Generating Genre-Based Automatic Feedback on English for Research Publication Purposes

Abstract

Artificial intelligence (AI) for supporting second language (L2) writing processes and practices has garnered increasing interest in recent years, establishing AI-mediated L2 writing as a new norm for many multilingual classrooms. As such, the emergence of AI-mediated technologies has challenged L2 writing instructors and their philosophies regarding computer-assisted language learning (CALL) and teaching. Technologies that can combine principled pedagogical practices and the benefits of AI can help to change the landscape of L2 writing instruction while maintaining the integrity of knowledge production that is so important to CALL instructors. To align L2 instructional practices and CALL technologies, we discuss the development of an AI-mediated L2 writing technology that leverages genre-based instruction (GBI) and large language models to provide L2 writers and instructors with tools to enhance English for research publication purposes. Our work reports on the accuracy, precision, and recall of our network classification, which surpass previously reported research in the field of genre-based automated writing evaluation by offering a faster network training approach with higher accuracy of feedback provision and new beginnings for genre-based learning systems. Implications for tool development and GBI are discussed.