Aplicaciones de la inteligencia artificial en la enseñanza y aprendizaje de la traducción español-árabe

Bachir Mahyub Rayaa

doi:10.31637/epsir-2025-1368

Authors

Bachir Mahyub Rayaa University of Granada https://orcid.org/0000-0001-5400-5374

DOI:

https://doi.org/10.31637/epsir-2025-1368

Keywords:

machine translation, neural translation, Spanish-Arabic, documentation, terminology, teaching-learning, artificial intelligence, computer-assisted translation tools

Abstract

Introduction: Artificial intelligence (AI) has experienced an unprecedented boom in recent years, driving advances in various fields, including Spanish-Arabic translation and interpreting (T&I). Methodology: A chronological review of the development of AI and its influence on professional practice and translators’ training in recent decades is offered, with special emphasis on the emergence of neural translation. In addition, an observational-descriptive approach is used to analyze the applications proposed within the framework of the subject Spanish-Arabic Translation, the reception of the AI-assisted translation exercises and the feedback from the participating students. Results: Valuable information is collected from two main sources: teacher observation and students’ feedback. Discussion: The information gathered is discussed, with pros and cons of AI applied to translation, in line with the objectives that were intended to be achieved in the Spanish-Arabic translation classroom. Conclusions: It is concluded that AI, applied in a critical and controlled way, brings benefits for translator training and allows for faster progress, saving time invested and facilitating skill acquisition. However, the study also leads to other conclusions that advise against its uncontrolled use.

Downloads

Download data is not yet available.

Author Biography

Bachir Mahyub Rayaa, University of Granada

Bachir Mahyub Rayaa holds a PhD in Didactics of Simultaneous Arabic-Spanish Interpreting from the University of Granada (2013). Since 2013, he has been a full-time lecturer in the Bachelor's Degree in Translation and Interpreting and in the Master's Degree in Conference Interpreting (UGR). Between 2007 and 2013, he was a lecturer and researcher at the Toledo School of Translators (Univ. of Castilla-La Mancha), where he was professor and coordinator of the Arabic program and professor of the postgraduate course “Specialist Course in Arabic-Spanish Translation”. He has also been a collaborating professor in the Master's Degree in Intercultural Communication, Interpretation and Translation in Public Services (Univ. of Alcalá de Henares), Arabic-Spanish linguistic combination. He has published 45 academic papers.

References

Bishop, C. M. (2006). Pattern recognition and machine learning. Springer.

Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.

Chan, S. W. (2018). The human factor in machine translation. Routledge.

Duque García, M. M., González, M. T. y Catrain, M. (1993). Transposición y modulación en la traducción técnica. En M. Raders y J. Sevilla Muñoz (Eds.), III Encuentros Complutenses en torno (pp. 137-149). Universidad Complutense de Madrid.

Ehrensberger-Dow, M. y Massey, G. (2017). Socio-technical issues in professional translation practice. Translation Spaces, 6(1), 104-121. https://doi.org/10.1075/ts.6.1.06ehr DOI: https://doi.org/10.1075/ts.6.1.06ehr

Goodfellow, I., Bengio, Y. y Courville, A. (2016). Deep learning. MIT Press.

Jiménez-Crespo, M. A. (2023). Augmentation and translation crowdsourcing: are collaborative translators minds really ‘augmented’? Translation, Cognition and Behavior, (online), 21-35. https://doi.org/10.1075/tcb.00079.jim DOI: https://doi.org/10.1075/tcb.00079.jim

Jiménez-Crespo, M. A. (2024). Professional Translators’ Attitudes Towards Control and Autonomy in the Human-Centered AI Era: Presenting a Survey Study. En C. Orasan, T. Ranasinghe, G. Corpas Pastor, R. Mitkov y M. Kunilovskaya (coord.), Proceedings of the New Trends in Translation and Technology Conference - NeTTT 2024 (pp. 91-98). NeTTT. https://bit.ly/4bIIYOU DOI: https://doi.org/10.26615/issn.2815-4711.2024_008

Kenny, D. (2020). Human Issues in Translation Technology. Routledge. DOI: https://doi.org/10.4324/9781315678627-65

Koehn, P. (2020). Neural Machine Translation. Cambridge University Press. DOI: https://doi.org/10.1017/9781108608480

Massey, G., Huertas-Barros, E. y Katan, D. (Eds.) (2023). The Human Translator in the 2020s. Routledge. DOI: https://doi.org/10.4324/9781003223344

Müller, V. C. (2020). Ethics of artificial intelligence and robotics. En E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy. Stanford University. https://stanford.io/4cGXp7o

Murphy, K. P. (2012). Machine learning: A probabilistic perspective. MIT Press.

O’Brien, S. (2023). Human-Centered augmented translation: against antagonistic dualisms. Perspectives, 32(3), 391-406. https://doi.org/10.1080/0907676X.2023.224742321 DOI: https://doi.org/10.1080/0907676X.2023.2247423

Russell, S. y Norvig, P. (2020). Artificial intelligence: A modern approach (4ª ed.). Pearson.

Schnell, M. (13 de octubre de 2023). Goodbye translators. And hello Language Specialists. RWS Blog. https://www.rws.com/blog/goodbye-translator-hello-language-specialist/

Shneiderman, B. (2020). Human-centered artificial intelligence: Three fresh ideas. AIS Transactions on Human-Computer Interaction, 12(3), 109-124. https://doi.org/10.17705/1thci.00131 DOI: https://doi.org/10.17705/1thci.00131

Shneiderman, B. (2022). Human-centered AI. Oxford University Press. DOI: https://doi.org/10.1093/oso/9780192845290.001.0001

Universidad de Granada. (2023). Guía docente de Traducción A-B Árabe. https://www.ugr.es/estudiantes/grados/grado-traduccion-interpretacion/traduccion-b-arabe-0/guia-docente