Journal of Vocational, Informatics and Computer Education
Vol 3, No 2 (2025): December 2025

Recognizing the Pluriversal Indigenous Ontologies for the Adoption of Gen AI in Glocal EFL Education: A Theoretical Reflection

Md. Saiful Alam (World University of Bangladesh)
Adelina Asmawi (University of Malaya)



Article Info

Publish Date
17 Dec 2025

Abstract

Since the emergence of generative artificial intelligence (hence, Gen AI), a newly created discursive wave has been pushing for the integration of the novel, non-human tool as both an inevitable and universally desirable ontology of technology-integrated language education. However, noticeably, this superficial celebratory narrative often overlooks locally valued pedagogical ontologies where Gen AI may appear as culturally foreign, pedagogically misaligned, and technologically impractical. Positing it within this ontological potential, the present paper takes a critical view on the universalist assumption of Gen AI-driven EFL teaching. By applying the method of theoretical reflections, the paper then argues for a “pluriversal” perspective that acknowledges localized epistemologies, classical pedagogies, and human-centered teaching traditions. In doing so, the paper draws on the key concepts, including glocalism, digital divides, technological foreignness, the value of pluriversality, contextualism and cultural-philosophical relativism. By highlighting these concepts, the paper contends that there are some legitimate antecedents for which some global South contexts may resist or remain unprepared or reluctant about the integration of GenAI in EFL practices. The discussion in this paper underscores that GenAI cannot be a one-size-fits-all solution. Otherwise, GenAI tooling of EFL education in indigenous lands may be positioned as a conflicting paradigm threatening the classical, humanist, unique pedagogical rhythm. Therefore, the paper calls for a localized theorization of Gen AI-integrated EFL education.

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Journal Info

Abbrev

VOICE

Publisher

Subject

Computer Science & IT Education

Description

1. Informatics and Computing Research addressing the design, development, implementation, and evaluation of computing technologies relevant to educational, professional, and digital learning environments, including but not limited to: Artificial Intelligence and Machine Learning Deep Learning and ...