The impact of AI-enhanced assistive technologies on the learning experiences of children with disabilities in Zimbabwe
Year: 2026
Type: article
Abstract: Educational inclusion for children with disabilities remains constrained by structural inequalities, limited specialist resources and persistent disparities in access to quality learning opportunities. Although specialised learning environments have traditionally relied on dedicated infrastructure and human support, such arrangements frequently reinforce educational segregation and restrict equitable participation in mainstream schooling, particularly in low-resource contexts. Artificial intelligence-enhanced assistive technologies (AI-AT) present a transformative opportunity to reconfigure these constraints by personalising learning, improving accessibility and extending instructional support beyond conventional pedagogical boundaries. Yet, evidence on their effectiveness within resource-constrained education systems remains limited. This study examines the influence of AI-AT on the learning experiences of children with disabilities in Zimbabwean primary schools, where infrastructural, financial and institutional limitations continue to shape inclusive education outcomes. Rather than assuming technological determinism, the study interrogates how contextual conditions mediate the educational value of AI-AT and the extent to which these technologies advance or reproduce existing inequalities. Guided by the Technology Acceptance Model and sociocultural theory, the study adopts a mixed-methods research design involving ten purposively selected primary schools in Zimbabwe. The findings demonstrate that AI-AT substantially enhances learner engagement, instructional accessibility, communication, personalised learning and participation, thereby expanding opportunities for meaningful educational inclusion. However, these gains are contingent upon institutional readiness, teacher digital competence, affordability and supportive policy environments. The analysis further reveals that algorithmic bias, data governance, cultural relevance and digital inequities represent systemic rather than merely technical challenges, with significant implications for equitable implementation. The study argues that the educational potential of AI-AT in developing countries depends less on technological sophistication than on its contextual adaptation within local pedagogical, socio-economic and cultural realities. It therefore contributes empirical evidence to debates on inclusive artificial intelligence by demonstrating that sustainable educational transformation requires the co-evolution of technology, institutional capacity and inclusive policy frameworks.
Source: The Dyke
Institution: Manicaland State University of Applied Sciences
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7219115751