Corpus-Based Engineering English for Professional Communication

Course aims

The course develops students’ enhanced understanding of Engineering English based on the principles of a good technical text: technical accuracy, usefulness, conciseness, completeness, clearness, consistency, correct spelling, grammar and punctuation, a targeted audience, clear organization, and interest. It allows students to perform their own language analyses with the help of computer concordancing programs that are aimed at identifying formulaic multi-word units/collocations, or word partnerships, in which certain words co-occur in a natural text with greater than random frequency. The course also develops communication skills and specific English language competence of engineering professionals enabling them to communicate more efficiently in the professional context of engineering.

Target group

Doctoral students, young researchers


B1/B1+ (level of English)

Course content
Course Objectives

In this course, students will learn to use Computer Linguistics to acquire facts about the language under investigation. Through the data-driven lexical approach, students will develop their English skills for technical writing to adequately express their ideas by producing various documents for workplace settings.

Students who successfully complete the course will:
  • improve their command of English in technical writing;
  • use computer concordancing programs that allow easier and faster access to language data;
  • establish a representative job-specific corpus that reflects the lexis and high frequency grammatical items;
  • encountered in current technical documentation, regardless of their fields of specialization;
  • create their own lists of language prefabs, or formulaic multi-word units/collocations, for technical and non-technical uses;
  • become independent writers able to make careful choices about the language use specific for various engineering domains;
  • address the aspects of the language relevant to the needs of the audience;
  • unlock valuable information stored in textual data.

  • Elena Bazanova, PhD, associate professor

    Moscow Institute of Physics and Technology, Russia

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