A Theory-Informed Framework for Selecting AI Tools in Language Teaching
DOI:
https://doi.org/10.46328/ijte.5175Keywords:
Artificial intelligence , Tool selection, Theory-informed framework , Educational technology , English instructionAbstract
The revolutionary progress of Artificial Intelligence (AI) is redefining educational technology, enabling innovative approaches to education. However, the absence of a theory-informed support for selecting AI tools has raised concerns about instructional consistency and quality in language teaching. To address this gap, this study proposes an AI Tool Selection (ATS) Framework to guide educators in choosing AI tools for effective language teaching. To ensure theoretical rigor, the proposed framework synthesizes insights from nine established theories across three interrelated components: Pedagogical Alignment, informed by CLT, CALL, and SLA; Technological Integration, drawing on SAMR, TPACK, and HCI; and Adoption and Usability, grounded in TAM, Sociocultural Theory and DOI. Each component is defined by three clear indicators and guiding questions that prompt informed, context-sensitive decisions in AI tool selection. Overall, the conceived ATS Framework advances AI tool selection in language teaching by offering operational practicality, theoretical depth, and ethical-contextual sensitivity, ensuring that decisions are actionable, conceptually grounded, and culturally responsible. Future research should empirically validate and refine the framework across diverse educational and cultural contexts.
References
Abuhussein, H. F., & Badah, A. (2025). The Role of AI-based Writing Tools on L2 Writing Competency: Evidence from Palestinian EFL Learners. Dirasat: Human and Social Sciences, 52(5), 6566–6566.https://orcid.org/0000-0003-0209-3135
AlAli, R., & Wardat, Y. (2024). Opportunities and challenges of integrating generative artificial intelligence in education. International Journal of Religion, 5(7), 784–793.https://doi.org/10.61707/8y29gv34
Alsager, H. (2024). To Look from Another Window in Education: Artificial Intelligence Assisted Language Learning and Its Reflections on Academic Demotivation, Foreign Language Learning Anxiety and Autonomy. Computer-Assisted Language Learning Electronic Journal, 25(4), 124–147. https://orcid.org/0000-0003-3778-5801
Alwaqdani, M. (2024). Investigating teachers’ perceptions of artificial intelligence tools in education: Potential and difficulties. Education and Information Technologies, 1–19. https://doi.org/10.1007/s10639-024-12903-9
Alzubi, A. A. F., Nazim, M., & Alyami, N. (2025). Do AI-generative tools kill or nurture creativity in EFL teaching and learning? Education and Information Technologies, 1–38. https://doi.org/10.1007/s10639-025-13409-8
Bax, S. (2003). CALL—past, present and future. System, 31(1), 13–28.https://doi.org/10.1016/S0346-251X(02)00071-4
Chawla, P., & Bisla, M. (2025). An Empirical Investigation of Educators’ Professional Expertise to Incorporate Artificial Intelligence (AI)-Based Tools into the Classroom in a Responsible and Ethical Manner: Approach Toward Intelligent-TPACK. In Handbook of Disruptive Technologies (pp. 67–85). CRC Press.
Chhabra, S., Kaushal, V., & Girija, S. (2025). Determining the causes of user frustration in the case of conversational chatbots. Behaviour & Information Technology, 44(8), 1557–1575. https://doi.org/10.1080/0144929X.2024.2362956
De la Vall, R. R. F., & Araya, F. G. (2023). Exploring the benefits and challenges of AI-language learning tools. International Journal of Social Sciences and Humanities Invention, 10(01), 7569–7576. https://doi.org/10.18535/ijsshi/v10i01.02
Dix, A. (2009). Human-computer interaction. In Encyclopedia of database systems (pp. 1327–1331). Springer.
Du, Y., & Gao, H. (2022). Determinants affecting teachers’ adoption of AI-based applications in EFL context: An analysis of analytic hierarchy process. Education and Information Technologies, 27(7), 9357–9384. https://doi.org/10.1007/s10639-022-11001-y
Gruetzemacher, R., & Whittlestone, J. (2022). The transformative potential of artificial intelligence. Futures, 135, 102884. https://doi.org/10.1016/j.futures.2021.102884
Kaplan-Rakowski, R., Grotewold, K., Hartwick, P., & Papin, K. (2023). Generative AI and teachers’ perspectives on its implementation in education. Journal of Interactive Learning Research, 34(2), 313–338. https://doi.org/10.70725/815246mfssgp
Kaswan, K. S., Dhatterwal, J. S., & Ojha, R. P. (2024). AI in personalized learning. In Advances in technological innovations in higher education (pp. 103–117). CRC Press.
Khan, I. (2024). The quick guide to prompt engineering: Generative AI tips and tricks for ChatGPT, Bard, Dall-E, and Midjourney. John Wiley & Sons.
Khan, M. W., Saad, S., Ammad, S., Rasheed, K., & Jamal, Q. (2024). Smart Infrastructure and AI. In AI in Material Science (pp. 193–215). CRC Press.
Krashen, S. (1982). Principles and practice in second language acquisition. Alemany Press
Kokkoniemi, M., & Isomöttönen, V. (2025). Theoretical Frameworks in Focus: Group Work Research in Project-Based CS Education. Informatics in Education. https://doi.org/10.15388/infedu.2025.08
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20(1), 56. https://doi.org/10.1186/s41239-023-00426-1
Lantolf, J. P., & Poehner, M. E. (2023). Sociocultural theory and classroom https://doi.org/10.1111/modl.12816 second language learning in the East Asian context: Introduction to the special issue. The Modern Language Journal, 107(S1), 3–23. https://doi.org/10.1111/modl.12816
Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., & Darwis, A. (2023). Exploring artificial intelligence in academic essay: Higher education student’s perspective. International Journal of Educational Research Open, 5, 100296. https://doi.org/10.1016/j.ijedro.2023.100296
Martin, K. D., & Zimmermann, J. (2024). Artificial intelligence and its implications for data privacy. Current Opinion in Psychology, 101829. https://doi.org/10.1016/j.copsyc.2024.101829
Mateos Blanco, B., Álvarez Ramos, E., Alejaldre Biel, L., & Parrado Collantes, M. (2024). Vademecum of artificial intelligence tools applied to the teaching of languages. JOTSE Journal of Technology and Science Education, 14(1), 77–94. https://doi.org/10.3926/jotse.2522
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
Mouta, A., Pinto-Llorente, A. M., & Torrecilla-Sánchez, E. M. (2024). Uncovering blind spots in education ethics: Insights from a systematic literature review on artificial intelligence in education. International Journal of Artificial Intelligence in Education, 34(3), 1166–1205. https://doi.org/10.1007/s40593-023-00384-9
Nguyen, T. H., & Hoang, T. N. H. (2025). Investigating the Promises and Perils of Generative AI in EFL Learning in Higher Education: A Literature Review. AsiaCALL Online Journal, 16(1), 1–15. https://doi.org/10.5485/acoj.241521
Nikolopoulou, K. (2024). Generative artificial intelligence in higher education: Exploring ways of harnessing pedagogical practices with the assistance of ChatGPT. International Journal of Changes in Education, 1(2), 103–111. https://doi.org/10.47852/bonviewIJCE42022489
Nussbaum, M., & Bekerman, Z. (2025). Advancing holistic educational goals through generative language-based technologies. Learning and Individual Differences, 117, 102600. https://doi.org/10.1016/j.lindif.2024.102600
Ojanperä, T. (2024). AI Revolution: Mastering AI for Personal and Organizational Growth. CRC Press.
Ortega-Bolaños, R., Bernal-Salcedo, J., Germán Ortiz, M., Galeano Sarmiento, J., Ruz, G. A., & Tabares-Soto, R. (2024). Applying the ethics of AI: a systematic review of tools for developing and assessing AI-based systems. Artificial Intelligence Review, 57(5), 110. https://doi.org/10.1007/s10462-024-10740-3
Puentedura, R. (2006). Transformation, technology, and education.
Puntambekar, S. (2022). Distributed scaffolding: Scaffolding students in classroom environments. Educational Psychology Review, 34(1), 451–472. https://doi.org/10.1007/s10648-021-09636-3
Ramnani, S. (2024). Exploring Ethical Considerations of Artificial Intelligence in Educational Settings: An Examination of Bias, Privacy, and Accountability. International Journal of Novel Research and Development (IJNRD), 9(2), 2456–4184. https://www.researchgate.net/publication/388890763
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2014). Diffusion of innovations. In An integrated approach to communication theory and research (pp. 432–448). Routledge.
Tiandem-Adamou, Y. (2024). Using Generative Artificial Intelligence to Support EFL Students’ Writing Proficiency in University in China. Journal of Educational Technology and Innovation, 6(4). https://doi.org/10.61414/jeti.v6i4.213
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Wang, S., Yang, J., & Shang, F. (2024). A personalized recommendation model with multimodal preference-based graph attention network. The Journal of Supercomputing, 80(15), 22020–22048. https://doi.org/10.1007/s11227-024-06200-y
Wasilewski, A., Chawla, Y., & Pralat, E. (2025). Enhanced E-Commerce Personalization Through AI-Powered Content Generation Tools. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3550956
Yang, C., Wei, M., & Liu, Q. (2025). Intersections between cognitive‐emotion regulation, critical thinking and academic resilience with academic motivation and autonomy in EFL learners: Contributions of AI‐mediated learning environments. British Educational Research Journal. https://doi.org/10.1002/berj.4140
Yeh, H.-C. (2025). The synergy of generative AI and inquiry-based learning: Transforming the landscape of English teaching and learning. Interactive Learning Environments, 33(1), 88–102. https://doi.org/10.1080/10494820.2024.2335491
Zhan, X., Xu, Y., & Liu, Y. (2024). Personalized UI Layout Generation using Deep Learning: An Adaptive Interface Design Approach for Enhanced User Experience. Journal of Artificial Intelligence General Science (JAIGS) ISSN: 3006-4023, 6(1), 463–478. https://doi.org/10.60087/jaigs.v6i1.270
Zhang, J. (2024). Application of Artificial Intelligence Tools in Educational Assessment: Enhancing Teaching and Learning Management in Beijing Junior High Schools. Eurasian Journal of Educational Research (EJER), 112. https://doi.org/10.14689/ejer.2024.112.017
Zhou, Q., Hashim, H., & Sulaiman, N. A. (2025). Supporting English speaking practice in higher education: The impact of AI chatbot-integrated mobile-assisted blended learning framework. Education and Information Technologies, 1–32. https://doi.org/10.1007/s10639-025-13401-2
Zong, Y., & Yang, L. (2025). How AI‐Enhanced Social–Emotional Learning Framework Transforms EFL Students’ Engagement and Emotional Well‐Being. European Journal of Education, 60(1), e12925. https://doi.org/10.1111/ejed.12925
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