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Artificial intelligence in aviation English testing

Year 2024, Volume: 10 Issue: 3, 362 - 384, 31.12.2024
https://doi.org/10.47216/literacytrek.1556603

Abstract

Abstract
In the field of aviation, English language proficiency is essential for ensuring clear communication and safe flight operations. Effective assessment of pilots’ and air traffic controllers’ aviation English (AE) proficiency is, therefore, crucial. Conventional AE proficiency assessments, while effective, face limitations in scalability, objectivity, and feedback mechanisms. This article reviews the advancements and effectiveness of AI-driven assessment tools for AE proficiency testing, highlighting their potential to overcome these limitations. The review encompasses AI technologies such as automated speech recognition (ASR), natural language processing (NLP), and intelligent tutoring systems (ITS) in the light of the language proficiency requirements stated by the International Civil Aviation Organization (ICAO). Overall, the present review concludes that AI-driven tools provide accurate, reliable, and immediate feedback, significantly improving learners' AE proficiency. Despite challenges such as speech recognition errors and ethical concerns, these tools offer scalable and accessible solutions for large aviation training programs. The review concludes with recommendations for future research, emphasizing the need for continued innovation to address technological limitations and enhance adaptive learning environments. This review offers valuable insights for English for Specific Purposes (ESP) practitioners and stakeholders in the aviation industry.

Ethical Statement

Ethical approval was not sought for the present study because it did not involve human subjects.

Supporting Institution

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Project Number

2024 SPECIAL ISSUE | Exploring Innovative Pedagogies for Enhanced Learning Outcomes in Language Teaching

Thanks

I would like to thank the journal editor(s) and the special editors Prof. Yasemin Kırkgöz and Dr. Zoe Marlowe for reviewing my submission.

References

  • Assassi , T., & Ghodbane, T. (2023). The recurring issue of aviation English test validity: Echoes from Test-takers and Assessors of the English for Aviation Language Testing System in Algeria. English Studies at NBU, 9(2), 239–269. https://doi.org/10.33919/esnbu.23.2.6
  • Chen, X., Zhang, Z., & Zhang, Y. (2020). AI in language testing: Current applications and future directions. Language Testing, 37(4), 524-540.
  • Demirdöken, G., & Atay, D. (2024). Enhancing aviation English competency: A simulation-based approach for aspiring pilots. English for Specific Purposes, 76, 106-121. https://doi.org/10.1016/j.esp.2024.08.001
  • Dinçer, N., & Demirdöken, G. (2023). Ab-initio pilots’ perspectives on the use of simulation in the aviation English course. The Journal of Teaching English for Specific and Academic Purposes, 11(1), 11-22. https://doi.org/10.22190/JTESAP230130003D
  • Dobson, A. (2017). A history of international civil aviation: from its origins through transformative evolution. Routledge
  • Farris, C. (2016). The role of English in international aviation: Historical perspectives and current issues. Journal of Aviation English, 5(1), 1-15.
  • González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021). Artificial intelligence for student assessment: A systematic review. Applied Sciences, 11(12), 5467. https://doi.org/10.3390/app11125467
  • Hakimi, L., Eynon, R., & Murphy, V. A. (2021). The ethics of using digital trace data in education: A thematic review of the research landscape. Review of Educational Research, 91(5), 671–717. https://doi.org/10.3102/00346543211020116
  • ICAO. (2007). Manual of Radiotelephony (4th Ed.). International Civil Aviation Organization. Canada. International Civil Aviation Organization (ICAO). (2008). Manual on the implementation of ICAO language proficiency requirements. ICAO.
  • Ishihara, N., & Prado, M. C. D. A. (2021). The negotiation of meaning in aviation English as a lingua franca: a corpus-informed discursive approach. The Modern Language Journal, 105(3), 639–654. https://doi.org/10.1111/modl.12718
  • Kim, H., & Elder, C. (2009). Understanding aviation English testing: How do international and professional constraints affect test design? Language Testing, 26(3), 285-308.
  • Luckin, R. (2017). Towards artificial intelligence-based assessment systems. Nature Human Behaviour, 1(3), 0028. https://doi.org/10.1038/s41562-016-0028
  • Lynch, T., & Maclean, J. (2003). Effects of feedback on performance: A study of advanced learners on an ESP speaking course. Edinburgh Working Papers in Applied Linguistics, 12, 19-44.
  • Nhac, H. T. (2021). Effect of teachers’ corrective feedback on learners’ oral accuracy in English speaking lessons. International Journal of Learning, Teaching, and Educational Research, 20(10), 313-330. https://doi.org/10.26803/ijlter.20.10.17
  • Tuomi, I. (2022). Artificial intelligence, 21st century competences, and socio-emotional learning in education: More than high-risk? European Journal of Education, 57(4), 601-619. https://doi.org/10.1111/ejed.12531
  • Wang, L., & Lee, H. (2020). Automated speech recognition in aviation English: Challenges and opportunities. Aviation English Journal, 8(2), 43-58.
  • Yoon, H., Lee, S., & Kim, J. (2021). Evaluating the effectiveness of AI-based language assessment tools in aviation English. Journal of Artificial Intelligence in Education, 31(2), 233-250.
  • Zhai, X., Chu, X., Chai, C.-S., Jong, M. S. Y., Siu, Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021). A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity, 2021, 1-18. https://doi.org/10.1155/2021/8812542
  • Zhang, X., Xie, Y., & Wang, W. (2019). Intelligent tutoring systems for language learning: An overview. Educational Technology & Society, 22(3), 38-49.
Year 2024, Volume: 10 Issue: 3, 362 - 384, 31.12.2024
https://doi.org/10.47216/literacytrek.1556603

Abstract

Project Number

2024 SPECIAL ISSUE | Exploring Innovative Pedagogies for Enhanced Learning Outcomes in Language Teaching

References

  • Assassi , T., & Ghodbane, T. (2023). The recurring issue of aviation English test validity: Echoes from Test-takers and Assessors of the English for Aviation Language Testing System in Algeria. English Studies at NBU, 9(2), 239–269. https://doi.org/10.33919/esnbu.23.2.6
  • Chen, X., Zhang, Z., & Zhang, Y. (2020). AI in language testing: Current applications and future directions. Language Testing, 37(4), 524-540.
  • Demirdöken, G., & Atay, D. (2024). Enhancing aviation English competency: A simulation-based approach for aspiring pilots. English for Specific Purposes, 76, 106-121. https://doi.org/10.1016/j.esp.2024.08.001
  • Dinçer, N., & Demirdöken, G. (2023). Ab-initio pilots’ perspectives on the use of simulation in the aviation English course. The Journal of Teaching English for Specific and Academic Purposes, 11(1), 11-22. https://doi.org/10.22190/JTESAP230130003D
  • Dobson, A. (2017). A history of international civil aviation: from its origins through transformative evolution. Routledge
  • Farris, C. (2016). The role of English in international aviation: Historical perspectives and current issues. Journal of Aviation English, 5(1), 1-15.
  • González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021). Artificial intelligence for student assessment: A systematic review. Applied Sciences, 11(12), 5467. https://doi.org/10.3390/app11125467
  • Hakimi, L., Eynon, R., & Murphy, V. A. (2021). The ethics of using digital trace data in education: A thematic review of the research landscape. Review of Educational Research, 91(5), 671–717. https://doi.org/10.3102/00346543211020116
  • ICAO. (2007). Manual of Radiotelephony (4th Ed.). International Civil Aviation Organization. Canada. International Civil Aviation Organization (ICAO). (2008). Manual on the implementation of ICAO language proficiency requirements. ICAO.
  • Ishihara, N., & Prado, M. C. D. A. (2021). The negotiation of meaning in aviation English as a lingua franca: a corpus-informed discursive approach. The Modern Language Journal, 105(3), 639–654. https://doi.org/10.1111/modl.12718
  • Kim, H., & Elder, C. (2009). Understanding aviation English testing: How do international and professional constraints affect test design? Language Testing, 26(3), 285-308.
  • Luckin, R. (2017). Towards artificial intelligence-based assessment systems. Nature Human Behaviour, 1(3), 0028. https://doi.org/10.1038/s41562-016-0028
  • Lynch, T., & Maclean, J. (2003). Effects of feedback on performance: A study of advanced learners on an ESP speaking course. Edinburgh Working Papers in Applied Linguistics, 12, 19-44.
  • Nhac, H. T. (2021). Effect of teachers’ corrective feedback on learners’ oral accuracy in English speaking lessons. International Journal of Learning, Teaching, and Educational Research, 20(10), 313-330. https://doi.org/10.26803/ijlter.20.10.17
  • Tuomi, I. (2022). Artificial intelligence, 21st century competences, and socio-emotional learning in education: More than high-risk? European Journal of Education, 57(4), 601-619. https://doi.org/10.1111/ejed.12531
  • Wang, L., & Lee, H. (2020). Automated speech recognition in aviation English: Challenges and opportunities. Aviation English Journal, 8(2), 43-58.
  • Yoon, H., Lee, S., & Kim, J. (2021). Evaluating the effectiveness of AI-based language assessment tools in aviation English. Journal of Artificial Intelligence in Education, 31(2), 233-250.
  • Zhai, X., Chu, X., Chai, C.-S., Jong, M. S. Y., Siu, Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021). A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity, 2021, 1-18. https://doi.org/10.1155/2021/8812542
  • Zhang, X., Xie, Y., & Wang, W. (2019). Intelligent tutoring systems for language learning: An overview. Educational Technology & Society, 22(3), 38-49.
There are 19 citations in total.

Details

Primary Language English
Subjects Language Studies (Other)
Journal Section Review articles
Authors

Gökhan Demirdöken 0000-0002-9442-0625

Project Number 2024 SPECIAL ISSUE | Exploring Innovative Pedagogies for Enhanced Learning Outcomes in Language Teaching
Publication Date December 31, 2024
Submission Date September 26, 2024
Acceptance Date December 25, 2024
Published in Issue Year 2024 Volume: 10 Issue: 3

Cite

APA Demirdöken, G. (2024). Artificial intelligence in aviation English testing. The Literacy Trek, 10(3), 362-384. https://doi.org/10.47216/literacytrek.1556603

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