Quantitative analysis examines teaching-related AI usage intentions in library science lecturers, indicating resource gaps.
The study examined determinants of library and information science lecturers’ artificial intelligence usage intention for teaching in two regions of Nigeria. The study adopted quantitative methods with the use of a survey. Multi-stage sampling technique comprising of, purposive sampling and total enumeration were used to select 222 lecturers from 20 selected universities in South west and North central, Nigeria. A questionnaire was administered virtually via Google form. After a period of five weeks, 168 of the expected respondents were returned, interpreted and analysed using inferential statistics including Pearson Product Moment Correlation and Multiple Regression and also simple percentages and descriptive statistics where appropriate. The findings revealed that LIS lecturers perceive artificial intelligence to be useful for teaching. Artificial intelligence infrastructure and tools needed for teaching are not available in the department of library and information science across south west and north central universities.
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Amupitan et al. (2026) studied this question.
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