
This qualitative research explores the intersection of policymaking, Artificial Intelligence (AI), and education in Nigeria, with a particular focus on the role of media in advocacy and awareness. While the potential of AI to transform education is widely recognized, the research identifies significant gaps in its effective integration within the Nigerian context. This study aims to understand how media platforms shape public perception and influence policymakers regarding the adoption and implementation of AI-driven educational initiatives. Specifically, the research investigates the following key gaps: (1) the lack of comprehensive policy frameworks that address ethical considerations, data privacy, and equitable access to AI-powered educational tools; (2) the limited public awareness and understanding of AI's potential benefits and risks within the education sector; (3) the underutilization of media platforms, particularly local media, in disseminating relevant information and fostering constructive dialogues; (4) the absence of collaborative partnerships between educators, policymakers, AI developers, and media practitioners; and (5) the inadequate training and capacity-building programs for educators to effectively utilize and integrate AI technologies. Through in-depth interviews with policymakers, educators, media professionals, and AI experts, this research seeks to uncover the challenges and opportunities associated with leveraging media for effective advocacy and awareness campaigns. The findings will inform recommendations for policymakers, educators, and media practitioners, aiming to promote the development of inclusive and sustainable AI-driven education policies and practices in Nigeria.
Policymaking, Education, Artificial Intelligence, Advocacy and Awareness, Media, Public Awareness:
Policymaking, Education, Artificial Intelligence, Advocacy and Awareness, Media, Public Awareness:
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
