Artificial Intelligence in Education, Bridging Community Gap: A Phenomenological Approach

Oluwaseyi Opesemowo

doi:10.24310/ijne.14.2024.20505

Authors

Oluwaseyi Opesemowo University of Johannesburg South Africa

DOI:

https://doi.org/10.24310/ijne.14.2024.20505

Keywords:

Learning assistance, Quality education, Data privacy, Phenomenological approach, Artificial intelligence

Abstract

Integrating Artificial Intelligence (AI) in education holds transformative potential for bridging community gaps, particularly in under-resourced and marginalized communities. This study explores the multifaceted ways AI technologies can enhance educational accessibility, quality, and equity, thereby fostering inclusive community development. The educational disparity between under-resourced and resourced communities in Nigeria is a pressing issue, primarily driven by unequal funding, insecurity, corruption, resource allocation, and teacher shortages. This gap affects academic performance and limits future opportunities for learners in the under-sourced communities. The study delves into AI-driven initiatives to reduce the digital divide, such as deploying AI-powered educational tools in underserved communities with limited access to quality education, which is imminent. By leveraging AI, this research underscores the potential to democratize education, offering tailored learning experiences that can adapt to students' diverse needs across different geographical locations in Nigeria. The study's core objective is to bridge the community gap via AI in education using a phenomenological approach. The qualitative study adopted a phenomenological approach. The population comprised all secondary school teachers in Nigeria. Fifteen public school teachers from under-resourced communities constituted the study's sample and drew purposively based on availability. The qualitative data were thematically evaluated, and three themes (i.e., learning assistance, quality education, and infrastructural deficiency) emerged from the research. This study's findings indicate that AI can provide learning assistance and improve quality education. While AI may potentially enhance learning experiences, stakeholders must quickly address the concerns about infrastructural deficiency, insecurity, corruption, and the impediment of social interaction in education. The study concluded that incorporating AI-based technology into under-resourced communities will bridge the community gap and enable all learners to compete favourably, regardless of where they reside.

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