Vocabulary in academic texts across disciplinary fields

This article reports on a corpus-based study examining vocabulary of texts used as reading materials in two academic fields at a higher education institution in New Zealand: Computer Science (CS) and Media Design (MD). It first presents the vocabulary profiles of academic texts from both fields using Nation’s (2020) British National Corpus/Corpus of Contemporary American English (BNC/COCA) word frequency lists. Then, it outlines the vocabulary load required to comprehend different types of academic texts within the two corpora. The results indicate that while CS texts contain a wide range of mathematical, statistical, and programming-related lexical items, MD texts include a considerable number of proper nouns, such as the names of brands, companies, designers, and locations, as well as many non-English words. In terms of vocabulary demand, reading CS texts requires knowledge of 4,000 to 6,000 word families to reach 95% to 98% lexical coverage. In contrast, MD texts require knowledge of up to 8,000 word families for optimal comprehension across various text types. Interestingly, journal articles in both corpora show lower lexical demands than other types of texts, such as book chapters, textbooks, and materials sourced from online platforms (e.g., magazines, newspapers). The findings suggest that lexical demands vary when handling reading materials across different disciplinary areas in higher education, and provide insights into the extent of vocabulary knowledge needed to understand and learn different subject content through texts.