SUSTAINABLE DIGITAL INCLUSION THROUGH AI-BASED LEARNING SYSTEMS IN EDUCATION: A SOUTHEAST NIGERIA PERSPECTIVE

Abstract

This study examines the potential and challenges of implementing AI-driven learning platform 
systems in Nigeria’s education sector to promote sustainable digital inclusion. Despite Nigeria’s 
rapidly growing population and the urgent need for scalable educational solutions, the sector 
continues to grapple with significant disparities in access, quality, and infrastructure. Artificial 
intelligence (AI) offers promising avenues for personalized learning, automated assessments, and 
expanding educational reach to underserved communities, thereby aligning with Nigeria’s national 
development goals and global sustainable development targets. This research explores the 
landscape of AI adoption in Nigerian education, highlighting successful pilot initiatives, 
infrastructural limitations, policy gaps, and socio-cultural considerations that influence 
implementation. Through a correlattonal approach, including surveys, the study assesses the 
effectiveness of AI-based platforms in improving learning outcomes and promoting inclusivity. 
The study adopted a correlational design. The population was 634 lecturers from six colleges and 
faculties of education in the studied universities. The sample size was 317 lecturers which 
represented 50% of the population. This consisted of 80 lecturers’ from Michael Okpra University 
of Agriculture, Umudike (MOUAU), 75 lecturers from University of Nigeria, Nsukka (UNN), 53 
lecturers’ from Alex Ekwueme Federal University Ndufo Alike Ikwo (AE-FUNAI), 28 lecturers 
from Abia State University, Uturu (ABSU), 48 lecturers from Imo State University, Owerri 
(IMSU) and 33 lecturers from Ebonyi State University Abakaliki (EBSU). The sample was arrived 
at using four-staged sampling technique. Data for the study was collected using researchers’ self
developed questionnaires The instruments were validated by two experts from the Department of 
Educational Management and one expert from the Department of Science Education specialized 
in Measurement and Evaluation, all from MOUAU. The reliability of the instruments was 
determined using Cronbach Alpha Method which yielded an alpha of.70 and .80 respectively 
which were considered reliable. Data were analyzed using Pearson Product Moment Correlation 
Coefficient (PPMCC) to answer the research questions while linear regression analysis was used 
to test the null hypotheses at .05 level of significance. It identifies critical barriers such as 
inadequate internet connectivity, limited technical capacity, data privacy concerns, and linguistic 
diversity, which impede widespread adoption. The study also underscores opportunities for 
sustainable integration of AI through targeted policy formulation, capacity building, infrastructural 
investments, and public-private partnerships. The findings aim to inform policymakers, educators, 
and technology developers on strategies to leverage AI for equitable access to quality education, 
fostering lifelong learning and socio-economic development. Ultimately, this research contributes 
to bridging the digital divide in Nigeria’s education system and advancing the nation’s vision of 
inclusive and sustainable development.