Across Africa, many adolescents enter or return to secondary school after long periods out of education due to poverty, conflict, displacement, or early learning disruption. These learners often carry severe foundational gaps and fragile memory, while prevailing instruction remains rote and exam-driven, uninformed by the psychological science of how durable learning forms. This paper presents CERMATCC — Concept Encoding, Retrieval and Memory, Application and Transfer, and Consolidation and Connection — a practitioner-developed learning cycle, originated at KNOSK ₦100-a-Day Charity Secondary School in Kuje, Abuja, that translates cognitive load theory, retrieval practice, and motivation research into a four-stage lesson sequence for disrupted secondary learners. The paper synthesises the cognitive and motivational literature underpinning the framework and reports early implementation evidence from two phases: a whole-school teacher rollout introduced in January 2026, in which structured feedback from 17 teachers across 17 subjects found that approximately 65% reported clear and consistent improvement in student recall and retention, with inconsistent outcomes correlating with inconsistent implementation of the sequence; and an April 2026 pilot of the framework's first AI-assisted expression — a Custom GPT that embeds the CERMATCC sequence — observed with 24 students and anchored by a non-subject teacher. Findings are reported as qualitative practitioner evidence ahead of formal empirical validation in the author's doctoral research. The paper argues that the framework's cognitive sequence, not its delivery channel, is the active ingredient — making CERMATCC operationalisable from AI tools to printed workbooks — and outlines implications for teacher preparation, curriculum policy, and EdTech procurement in African contexts.
Prepared in connection with the African International Conference (AIC) 2026.