Computer-assisted DDL vs. Mobile-assisted DDL: Exploring EFL Learners’ Preferences and Experiences with Two Corpus Interfaces

Abstract

Data-driven learning (DDL) has traditionally been studied via standard corpus interfaces, such as COCA, Sketch Engine, IntelliText, and other similar corpus tools. In addition, DDL has traditionally been seen as part of the computer-assisted language learning (CALL) approach, primarily because access to corpora and corpus interfaces has historically been limited to desktop computers. However, with the emergence of several simplified and mobile-friendly web corpus interfaces and with mobile assisted language learning (MALL) gaining momentum in language education, along with its potential in DDL, mobile-assisted DDL has become an alternative learning technique. This paper reports on a study carried out with a group of undergraduate EFL students studying at International Balkan University (IBU). In this study, the participants were given linguistic tasks to complete using new web corpus interfaces as reference tools, namely, CorpusMate and Netspeak. The first corpus interface was exploited via the traditional CALL approach, whereas the latter was utilized with mobile technology. The results of the study revealed positive learner perceptions and experiences with the newly introduced tools, while they also displayed enthusiasm and motivation to engage in DDL within the context of MALL. The present study provides valuable insights into students’ perspectives and experiences with state-of-the-art corpus tools and mobile technology, which can help shape future paths for research in DDL and MALL.