Addressing discipline specificity in a multidisciplinary EAP classroom through data-driven learning

Abstract

Mastering academic writing is one of the challenges frequently experienced by university students across all levels and disciplines. As writing remains one of the most common ways of demonstrating knowledge in university settings, developing an appropriate academic style is a vital skill for success. In the context of British universities, academic writing skills are generally catered for by English for Academic Purposes (EAP) provision in the form of pre-sessional and in-sessional courses. Ideally, these courses should focus on the characteristics and conventions of the students’ specific fields of study to meet their academic needs. This, however, poses a challenge for EAP practitioners, who are usually not specialists in the students’ subject domain, amplified by the fact that EAP classes are often taken by a diverse group of learners from a wide range of disciplines. This paper reports on how the issue of discipline specificity in a multidisciplinary EAP classroom in a PhD pre-sessional programme at a British University was addressed by employing a data-driven learning (DDL) approach for the acquisition and development of disciplinary writing conventions including specialised technical vocabulary. After an evaluation of this approach, we conclude that DDL can be usefully implemented in wider EAP contexts to inform students’ knowledge of writing in their disciplines.