Navigating the (dis)connect: advancing equitable and inclusive practices in Computer Assisted Language Learning (CALL)

Abstract

This paper explores the potential of digital technologies to foster equitable and inclusive practices in Computer Assisted Language Learning (CALL) within a postdigital context, where digital and analog modalities are increasingly entangled (Bhatt & Gourlay, Fawns, Citation2019; Knox, Citation2019). While CALL has long been associated with widening access and participation, persistent inequalities in digital access, skills, motivation, and trust continue to constrain its transformative potential (Tafazoli, Citation2025). Responding to these concerns, the 2025 International CALL Research Conference foregrounded Inclusive CALL as a key theme (Wang, Moore et al., 2025). Drawing on the New Zealand Digital Inclusion Blueprint and its four interrelated dimensions namely; Motivation, Access, Skills, and Trust (MAST) (New Zealand Government, Citation2021), this paper critically examines how digital inclusion is conceptualised and represented in the Inclusive CALL proceedings. The analysis is theoretically informed by postdigital theory and ecological models of inclusive CALL (Tafazoli et al., Citation2025), offering a lens to interrogate the sociocultural, infrastructural, and more-than-digital conditions shaping CALL environments. Using the MAST framework as an analytic lens, a deductive thematic analysis of the 2025 conference proceedings highlights dominant research emphases and underexplored areas. Findings suggest that while the scholarship analysed strongly foregrounds skills development, personalization, and engagement, comparatively little attention is paid to structural barriers such as device poverty, linguistic marginalization, and concerns around trust, data privacy, and surveillance. The paper argues for a shift away from techno-solutionist approaches toward contextually grounded, justice-oriented, and participatory models of inclusive CALL, and proposes a postdigital framework to guide future research, pedagogy, and policy.

The authors' abstract, as published at the source. Computer Assisted Language Learning, 2026 · DOI ↗