Applying the SAMR Model to AI-Enhanced Business Language Instruction: Comparative Insights from German and Spanish Contexts
Abstract
Background: The SAMR model offers a structured way to analyze how technology reshapes teaching and learning. In the context of Generative Artificial Intelligence (GAI), it provides a productive lens for reconsidering how language instruction - especially within Languages for Specific Purposes (LSP) - evolves in response to AI integration.
Purpose: This article examines the use of AI-driven tools in Business German and Business Spanish across two contrasting settings: higher education and corporate training. It aims to build a comparative perspective that highlights how pedagogical intentions and constraints differ across these environments and what that means for responsible and effective AI integration.
Conceptual Contribution: We propose that the SAMR model can be reframed specifically for Generative AI in Business LSP to clarify how instructional practices move between enhancement and transformation. Rather than reporting empirical findings, the article argues that AI-enabled personalization, collaboration, and authentic task design can be interpreted as occupying distinct SAMR levels. This conceptual reframing distinguishes between uses of AI that streamline existing practices and those that fundamentally rethink language learning experiences.
Implications: By repositioning SAMR as a flexible analytic tool rather than a descriptive taxonomy, this article contends that educators can better anticipate both opportunities and risks in professional language instruction. The argument advances a foundation for integrating GAI in ways that support pedagogical innovation while safeguarding equity, integrity, and quality in Business German and Business Spanish education.
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References
Alonso-Rodríguez, A. M. (2024). Towards an Ethical Framework for Artificial Intelligence in Education. Revista Interuniversitaria, 36(2), 79-98. https://doi.org/10.14201/teri.31821
Amelina, S. M., Tarasenko, R. O., & Semerikov, S. O. (2023). Enhancing foreign language learning with cloud-based mind mapping techniques. Proceedings of the VIII International Workshop on Professional Retraining and Life-Long Learning using ICT: Person-oriented Approach (vol. 3535, pp. 48-60). CEUR. https://doi.org/10.31812/123456789/8484
Aoun, J. E. (2017). Robot-proof: Higher education in the age of artificial intelligence. MIT Press.
Bax, S. (2018). MOOCs as a new technology: Approaches to normalising the MOOC experience for our learners. In Flipping the blend through MOOCs, MALL and OIL – new directions in CALL (pp. 9-16). Research-Publishing.net.
Boateng, S., & Kalonde, G. (2024). Exploring the synergy of the SAMR (Substitution, Augmentation, Modification, and Redefinition) model and technology integration in education: The key to unlocking student engagement and motivation. Proceedings of the International Conference on Advanced Research in Education, Teaching, and Learning, 1(1), 37- 46. https://doi.org/10.33422/aretl.v1i1.185
Caines, A., Benedetto, L., Taslimipoor, S., Davis, C., Gao, Y., Andersen, Ø., Yanakoudakis, H., Nicholls, D. (2023). On the application of large language models for language teaching and assessment technology. arXiv Preprint. https://doi.org/10.48550/arXiv.2307.08393
Chen, Z., Wang, L., & Huang, W. (2025). Generative AI technology and language learning: A sequential mixed- method study of emotional self-reflection in ChatGPT-assisted language practice. Interactive Learning Environments. https://doi.org/10.1080/10494820.2025.2511248
Dabis, A., & Csáki, C. (2024). AI and ethics: Investigating the first policy responses of higher education institutions to the challenge of generative AI. Humanities and Social Sciences Communications, 11(1), Article 1006. https://doi.org/10.1057/s41599-024-03526-z
Floridi, L. (2024). The ethics of Artificial Intelligence: Exacerbated problems, renewed problems, unprecedented problems. American Philosophical Quarterly. http://dx.doi.org/10.2139/ssrn.4801799
Gallacher, A., Thompson, A., & Howarth, M. (2018). - My Robot is an Idiot! - Students’ perceptions of AI in the L2 classroom. Research presentation at EUROCALL International Convention. https://doi.org/10.14705/rpnet.2018.26.815
Grib, M., Kirste, L., & Holtbrügge, D. (2024). The Use of AI in teaching international business: Making online lecturing more inclusive and interactive. AIB Insights, 25(1). https://doi.org/10.46697/001c.127712
Hamilton, E. R., Rosenberg, J. M., & Akcaoglu, M. (2016). The substitution augmentation modification redefinition (SAMR) model: A critical review and suggestions for its use. TechTrends, 60, 433–441. https://doi.org/10.1007/s11528-016-0091-y
Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning - Are they really useful? A systematic review of chatbot-supported language learning. Journal of Computer Assisted Learning, 38(1), 237-257. https://doi.org/10.1111/jcal.12610
Koehler, M.J., Mishra, P., Kereluik, K., Shin, T.S., Graham, C.R. (2014). The technological pedagogical content knowledge framework. In J. Spector, M. Merrill, J. Elen, M. Bishop (Eds.), Handbook of research on educational communications and technology. Springer. https://doi.org/10.1007/978-1-4614-3185-5_9
Koehler, M., & Mishra, P. (2009). What is technological pedagogical content knowledge (TPACK)? Contemporary Issues in Technology and Teacher Education, 9(1), 60–70.
Koehler, M.J., Mishra, P., & Cain, W. (2013). What is Technological Pedagogical Content Knowledge (TPACK)? Journal of Education, 193(3), 13-19. https://doi.org/10.1177/002205741319300303
Kohnke, L., Moorhouse, BL., & Zou, D. (2023). Using Chat GPT for language teaching and learning. RELC Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868
Kohnke, L., Zou, D., & Moorhouse, B.L. (2024). Technostress and English language teaching in the age of generative AI. Educational Technology & Society, 27(2), 306-320. https://doi.org/10.30191/ETS.202404_27(2).TP02
Leslie, D., Burr, C., Aitken, M., Cowls, J., Katell, M., & Briggs, M. (2021). Artificial intelligence, human rights, democracy, and the rule of law: A primer. Council of Europe.
Mollick, E. R., & Mollick, L. (April 22, 2024). Instructors as innovators: A future-focused approach to new AI learning opportunities. The Wharton School Research Paper. http://dx.doi.org/10.2139/ssrn.4802463
Pack, A., & Maloney, J. (2023). Potential affordances of generative AI in language education: Demonstrations and an evaluative framework. Teaching English with Technology, 23(2), 4–24. https://doi.org/10.1177/10.56297/buka4060/vrro1747
Pratschke, M. (2024). Generative AI and education. Digital pedagogies, teaching innovation and learning design. Springer.
Sharples, M. (2023). Towards social generative AI for education: Theory, practices and ethics. arXiv Preprint. https://doi.org/10.48550/arXiv.2306.10063
Skrabut, S. (2023). 80 Ways to use ChatGPT in the classroom. Stanley A. Skrabut. Son, J.-B., Ruzic, N., & Philpott, A. (2023). Artificial intelligence technologies and applications for language learning and teaching. Journal of China Computer-Assisted Language Learning. https://doi.org/10.1515/jccall-2023-0015
Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1), 1-10. https://doi.org/10.37074/jalt.2023.6.1.17
Wan, Y., & Moorhouse, B. L. (2024). Using Call Annie as a generative artificial intelligence speaking partner for language learners. RELC Journal. https://doi.org/10.1177/00336882231224813
Weng, Z., & Fu, Y. (2025). Generative AI in language education: Bridging divide and fostering inclusivity. International Journal of Technology in Education, 8(2), 395-420. https://doi.org/10.46328/ijte.1056
Yan, L., Sha, L., Zhao, L., Li, Y., MartinezMaldonado, R., Chen, G., Gašević, D. (2023). Practical and ethical challenges of large language models in education: A systematic scoping review. arXiv Preprint. https://doi.org/10.48550/arXiv.2303.13379
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