TRANSFORMING LINGUISTICS AND LANGUAGE ARTS THROUGH ARTIFICIAL INTELLIGENCE: NEW FRONTIERS IN INSIGHT AND EDUCATION
Abstract
The traditional methods of teaching linguistics and language arts are no longer sufficient to meet the evolving educational needs of the 21st century, and the integration of artificial intelligence (AI) to enhance learning and insight in these fields is lacking. This study examined the transformation of linguistics and language arts through AI: new frontiers in insight and education. The study was anchored on Lev Vygotsky’s sociocultural theory and employed an in-depth descriptive survey research design. The population comprised 5,000 language arts students and 7,000 lecturers at Rivers State University (RSU) and the University of Port Harcourt (UniPort), estimated at 5,000 and 7,000 respectively. A purposive sampling technique was to identify 12 lecturers (six from each institution) and 24 final-year undergraduates (12 from each), for a total sample size of 36, ensuring that participants have sustained engagement with AI tools. Data were collected via one-on-one, audio-recorded interviews guided by an interview protocol. Transcripts were analysed using Braun and Clarke’s (2006) six-phase thematic analysis to inductively derive themes reflecting the dynamics between AI tool use and linguistic proficiency (LP). The findings revealed that AI tools significantly enhance students’ linguistic proficiency by providing instant, personalized feedback on grammar, vocabulary, and writing structure, especially when integrated consistently in secondary and tertiary language learning environments. The study concluded that the integration of AI into language learning has significantly improved students’ vocabulary development and communication skills, affirming that AI serves as a powerful tool for enhancing linguistic competence and learner engagement in language classrooms when appropriately implemented. The study recommended that educational institutions invest in AI-based language learning tools to enhance students’ vocabulary and communication skills
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Transforming Linguistics, Language Arts, Artificial Intelligence, New Frontiers, Insight, EducationDownloads
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Copyright (c) 2025 Otuogha, Austin Mathias (PhD) , Eke Chigozi
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References
Adediran, A., & Olanrewaju, T. (2023). Digitizing indigenous languages in Nigeria: The role of AI in language preservation and education. Nigerian Journal of Educational Technology, 14(2), 89 –105.
Almalki, A., & Aziz, A. (2022). AI in language education: An analysis of intelligent tutoring systems. International Journal of Educational Technology in Higher Education, 19(1), 1–20. https://doi.org/10.1016/ijt.2011.09.010.
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922
Blodgett, S. L., Barocas, S., Daumé III, H., & Wallach, H. (2020). Language (technology) is power: A critical survey of “bias” in NLP. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 5454–5476. https://doi.org/10.18653/v1/2020.acl-main.485
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Choi, H., & Park, J. (2023). Generative AI in humanities research: Opportunities and ethical dilemmas. AI & Society, 38(1), 231–246.
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). Sage Publications.
Donato, R. (1994). Collective scaffolding in second language learning. In J. P. Lantolf & G. Appel (Eds.), Vygotskian approaches to second language research (pp. 33–56). Ablex.
Jurafsky, D., & Martin, J. H. (2023). Speech and language processing (3rd ed.). Pearson.
Kozulin, A. (2003). Vygotsky’s educational theory in cultural context. Cambridge University Press.
Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation (4th ed.). Jossey-Bass.
Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Sage Publications.
Okunade, K. S., & Omidiora, E. O. (2022). Artificial intelligence and African languages: A framework for revitalization. African Journal of Language and Linguistics, 18(1), 33–47. https://doi.org/10.1016/j.aji.2018.01.013.k
Ravitch, S. M., & Riggan, M. (2017). Reason & rigor: How conceptual frameworks guide research (2nd ed.). Sage Publications.
Reiser, B. J., & Tabak, I. (2014). Scaffolding. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (2nd ed., pp. 44–62). Cambridge University Press.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30. https://papers.nips.cc/paper_files/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds. & Trans.). Harvard University Press.
Wertsch, J. V. (1991). Voices of the mind: A sociocultural approach to mediated action. Harvard University Press.
Young, R., & Wang, Y. (2021). Using AI to advance language learning: Personalized systems and pedagogical innovation. Journal of Computer Assisted Learning, 37(6), 1561–1576.
