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article · International Journal of Educational Research and Library Science

AI-DRIVEN PEDAGOGY AND LECTURERS’ JOB PERFORMANCE IN SOUTH-WEST NIGERIAN UNIVERSITIES: AN ANALYSIS OF IMPACTS AND CHALLENGES

Abstract

Adoption and integration of transformative and digital technologies such as artificial intelligence (AI) and machine learning (ML) can redesign and reshape the future of higher education in Nigeria. AI-Driven pedagogy signifies a paradigm shift from the traditional classroom engagement of “talk and chalk” approach to a more technologically enhanced delivery and learning system which is not void of its associated challenges. This study therefore investigates the impacts and challenges of AI-driven pedagogy on lecturers’ job performance in south-west Nigerian universities. The study adopted descriptive survey research design and multi-stage non-probability sampling procedure was employed to select a sample of 3520 respondents across private and public universities in the south-west Nigeria. A validated ‘AI-Driven Pedagogy and Job Performance Questionnaire’ (APJPQ; r=0.92) was used to collect relevant data. Descriptive statistical analysis (simple percentages, frequency counts, means, standard deviation, skewness, and kurtosis) was used to answer the research questions, and inferential statistics (t-test and ANOVA) was used to test the hypotheses at 0.05 level of significance. The findings show predominantly positive view of AI’s impact on lecturers’ work, with much worries about funding, infrastructure, internet connectivity, cybersecurity, access and inequality, bias and isolation. The findings further show statistically significant gender and rank differences with exception to gender difference on the perceived challenges of AI-driven pedagogy. Implications to dialogues in educational settings were discussed, and it was recommended among others that, ministry of education should develop a national roadmap and funding framework for AI adoption in higher education.

Research topics

  • AI in Service Interactions
  • Artificial Intelligence in Healthcare and Education
  • Technology-Enhanced Education Studies

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DOI: 10.70382/tijerls.v09i8.041

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