Subject Specialisation in Lower Primary Grades: Academic Outcomes, Teacher Competence, and Digital Learning in Senanga District, Zambia

Kwalombota Mulima, Dr. Siyumbwa Costa

Subject Specialisation; Primary Education; Lower Grades; Zambia, Senanga District; AI In Education; Digital Curriculum; Instructional Quality.

Subject specialisation the assignment of primary school teachers to specific subject areas rather than the conventional generalist class teaching approach has attracted growing scholarly and policy attention as a potential lever for improving instructional quality and learner outcomes in primary education. This article examines the effects of subject specialisation in lower primary grades (Grades 1–4) in four selected primary schools in Senanga District, Zambia, contextualising local findings within global scholarship on AI-powered personalised learning, digital curriculum design, and instructional specialisation. Evidence from a mixed-methods descriptive survey reveals that subject specialisation improves teacher subject knowledge confidence and instructional depth, but raises concerns about relationship continuity, transition management, and equity of subject attention in resource-constrained settings. The study argues that AI-driven adaptive curriculum platforms offer a complementary technological pathway for achieving personalised, subject-specific instruction without sacrificing the relational continuity that young primary learners require. Policy implications and recommendations are offered

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