Prospects for Digital English Language Teaching and Learning: Pronunciation and Speaking between Phonetic Standards and Linguistic Diversity

Abstract

The rapid acceleration of digital technologies, artificial intelligence (AI), automatic speech recognition , and computer-assisted pronunciation training has fundamentally transformed English language teaching and learning. However, these technological innovations bring to the fore a profound theoretical and pedagogical dilemma: should digital pronunciation and oral communication instruction enforce strict adherence to traditional canonical native-speaker standards (such as Received Pronunciation or General American), or should it embrace an inclusive, intelligibility-driven paradigm that recognizes English as a Lingua Franca and the legitimacy of global World Englishes? Grounded in an epistemology of critical applied linguistics and digital sociophonetics, this paper synthesizes recent empirical and theoretical scholarship to examine the dynamic reconstruction of pronunciation standards in technology-mediated environments. Moving beyond the instrumental view of technology as a mere delivery mechanism, this paper investigates how multimodal learning ecosystems, conversational agents, and acoustic feedback systems reshape communicative competence, interactional agency, and learner identity. It proposes a five-stage pedagogical cycle—diagnosis, targeted practice, authentic interaction, differentiated feedback, and reflective reassessment—that harmonizes technological precision with linguistic inclusivity. By distinguishing communication-inhibiting phonological breakdowns from legitimate accent variation, this framework offers evidence-based curricular and technological principles for researchers, teacher educators, curriculum designers, and educational developers.