoretical models, followed by a discussion of the implications for such an understanding for pedagogy in TESOL.
Abstract Background Forums in massive open online courses (MOOCs) enable written exchanges on course content; hence, they can potentially facilitate learners' cognitive engagement. Given the myriad of MOOC forum messages, this engagement is commonly analysed automatically through the linguistic features of the messages. Assessing linguistic features of learners' forum messages involves consideration of the learning tasks. MOOC forum discussion tasks, however, have not been previously considered. Objective and Method This study explores the effects of MOOC forum discussion tasks on learners' cognitive engagement. Based on the structure of observed learning outcomes (SOLO) taxonomy, we manually annotate distinct levels of cognitive engagement encouraged in forum discussion tasks and displayed by learners in messages starting discussions (i.e., thread starters). We study the linguistic features of thread starters in relation to the pedagogical design of the discussion tasks. Additionally, we use random‐forest modelling to identify the linguistic and task‐related features that help to categorise learners' cognitive engagement according to SOLO levels. Results Manual analysis showed that learners' thread starters mainly reflect surface SOLO levels and include few academic words and cohesive language. Random‐forest modelling showed that these linguistic features, together with the SOLO levels encouraged in the discussion tasks, played an important role in identification of learners' cognitive engagement. Major Takeaways Our results highlight the importance of the pedagogical design of MOOC forum tasks in helping learners engage cognitively. Our study also contributes to the empirical evidence that learners' linguistic choices can afford insights into the quality of their cognitive engagement.
Advances in Learner Corpus Research (LCR) and Second Language Acquisition (SLA) have brought these two fast-moving fields significantly closer in recent years. This volume brings together contributions from internationally recognized experts in both LCR and SLA to provide an innovative, cross-collaborative examination of how both areas can provide rich insights for the other. Chapters present recent advances in LCR and illustrate in a clear and accessible style how these can be exploited for the study of a broad range of key topics in SLA, such as complexity, tense and aspect, cross-linguistic influence vs. universal processes, phraseology and variability. It concludes with two commentary chapters written by eminent scholars, one from the perspective of SLA, the other from the perspective of LCR, allowing researchers and students alike to reflect upon the mutually beneficial harmony between the two fields and link up LCR and SLA research and theory.
The field of lexicography is undergoing a major revolution. The rapid replacement of the traditional paper dictionary by electronic dictionaries opens up exciting possibilities but also constitutes a major challenge to the field. The 'eLexicography in the 21st Century: New Challenges, New Applications' conference organized by the Centre for English Corpus Linguistics of the Universite catholique de Louvain in October 2009 aimed to bring together the many researchers around the world who are working in the fast developing field of electronic lexicography and to act as a showcase for the latest lexicographic developments and software solutions in the field. The conference attracted both academics and industrial partners from 30 different countries who presented electronic dictionary projects dealing with no less than 22 languages. The resulting proceedings volume bears witness to the tremendous vitality and diversity of research in the field. The volume covers a wide range of topics, including: - the use of language resources for lexicographic purposes, in the form of lexical databases like WordNet or corpora of different types - innovative changes to the dictionary structure afforded by the electronic medium, in particular multiple access routes and efficient integration of phraseology - specialised dictionaries (e.g. SMS dictionaries, sign language dictionaries) - automated customisation of dictionaries in function of users' needs - exploitation of Natural Language Processing tools - integration of electronic dictionaries into language learning and teaching tools
Recent studies in English for Academic Purposes (EAP) have brought to light a high degree of variation across academic texts and led some authors to question the usefulness of a general EAP approach. Some highlight differences between disciplines (e.g. Hyland 2000) or even sub-disciplines (e.g. Ozturk 2007). Others show that the use of linguistic features varies across text types (e.g. Hyland and Tse 2007) and sections (e.g. Martinez 2003). These findings pose a tremendous challenge to ELT practitioners who are regularly faced with mixed groups of students, most notably in EAP programmes for international students. In addition, general EAP textbooks have been criticized for being a poor reflection of authentic use (Paltridge 2002). Teachers and material designers arguably need more corpus-based research into the nature and extent of General Academic English. In our presentation we will report the preliminary results of the investigation of a new ESP corpus, the 'Varieties of English for Specific Purposes DAtabase' (VESPA), which contains scientific articles from top journals in three domains: business, medicine and linguistics. We will extract the lexical verbs from the three subcorpora and analyse them with a view to identifying the similarities and differences between them and extracting a common core that can be taught in a general EAP context. The investigation is part of a wider study into EAP vocabulary (De Cock et al 2007; Gilquin et al 2007; Paquot 2007) and is a follow up of a previous study that compares the use of lexical verbs in academic writing by native writers and intermediate/advanced EFL learners (Granger & Paquot forthcoming).
In this presentation, we will introduce the Louvain English for Academic Purposes dictionary (LEAD), viz. a customisable web-based dictionary-cum-writing-aid tool. The LEAD aims to meet the growing needs of non-native speakers, be they students of English or researchers, who have to write academic texts that conform to the established conventions of the genre (more particularly its phraseology). The dictionary contains a rich corpus-based description of c. 900 academic words from the Academic Keyword List (Paquot, 2010) that express key functions in academic discourse. The list contains nouns (e.g. issue, contrast, parallel), verbs (argue, discuss, emerge), adjectives (differing, opposite), adverbs (namely, notably, however), prepositions (despite, such as) and conjunctions (while, albeit). To extract the phraseology (collocations and recurrent phrases) of these words, we made use of large corpora of academic texts, in particular the academic component of the British National Corpus which we supplemented with a number of home-made discipline-specific corpora. We also made use of the International Corpus of Learner English (Granger et al., 2009) to identify EFL learners’ difficulties in using these particular words. The main originality of the LEAD is its customisability: the content is automatically adapted to users’ needs in terms of discipline and mother tongue background. Before using the dictionary, users have to select a domain (currently business, medicine, linguistics) and specify their L1 background (currently French and Dutch). Domain selection makes it possible to customise the output and illustrate the phraseological environment of a search word by means of example sentences automatically extracted from a corpus of either business, medicine or linguistics texts. One of the purposes of L1-background identification is to give feedback on errors and problems that a specific L1 population typically encounters. The dictionary is not only corpus-informed but can also be described as a dictionary-cum-corpus as users have direct access to discipline-specific corpora. We make use of a new open source web-based corpus analysis system, viz. CQPweb, developed by A. Hardie (Hardie, 2009) for two main purposes: - give access to concordances of academic words and their collocations to provide users with more examples and make it possible for them to check whether a collocation or phrase that is not in the LEAD is correct or not; - query words that are not in the LEAD so that users can check how to use a word even though it is not in the dictionary. As we are focusing on a very specific and quite limited vocabulary, we want to be able to provide another kind of feedback than the very frustrating “No match found!” when the search word is not in the dictionary. The automatic customisation of the dictionary to users’ discipline and L1 coupled with direct corpus access makes it a particularly dynamic tool. The inclusion of error warnings and targeted exercises gives it the status of a hybrid tool, i.e. both a dictionary and a learning resource. The LEAD is also a highly flexible tool, which could easily be customised to other L1 background populations, other disciplines, and other languages. References Granger, S., Dagneaux, E., Meunier, F. & Paquot, M. (2009). The International Corpus of Learner English. Handbook and CD-ROM. Version 2. Louvain-la-Neuve: Presses universitaires de Louvain. Hardie, A. (2009). ‘CQPweb – combining power, flexibility and usability in a corpus analysis tool’. Paper presented at the 30th ICAME conference, Lancaster, 27-31 May 2009. Paquot, M. (2010). Academic Vocabulary in Learner Writing: From Extraction to Analysis. London & New-York: Continuum
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