Evaluating the Convergence of Digital Information Literacy and Artificial Intelligence Competencies among Postgraduate Students: A Case Study of Uttar Banga Krishi Vishwavidyalaya

Sagar Sherpa

doi:10.22161/ijels.v2.n3.12

Abstract

Digital information literacy and AI skills are coming together fast, and that’s changing how postgraduate education works especially in specialized agricultural universities like Uttar Banga Krishi Vishwavidyalaya (UBKV). In this study, we look at how these skill sets overlap among UBKV’s postgraduates. We used a convergent mixed-methods survey (N=120) to take a hard look at how students use digital platforms, how well they can judge the quality of sources, how confident they feel running AI and machine learning (ML) tools, and what barrier they’re dealing with. About 85% of students use digital repositories and academic search engines all the time. Still, there’s a clear gap when it comes to actually evaluating information: only 37% can confidently tell whether an online source is credible. And even though most students say they know about AI technologies, only 22% feel at ease actually using AI or ML tools for data analysis. Digging into the qualitative data, we keep running into the same problems students just aren’t getting enough formal digital literacy training, and the institutional infrastructure isn’t keeping up. Wi-Fi on campus is unreliable, and access to important paid databases like INDIASTAT is far too limited. On top of all that, worries about AI-driven misinformation and unresolved copyright issues make students even more hesitant. All these factors feed into what we’re calling a “credibility paradox”: students have near-total access to information, but their ability to critically evaluate that information lags behind. To close that gap, we need to act fast. The recommendations are clearwork algorithmic source evaluation into the curriculum right away, set up focused AI-ML “Knowledge Camps,” and fix the basic campus infrastructure problems. Without these changes, students will keep falling short, even in a landscape bursting with new tools and endless information.

References

Balinas, E. (2025). The Impact of Generative Artificial Intelligence on University Information Literacy Education: A Systematic Review from Challenges to Changes. International Journal of Latest Technology in Engineering Management & Applied Science. https://doi.org/10.51583/ijltemas.2025.1402004

Bećirović, S., Polz, E., & Tinkel, I. (2025). Exploring students’ AI literacy and its effects on their AI output quality, self-efficacy, and academic performance. Smart Learning Environments, 12. https://doi.org/10.1186/s40561-025-00384-3

Carroll, A., & Borycz, J. (2024). Integrating large language models and generative artificial intelligence tools into information literacy instruction. The Journal of Academic Librarianship. https://doi.org/10.1016/j.acalib.2024.102899

Charow, R., Jeyakumar, T., Younus, S., Dolatabadi, E., Salhia, M., Al-Mouaswas, D., Anderson, M., Balakumar, S., Clare, M., Dhalla, A., Gillan, C., Haghzare, S., Jackson, E., Lalani, N., Mattson, J., Peteanu, W., Tripp, T., Waldorf, J., Tavares, W., & Wiljer, D. (2021). Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review. JMIR Medical Education, 7. https://doi.org/10.2196/31043

Hashish, E. A., Alsayed, S., & Razek, N. M. F. A. (2025). Embracing AI in academia: A mixed methods study of nursing students’ and educators’ perspectives on using ChatGPT. PLOS One, 20. https://doi.org/10.1371/journal.pone.0327981

Hershkovitz, A., Tabach, M., Reich, Y., Lurie, L., & Cholcman, T. (2025). Framing and Evaluating Task-Centered Generative Artificial Intelligence Literacy for Higher Education Students. Syst., 13, 518. https://doi.org/10.3390/systems13070518

Hornberger, M., Bewersdorff, A., & Nerdel, C. (2023). What do university students know about Artificial Intelligence? Development and validation of an AI literacy test. Comput. Educ. Artif. Intell., 5, 100165. https://doi.org/10.1016/j.caeai.2023.100165

Joseph, G., P, A., M, A. T., Jose, D., Roy, T., & Prasad, M. (2024). Impact of Digital Literacy, Use of AI tools and Peer Collaboration on AI Assisted Learning- Perceptions of the University students. Digital Education Review. https://doi.org/10.1344/der.2024.45.43-49

Laupichler, M., Aster, A., Meyerheim, M., Raupach, T., & Mergen, M. (2024). Medical students’ AI literacy and attitudes towards AI: a cross-sectional two-center study using pre-validated assessment instruments. BMC Medical Education, 24. https://doi.org/10.1186/s12909-024-05400-7

Lin, X., Xu, G., & Xiong, B. (2025). Artificial intelligence literacy, sustainability of digital learning and practice achievement: A study of vocational college students. PLOS One, 20. https://doi.org/10.1371/journal.pone.0332175

Mansoor, H., Bawazir, A., Alsabri, M. A., Alharbi, A., & Okela, A. H. (2024). Artificial intelligence literacy among university students—A comparative transnational survey. Frontiers in Communication. https://doi.org/10.3389/fcomm.2024.1478476

Mapping between Digital Competencies and Digitalization of the Accounting Profession among Postgraduate Accounting Students. (2023). Asian Journal of University Education. https://doi.org/10.24191/ajue.v19i1.21226

Ng, D., Wu, W., Leung, J., Chiu, T., & Chu, S. (2023). Design and validation of the AI literacy questionnaire: The affective, behavioural, cognitive and ethical approach. Br. J. Educ. Technol., 55, 1082–1104. https://doi.org/10.1111/bjet.13411

Rojo, A. P., Fontaines-Ruiz, T., Bracho, A. S., & Rincón, L. C. (2025). From Digital Natives to AI Natives: Emerging Competencies and Media and Information Literacy in Higher Education. Education Sciences. https://doi.org/10.3390/educsci15091134

Skalka, J., Przybyła-Kasperek, M., Smyrnova-Trybulska, E., Klimeš, C., Farana, R., Dagiene, V., & Dolgopolovas, V. (2025). Cross-national survey data on student attitudes toward artificial intelligence. Data in Brief, 62. https://doi.org/10.1016/j.dib.2025.112022

Southworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Comput. Educ. Artif. Intell., 4, 100127. https://doi.org/10.1016/j.caeai.2023.100127

Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21, 1–29. https://doi.org/10.1186/s41239-024-00448-3

Wu, J., Zhang, Q., Gan, X., Liu, X., Hu, J., & Wang, Y. (2025). The relationship between digital literacy and innovative behavior among Chinese medical students: The chain mediating roles of diversity experience and creative self-efficacy. BMC Medical Education, 25. https://doi.org/10.1186/s12909-025-07799-z

Yi, W., & Wang, S. (2025). Digital Literacy Education Among Students: Status, Pathways, and Implications in the Current Digital Era. International Journal of Education and Teaching Zone. https://doi.org/10.57092/ijetz.v4i1.385

Published

02 Sep 2026

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Vol-2, No-3, Jul - Sep 2026

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69 │ 2 │ 83-89

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