Assessing Awareness, Perception and Adoption Intentions towards Artificial Intelligence and Blockchain Technologies among Agricultural University Students in Gujarat, India
Prajapati Piyush *
SMC College of Dairy Science, Kamdhenu University, Anand, India.
K. C. Kamani
SMC College of Dairy Science, Kamdhenu University, Anand, India.
M. C. Prajapati
SMC College of Dairy Science, Kamdhenu University, Anand, India.
A. K. Makwana
G.N. Patel College of Dairy Science, Kamdhenu University, Sardarkrushinagar, India.
M. D. Gurjar
SMC College of Dairy Science, Kamdhenu University, Anand, India.
*Author to whom correspondence should be addressed.
Abstract
The increasing integration of emerging digital technologies in agriculture has accelerated the transition towards Agriculture 4.0 and created new opportunities for improving productivity, decision-making, supply chain transparency, and sustainability. This study assessed awareness, knowledge, perceptions, adoption intentions, and constraints related to Artificial Intelligence (AI) and Blockchain technologies among students of the five State Agricultural Universities of Gujarat. A descriptive and analytical research design was adopted, and primary data were collected from 251 agricultural university students using a pre-tested structured questionnaire. The data were analysed using descriptive statistics, mean score analysis, reliability analysis, chi-square tests, and multiple regression analysis. The findings revealed that awareness of AI (88.8%) was substantially higher than awareness of Blockchain technology (39.0%). Internet websites, social media, and classroom lectures were the major sources of information. Students showed moderate knowledge of AI applications in agriculture, whereas considerable knowledge gaps were observed for Blockchain applications. The Technology Acceptance Model results indicated that perceived usefulness and perceived ease of use significantly influenced students’ adoption intentions. The regression model explained 68.6% of the variation in adoption intention (R² = 0.686). Lack of training, inadequate knowledge, high costs, and limited practical exposure were identified as major constraints. The study concludes that agricultural students show positive attitudes towards AI and Blockchain technologies, but practical exposure, structured training, and institutional support are necessary to strengthen digital agriculture competencies.
Keywords: Artificial Intelligence, blockchain technology, agriculture 4.0, agricultural students, technology acceptance model, digital agriculture, awareness, perception, adoption intention