Exploring the Drivers of AI Tool Usage in Agricultural Education in Andhra Pradesh, India
Harisha. N *
Vignan Institute of Agriculture and Technology, VFSTR, Vadlamudi, India.
M. Shanmukh Raju
Centre for Agricultural Extension Policy, MANAGE, Hyderabad, India.
Shriramulu
Reva University, Bangalore, India.
V. Chinmayi
Agricultural College, Gangavathi UAS, Raichur, India.
*Author to whom correspondence should be addressed.
Abstract
Artificial Intelligence (AI) has emerged as a game-changing technology in a number of industries, including education and agriculture, thanks to the Fourth Industrial Revolution. AI tools are being used more and more in agricultural education to improve learning outcomes, assist with data analysis and research, and get students ready for ecosystems powered by agri-tech. With an emphasis on perceived usefulness, simplicity of use, digital confidence, and worries about career growth, real-world applications, and confidence in AI correctness, this study sought to evaluate the attitudes of B.Sc. (Hons.) Agriculture students toward AI-driven products. Students from Vignan Institute of Agriculture and Technology (VIAT), which is connected to VFSTR University in Vadlamudi, Andhra Pradesh, participated in a descriptive study design utilizing the survey method. A proportionate stratified random sample of 180 students was selected from a population of 443 students spanning four academic years.
The mean scores and rankings of the variables affecting the use of AI tools were ascertained through data analysis. The findings showed that the most important elements driving AI adoption were improved learning efficiency (Mean = 3.56, Rank II) and simple access to updated knowledge (Mean = 3.66, Rank I). Aspects including practical field applications, curricular integration, professional relevance, real-world applicability, and confidence in AI accuracy had less of an impact than other criteria like research and data analysis, as well as enhanced communication and presenting abilities. These results imply that students value short-term academic gains over long-term professional or real-world uses. Through curricular integration, real-world assignments, and the development of digital confidence, the study emphasizes the necessity of institutional support to increase adoption in underdeveloped areas. Through curricular integration, real-world assignments, and the development of digital confidence, the study emphasizes the necessity of institutional support to increase adoption in underdeveloped areas. Policymakers, curriculum designers, and educational technologists can create pedagogically sound and contextually relevant AI-integrated learning environments for agriculture education by taking into account students' attitudes regarding AI.
Keywords: AI adoption, student attitudes, digital learning, higher education, agricultural education, artificial intelligence