Research Article

‘OMG! You used AI’ – A critical exploration of linguistic stigmatization in the era of generative artificial intelligence

Ntshimane Elphas Mohale 1 * , Kershnee Sevnarayan 1 , Kgabo Bridget Maphoto 1 , Zuleika Suliman 1
More Detail
1 Department of English Studies, College of Human Sciences, University of South Africa, Pretoria, SOUTH AFRICA* Corresponding Author
Online Journal of Communication and Media Technologies, 15(4), October 2025, e202536, https://doi.org/10.30935/ojcmt/17484
Published: 02 December 2025
OPEN ACCESS   205 Views   112 Downloads
Download Full Text (PDF)

ABSTRACT

The popularity of generative artificial intelligence (GenAI) in higher education institutions has sparked significant debate among scholars, lecturers, markers, and students. Reactions range from enthusiasm to concern. On the one hand, GenAI is embraced for its incidental benefits in language learning; and, on the other, it is met with resistance due to issues such as reduced cognitive engagement, technophobia, and fears of academic dishonesty. An area of concern involves the emergence and frequent recurrence of certain linguistic features and vocabulary associated with GenAI texts. This study explores the stigmatization of these linguistic patterns in an open distance e-learning (ODeL) context and explores how their usage influences perceptions of students’ work. A case study design was used in this mixed-methods approach. Data were collected through an online questionnaire distributed to students and an open-ended evaluation form completed by markers. The study is grounded in the framing theory, which examines how GenAI content is presented in academic contexts, either as unethical and inauthentic or as a tool for empowerment. The findings reveal that markers have developed biases against linguistic features commonly associated with GenAI and students use GenAI to improve their writing. Although GenAI can be a useful linguistic aid, ethical use and transparent disclosure are critical to maintain academic integrity. These findings call for the development of clear institutional guidelines and marker training to ensure fair and informed assessment in the age of GenAI in ODeL.

CITATION (APA)

Mohale, N. E., Sevnarayan, K., Maphoto, K. B., & Suliman, Z. (2025). ‘OMG! You used AI’ – A critical exploration of linguistic stigmatization in the era of generative artificial intelligence. Online Journal of Communication and Media Technologies, 15(4), e202536. https://doi.org/10.30935/ojcmt/17484

REFERENCES

  1. Agarwal, D., Naaman, M., & Vashistha, A. (2025). AI suggestions homogenize writing toward western styles and diminish cultural nuances. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Article 1117. https://doi.org/10.1145/3706598.3713564
  2. Bannister, P. (2024). English medium instruction educator language assessment literacy and the test of generative AI in online higher education. Journal of Research in Applied Linguistics, 15(2), 55–72.
  3. Borah, P. (2011). Conceptual issues in framing theory: A systematic examination of a decade’s literature. Journal of Communication, 61(2), 246–263. https://doi.org/10.1111/j.1460-2466.2011.01539.x
  4. Bozkurt, A. (2023a). A global outlook to the interruption of education due to the COVID-19 pandemic: Navigating in a time of uncertainty and crisis. Open Praxis, 15(1), 5–22.
  5. Bozkurt, A. (2023b). Prompt engineering, emotional intelligence, and the ethics of AI in education: Reimagining pedagogy in the age of generative AI. Asian Journal of Distance Education, 18(2), 62–75.
  6. Bozkurt, A., & Sharma, R. C. (2023). Challenging the status quo and exploring the new boundaries in the age of algorithms: Reimagining the role of generative AI in distance education and online learning. Asian Journal of Distance Education, 18(1), i–viii.
  7. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
  8. Carspecken, P. F. (1996). Critical ethnography in educational research: A theoretical and practical guide. Routledge.
  9. Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education. Educational Technology & Society, 25(1), 28–47.
  10. Chong, D., & Druckman, J. N. (2007). Framing theory. Annual Review of Political Science, 10(1), 103–126. https://doi.org/10.1146/annurev.polisci.10.072805.103054
  11. Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (2nd ed.). SAGE.
  12. de Vreese, C. H. (2005). News framing: Theory and typology. Information Design Journal + Document Design, 13(1), 51–62. https://doi.org/10.1075/idjdd.13.1.06vre
  13. de Vreese, C. H., & Lecheler, S. (2015). Framing theory. In R. L. Colebatch, H. M. Rasheed, & R. Z. Farrelly (Eds.), The international encyclopedia of political communication (pp. 1–10). Wiley. https://doi.org/10.1002/9781118541555.wbiepc121
  14. Dergaa, I., Fekih-Romdhane, F., Glenn, J. M., Saifeddin Fessi, M., Chamari, K., Dhahbi, W., Makram, Z., Bragazzi, N., Aissa, M. B., Guelmemi, N., El Omri, A., Swed, S., Weiss, K., Knechtle, B., & Saad, H. B. (2023). Moving beyond the stigma: Understanding and overcoming the resistance to the acceptance and adoption of artificial intelligence chatbots. New Asian Journal of Medicine, 1(2), 29–36.
  15. dos Santos, A. E. (2024). Generative artificial intelligence and its impact on writing [PhD thesis, Universidade Federal de Sergipe].
  16. Drake, L. E., & Donohue, W. A. (1996). Communicative framing theory in conflict resolution. Communication Research, 23(3), 297–322. https://doi.org/10.1177/009365096023003003
  17. Eckert, P. (2018). Meaning and linguistic variation: The third wave in sociolinguistics. Cambridge University Press.
  18. Entman, R. M. (1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51–58. https://doi.org/10.1111/j.1460-2466.1993.tb01304.x
  19. Fairclough N. (1992). Discourse and social change. Polity.
  20. Fathi, J., Rahimi, M., & Derakhshan, A. (2024). Improving EFL learners’ speaking skills and willingness to communicate via artificial intelligence-mediated interactions. System, 121, Article 103254. https://doi.org/10.1016/j.system.2024.103254
  21. Fleisig, M., Smith, A., Bossi, L., Rustagi, R., & Yin, H. (2024). Bias in the machine: An empirical study of dialect misrecognition and stylistic conformity in ChatGPT. Language and Society in the Digital Age, 3(2), 101–128.
  22. Fu, Y., Bin, H., Zhou, T., Wang, M., Chen, Y., da Costa Lai, Z. G., Wobbrock, J. O., & Hiniker, A. (2024). Creativity in the age of AI: Evaluating the impact of generative AI on design outputs and designers’ creative thinking. arXiv. https://doi.org/10.48550/arXiv.2411.00168
  23. Furze, L., Perkins, M., Roe, J., & Ruelle, D. (2024). The AI assessment scale in action: A pilot implementation of GenAI-supported assessment. Australasian Journal of Educational Technology, 40(4), 38–55. https://doi.org/10.14742/ajet.9434
  24. Giray, L., Sevnarayan, K., & Ranjbaran Madiseh, F. (2025). Beyond policing: AI writing detection tools, trust, academic integrity, and their implications for college writing. Internet Reference Services Quarterly, 30(1), 1–34. https://doi.org/10.1080/10875301.2024.2437174
  25. Goffman, E. (1974). Frame analysis: An essay on the organization of experience. Harvard University Press.
  26. Güran, M. S., & Özarslan, H. (2022). Framing theory in the age of social media. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (48), 446–457. https://doi.org/10.52642/susbed.1142562
  27. Hendawy, M. (2024). The intensified digital divide: Comprehending GenAI. Internet Policy Review, 13(1).
  28. Heritage, J. (1985). A change-of-state token and aspects of its sequential placement. In J. M. Atkinson (Ed.), Structures of social action. Studies in emotion and social interaction (pp. 299–345). Cambridge University Press. https://doi.org/10.1017/CBO9780511665868.020
  29. Hikmah, D., & Walida, B. (2024). The role of ChatGPT in enhancing students’ critical thinking in academic writing. Ethical Lingua. Journal of Language Teaching and Literature, 11(2). https://doi.org/10.30605/25409190.780
  30. Hohenstein, J., Kizilcec, R. F., DiFranzo, D., Aghajari, Z., Mieczkowski, H., Levy, K., Naaman, N., Hancock, J., & Jung, M. F. (2023). Artificial intelligence in communication impacts language and social relationships. Scientific Reports, 13, Article 5487. https://doi.org/10.1038/s41598-023-30938-9
  31. Khampusaen, D. (2025). The impact of ChatGPT on academic writing skills and knowledge: An investigation of its use in argumentative essays. LEARN Journal: Language Education and Acquisition Research Network, 18(1), 963–988. https://doi.org/10.70730/PGCQ9242
  32. Konyrova, L. K. (2024). The evolution of language learning: Exploring AI’s impact on teaching English as a second language. Eurasian Science Review, 2(4), 134–146. https://doi.org/10.63034/esr-42
  33. Kuan, D., Hasan, N. A. M., Zawawi, J. W. M., & Abdullah, Z. (2021). Framing theory application in public relations: The lack of dynamic framing analysis in competitive context. Media Watch, 12(2), 333–351. https://doi.org/10.15655/mw/2021/v12i2/160155
  34. Lakshmi, R. (2025). Rebranding empire in the age of generative AI: Cultural gatekeeping and the algorithmic imagination. Frontiers in Artificial Intelligence, 8. https://doi.org/10.3389/fcomm.2025.1604361
  35. Lather, P. (2006). Paradigm proliferation as a good thing to think with: Teaching research in education as a wild profusion. International Journal of Qualitative Studies in Education, 19(1), 35–57. https://doi.org/10.1080/09518390500450144
  36. Law, L. (2024). Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, 5, Article 100174. https://doi.org/10.1016/j.caeo.2024.100174
  37. Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Article 1121. https://doi.org/10.1145/3706598.3713778
  38. Liu, H., Zhang, X., Zhou, J., Shou, Y., Yin, Y., & Chai, C. (2024). Cognitive styles and design performances in conceptual design collaboration with GenAI. International Journal of Technology and Design Education, 35, 1169–1202. https://doi.org/10.1007/s10798-024-09937-y
  39. Luo, J. (2024). A critical review of GenAI policies in higher education assessment: A call to reconsider the “originality” of students’ work. Assessment & Evaluation in Higher Education, 49(5), 651–664. https://doi.org/10.1080/02602938.2024.2309963
  40. Mahapatra, S. (2024). Impact of ChatGPT on ESL students’ academic writing skills: A mixed methods intervention study. Smart Learning Environments, 11(1), Article 9. https://doi.org/10.1186/s40561-024-00295-9
  41. Maloy, R. W., & Gattupalli, S. (2024). Prompt literacy. In O. St. Pierre, & R. Johnson (Eds.), EdTechnica: The open encyclopedia of educational technology (pp. 211–216). EdTech Books. https://doi.org/10.59668/371.14442
  42. Medina, D. (2024). Generative AI in writing education: Policy and pedagogical implications. Taylor & Francis. https://doi.org/10.4324/9781003493563
  43. Nguyen, K. V. (2025). The use of generative AI tools in higher education: Ethical and pedagogical principles. Journal of Academic Ethics, 23, 1435–1455. https://doi.org/10.1007/s10805-025-09607-1
  44. Noroozi, O., Soleimani, S., Farrokhnia, M., & Banihashem, S. K. (2024). Generative AI in education: Pedagogical, theoretical, and methodological perspectives. International Journal of Technology in Education, 7(3), 373–385. https://doi.org/10.46328/ijte.845
  45. Nyaaba, A., Wright, C., & Choi, Y. (2024). Generative AI and the marginalisation of indigenous pedagogies in higher education. arXiv. https://arxiv.org/pdf/2406.02966
  46. Patton, M. Q. (2015). Qualitative research and evaluation methods (4th ed.). SAGE.
  47. Rettberg, J. W. (2024). How generative AI endangers cultural narratives. Issues in Science and Technology, 40(2), 77–79. https://doi.org/10.58875/RQJD7538
  48. Roe, J., Perkins, M., & Ruelle, D. (2024). Is GenAI the future of feedback? Understanding student and staff perspectives on AI use in assessment. Intelligent Technologies in Education. https://doi.org/10.53761/ITED/1.7
  49. Sacks, H., Schegloff, E. A., & Jefferson, G. (1974). A simplest systematics for the organization of turn-taking for conversation. Language, 50(4), 696–735. https://doi.org/10.1353/lan.1974.0010
  50. Sahu, M. N. (2024). The GenAI revolution: Unleashing the role of information technology in education. Sudarshan Research Journal, 2(5), 55–57.
  51. Samala, A. D., Rawas, S., Wang, T., Reed, J. M., Kim, J., Howard, N. J., & Ertz, M. (2025). Unveiling the landscape of generative artificial intelligence in education: A comprehensive taxonomy of applications, challenges, and future prospects. Education and Information Technologies, 30(3), 3239–3278. https://doi.org/10.1007/s10639-024-12936-0
  52. Shabalala, N. P. (2024). Elevating STEM learning: Unleashing the power of AI in open distance eLearning. Research in Social Sciences and Technology, 9(3), 269–288. https://doi.org/10.46303/ressat.2024.59
  53. Sidnell, J. (2010). Conversation analysis: An introduction. John Wiley & Sons. https://doi.org/10.1093/obo/9780199772810-0062
  54. Smith, G., Fleisig, E., Bossi, M., Rustagi, I., & Yin, X. (2024). Standard language ideology in AI-generated language. arXiv. https://doi.org/10.48550/arXiv.2406.08726
  55. Sourati, M., Chen, L., & Idris, M. (2025). The erasure of voice: Linguistic flattening in AI-assisted student writing. Language and Education.
  56. Stake, R. E. (1995). The art of case study research. SAGE.
  57. Suh, S., Bang, J., & Han, J. W. (2025). Developing critical thinking in second language learners: Exploring generative AI like ChatGPT as a tool for argumentative essay writing. arXiv. https://doi.org/10.48550/arXiv.2503.17013
  58. Wadinambiarachchi, S., Kelly, R. M., Pareek, S., Zhou, Q., & Velloso, E. (2024). The effects of generative AI on design fixation and divergent thinking. Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, Article 380. https://doi.org/10.1145/3613904.3642919
  59. Wodak, R. (2014). Critical discourse analysis and the study of doctor-patient interaction. In B. L. Gunnarsson, P. Linell, & B. Nordberg (Eds.), The construction of professional discourse (pp. 173–200). Routledge.
  60. Wodak, R. (2022). Critical linguistics and critical discourse analysis. In L. R. Horn, & G. Ward (Eds.), Handbook of pragmatics (pp. 426–443). John Benjamins Publishing Company. https://doi.org/10.1075/hop.m2.cri1
  61. Yin, R. K. (2014). Case study research: Design and methods (5th ed.). SAGE.