Innovation and digital technologies in teaching specialised English: Data Driven Learning in postgraduate disciplinary writing

Abstract

Data-Driven Learning (DDL, Johns, 1991) is a methodology that has become popular in tertiary education contexts to enhance the teaching of English for Academic Purposes (EAP). DDL promotes student discovery of language patterns by examining authentic language from corpora, it also encourages learner autonomy and enhances language awareness. Students can observe patterns of collocation, contexts, frequencies of words, multi-word units, grammatical patterns and uses of language. This paper describes the introduction of a systematic multidisciplinary thesis writing support resource for teachers and students involved with two large Graduate School Thesis Writing courses for all postgraduate students in a top research university, utilizing a new in-house corpus of highly rated Ph.D. and MPhil theses collected across all faculties at the university. The design and functionality of the corpus is described, and the processes involved in the development of accompanying learning and teaching materials designed specifically for both general and discipline-specific data-driven language enhancement provision for postgraduate students in the sciences and humanities is outlined. How the activities developed help raise knowledge and awareness of the key features of successful disciplinary writing, focusing on teacher-developed exemplars of good practice, as well as student-driven discovery of the knowledge and skills required to access the resource before applying the knowledge gained of such linguistic features in their own writing is discussed. Students' and teachers' perceptions of the resources are evaluated. Implications for enhancing postgraduate thesis writing using a disciplinary data-driven learning approach are provided.