By Magali Paquot
An research of educational vocabulary within the overseas Corpus of Learner English. >
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Extra info for Academic Vocabulary in Learner Writing: From Extraction to Analysis (Corpus And Discourse)
2. Annotate: manual or automatic analysis of the corpus. 30 Academic Vocabulary in Learner Writing 3. Retrieve: quantitative and qualitative analyses of the corpus. 4. Question: devise a research question or model (iteration back to Step 3). 5. Interpret: interpretation of the results or confirmation of the accuracy of the model. Studies that make use of the data-driven approach first focus on whole texts (Step 3) and then refine the research question or suggest specific linguistic features to study in further detail (Step 4).
To achieve this coverage, it is commonly believed that students in higher education settings need to master three lists of vocabulary: a core vocabulary of 2,000 high-frequency words, plus some academic words, and technical terms. Some researchers, however, do not agree that vocabulary categories can be described as if they were clearly separable. In this section, the notions of core vocabulary, academic vocabulary and technical terms are described and illustrated. The criticisms levelled at the division of vocabulary into mutually exclusive lists are then reviewed.
It relies on pre-existing part-of-speech tagsets but considers corpus data as ‘the starting point of a path-finding expedition that will allow linguists to uncover new grounds, new categories and formulate new hypotheses on the basis of the patterns that were observed’ (De Cock, 2003: 197). The model is also testimony to the fact that the ‘distinction between the corpus-based vs. corpus-driven approaches to language studies is overstated. , 2006: 8). Following Rayson’s (2008) data-driven approach, I first detail the corpora used (Step 1) and the type of annotation adopted (Step 2).
Academic Vocabulary in Learner Writing: From Extraction to Analysis (Corpus And Discourse) by Magali Paquot