Over the past decade, engineering has been one of the most oft-chosen fields of study for domestic and international students at US colleges and universities (IIE 2017; NCES 2018). As a result, the number of students in undergraduate engineering courses has steadily grown, leading to increased attention devoted to the written discourse encountered in engineering courses. The present study investigates the linguistic overlap between published textbooks used in lower-division undergraduate engineering courses by focusing on the analysis of multi-word sequences – 5-word phrase-frames – commonly found in five engineering disciplines. Overall, it was found that, while frequency distribution and structural characteristics of the identified phrase-frames were consistent across the five corpora, there were dissimilarities in the discourse functions performed by these patterns.

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With an increasing need for teaching discipline‐specific language to second language (L2) learners, language instructors are tasked with a challenging objective to target the vocabulary that is necessary for students to understand and produce discipline‐specific discourse. To meet this objective, language corpora and corpus software have been used extensively to examine the vocabulary demands of commercial textbooks and research articles as well as to enhance students' language‐learning experiences (Hsu, ; Mudraya, ; Ward, ). This article describes how to develop teaching materials for L2 vocabulary instruction using corpus‐based techniques. Focusing on a case study from an introductory engineering course, the authors demonstrate how freely available software programs (e.g., AntConc, Range, Compleat Lexical Tutor) can be used to identify and select relevant vocabulary items. The authors discuss the three types of vocabulary that might be targeted in an English for specific purposes course (technical, semitechnical, and nontechnical words) and explain the principles employed to guide the vocabulary selection process (i.e., keyness and frequency of words and their distribution in the materials). Finally, drawing on Nation's () framework of word knowledge, the authors provide an overview of several corpus‐informed activities developed for teaching vocabulary in engineering.

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