Back to Search
Start Over
Language assessment and the inseparability of lexis and grammar: Focus on the construct of speaking
- Source :
- Language Testing. 34:477-492
- Publication Year :
- 2017
- Publisher :
- SAGE Publications, 2017.
-
Abstract
- This paper aims to connect recent corpus research on phraseology with current language testing practice. It discusses how corpora and corpus-analytic techniques can illuminate central aspects of speech and help in conceptualizing the notion of lexicogrammar in second language speaking assessment. The description of speech and some of its core features is based on the 1.8-million-word Michigan Corpus of Academic Spoken English (MICASE) and on the 10-million-word spoken component of the British National Corpus (BNC). Analyses of word frequency and keyword lists are followed by an automatic extraction of different types of phraseological items that are particularly common in speech and serve important communicative functions. These corpus explorations provide evidence for the strong interconnectedness of lexical items and grammatical structures in natural language. Based on the assumption that the existence of lexicogrammatical patterns is of relevance for constructs of speaking tests, the paper then reviews rubrics of popular high-stakes speaking tests and critically discusses how far these rubrics capture the central aspects of spoken language identified in the corpus analyses as well as the centrality of phraseology in language. It closes with recommendations for speaking assessment in the light of this characterization of real-world spoken lexicogrammar.
- Subjects :
- 060201 languages & linguistics
Lexis
Linguistics and Language
Grammar
media_common.quotation_subject
05 social sciences
Phrase structure rules
050301 education
Speech corpus
06 humanities and the arts
Language and Linguistics
Linguistics
Corpus linguistics
Language assessment
Phraseology
0602 languages and literature
Computational linguistics
Psychology
0503 education
Social Sciences (miscellaneous)
media_common
Subjects
Details
- ISSN :
- 14770946 and 02655322
- Volume :
- 34
- Database :
- OpenAIRE
- Journal :
- Language Testing
- Accession number :
- edsair.doi...........8ee34930fec2d0f8d2625fbfe0a318a5
- Full Text :
- https://doi.org/10.1177/0265532217711431