ASSESSING THE IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE IN CHILDHOOD EDUCATION IN IMO STATE: IMPLICATIONS FOR CHILD-CENTERED LEARNING

Abstract

Artificial intelligence (AI) is increasingly being explored as a means of supporting personalized, interactive, and learner-responsive educational experiences. However, evidence concerning its implementation in early childhood education within public primary schools in Imo State, Nigeria, remains limited. This study assessed the implementation of identified AI-enabled educational tools in early childhood education and examined their implications for child-centred learning. Specifically, it examined the perceived availability of AI-enabled educational tools, teachers’ reported use of the tools in classroom activities, and perceived barriers to their implementation. A descriptive survey research design was adopted. The target population comprised 1,037 teachers responsible for early childhood classes in public primary schools across Owerri Education Zones 1 and 2, Imo State. A sample of 100 eligible teachers was selected from 10 purposively selected public primary schools using a multistage sampling procedure. Data were collected using the researcher-developed Artificial Intelligence Implementation in Early Childhood Education Questionnaire (AIIECEQ) and analysed using frequency counts, percentages, mean, and standard deviation, with a criterion mean of 2.50. Findings indicated low perceived availability of identified AI-enabled educational tools (Grand Mean = 1.55) and low teacher-reported use in classroom activities (Grand Mean = 1.64). Perceived barriers were high (Grand Mean = 2.99), particularly limited infrastructure, restricted access to AI-enabled tools, insufficient teacher training, high student–teacher ratios, limited administrative awareness, and high costs. The study concludes that AI implementation remains limited, constraining opportunities for AI-supported child-centred learning. It recommends improved access to appropriate AI-enabled tools, strengthened ICT infrastructure, continuous teacher capacity development, sustainable funding, and clear institutional and policy guidelines for responsible AI integration.