Educational Technology for Equity: A Framework for Effective Adoption to Improve Literacy and Access in Low-Income Communities—Insights from Mushin, Lagos State, Nigeria
Year: 2025
Type: preprint
Study design: Systematic Review
Abstract: Purpose: Nigeria’s literacy crisis is most acute in low-income urban districts such as Mushin, Lagos State. This study synthesises evidence and theory to design a context-sensitive framework for equitable educational-technology (edtech) adoption that can raise literacy and access in such settings. Design/methodology/approach: Guided by Diffusion of Innovations, the Technology Acceptance Model, Constructivist Learning Theory, and Social Cognitive Theory, we conducted a systematic desk-based review of peer-reviewed scholarship, policy documents, and programme reports published between 2018 and 2025. AI-assisted thematic coding linked sociotechnical determinants to implementation levers. Findings: Adoption in Mushin-like contexts is constrained by device scarcity, unreliable power, high data costs, and limited teacher digital pedagogy. Evidence shows that offline-first platforms, low-cost shared devices, local-language content, practice-embedded professional development, community stewardship, and transparent procurement can overcome these barriers. These insights inform a five-pillar framework that aligns Infrastructure and Access, Teacher Capability and Pedagogy, Contextualised Content, Community Engagement and Trust, and Governance and Data. Originality/value: The article extends diffusion and acceptance models with a capability-centred, justice-oriented lens, turning fragmented findings into a practical roadmap for policymakers, school leaders, and investors. By foregrounding offline-first strategies and local knowledge, it redefines effective adoption as the expansion of learners’ real opportunities to read, reason, and participate in knowledge creation. Practical implications: The framework offers clear levers for staged pilots, cost tracking, and learning analytics, and complies with Nigeria’s Data Protection Act as well as UNESCO guidance on generative AI in education.
Institution: African Leadership University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4415016267
Cites:
Cited by:
Related to: