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

Introduction

The digital era has significantly influenced higher education and agriculture globally, with social media and AI technologies becoming vital for education and innovation. Postgraduate students at Mahatma Phule Krishi Vidyapeeth (MPKV), Rahuri, are utilizing platforms like YouTube, WhatsApp, and Agri Tech apps to enhance academic performance and explore Agri-startup opportunities. However, there is a knowledge gap regarding how these students employ these technologies, the socioeconomic factors influencing their use, and the challenges they face. The study is significant as it aligns with India's strategic focus on digital agriculture through initiatives like the National Agriculture Market (eNAM) and Agri Stack. It aims to offer practical recommendations to institutions like MPKV to enhance curricula with AI training and foster an Agri-entrepreneurial culture. By identifying barriers and facilitators to digital tool adoption, this research will help guide policymakers and educators in creating inclusive solutions for agriculture students. The study specifically evaluates the current state of digital integration within the curricula at MPKV and identifies areas that need improvement, including the need for formal AI training, enhanced infrastructure, and increased entrepreneurial support. Focusing on postgraduate students, the research aims to prepare future leaders in India's agricultural sector. It assesses how these students use social media and AI, as well as the implications for their academic www.extensionjournal.com growth and entrepreneurship. Despite acknowledging the potential benefits, students mainly use WhatsApp for communication and YouTube for tutorials, but are not fully utilising advanced AI tools for research or business planning.

Objectives 1.

To study the utilization patterns of social media and AI platforms amongst postgraduate students. 2. To obtain operational suggestions for effective use of social media and AI platforms by students and other stakeholders.

Methodology

To assess the use of social media and AI platforms among postgraduate students, five indicators were utilised: Purpose of use, Level of engagement, Accessibility and usability, Type of content, and Impact on academic and professional outcomes.

Purpose of use

This part deals with questions related to the Purpose of use. This dependent variable identifies how students strategically select digital tools to fulfil specific needs, aligning with Uses and Gratifications Theory (Katz et al., 1973) [7] , which posits that users actively choose media to satisfy defined goals. [15] and Junco et al. (2015) [6] . [9] and Junco et al. (2014) [5] . [10] . Conversely, the reported satisfaction with loading speed (57.93 percent) and multilingual support (28.96 percent) highlights significant barriers, pointing to potential deficiencies in infrastructure and localization. The low prioritization of offline functionality (19.31 percent) contrasts with findings from studies focusing on rural education contexts (Selwyn, 2012) [12] , suggesting a disconnect between platform design and the needs of students lacking reliable internet access. Usability is closely tied to intuitive interfaces (66.89 percent), reinforcing the premise of Davis's (1989) Technology Acceptance Model, which posits ease of use as a critical factor for adoption. These findings are partially consistent with the research conducted by Selwyn et al. (2020) [13] and the Pew Research Centre (2023) [10] . Offline functionality 28 19.31

Sr. No

Type of content

The content preference analysis among postgraduate agriculture students reveals clear trends in their engagement with social media and AI platforms. Regarding social media, a striking 96.55 percent of students favour www.extensionjournal.com Entertainment content, highlighting its predominant role as a source of enjoyment and leisure. Additionally, video lectures are highly utilized by 84.82 percent of students, showcasing platforms like YouTube as vital tools for visual learning that complement traditional classroom instruction. While News (44.82 percent) and Discussion forums (46.89 percent) do see some usage, reliance on more formal academic resources, such as Academic articles (35.17 percent) and Notes (24.82 percent), is notably lower. This trend suggests that, despite some academic benefits, social media primarily serves as a recreational outlet for these students while supporting traditional study methods. In contrast, AI platforms are predominantly used for academic and research-focused materials. An impressive 90.34 percent of students turn to these platforms for Academic articles, emphasizing their crucial role in facilitating research and literature reviews. Additionally, 70.34 percent of students prefer using AI for Notes, indicating its utility in note-taking, summarizing, or crafting study materials. While Video lectures (55.17 percent) and News (50.34 percent) also attract a significant user base, their popularity pales in comparison to academic articles and notes, further underscoring the research-oriented application of AI tools. Furthermore, 37.93 percent of students engage with discussion forums, reflecting a degree of collaborative interaction. Most notably, Entertainment content is rarely sought after on AI platforms, with only 10.34 percent of participants using them for this purpose. These findings align partially with research conducted by Borrego et al. (2020) [2] and Kahu and Nelson et al. (2018) [8] . Discussion forums 55 37.93

Impact of Academic and Professional outcomes

The platform usage effects analysis identifies a number of important trends among postgraduate students. First, skill Acquisition was the most common outcome 87.58 per cent, as predicted by van Laar et al. (2020) [14] digital competence model, with students using these platforms actively for upskilling. Almost 79.31 per cent respondents cited improved research effectiveness respectively, as noted by Bond et al. (2020) [1] evidence of AI-supported scholarly work. Notably, although 70.34 per cent reported a boost in confidence in academic skills -in line with Bandura (1997) self-efficacy theory, 51.74 per cent comes under enhanced information access. The considerable time savings of 55.17 per cent of users supports Clark (1994) [3] media efficiency theory, although this does not necessarily equate to improved-quality outputs. These findings imply an impact hierarchy, this trend points towards the necessity for specific training in assisting students in translating usage of the platform into concrete scholarly outputs. The findings are in line with van Laar et al. (2020) [14] and Bond et al. (2020) [1] .

Operational suggestions for effective use of social media and AI platforms by students and other stakeholders

The study provides an in-depth analysis of strategies to enhance the integration of social media and artificial intelligence (AI) among postgraduate students at Mahatma Phule Krishi Vidyapeeth (MPKV) in Rahuri. A significant 80.77 percent of respondents advocate for the inclusion of AI and machine learning (ML) training within the academic curriculum. This insight reveals a pressing gap in the current educational offerings, suggesting that the curriculum falls short of equipping students with essential skills that align with global trends emphasizing digital agriculture competencies. Additionally, there is a notable demand for the establishment of verified information hubs, with 70.34 percent of students expressing concern regarding the reliability of information sources. This highlights a critical need for institutional initiatives that can effectively filter and curate high-quality content, ensuring that students have access to accurate and trustworthy information. The study also reveals a strong preference for implementing AI platforms in regional languages, as indicated by 60.74 percent of participants. This points to an important linguistic barrier that hinders technology adoption, particularly for the rural student demographic in Maharashtra, who may find it challenging to engage with content presented exclusively in English. Moreover, students exhibit a keen interest in privacyprotected networking platforms (58.62 percent) and Digital Agri-Clinics (52.48 percent). These preferences underscore a growing desire for secure, application-based digital environments that can effectively bridge the gap between academic theories and practical agricultural challenges faced in the field. Infrastructure remains a vital concern, with 46.94 percent of respondents emphasizing the necessity for improved internet connectivity as a foundational requirement for the

References

1. Bond M, Buntins K, Bedenlier S, Zawacki-Richter O, Kerres M. Mapping research in student engagement and educational technology in higher education: A systematic evidence map. Int J Educ Technol High Educ. 2020;17(1):2.
2. Borrego M, Foster MJ, Froyd JE. What is the state of the art of systematic review in engineering education? J Eng Educ. 2020;104(4):393-413.
3. Clark RE. Media will never influence learning. Educ Technol Res Dev. 1994;42(2):21-9.
4. Food and Agriculture Organization of the United Nations. Digital agriculture report: Rural e-commerce development experience from China. Rome: FAO; 2021.
5. Junco R. Engaging students through social media: Evidence-based practices for use in student affairs. J Coll Stud Dev. 2014;55(5):509-12.
6. Junco R, Heiberger G, Loken E. The effect of Twitter on college student engagement and grades. J Comput Assist Learn. 2015;27(2):119-32.
7. Katz E, Blumler JG, Gurevitch M. Uses and gratifications research. Public Opin Q. 1973;37(4):50923.
8. Kahu ER, Nelson K, Picton C. Student interest as a key driver of engagement for first year students. Stud Success. 2018;8(2):55-66.
9. Nielsen J, Loranger H. Prioritizing web usability. Berkeley: New Riders Press; 2006.
10. Salami CK, Kamara JS, Bangura MJ. The impact of social media on agricultural entrepreneurship among youth in Sierra Leone. J Agric Ext. 2020;24(3):112-25.
11. Selwyn N. Making sense of young people, education and digital technology: The role of sociological theory. Oxf Rev Educ. 2012;38(1):81-96.
12. Selwyn N. Education and technology: Key issues and debates. 2nd ed. London: Bloomsbury Academic; 2016.
13. van Laar E, van Deursen AJAM, van Dijk JAGM, de Haan J. Determinants of 21st-century skills and 21stcentury digital skills for workers: A systematic literature review. SAGE Open. 2020;10(1):1-14.
14. Venkatesh V, Thong JYL, Xu X. Unified theory of acceptance and use of technology: A synthesis and the road ahead. J Assoc Inf Syst. 2016;17(5):328-76.