The idea of an academic vocabulary has a long history in teaching English for academic or specific purposes Indeed, academic vocabulary is used to refer to items which are reasonably frequent in a wide range of academic genres but are relatively uncommon in other kinds of texts (Coxhead & Nation, 2001).
Many university-level structures regard helping students develop control over such vocabularies as an important part of their role, and attempts have been made to assemble lists of key terms to guide materials writers and help students plan their learning more efficiently. Early ESP materials, for example, sought to identify and present forms with a high frequency in scientific and technical writing (e.g., Barber, 1988; Herbert, 1965) and considerable effort has been devoted to investigating the vocabulary needed for academic study (e.g., Campion & Elley, 1971; Coxhead, 2000; Nation, 1990). Such research is usually based on the assumption that learners are seeking to build a repertoire of specialized academic words in addition to their existing basic or general service vocabulary, and this repertoire building is often seen as the purpose of developing university vocabulary.
2. Literature review
Vocabulary is typically seen as falling into three main groups (Nation, 2001):
High frequency words such as those included in West’s (1953) General Service List (GSL) of the most widely useful 2,000-word families in English, covering about 80% of most texts.
An academic vocabulary of words which are reasonably frequent in academic writing and comprise some 8%-10% of running words in academic texts.
A technical vocabulary which differs by subject area and covers up to 5% of texts.
ESL/EFL students are said to find an academic vocabulary a particularly challenging aspect of their learning (Li & Pemberton, 1994). This aspect of their learning is challenging because, although technical vocabulary is central to students’ specialized areas, general academic vocabulary serves a largely supportive role and the words are “not likely to be glossed by the content teacher” (Flowerdew, 1993, p. 236). Many of these words also occur too infrequently to allow incidental learning (Worthington & Nation, 1996), encouraging researchers and teachers to develop vocabulary lists for directly teaching these terms.
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3. Problem statement
Shiraz Paramedical and Medical Universities as leading research intensive public universities offer undergraduates and postgraduate courses to both national and international students. To participate effectively in the research-oriented environment of higher education, they have to understand lectures, participate in class discussions, read course texts, and write research papers. In developing those necessary study skills, they must possess a high level of language proficiency including a great command of academic and technical words.
Although there are many academic word lists available, however, unfortunately, these lists are not publicly available because publishers do not want rival publishers to get hold of their lists. This of course makes it more difficult for university lecturers to prepare their students for such advanced readings. Furthermore, it has been argued that individual lexical items on the lists often occur and behave in different ways across disciplines and that words commonly contribute to ‘lexical bundles’ which also reflect disciplinary preferences. Hence, for example high frequency words such as those included in Coxhead’s Academic Corpus are still considered general and might not really show the same preference or tendency towards medical science disciplines. Ignoring important differences in the collocational and semantic behavior of words in different disciplines might seriously mislead our medical students.
Not mastering the relevant academic word list, particularly for medical students may cause many problems that are explained in the following. The presence of unfamiliar words and expressions in academic texts is a serious obstacle to EFL learners’ reading in a foreign language. Although university students may pass entrance exam, it has been argued that the limitations in academic vocabulary knowledge hamper their ability to produce essays where transferring information requires effective vocabulary use in an academic environment (Kaur & Hegelmeir, 2005).
Academic words are said to pose a challenge for many ESL and EFL students because of their lack of salience and relative low frequency. Unlike technical or discipline specific words, academic words (e.g. analyse, inherent) play a supportive rather than a central role in constructing the meaning of a text (Coxhead, 2000). Furthermore, their low frequency means that they are unlikely to be learnt incidentally (Worthington & Nation, 1996).
Since at university level, student researchers need to publish in international refereed journals both for career advancement and to get financial support, this requirement has turned into a problem, as the chances of publishing in indexed journals have become extremely difficult for students that their academic vocabulary knowledge is not broad enough.
1. To find out the distributions of academic vocabulary used in medical science.
2. To investigate the distributions and the categories of words that collocates with academic vocabularies in medical science.
3. To investigate the distributions and the semantic functions of academic vocabulary used in medical science.
4. To compare and contrast the high frequency words in medical corpus (the one which are going to be build) and the pedagogic corpus (General English I, II, and specific English textbooks).
5. Significance of the Study
Knowing which words are the most useful words at each stage of proficiency clearly has benefits for curriculum designers and writers of university course books. However, the value of word lists goes beyond this. The findings of this study can be mainly beneficial for designing courses. This specialized academic word list is designed to pool together a list and word families that our university medical students would likely encounter in academic texts; these are word families that are not subject-specific enough to be found across multiple areas of research, and these are also word families there are not included in the General Service List (GSL). Hence, this list provides data that can guide the sequencing of words and groups of words in English for Specific Purposes (ESP) courses, so that at any level in the course our university students are getting the best return for their learning effort.
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The findings of this study can be published as a reference book for medical students in order to inspire them to have scheduled vocabulary lessons independently and to ensure that they have the academic background knowledge they need to understand the content they will encounter in their courses. This in turn, will equip them with enough background knowledge to write for publication in English.
6.1. The development of the medical corpus
Research in corpus linguistics has shown that the linguistic features of texts differ across registers. Perhaps the most notable of these features is vocabulary. To describe the vocabulary of a particular register, such as academic texts, the corpus must therefore contain texts that are representative of the varieties of texts they are intended to reflect (Atkins, Clear, & Ostler, 1992; Biber, 1993; Sinclair, 1991). Sinclair (1991) warns that a corpus should contain texts whose size and shapes accurately reflect the texts they represent. He further posits that if long texts are included in a corpus, “peculiarities of an individual style or topic occasionally show through” (p.19), particularly through vocabulary. Making use of a variety of short text allows more variation in vocabulary (Sutarsyah, Nation, & Kennedy, 1994). Inclusion of texts written by a variety of writers help neutralise bias that may result from idiosyncratic style of one writer (Atkins et al., 1992; Sinclair 1991) and increases the number of lexical items in the corpus (Sutarsyah et al, 1994). Therefore for this study the most used reference books in medicine (perhaps 3 textbooks) and research articles in the medical science are going to be compiled to build a representative corpus of long and short texts.
The exact amount of language required, of course, depends on the purpose and use of the research; however, in general more language means that more information can be gathered about lexical items and more words in context can be examined in depth. In the current study it is planned to gather approximately 2 million running words. The corpus is representative of a genre, and of a discipline, medicine. It will consist of articles taken from the on-line versions of journals indexed by the Science Citation Index (SCI) Report. The corpus is going to contain X number of articles produced academics working in English-speaking universities, and selected from journals published between 2007 and 2012, which were specifically recommended by subject specialists at Shiraz Medical University. The articles will have the Introduction-Method-Results-Discussion format (IMRD, Swales, 1990). The documents are going to be prepared to be accessed as whole texts or as individual sections (sub-corpora). Numbers, abstracts, acknowledgements, references, captions and appendices will be excluded from the word count. The units of analysis are tokens, types and families. Types are defined as single word forms; tokens as the number of occurrences of each type; and families as a collection of formally and semantically related word types (Bauer & Nation, 1993, in Chung & Nation, 2003).
6.2. The development of the pedagogic corpus
Since one of the objectives of this research is to investigate the overlap between high frequency words in our reference corpus and the three textbooks that are currently taught at Shiraz medical university, making another corpus which consists these three textbooks is necessary. To make this pedagogic corpus, the soft copy of 1) General English I, 2) General English II, and 3) English in Medicine textbooks are going to be converted into a Tagged Image File (TIF) format. This will then be saved and processed with Optical Character Recognition (OCR) software, which convert all TIF files into text files (.txt). The txt files will then be checked for errors before saving and renaming them according to the respective units of the textbook.
6.3. The software for analysis
The WordSmith Tools Version 4.0 will be used almost entirely for the purpose of this research, because it has been recognized as a capable and suitable tool to support quantitative and qualitative data analysis by many researchers (Baker, 2006; Bondi, 2001; De Klerk, 2004; Flowerdew, 2003; Henry & Roseberry, 2001; Menon, 2009, to name a few).
WordSmith Tools Version 4.0 is a relatively small, but undoubtedly useful piece of software running on a personal computer. The programs in WordSmith Toolscan handle virtually unlimited amounts of text. They can read text from CD-ROMs, so giving access to corpora containing many millions of words. The main advantage of WordSmith Tools is that it displays the output directly on the screen. The output can also be saved as a file and printed out. WordSmith Tool scan be used not only on plain English texts, but also on texts in other languages, and on English texts with grammatical encoding. The functions of the WordSmith Tools include frequency listing, alphabetical listing, keyword in context (KWIC) analysis, further searching on both sides of the keywords, and closer investigation of the target items in larger contexts (Reppen, 2001).
6.4. Data processing and analysis
For the purpose of this study, first the frequency and distribution of word types and tokens in the corpus will be determined. Also, qualitative observations are going to be made about the particular behaviour of certain specific words.
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