Exploring the relationship between critical thinking, attitude, and anxiety in shaping the adoption of artificial intelligence in translation among Saudi translators
Hassan Saleh Mahdi 1 * , Yousef Mohammed Sahari 2
More Detail
1 Arab Open University, Kingdom of Saudi Arabia
2 Department of English Language, The University of Bisha, Bisha, Kingdom of Saudi Arabia
* Corresponding Author


Critical thinking and anxiety influenced the translation competence of translators. This study sought to examine the interactions between critical thinking, attitude, and anxiety influenced the translation competence of translators. This study adopted an empirical approach to collect data from 145 student translators from many colleges in Saudi Arabia. The questionnaire was used as a data collection tool. Data were analyzed by using structural equation modelling to find out the relationship between the study factors. The results indicated that there was a negative relationship between AI anxiety with critical thinking and attitude. However, there was a strong positive relationship between attitude with critical thinking, and Machine Translation anxiety. Also, there was a positive relationship between Machine Translation anxiety with AI anxiety and critical thinking.



  • Azin, N., & Tabrizi, H. H. (2016). The relationship between critical thinking ability of Iranian English translation students and their translation ability. Theory and Practice in Language Studies, 6(3), 541-548. https://doi.org/10.17507/tpls.0603.12
  • Banat, M., & Adla, Y. A. (2023). Exploring the effectiveness of Gpt-3 in translating specialized religious text from Arabic to English: a comparative study with human translation. Journal of Translation and Language Studies, 4(2), 1-23. https://doi.org/10.48185/jtls.v4i2.762
  • Benmansour, M., & Hdouch, Y. (2023). The role of the latest technologies in the translation industry. Emirati Journal of Education and Literature, 1(2), 31-36.
  • Boloori, L., & Naghipoor, M. (2013). The relationship between critical thinking and performance of Iranian EFL learners on translation tests. The International Research Journal, 2, 155-165.
  • Carvalho, I., Ramires, A. & Iglesias, M. Attitudes towards machine translation and languages among travelers. Information Technologies in Tourism, 25, 175–204. https://doi.org/10.1007/s40558-023-00253-0
  • Cheng, S. (2022). Exploring the role of translators’ emotion regulation and critical thinking ability in translation performance. Frontiers in Psychology, 13, 1037829. https://doi.org/10.3389/fpsyg.2022.1037829
  • Chopra, S., & White, L. (2007). Privacy and artificial agents, or, is google reading my email?. In M. M. Veloso (Ed.), Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (pp. 1245-1250). IJCAI.
  • Galán-Mañas, A. (2016). Learning portfolio in translator training: the tool of choice for competence development and assessment. The Interpreter and Translator Trainer, 10(2), 161-182. https://doi.org/10.1080/1750399X.2015.1103108
  • Ghaemi, H., & Sadoughvanini, S. (2020). The relationship between translation competence and higher-order thinking skills of novice translators. Athens Journal of Philology, 7(4), 273-288. https://doi.org/10.30958/ajp.7-4-3
  • Göpferich, S. (2013). Translation competence: Explaining development and stagnation from a dynamic systems perspective. Target. International Journal of Translation Studies, 25(1), 61-76. https://doi.org/10.1075/target.25.1.06goe
  • Gutierrez, R. (2024). Unifying linguistic landscapes: The potential of AI and nanotechnology in facilitating real-time translation. In W. Jaber (Ed.), Artificial Intelligence in the Age of Nanotechnology (pp. 76-97). IGI Global. https://doi.org/10.4018/979-8-3693-0368-9.ch005
  • Halverson, S. L. & Martin, R. M. (2020). The times, they are a-changin’. Multilingual mediated communication and cognition. In R. M. Martin & S. L. Halverson (Eds.), Multilingual Mediated Communication and Cognition (pp. 1-17). Routledge. https://doi.org/10.4324/9780429323867-1
  • Hendy, A., Abdelrehim, M., Sharaf, A., Raunak, V., Gabr, M., Matsushita, H., Kim, Y. J., Afify, M. & Awadalla, H. H. (2023). How good are GPT models at machine translation? a comprehensive evaluation. Arxiv. https://doi.org/10.48550/arXiv.2302.09210
  • Jahromi, P. P., & Suzani, S. M. (2016). A study of relationship between translation studies students' critical thinking ability and the quality of literary prose text translation. Theory and Practice in Language Studies, 6(9), 1855. https://doi.org/10.17507/tpls.0609.19
  • Jiao, W., Wang, W., Huang, J. T., Wang, X., & Tu, Z. (2023). Is ChatGPT a good translator? A preliminary study. Arxiv. https://doi.org/10.48550/arXiv.2301.08745
  • Johnson, D. G., & Verdicchio, M. (2017). AI anxiety. Journal of the Association for Information Science and Technology, 68(9), 2267-2270.
  • Khoshafah, F. (2023). ChatGPT for Arabic-English translation: Evaluating the accuracy. Research Square. Advance Online Publication. https://doi.org/10.21203/rs.3.rs-2814154/v1
  • Kirov, V., & Malamin, B. (2022). Are translators afraid of artificial intelligence? Societies, 12(2), 70. https://doi.org/10.3390/soc12020070
  • Koka, N. A. (2024). The integration and utilization of artificial intelligence (AI) in supporting older/senior lecturers to adapt to the changing landscape in translation pedagogy. Migration Letters, 21(S1), 59-71. https://doi.org/10.59670/ml.v21iS1.5939
  • Kornacki, M. (2018). Computer-assisted translation (CAT) tools in the translator training process. Peter Lang. https://doi.org/10.3726/b14783
  • Kussmaul, P. (1995). Training the translator. John Benjamins. https://doi.org/10.1075/btl.10
  • Lee, T. K. (2023). Artificial intelligence and post-humanist translation: ChatGPT versus the translator. Applied Linguistics Review. Advance Online Publication. https://doi.org/10.1515/applirev-2023-0122
  • Li, X., Gao, Z., & Liao, H. (2023). The effect of critical thinking on translation technology competence among college students: the chain mediating role of academic self-efficacy and cultural intelligence. Psychology Research and Behavior Management, 16, 1233-1256. https://doi.org/10.2147/PRBM.S408477
  • Liu, H. (2019, October). Teaching models of translation courses aiming at fostering critical thinking skills. In C. Ma (Ed.), 2019 International Conference on Advanced Education, Service and Management (Vol. 3, pp. 404-407). The Academy of Engineering and Education.
  • Lv, S., Chen, C., Zheng, W., & Zhu, Y. (2022). The relationship between study engagement and critical thinking among higher vocational college students in China: a longitudinal study. Psychology Research and Behavior Management, 15, 2989-3002. https://doi.org/10.2147/PRBM.S386780
  • Mohseni, A., & Satariyan, A. (2011). The relation between critical thinking and translation quality. Journal of Language and Translation, 2(2), 23-32.
  • Mokyr, J., Vickers, C., & Ziebarth, N. L. (2015). The history of technological anxiety and the future of economic growth: Is this time different? Journal of Economic Perspectives, 29(3), 31-50. https://doi.org/10.1257/jep.29.3.31
  • Neubert, A. (1997). Postulate for a theory of translation. In J. Danks et al. (Eds), Cognitive process in translation and interpreting (pp. 250–268). Sage.
  • Parham, F., & Fahim, M. (2013). The relationship between critical thinking and translation quality. Translation Studies, 11, 10–22.
  • Pintrich, R. R., & DeGroot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82, 33−40. https://doi.org/10.1037/0022-0663.82.1.33
  • Rico, C., & González Pastor, D. (2022). The role of machine translation in translation education: a thematic analysis of translator educators' beliefs. Translation & Interpreting, 14(1), 177-197. https://doi.org/10.12807/ti.114201.2022.a010
  • Saud, W. I. (2020). The relationship between critical thinking and translation ability of EFL undergraduate students. International Journal of Social Sciences & Educational Studies, 7(3), 19-28. https://doi.org/10.23918/ijsses.v7i3p19
  • Scherer, M. U. (2015). Regulating artificial intelligence systems: Risks, challenges, competencies, and strategies. Harvard Journal of Law & Technology, 29(2), 354-400. https://doi.org/10.2139/ssrn.2609777
  • Soori, M., Arezoo, B., & Dastres, R. (2023). Artificial intelligence, machine learning and deep learning in advanced robotics, A review. Cognitive Robotics, 3, 54-70. https://doi.org/10.1016/j.cogr.2023.04.001
  • Sosu, E. M. (2013). The development and psychometric validation of a Critical Thinking Disposition Scale. Thinking Skills and Creativity, 9, 107-119. https://doi.org/10.1016/j.tsc.2012.09.002
  • Waltz, D. L. (2006). Evolution, sociobiology, and the future of artificial intelligence. IEEE Intelligent Systems, 21(3), 66-69. https://doi.org/10.1109/MIS.2006.46
  • Wang, Y. Y., & Wang, Y. S. (2022). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interactive Learning Environments, 30(4), 619-634. https://doi.org/10.1080/10494820.2019.1674887
  • Yang, Y., & Wang, X. (2023). Predicting student translators’ performance in machine translation post-editing: interplay of self-regulation, critical thinking, and motivation. Interactive Learning Environments, 31(1), 340-354. https://doi.org/10.1080/10494820.2020.1786407


This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.