ADOPTION OF ARTIFICIAL INTELLIGENCE IN AGRICULTURAL SCIENCE TEACHING: EVIDENCE AND CHALLENGES COLLEGES OF EDUCATION IN SOUTH-EAST NIGERIA

Artificial Intelligence (AI) is increasingly transforming educational systems worldwide by enhancing instructional delivery, personalizing learning, improving assessment, and supporting educational decision-making. Despite these advancements, the adoption of AI in teacher education institutions in many developing countries remains limited. This study investigated the adoption of Artificial Intelligence in the teaching of Agricultural Science in Colleges of Education in South-East Nigeria. Specifically, the study examined the current level of AI adoption, identified the AI technologies currently used in instruction, assessed the perceived benefits of AI adoption, identified the challenges hindering AI integration, and determined strategies for enhancing AI adoption. A descriptive survey research design was adopted for the study. The study was conducted in four Colleges of Education offering Agricultural Science Education in South-East Nigeria. A sample of 69 respondents, comprising 38 Agricultural Science lecturers and 31 Agricultural Education students, participated in the study. Data were collected using a structured questionnaire validated by experts, while the reliability of the instrument was established using Cronbach's Alpha. Data were analyzed using frequency counts, percentages, mean, and standard deviation to answer the five research questions. The findings revealed that the current level of AI adoption in the teaching of Agricultural Science was low, with only limited use of AI-supported instructional technologies. However, respondents reported a high perception of the educational benefits of AI, particularly in improving instructional effectiveness, student engagement, personalized learning, and the quality of Agricultural Science education. The study also identified inadequate ICT infrastructure, poor internet connectivity, insufficient lecturer training, inadequate funding, weak institutional policies, and limited technical support as the major barriers to AI adoption. Respondents further indicated strong support for strategies including increased investment in ICT infrastructure, continuous professional development for lecturers, curriculum integration of AI, improved internet access, and enhanced institutional support. The study concludes that while Artificial Intelligence has considerable potential to transform Agricultural Science teaching in Colleges of Education, its effective integration requires sustained investment in infrastructure, capacity building, and supportive institutional policies. Implementing these measures will strengthen teacher preparation and contribute to improved teaching and learning outcomes in Agricultural Science education