From Promise to Peril: generative artificial intelligence's potential to deepen educational inequalities in geographically diverse contexts
Ben ArcherPurpose
This study critically examines how van Dijk's Digital Divide Theory applies to generative artificial intelligence (GenAI) access in regional, remote and rural (RRR) educational contexts. It interrogates whether a framework designed for standardised digital tools adequately captures GenAI-specific barriers, while mapping where existing research concentrates and where significant gaps remain across van Dijk's four dimensions of access.
Design/methodology/approach
A scoping review was conducted using the Population, Concept, Context (PCC) framework across four academic databases, with AI-assisted Boolean search development validated through pilot testing and supervisory oversight. Strict inclusion criteria focused on peer-reviewed publications examining GenAI in RRR educational settings. Twenty-nine articles were analysed using van Dijk's four-dimensional framework: material access, skills access, usage access and motivational access.
Findings
Material and skills access emerged as the most researched dimensions, with material access representing a necessary but insufficient condition for equitable GenAI engagement and skills access requiring interventions across student, educator and policy levels simultaneously. Usage patterns cannot be assumed to follow naturally from material and skills access, requiring sustained time investment, pedagogical framing and institutional support. Motivational access remained critically under-researched, with only one study explicitly examining this dimension. The synthesis suggests sequential relationships across the four dimensions, where foundational precursors in material, skills and usage shape the conditions under which motivational engagement develops. This sequential pattern is presented as a provisional theoretical proposition warranting targeted empirical investigation.
Research limitations/implications
The interconnected nature of access barriers creates systemic constraints extending beyond van Dijk's original conceptualisation. The synthesis suggests that sequential relationships between dimensions help explain why motivational access remains under-researched, with GenAI lacking foundational precursors necessary for widespread motivational engagement in RRR communities. Evidence-based policy addressing material and skills dimensions becomes essential for preventing systematic exclusion from GenAI's transformative educational potential.
Practical implications
This research reveals that GenAI introduces a less visible form of digital exclusion in regional, remote and rural (RRR) educational contexts. Unlike previous digital divides characterised by observable access deficits, GenAI enables superficially sophisticated outputs from shallow engagement. This produces performative usage, defined here as the production of well-formed GenAI outputs that mask shallow understanding of subject content. Students in RRR communities may appear to use GenAI productively while developing neither subject mastery nor critical evaluation skills. Educational institutions serving RRR populations must therefore develop context-specific assessment frameworks capable of distinguishing between performative and meaningful GenAI engagement, ensuring that technology deployment addresses rather than obscures the educational disadvantages these communities already experience.
Social implications
This research highlights that motivational disengagement from GenAI in regional, remote and rural (RRR) communities emerges not from technology rejection but from cascading structural barriers. When infrastructure deficits create skills gaps and repeated failure diminishes perceived effort-to-benefit ratios, self-reinforcing cycles of technological disengagement develop that persist even when access improves. Motivational access remains the least researched dimension of GenAI's digital divide, despite being central to the conditions under which other access dimensions translate into sustained engagement. Policymakers and educational institutions serving RRR communities must recognise that addressing material and skills barriers alone proves insufficient without concurrent attention to how these compounding disadvantages shape willingness and aspiration to engage with GenAI technologies.
Originality/value
This study provides the first application of van Dijk's Digital Divide Theory as an analytical framework for examining generative artificial intelligence education research in regional, remote and rural (RRR) contexts. Theoretically, it proposes a provisional reconceptualisation of van Dijk's sequential dimensions, suggesting that material access supports skills development, which supports usage patterns, which subsequently shape motivational engagement. This proposition offers a coherent explanation for why motivational access remains critically under-researched in RRR communities, namely that foundational precursors necessary for motivational engagement are themselves absent. Practically, by exposing significant gaps in understanding how cascading access barriers shape GenAI engagement in geographically disadvantaged settings, this review establishes the empirical justification for targeted research into GenAI adoption and implementation within RRR educational institutions.