A Theoretical Framework for Context-Aware Adaptive Learning Systems in Low-Resource Nigerian Classroom Environments

Adaptive learning systems that personalise content delivery based on learner performance have shown substantial efficacy in well-resourced settings, but their application in low-resource Nigerian classroom environments, characterised by unreliable internet, device heterogeneity, and large class sizes, requires fundamental theoretical rethinking. This study develops an original theoretical framework for context-aware adaptive learning systems suitable for low-resource Nigerian educational contexts. The framework, designated the Context-Adaptive Learning Architecture (CALA), synthesises three theoretical contributions: a context sensitivity model that incorporates infrastructure availability (power, connectivity), device capability, and classroom management constraints as adaptive system variables alongside traditional learner performance metrics; a culturally-grounded knowledge representation model that accommodates Nigerian curriculum content, oral learning tradition integration, and multilingual presentation switching; and an offline-first adaptive algorithm that maintains personalisation continuity across disconnected sessions using a compressed local learner model. CALA was formally specified and validated through expert review by eight educational technology researchers and twelve Nigerian secondary school teachers across the South East, North Central, and South West zones. A proof-of-concept prototype implementing CALA in a mathematics learning application was developed and evaluated with 120 SS2 students across six schools in different connectivity conditions. Students in offline adaptive mode showed 18 percent higher learning gain scores than those in non-adaptive offline mode. The framework constitutes an original contribution to the theory of adaptive learning for underserved educational environments.

Keywords: adaptive learning, low-resource environments, Nigeria, educational technology, theoretical framework