Agency Construction in AI English Language Learning Applications: A Transitivity Analysis of Promotional Discourse
DOI:
https://doi.org/10.17507/tpls.1605.12Keywords:
agency, English learning applications, AI tools, promotional discourse, transitivity analysisAbstract
This study explored how AI tools and human learners are represented in the promotional texts of AI-based English learning applications through quantitative and qualitative methods. The study aims to analyze promotional texts from globally popular applications—Grammarly, QuillBot, Mondly, Lingopie, and ELSA Speak— collected from App Store descriptions and official websites employing Halliday’s transitivity system. Quantitatively, the analysis of 148 clauses showed that only three process types were employed: material (83.73%), relational (11.49%), and mental (4.73%). Learners were foregrounded as central actors (83.7%) and beneficiaries (16.3%), while the AI tools were less frequent as actors (56.1%) but appeared more often as instrumental circumstances (24.2%). Qualitatively, three themes emerged: (1) AI tools as active, supportive, and authoritative agents, (2) human learners as autonomous yet dependent agents, and (3) shared agency in which learners remained central doers, but their abilities were consistently enabled by AI tools. These findings highlight how promotional discourse constructs a learner-centered orientation while normalizing AI’s authority. The study contributes by illustrating how transitivity analysis can reveal patterns of representation and agency in promotional texts, offering insights for researchers, educators, and developers of AI English learning tools.
References
Alhumsi, M. H., & Alsaedi, N. (2023). A transitivity analysis of two political articles: An investigation of gender variations in political media discourse. World Journal of English Language, 13(6), 107. https://doi.org/10.5430/wjel.v13n6p107
Alhumsi, M. H., Alsaedi, N., Fallata, S., & Alharbi, A. (2024). Transitivity analysis of an academic document: A case of English course syllabi at Saudi electronic University. Pakistan Journal of Life and Social Sciences (PJLSS), 22(2). https://doi.org/10.57239/pjlss-2024-22.2.001062
Alkhalil, S. F. (2018). Promoting English in Saudi Arabia: A critical discourse analysis of advertisements for private English language teaching institutes [Unpublished master's thesis]. Macquarie University.
Alm, A. (2024). Exploring autonomy in the AI wilderness: Learner challenges and choices. Education Sciences, 14(12), Article 1369. https://doi.org/10.3390/educsci14121369
Al-Qahtani, A. (2021). Website representations of Saudi universities in Makkah region: A critical discourse analysis approach. Cogent Arts & Humanities, 8(1). https://doi.org/10.1080/23311983.2021.1895463
Alsaedi, N. (2024). Empowering Saudi women through automobile advertisements: A transitivity analysis. International Journal of Language and Literary Studies, 6(2), 297-315. https://doi.org/10.36892/ijlls.v6i2.1714
Alsaedi, N. (2024). ChatGPT and EFL/ESL writing: A systematic review of advantages and challenges. English Language Teaching, 17(5), Article 41. https://doi.org/10.5539/elt.v17n5p41
Arbain, Pane, W. S., & Jannah, R. M. (2023). Comparative efficacy of Elsa and English speaking practice: A quasi-experimental study on EFL learning outcomes. Eduvelop: Journal of English Education and Development, 7(1), 22-31. https://doi.org/10.31605/eduvelop.v7i1.2974
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264-75278. https://doi.org/10.1109/access.2020.2988510
Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). SAGE.
Florez, J. L. (2024). Analysis of mobile applications for language learning: Unpacking discourses about second language learning trends and marketing strategies [Unpublished master's thesis]. Universidad Tecnológica de Pereira.
Godwin-Jones, R. (2024). Distributed agency in second language learning and teaching through generative AI. Language Learning & Technology, 28(2), 5-31. https://doi.org/10.64152/10125/73570
Halliday, M. A. (1978). Language as social semiotic: The social interpretation of language and meaning. Hodder Education.
Halliday, M. A. (1985). An introduction to functional grammar. Edward Arnold.
Halliday, M. A. (1994). Language as social semiotic. In Language and Literacy in Social Practice (pp. 23-43). Multilingual Matters.
Halliday, M. A., & Matthiessen, C. M. (2014). Halliday’s introduction to functional grammar (4th ed.). Routledge.
Halliday, M. K., & Webster, J. J. (2014). Text linguistics: The how and why of meaning. Equinox Publishing Ltd.
Heaton, D., Nichele, E., Clos, J., & Fischer, J. E. (2023). “The algorithm will screw you”: Blame, social actors and the 2020 A level results algorithm on Twitter. Plos One, 18(7), Article e0288662. https://doi.org/10.1371/journal.pone.0288662
Heaton, D., Nichele, E., Clos, J., & Fischer, J. E. (2024). “ChatGPT says no”: Agency, trust, and blame in Twitter discourses after the launch of ChatGPT. AI and Ethics, 5(1), 653-675. https://doi.org/10.1007/s43681-023-00414-1
Hoang, T. V., & Rojas-Lizana, I. (2015). Promotional discourse in the websites of two Australian universities: A discourse analytic approach. Cogent Education, 2(1), Article 1011488. https://doi.org/10.1080/2331186x.2015.1011488
Holmes, W., Bialik, M., & Fadel, C. (2023). Artificial intelligence in education. In Data Ethics: Building Trust (pp. 621-653). Globethics Publications. https://doi.org/10.58863/20.500.12424/4276068
Huang, X., & Gadavanij, S. (2025). Power and marginalization in discourse on AI in education (AIEd): Social actors’ representation in China daily (2018–2023). Humanities and Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-025-04621-5
Ignatieva, N., Rodríguez, D., Zamudio, V., & Jiménez, G. (2021). The construal of experience through transitivity in student academic writing across humanistic disciplines: A systemic functional analysis. Signum: Estudos da Linguagem, 24(1), 17–34.
Ismailia, T., & Novawan, A. (2025). Enhancing EFL students’ recount writing: A comparative analysis of Grammarly, QuillBot, and GrammarCheck applications. Journal of English in Academic and Professional Communication, 11(2), 89-102. https://doi.org/10.25047/jeapco.v11i2.5095
Koller, V. (2020). Discourse analysis and systemic functional linguistics. In Researching discourse: A student guide (1st ed.). Routledge.
Llausas, S. M., Ruiz, E., Ayucan, S. M., & Evardo Jr., O. J. (2024). A systematic literature review on the use of Grammarly in improving the writing skills of ESL/EFL students. International Journal of Multidisciplinary: Applied Business and Education Research, 5(9), 3507-3516. https://doi.org/10.11594/ijmaber.05.09.10
Miller, A. (2025). Integrating AI in education: Educational technology practices, tools, and accessibility. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5361763
Nugraheni, Y., Santosa, R., Nababan, M. R., & Wiratno, T. (2023). Gender roles construction through transitivity in Indonesia’s facial care advertisement for woman. Advances in Social Science, Education and Humanities Research, 361-368. https://doi.org/10.2991/978-2-38476-078-7_37
Nushi, M., Fattahi, N., & Ebn-Abbasi, F. (2024). An evaluative review of Mondly: A mobile language learning application. The EuroCALL Review, 30(2), 69-85. https://doi.org/10.4995/eurocall.2023.15763
Nushi, M., & Sadeghi, M. (2021). A critical review of ELSA: A pronunciation app. Computer-Assisted Language Learning Electronic Journal, 22(3), 287-302. https://callej.org/index.php/journal/article/view/365
Nusra, T. R. (2025). Critical discourse analysis of entrepreneurship in e-Learning platforms: A Fairclough model application [Unpublished master's thesis]. BRAC University.
Roza, N. (2025, March 6). Grammarly statistics facts and trends for 2025- How many people use Grammarly? Nikola Roza- SEO for the Poor and Determined. Retrieved September 5, 2025, from https://nikolaroza.com/grammarly-statistics-facts-trends/
Saldanha, G., & O’Brien, S. (2014). Research methodologies in translation studies (1st ed.). Routledge.
Salsabila, V. A., Maolida, E. H., & Nuraini, W. (2023). Transitivity analysis: Gender representation in two English textbooks for tenth grade students. Jurnal JOEPALLT (Journal of English Pedagogy, Linguistics, Literature, and Teaching), 11(1), 10. https://doi.org/10.35194/jj.v11i1.2906
Shahnaz, A., & Suleman, N. (2023). Semiotic analysis of university prospectuses in Pakistan: Marketization, identity, and power dynamics. Social Semiotics, 35(2), 208-227. https://doi.org/10.1080/10350330.2023.2286452
Tan, R., Djonov, E., & Chik, A. (2025). Balancing professionalism and accessibility: Comparing preschool English teaching by teachers and by applications. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13576-8
Wah, J. N. (2025). Artificial intelligence in language learning: A systematic review of personalization and learner engagement. Forum for Linguistic Studies, 7(9). https://doi.org/10.30564/fls.v7i9.10336
Wulandari, D. A., Putry, V. U., Rahmadani, F. N., & Pohan, E. (2024). Trend issue of using technology in English foreign language teaching context. English Education Journal, 2(2), 104-108. https://doi.org/10.59966/eduj.v2i2.1468
Zapata, G. C., Tzirides, A., & Cope, B. (2025). A systemic functional linguistics discourse analysis of learner-centered, generative AI feedback in higher education. EdArXiv. https://doi.org/10.35542/osf.io/nuhq2_v1
