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Identifying key criteria of written and spoken English at C1: A qualitative study of key language points at C1

Abstract

This project set out to identify criterial features of written and spoken English at C1 by examining test data to establish which of the language points included at C1 in the British Council – EAQUALS Core Inventory for General English (the Core Inventory) were produced by the test-takers. The test data were also examined to see if there were recurring language points which had not been included in the Core Inventory. The Core Inventory was created to provide a practical inventory of language points that characterise the levels of the Common European Framework of Reference for Languages: Learning, Teaching, Assessment (CEFR). It includes functions, grammar points, discourse markers, vocabulary and topics. This project aimed to establish if the features included in the Core Inventory were present in test data. The test had been created to satisfy the requirements of an external validation agency. The target level of the test was C1 and so was the test-takers level of language proficiency. This had been established through IELTS scores and scores on pre-sessional course tests. A total of 36 participants took the test which included tasks focused on grammar, lexis and an extended writing task. A test of spoken English was the second part of the test. Aptis test data were also included to increase the scale of the project. The test data were manually coded using qualitative data analysis software. The occurrences of each feature were counted. The Core Inventory contains 35 language points at C1 and six topic areas. This project found that 15 language points could be described as criterial in written and spoken English. One of the C1 topic areas featured consistently in the test data. This would seem to suggest that limited data-based evidence has been found to support an existing theoretical framework. A significant finding of the project is, perhaps, the identification of an approach of establishing criterial language points through use of the Core Inventory. This approach could be replicated with larger data sets across the full range of the CEFR levels discussed in the Core Inventory

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