Artificial Intelligence Literacy as a Predictor of Readiness for Digital Agriculture among Agricultural Education Students in Colleges of Education in South-East Nigeria

Abstract

The study examined artificial intelligence (AI) literacy and readiness for digital agriculture among Agricultural Education students in Colleges of Education in South-East Nigeria. A correlational survey design was adopted. The population comprised 585 Agricultural Education students, from which 210 students were selected through proportionate sampling across Abia, Anambra, Ebonyi, Enugu and Imo States. Data were collected using a researcher-developed 35 item Artificial Intelligence Literacy and Digital Agriculture Readiness Questionnaire (AILDARQ). The instrument measured AI knowledge, AI skills, AI application competence, AI ethical awareness, digital agriculture knowledge and awareness, digital technology confidence, and adoption readiness. The instrument was validated by experts in Agricultural Education, Educational Technology, and Measurement and Evaluation, and its overall internal consistency yielded a Cronbach's alpha coefficient of 0.82. Mean and standard deviation were used to answer the research questions, while Pearson Product-Moment Correlation was used to test the hypothesis at the 0.05 level of significance. The findings showed that students had a high level of AI literacy (M = 2.65, SD = 0.53) and a high level of readiness for digital agriculture (M = 3.04, SD = 0.49). A moderate positive and statistically significant relationship existed between AI literacy and readiness for digital agriculture (r = 0.467, p < 0.0001). The null hypothesis was rejected. The study concluded that AI literacy was positively associated with readiness for digital agriculture among the students. It recommended systematic integration of AI literacy, practical digital agriculture activities, ethical AI use, and technology-supported agricultural learning into Agricultural Education programmes.