Embodied English as Interactional Competence: A Multimodal Corpus Study of Gestures in L2 Group Interaction

Description

Students of English as a second language may acquire excellent pronunciation, vocabulary, and grammar, but still lack basic skills needed to interact socially in groups, such as turn-taking, staying on topic, making eye-contact and gesturing, and negotiating communication breakdowns. These skills are essential to effective English language communication in a range of academic, professional, and social settings. Consequently, Interactional Competence is now taught and assessed on high stakes English language proficiency exams worldwide in the form of 'group interaction' activities.Group interaction activities are designed for students to present, challenge, support, and modify each other's ideas and opinions as they practice interacting socially in English. In addition to well-documented linguistic structures, students accomplish these interactive strategies with a vast array of embodied actions and gestures. The topic of gesture has gained increasing attention in the fields of second language acquisition and language testing, but our understanding of interactional competence remains insufficiently informed by the results of empirical research in gesture studies and multimodal interaction. Second language acquisition scholars have found that spontaneous and idiosyncratic gestures offer a window onto the collaborative learning process, however, the role of gestures that are known to routinely associate with certain pragmatic and interactive functions (often called 'recurrent gestures') have not yet been studied in the L2 group interaction format. This is despite such functions (a) being directly relevant to our understanding of the interactional competence construct and (b) having implications for teaching and assessing students' performance in L2 group interaction.Building on the work of a research team at City University of Hong Kong, this project will investigate the forms and functions of gesture in a twelve-hour multimodal corpus of advanced student group interactions recorded on the campus of a British university in China. The corpus will be processed and transcribed using software for multi-tiered analysis of naturally-occurring interaction data (ELAN). The spoken language transcriptions will be annotated for interactive language functions to provide the starting point for a data-driven analysis of gestures, which can be identified and analyzed following the Linguistic Annotation System for Gestures (LASG). The results will contribute detailed descriptions and micro-interactional analyses of gestures supporting interactional competence in L2 group interaction. The overall goal is to better understand students' gestures and develop a multimodal model of interactional competence, which will provide the basis for educational resources that will help students who might otherwise be destined for impoverished English language interactions.