Embracing machine translation in L2 education: Bridging theory and practice in the AI Age

This chapter examines the evolving role of machine translation (MT) in second language (L2) education. It first summarises recent research on MT's pedagogical applications, synthesising findings from systematic reviews that highlight MT's effectiveness in L2 writing when used appropriately. The chapter explores learner and teacher perceptions, noting a generally positive attitude among students but a more divided stance among educators. It presents a comprehensive framework for understanding factors influencing MT use in L2 writing, encompassing linguistic, personal, contextual, and ideological dimensions. The chapter introduces the concept of "MT as Augmented L2 Competence," offering a new paradigm for integrating MT into language learning. It discusses various models of MT instruction, including the Guided Use of MT (GUMT) model. Finally, the chapter proposes the Metacognitive Resource Use (MRU) framework, which positions learners as metacognitive agents capable of strategically utilising a wide range of language resources, including MT and generative AI (GenAI) tools. This integrated approach aims to foster autonomous learners who can effectively navigate the complex landscape of digital language learning resources.