Abstract
AI READINESS AMONG FIRST-YEAR AGRICULTURAL SCIENCE STUDENTS IN INDIA: A GENDER-BASED STUDY
Author : Rameshwar Gupta, Jyoti Yadav, Rishabh Gupta, Sanjay Kumar, Dr. Pawan Sahu & Dr. Geetanjali Baswani
Abstract
Artificial intelligence (AI) has the potential to enhance learning, but its use also raises challenges related to ethics, authorship, agency, transparency, privacy, and digital literacy. With the rapid growth of generative AI tools such as ChatGPT, as well as agricultural AI applications, students’ readiness to engage with these technologies has become an essential skill. This study examines gender differences in AI readiness among first-year agricultural science students at Chandra Shekhar Azad University of Agriculture & Technology, Kanpur, Uttar Pradesh. A total of 89 students participated in the survey conducted between March and May 2025, of which 48.3% (n=43) were female and 51.7% (n=46) were male. AI readiness was measured using an 18-item scale (revised to 21 in final analysis) across four themes: cognition, ability, vision, and ethics. Responses were recorded on a five-point Likert scale. Students were also asked an open-ended question about their expectations for AI teaching in their degree programme. Results showed that mean scores were highest for Morel Awareness (4.61 female, 4.39 male), followed by Insight (4.11 female, 4.29 male), Knowledge (3.61 female, 3.99 male), and Skills (3.50 female, 3.86 male). While overall gender differences were not statistically significant, patterns emerged: female students tended to report lower confidence than males across cognition, vision, and ability, but higher confidence in ethics. Notably, more female students (33.2%) than male students (21.14%) expressed interest in formal AI teaching. The findings suggest that while both male and female students view AI positively, their levels of confidence differ across themes. These results highlight the importance of fostering confidence, digital literacy, and equal opportunities for all students, with particular attention to supporting female students in developing AI-related skills.
