Researchers have investigated discipline-specific and academic vocabulary in multiple academic disciplines through the creation of word lists (Dang, 2018; Gilmore and Millar, 2018; Watson Todd, 2017; Valipouri and Nassajii, 2013). However, there are currently no mathematics wordlists based on spoken corpora that are suitable for the context in question. The present study involved the creation of a context-specific corpus to investigate the frequency of technical and sub-technical vocabulary in a series of mathematics lectures through the creation of a keyword list. The keyword list was created using Sketch Engine from a 152,443-word corpus of 46 mathematics lectures. The final wordlist comprised 202 lemmas, covering 12.89% of the corpus. The benefit of creating a context-specific wordlist was clear. The New Academic Word List (NAWL) (Browne et al., 2013a) provided just 4.51% coverage of the corpus. Assuming students have knowledge of the first 2000 word families of the New General Service List (NGSL) (Browne et al., 2013b), which provided 84% coverage, total coverage was nearly 97% with the mathematics wordlist, compared to 88.67% with the general academic list. Of the 202 lemmas in the mathematics wordlist, 116 were sub-technical, meaning that they are polysemous, with both a general meaning and a mathematical meaning. This is a feature of the language of mathematics and may be an added challenge for students.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)