Artificial Intelligence-Driven Adaptive Learning Technologies and Their Influence on Inclusive Early Childhood Education Outcomes among Diverse Learners in Ibadan North, Nigeria

This study investigated the influence of artificial intelligence (AI)–driven adaptive learning technologies on inclusive early childhood education outcomes among diverse learners in Ibadan North Local Government Area of Oyo State, Nigeria. Inclusive early childhood education outcomes, such as cognitive development, learner engagement, and equitable access to learning opportunities, remain a concern in contexts characterized by learner diversity and limited resources. The study adopted a mixed-methods research approach, combining quantitative and qualitative data to provide a comprehensive understanding of the phenomenon. The sample comprised 50 early childhood educators and 50 parents of diverse learners drawn from 10 inclusive early childhood education centres in Ibadan North. Data were collected using the AI-Driven Adaptive Learning Technologies Questionnaire (AIALTQ), the Educators’ and Parents’ Perception of AI Adaptive Learning Interview Guide (EPPAALIG), and the Inclusive Early Childhood Classroom Observation Checklist for AI Use (IECCOC-AIU). Quantitative data were analyzed using descriptive statistics, while qualitative data were analyzed thematically. Findings revealed that AI-driven adaptive learning technologies positively influenced inclusive early childhood education outcomes by enhancing cognitive development, learner engagement, self-paced learning, and equitable access for diverse learners. Educators and parents expressed positive perceptions regarding the effectiveness of AI-driven adaptive learning technologies in addressing individual learning differences and supporting inclusive practices. However, challenges such as inadequate infrastructure, limited teacher training, and ethical concerns related to data privacy were identified, alongside opportunities for personalized instruction and reduced teacher workload. Anchored on the Universal Design for Learning framework, the study concluded that AI-driven adaptive learning technologies hold significant potential for promoting inclusive early childhood education when supported by adequate resources, training, and ethical guidelines. The study recommends increased investment in digital infrastructure, capacity building for educators, and the development of clear policies to guide the effective and ethical integration of AI in early childhood education.