Examining the Association between Meta -

Examining the Association between Meta AI Use and English Language Pedagogy among Teachers and Students in North-Eastern Nigeria: A Convergent Mixed-Methods Study

^*1Benjamin Terzungwe Iorhemen, ²Musa Haruna, and ³Aliyu Dahiru

^*1Department of Arts and Social Science Education, Faculty of Education, Federal University of Kashere, Gombe State, Nigeria. Email: benudus2016@gmail.com, ORCID :https://orcid.org/0000-0002-13577859

²Department of General Studies Education, Federal College of Education Technical, Potiskum, Yobe State Nigeria. Email: harunamusa7029@gmail.com

³Department of Arts and Social Science Education, Faculty of Education, Federal University of Kashere, Gombe State, Nigeria. Email: dahirualiyu@fukashere.edu.ng

DOI: https://doi.org/10.65760/rijessu.v5.3.13

Abstract

This study examined the association between Meta AI and English language pedagogy in selected institutions in North-Eastern Nigeria. The study was anchored on the Technology Acceptance Model, Constructivist Learning Theory, Second Language Acquisition Theory and Activity Theory to explain technology adoption, learner-centred instruction, language acquisition processes and socio-technical dynamics of AI integration. A convergent parallel mixed-methods design was employed. A minimum sample size of 343 participants, determined using the Taro Yamane formula, was increased to 360 to accommodate possible non-response. The quantitative sample comprised 55 English language lecturers, 85 teachers, and 220 undergraduate students selected through multistage sampling. Qualitative data were obtained through semi-structured interviews with 12 purposively selected participants comprising four English language lecturers, four English language teachers, and four undergraduate students. Data were collected using a structured questionnaire and a semi-structured interview guide. The validity of the instruments was established through expert review, while reliability was confirmed using Cronbach's alpha coefficients of 0.81. Quantitative data were analysed using descriptive statistics and Chi-square analysis, while qualitative data were analysed thematically. Findings revealed significant positive associations between Meta AI use and respondents' perceptions of writing proficiency, vocabulary acquisition, learner motivation, pedagogical practices, and learner engagement (χ² = 42.63, p < .05). Qualitative findings corroborated these results, highlighting improved personalized learning, immediate feedback, learner autonomy, and classroom interaction, alongside challenges such as poor internet connectivity, inadequate teacher training, and overreliance on AI tools. The study concludes that Meta AI is significantly associated with improved English language pedagogy and recommends strengthened digital infrastructure, teacher training, and policy frameworks for responsible AI integration.

Keywords: Artificial Intelligence, English Language Pedagogy, Meta AI, Mixed Methods Technology Acceptance Model

Reference

Akpa, N. A., & Iorhemen, B. T. (2026). Effects of artificial intelligence-assisted instruction on English language achievement in Nigerian secondary schools: A quasi-experimental study. Akasa Multidisciplinary Journal, 4(1), 302–316

Bruner, J. S. (1966). Toward a theory of instruction. Harvard University Press.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Engeström, Y. (1987). Learning by expanding: An activity-theoretical approach to developmental research. Orienta-Konsultit.

Jeon, E.-Y. (2025). Artificial intelligence in ESL/EFL education: Evidence from recent reviews (2024–2025). International Journal of Learning, Teaching and Educational Research, 24(10), 509–526. https://doi.org/10.26803/ijlter.24.10.24

Iorhemen, B. T., Wasagu, S. M., & Dahiru, A. (2026). Transforming English language teaching in the era of artificial intelligence: Examining the opportunities and challenges of ChatGPT. In Synergy of Ideas: AKASA Multidisciplinary Book Chapter Contributions (2nd ed., pp. 37–55). AKASA. https://doi.org/10.64726/m83kg860

Koç, F. Ş., & Savaş, P. (2024). The use of artificially intelligent chatbots in English language learning: A systematic meta-synthesis study of articles published between 2010 and 2024. ReCALL, 37(1), 1–18. https://doi.org/10.1017/S0958344024000168

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. https://doi.org/10.1177/001316447003000308

Lee, S., Jeon, J., McKinley, J., & Rose, H. (2025). Generative AI and English language teaching: A global Englishes perspective. Annual Review of Applied Linguistics, 45, 1–24. https://doi.org/10.1017/S0267190525100184

Li, B., Tan, L., Wang, C., & Lowell, V. L. (2025). Two years of innovation: A systematic review of empirical generative AI research in language learning and teaching. Computers and Education: Artificial Intelligence, 9, 100445. https://doi.org/10.1016/j.caeai.2025.100445

Liu, G., Darvin, R., & Mac, C. (2025). Exploring AI-mediated informal digital learning of English (AI-IDLE): A mixed-method investigation of Chinese EFL learners’ AI adoption and experiences. Computer Assisted Language Learning, 38(7), 1632–1660. https://doi.org/10.1080/09588221.2024.2310288

Lee, T., & Cho, V. (2025). Enhancing language learning through generative artificial intelligence in blended learning: An empirical study on productive and receptive informal digital learning English. Journal of Educational Technology Systems, 53(3). https://doi.org/10.1177/00472395241266454

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill Education https://doi.org/10.1080/2331186X.2024.2433814

Mohebbi, A. (2024). Enabling learner independence and self-regulation in language education using AI tools: A systematic review. Cogent Education, 11(1).

Torres, P. J., & Kahveci, Y. E. (2025). Effectiveness of artificial intelligence (AI) in language teaching. Computers and Education: Artificial Intelligence, 9, 100522. https://doi.org/10.1016/j.caeai.2025.100522

Swain, M. (1985). Communicative competence: Some roles of comprehensible input and comprehensible output in its development. In S. Gass & C. Madden (Eds.), Input in second language acquisition (pp. 235–253). Newbury House..

Wang, Y., Zhang, T., Yao, L., & Seedhouse, P. (2025). A scoping review of empirical studies on generative artificial intelligence in language education. Innovation in Language Learning and Teaching, 19(4), 1–23. https://doi.org/10.1080/17501229.2025.2509759

Krashen, S. D. (1982). Principles and practice in second language acquisition. Pergamon Press.

Leont’ev, A. N. (1978). Activity, consciousness, and personality. Prentice-Hall.

Xiong, M., & Teo, T. (2025). Unveiling the effects of GenAI on motivation of learning English as a second/foreign language: Evidence from meta-analysis. Educational Research Review, 49, 100744. https://doi.org/10.1016/j.edurev.2025.100744

Yamane, T. (1967). Statistics: An introductory analysis (2nd ed.). Internet Archive

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

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