Asian Journal of Research and Review in Agriculture

The study focused on the knowledge, attitudes, and readiness of Agricultural Science teachers in Delta State to use artificial intelligence (AI) in teaching Livestock Farming. Three research questions and three null hypotheses guided the study. A descriptive survey research design was used. The population comprised 722 Agricultural Science teachers who taught Livestock Farming in public secondary schools across the 25 Local Government Areas of Delta State. A sample of 257 teachers was determined using the Taro Yamane formula and selected through proportionate stratified random sampling. The Agricultural Science Teachers’ Knowledge, Attitude, and Readiness for Artificial Intelligence in Livestock Farming Instruction Questionnaire (ASTKAR-AILFIQ), with a split-half reliability coefficient of 0.76, was used for data collection. Frequencies, percentages, means, standard deviations, and an independent-samples t-test at the 0.05 level of significance were used for data analysis. The findings revealed moderate perceived knowledge of AI applications in Livestock Farming instruction and positive attitudes towards the use of AI technologies. However, item-level findings showed limited readiness, as teachers were ready for four of the fifteen assessed activities and not ready for eleven. No significant differences were found in perceived knowledge or readiness based on school location, or in attitudes based on gender. The study concluded that Agricultural Science teachers expressed positive attitudes towards the use of AI in Livestock Farming instruction but reported limited readiness across most assessed instructional activities. The findings underscore the need for targeted practical training and continuing professional development to enhance teachers’ preparedness to use and facilitate the use of AI tools in Livestock Farming instruction.