Artificial Intelligence, Insecurity, and the Quest for Quality Computing and Digital Education in Nigeria

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@article{1719025,
      author = {Iwaloye Ojo Ayodeji, Goshit Nenbunmwa Amos, Kazeem Suleiman},
      title = {Artificial Intelligence, Insecurity, and the Quest for Quality Computing and Digital Education in Nigeria},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {12},
      pages = {3689-3699},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719025.pdf},
      abstract = {The quality of computing and digital education in Nigeria is increasingly shaped by the rapid emergence of Artificial Intelligence and persistent insecurity challenges. While Artificial Intelligence offers opportunities for personalized learning and instructional support, it also raises concerns related to academic integrity, over-reliance, and the weakening of core computing skills. Concurrently, insecurity across various regions of Nigeria continues to limit access to quality education, disrupt learning continuity, and constrain effective delivery of computing and digital education. This conceptual and analytical paper examines the influence of Artificial Intelligence on the quality of computing and digital education in Nigeria and analyzes the impact of insecurity on access to quality learning opportunities. Drawing on existing literature and contextual analysis, the paper further analyzes the combined effects of Artificial Intelligence and insecurity on the development of core computing competencies among learners. Based on these analyses, context-sensitive strategies are proposed to sustain quality computing and digital education, including guided integration of Artificial Intelligence in instruction, capacity building for educators, strengthened assessment frameworks, and resilient digital learning models suited to insecure contexts. The paper contributes to ongoing discourse on maintaining educational quality in complex and evolving learning environments},
      month = {June},
      doi = {https://doi.org/10.64388/IREV9I12-1719025}
  }