Corpus-based approach to developing teaching materials for aerospace english

Abstract

It is widely known that academic English is used for specific purposes in cross-cultural communication between scientists. Simultaneously, there is a shortage of teaching materials, leading to a demand for the development of such materials. A remote-sensing field was chosen for this study. This study describes the results of a corpus-based analysis of academic vocabulary in remote sensing articles. The research was conducted using corpus linguistics methods and distributive statistical analysis, and a corpus manager, Sketch Engine, was used as a tool to process a large amount of data. This study used a corpus compiled from academic papers published between 2020 and 2022. The frequency of lexical units was extracted to analyse the coverage of Academic Word List Sublist 1 in the corpus; keywords, multi-word units, and word formation were also analysed in this study. Units from two remote sensing glossaries were retrieved from the corpus to analyse how often they occurred in the corpus. Corpus linguistic methods and distributive statistical analysis proved effective in creating a discipline-specific shortlist that can be used by educators, ESP learners, and authors in the field of remote sensing. Despite the narrow field coverage of this study, the results obtained can be applied to general academic English vocabulary and to further research in the field of ESP.