Social Media as an Informal Learning Environment: Opportunities and Risks for Student Development
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Informal Learning, Social Media, Student Development
Abstract
Background. Social media platforms have increasingly become informal learning environments where students engage in knowledge sharing, collaboration, and skill development outside formal educational settings. These digital spaces offer opportunities for peer interaction, access to diverse resources, and experiential learning, yet they also present risks such as misinformation, distraction, and negative social influences. Understanding the dual impact of social media on student development is critical for guiding effective educational practices and digital literacy initiatives.
Purpose. This study aims to explore the opportunities and risks associated with social media as an informal learning environment, focusing on its influence on cognitive, social, and emotional development.
Method. A mixed-methods research design was employed, combining surveys of 250 students with semi-structured interviews to capture qualitative insights into learning behaviors, engagement patterns, and perceived benefits and drawbacks of social media usage.
Results. Findings indicate that students leverage social media for collaborative learning, problem-solving, and information seeking, enhancing critical thinking and communication skills. However, exposure to inaccurate content, online distractions, and social comparison negatively impacted focus, motivation, and emotional well-being.
Conclusion. The study concludes that while social media can serve as a valuable informal learning environment, structured guidance, digital literacy education, and awareness of potential risks are essential for maximizing benefits and mitigating harms. Educators and policymakers should balance opportunities with safeguards to support holistic student development in digital contexts.
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References
Al Arafat, K. A., Roni, M. R., Siddique, S., Yousuf, M. A., & Moni, M. A. (2025). Sentiment Analysis in Twitter Data Using Machine Learning-Based Approach: Vol. 1034 LNNS (M. Mahmud, M. S. Kaiser, A. Bandyopadhyay, K. Ray, & S. Al Mamun, Eds.; pp. 169–184). Springer Science and Business Media Deutschland GmbH; Scopus. https://doi.org/10.1007/978-981-97-3937-0_12
Ali, E. H. F., Kottaparamban, M., Usmani, S., & Mohammed, J. K. K. (2025). Saudi Students’ Perceptions of the Influence of Social Media New Vocabulary on English Language Proficiency. Theory and Practice in Language Studies, 15(2), 452–461. Scopus. https://doi.org/10.17507/tpls.1502.15
Anusha, M., & Leelavathi, R. (2025). Sarcasm detection using enhanced glove and bi-LSTM model based on deep learning techniques. International Journal of Intelligent Engineering Informatics, 13(1), 26–54. Scopus. https://doi.org/10.1504/IJIEI.2025.144268
Bowman, R. D. (2025). Resilience and Resourcefulness: Informal Education Strategies in Rural Queer Contexts (pp. 164–172). Taylor and Francis; Scopus. https://doi.org/10.4324/9781003529415-28
Chanda, S., & Pal, S. (2025). Word Level Language Identification from Social Media Code-Mixed Data Leveraging Transformer-Based Models. SN Computer Science, 6(7). Scopus. https://doi.org/10.1007/s42979-025-04377-4
Danielson, R. W., Jacobson, N. G., Patall, E. A., Sinatra, G. M., Adesope, O. O., Kennedy, A. A. U., H Bhat, B., Ramazan, O., Akinrotimi, B., Nketah, G., Jin, G., & Sunday, O. J. (2025). The effectiveness of refutation text in confronting scientific misconceptions: A meta-analysis. Educational Psychologist, 60(1), 23–47. Scopus. https://doi.org/10.1080/00461520.2024.2365628
de Gaulmyn, A., Boutteau, M., Doyen, C., Rousseau, M., McKinnon, S., Bourassa, J., & Cappe, E. (2025). Teleconsultation, a promising technique for psychoeducational programs for parents of children with autism spectrum disorder. Annales Medico-Psychologiques, 183(4), 421–428. Scopus. https://doi.org/10.1016/j.amp.2024.04.005
Desai, K. S., Tiyyala, V. M., Tiyyala, P., Yeola, A., Gallegos-Rangel, A., Montiel-Torres, A., Allen, M. R., Dredze, M., Vandrey, R. G., Thrul, J., Leas, E. C., Hogarth, M., Smith, D. M., & Ayers, J. W. (2025). Waldo: Automated discovery of adverse events from unstructured self reports. PLOS Digital Health, 4(9 September). Scopus. https://doi.org/10.1371/journal.pdig.0001011
Dixit, M., Bali, M. S., Kour, K., Ioannou, I., Pradeep Ghantasala, G. S. P., & Vassiliou, V. (2025). Video sentiment analysis on social media using an advanced VADER technique. International Journal of Data Science and Analytics, 20(7), 6729–6761. Scopus. https://doi.org/10.1007/s41060-025-00849-1
Galindo-Domínguez, H., Bezanilla, M. J., & Campo, L. (2025). Relationship between social media use and critical thinking in university students. Education and Information Technologies, 30(5), 6641–6665. Scopus. https://doi.org/10.1007/s10639-024-12953-z
Garrido Castellano, C. G., Rivera, E. M., & Tello, S. M. (2025). Radical Listening as Collective Education: Learning from Cádiz Carnival Music (pp. 62–73). Taylor and Francis; Scopus. https://doi.org/10.4324/9781003473800-6
Groller, K. D., Curley, B., & Gourash, W. (2025). The practice of preoperative patient education in metabolic bariatric surgery: Results of a national survey. Surgery for Obesity and Related Diseases, 21(8), 971–981. Scopus. https://doi.org/10.1016/j.soard.2025.05.006
Krutka, D. G., & Greenhalgh, S. P. (2025). The dark side of affinity spaces for teacher professional learning. British Journal of Educational Technology. Scopus. https://doi.org/10.1111/bjet.13593
Li, Y., Xiang, R., Song, Y., & Li, J. (2025). UniPoll: A Unified Social Media Poll Generation Framework via Multiobjective Optimization. IEEE Transactions on Neural Networks and Learning Systems, 36(8), 13818–13832. Scopus. https://doi.org/10.1109/TNNLS.2024.3512868
Majcen, A., & Spitzer, P. (2025). What do students look for? Insights into their quality criteria for science communication on social media. International Journal of Science Education, Part B: Communication and Public Engagement. Scopus. https://doi.org/10.1080/21548455.2025.2551292
McShane, I. (2025). The Museum Movement: Carnegie Cultural Philanthropy and Museum Development in the Anglosphere, 1920–1940 (p. 150). Taylor and Francis; Scopus. https://doi.org/10.4324/9781003109099
Nguyen, A. T.-H., Nguyen, D. H., & van Nguyen, K. (2025). ViSoLex: An Open-Source Repository for Vietnamese Social Media Lexical Normalization (O. Rambow, L. Wanner, M. Apidianaki, H. Al-Khalifa, B. Di Eugenio, S. Schockaert, B. Mather, & M. Dras, Eds.; pp. 183–188). Association for Computational Linguistics (ACL); Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000099210&partnerID=40&md5=ebf4b228315251d223918235f7e7b938
Pattison, K. (2025). TAYLOR-MADE LEARNING: Fan Labour, Skill Development, and Celebrity Interaction in the Taylor Swift Affinity Space (pp. 11–22). Taylor and Francis; Scopus. https://doi.org/10.4324/9781003509271-3
Pérez-Marín, C. C. (2025). Use of Instagram as an Educational Strategy for Learning Animal Reproduction. Veterinary Sciences, 12(8). Scopus. https://doi.org/10.3390/vetsci12080698
Pokhriyal, H., & Jain, G. (2025). Supposititious Sarcasm Detection and Sentiment Analysis Coping Hindi Language in Social Networks Harnessing Zipf- Mandelbrot Probabilistic Optimisation and Perplexity Entropy Learning. ACM Transactions on Asian and Low-Resource Language Information Processing, 24(2). Scopus. https://doi.org/10.1145/3712061
Ro‘ziyeva, G. G., Otaxonova, B. I., & Shaazizova, M. E. (2026). Text Classification for Social Networks: Solving Short Text and Informal Language Problems: Vol. 15555 LNCS (Y. Koucheryavy & A. Aziz, Eds.; pp. 121–127). Springer Science and Business Media Deutschland GmbH; Scopus. https://doi.org/10.1007/978-3-031-95296-8_11
Ryu, S., Jung, S.-H., Kim, G.-H., & Lee, S. (2025). Visitor Number Prediction for Daegwallyeong Forest Trail Using Machine Learning. Sustainability (Switzerland), 17(13). Scopus. https://doi.org/10.3390/su17136061
Seifert, T., & Machado, C. (2025). Using a Facebook group to engage college students in Israel and USA in cross-cultural dialogue: A mixed method study. Journal of Further and Higher Education, 49(5), 627–643. Scopus. https://doi.org/10.1080/0309877X.2025.2480647
Swetha, C. V., Shaji, S., & Jaya Kumar, C. (2025). Review of State-of-the-Art Literature on Learning Techniques for Cyberthreat Detection on Online Social Media Networks. Journal of Engineering Science and Technology Review, 18(3), 152–169. Scopus. https://doi.org/10.25103/jestr.183.15
Varma, M. S., & Ghosh, S. (2025). Transforming Sentimental Analysis: Applying Deep Learning with BERT and GPT for X Data Insights. 561–566. Scopus. https://doi.org/10.1109/ICVADV63329.2025.10961289
Yoon, S., Sun, F., Broadwell, P., Crupi, R., Patterson, M., Pottinger, T. D., Kim, M., & Davis, N. (2025). Using C4.5 Algorithm to Gain Insights on Stakeholder Engagement and Use of Artificial Intelligence on Social Media in Dementia Caregiving Disparity Research (J. Mantas, A. Hasman, E. Zoulias, K. Karitis, P. Gallos, M. Diomidous, S. Zogas, & M. Charalampidou, Eds.; Vol. 323, pp. 91–95). IOS Press BV; Scopus. https://doi.org/10.3233/SHTI250055
Zhang, H., Luo, S., & Tang, Y. (2025). Unlocking EFL achievement through informal digital learning: The mediating roles of anxiety and enjoyment among school-age students in the Chinese mainland. Asian-Pacific Journal of Second and Foreign Language Education, 10(1). Scopus. https://doi.org/10.1186/s40862-025-00352-x
Zhang, W.-F., & He, Y. (2025). The role of public cognition and emotion in behavioral engagement in science communication -A comparative analysis between scientists and citizen scientists. Studies in Science of Science, 43(4), 763–774. Scopus.
