Assessment of Teachers Preparedness and Challenges on Integration of Artificial-Intelligence Tools for Basic-Science Teaching among Universal-Basic-Education Schools in Kaduna State, Nigeria

OMAGWU, Ameh; NUHU, I. Lawal; BABALOLA, Victor T.; OBEDA, Godwin

doi:10.64348/zije.2026352

Authors

OMAGWU, Ameh Author
NUHU, I. Lawal Author
BABALOLA, Victor T. Author
OBEDA, Godwin Author

DOI:

https://doi.org/10.64348/zije.2026352

Abstract

This study investigates the preparedness of Basic Science teachers in Universal Basic Education (UBE) schools in Kaduna State to utilize Artificial Intelligence (AI) tools in teaching. A Descriptive research design was employed, gathering data through structured AI Integration in Basic Science Teaching Questionnaire" (AIIBST-Q) administered to 400 Basic Science teachers across UBE Schools in Kaduna State was validated through expert review and pilot testing, and its high reliability (Cronbach's Alpha = 0.87) was established, making it a robust tool for collecting the data presented in the study. The study utilized descriptive statistics and hypothesis testing to analyze the collected data Results reveal moderate technical proficiency (M = 3.2) but low pedagogical integration (M = 2.8), consistent with global patterns yet lower than in technologically advanced regions. Guided by the Diffusion of Innovation (DOI) theory, findings show AI adoption limited to early adopters mainly in private schools while a significant urban–rural gap (t = 4.12, p < .001) reflects deep infrastructure inequities. Major barriers include electricity shortages (78%), poor internet access (60%), lack of institutional support (90%), and inadequate training (65%), all of which hinder implementation of the Technological Pedagogical Content Knowledge (TPACK) framework. Additionally, psychological resistance (41%) suggests heightened techno-skepticism compared to other regions, shaped by local cultural contexts. The study concludes that AI integration in Kaduna’s UBE schools is a systemic challenge, requiring multi-level action. Recommendations include creating a national AI education framework, investing in solar-powered solutions, subsidizing internet, embedding AI training in teacher professional development, and establishing supportive institutional policies. By addressing infrastructural, institutional, and attitudinal constraints, Kaduna State can leverage the moderate baseline preparedness of teachers to achieve sustainable AI adoption in education. This research offers practical roadmap for enhancing AI integration in low-resource settings.

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