Use of social media and AI platforms by postgraduate students in MPKV, Rahuri

Abstract

The advent of digital technologies has revolutionized higher education and agricultural practices, offering unprecedented opportunities for learning, research, and entrepreneurial innovation. This study investigates the adoption and utilization patterns among postgraduate students at Mahatma Phule Krishi Vidyapeeth (MPKV), Rahuri a premier agricultural university in India. Against the backdrop of India’s agrarian economy, which faces pressing challenges such as climate change, market instability, and food security, digital tools like AI-driven analytics, social media platforms, and Agri-Tech applications hold immense potential to transform traditional farming practices and academic methodologies. However, despite their growing prevalence, there remains a critical knowledge gap regarding how agricultural students engage with these technologies, the factors shaping their adoption, and the systemic barriers limiting their full potential. This research is structured around five primary objectives (1) mapping their utilization patterns of social media (e.g., WhatsApp, YouTube, LinkedIn) and AI platforms (e.g., ChatGPT, Agri-Bots) for academic, professional, and entrepreneurial purposes; (2) formulating actionable recommendations for students, educators, policymakers, and technology developers to enhance digital integration in agricultural education and entrepreneurship. Employing a mixed-methods approach, the study collected data from 145 postgraduate students across 16 disciplines including Agronomy, Agricultural Engineering, and Agri-Business Management using stratified random sampling. Quantitative data were gathered through structured questionnaires, while qualitative insights were derived from focus group discussions and interviews. Statistical tools such as frequency distribution, percentages, mean, and standard deviation were used to analyse the data, complemented by thematic analysis for qualitative responses. The study concludes with targeted recommendations to bridge these gaps and operational suggestions: (1) integrating AI and digital literacy modules into agricultural curricula; (2) developing low-cost, vernacular AI tools to cater to rural students; (3) establishing institutional partnerships with Agri-Tech firms for hands-on training; (4) creating