Assessing Lecturers’ Knowledge and Utilisation of Artificial Intelligence for Teaching and Research in Adamawa State Tertiary Institutions
Artificial intelligence (AI) is rapidly reshaping global higher education, yet its diffusion within resource-constrained contexts remains poorly documented. This study assessed lecturers’ knowledge and utilisation of AI for teaching and research across six tertiary institutions in Adamawa State, Nigeria. Guided by a descriptive-survey design, a structured questionnaire was distributed to the entire population of 200 full-time lecturers, yielding a 100 % return rate. Descriptive statistics and Pearson chi-square tests analysed data in IBM SPSS 26. Results show 71 % of respondents understood the concept of AI, but only 40–48 % integrated AI deeply into lesson planning, assessment or research analytics. Utilisation varied significantly by institution type (χ² = 14.87, p = 0.011), teaching experience (χ² = 10.32, p = 0.016) and perceived training adequacy (χ² = 82.47, p < 0.001). Inadequate professional development (72 %) and unreliable internet access (67 %) emerged as critical barriers, whereas fear of job displacement was comparatively minor (35 %). Despite these constraints, over 86 % of lecturers endorsed regular AI workshops, improved institutional resources and government-backed policy support as pathways to adoption. The study concludes that Adamawa’s state lecturers possess foundational AI awareness but require focused capacity-building and infrastructural investment to translate knowledge into transformative practice. Consequently, it recommends ring-fenced government funding for broadband, National Universities Commission accreditation criteria mandating AI training, establishment of campus innovation hubs, union-negotiated incentives, bulk procurement of licensed software, curriculum integration of AI literacy and public–private partnerships for contextualised support as measures worth adopting. Implementing these measures will enable the state’s tertiary sector to harness AI’s potential for improved pedagogy, research output and student employability.
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Assessing Lecturers’ Knowledge and Utilisation of Artificial Intelligence for Teaching and Research in Adamawa State Tertiary Institutions
Semantic Scholar · 2025
Abstract
Artificial intelligence (AI) is rapidly reshaping global higher education, yet its diffusion within resource-constrained contexts remains poorly documented. This study assessed lecturers’ knowledge and utilisation of AI for teaching and research across six tertiary institutions in Adamawa State, Nigeria. Guided by a descriptive-survey design, a structured questionnaire was distributed to the entire population of 200 full-time lecturers, yielding a 100 % return rate. Descriptive statistics and Pearson chi-square tests analysed data in IBM SPSS 26. Results show 71 % of respondents understood the concept of AI, but only 40–48 % integrated AI deeply into lesson planning, assessment or research analytics. Utilisation varied significantly by institution type (χ² = 14.87, p = 0.011), teaching experience (χ² = 10.32, p = 0.016) and perceived training adequacy (χ² = 82.47, p < 0.001). Inadequate professional development (72 %) and unreliable internet access (67 %) emerged as critical barriers, whereas fear of job displacement was comparatively minor (35 %). Despite these constraints, over 86 % of lecturers endorsed regular AI workshops, improved institutional resources and government-backed policy support as pathways to adoption. The study concludes that Adamawa’s state lecturers possess foundational AI awareness but require focused capacity-building and infrastructural investment to translate knowledge into transformative practice. Consequently, it recommends ring-fenced government funding for broadband, National Universities Commission accreditation criteria mandating AI training, establishment of campus innovation hubs, union-negotiated incentives, bulk procurement of licensed software, curriculum integration of AI literacy and public–private partnerships for contextualised support as measures worth adopting. Implementing these measures will enable the state’s tertiary sector to harness AI’s potential for improved pedagogy, research output and student employability.