Exploring the Impact of AI on The EFL Context: A Case Study of Saudi Universities

Abdalilah. G. I. Alhalangy (1), Mohammed AbdAlgane (2)
(1) Assistant Professor of Information Systems Department of Computer Science, College of Science and Arts, Ar Rass, Qassim University, Saudi Arabia, Saudi Arabia,
(2) Department of English & Translation, College of Science and Arts, Ar Rass, Qassim University, Saudi Arabia

Abstract

This research aims to determine whether or not it is possible to use artificial intelligence (AI) in English for speakers of other languages (ESOL) courses and review previous research pertinent to artificial intelligence in EFL/ESL instruction to present a comprehensive picture of the current degree of artificial intelligence in EFL/ESL instruction. Utilization of intelligent teaching systems, self-regulated learning, virtual reality, immersive virtual environment, and natural language processing in teaching English as a foreign language classroom. The study adopted the questionnaire as a tool for data collection then data was analyzed and discussed to reach the results. The results showed that the ethical responsibility for making the most effective use of AI in the classroom now falls on both educators and students themselves. The article also concludes that artificial intelligence (AI) positively impacts the field of English language teaching (ELT) and learning; however, it needs to be better integrated into educational settings. Teachers and students need to be more aware of the new applications and tools that have flooded the field of AI in recent years. This conclusion was reached in the context of the article.

Full text article

Generated from XML file

References

Abu Ghali, M. J., Abu Ayyad, A., Abu-Naser, S. S., & Abu Laban, M. (2018). An intelligent tutoring system for teaching English grammar. International Journal of Academic Engineering Research, 2(2), 1 - 6.

Adolphs, S., Clark, L., Dörnyei, Z., Glover, T., Henry, A., Muir, C., & Valstar, M. (2018). Digital innovations in L2 motivation: Harnessing the power of the Ideal L2 Self. The system, 78, 173-185. https://doi.org/10.1016/j.system.2018.07.014

Amarasinghe, I., Michos, K., Crespi, F., & Hernández‐Leo, D. (2022). Learning analytics support to teachers' design and orchestrating tasks. Journal of Computer Assisted Learning, 1 - 16. https://doi.org/10.1111/jcal.12711

Baghban, H., Rezapour, A., Hsu, C. H., Nuannimnoi, S., & Huang, C. Y. (2022). Edge-AI: IoT Request Service Provisioning in Federated Edge Computing Using Actor-Critic Reinforcement Learning. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2022.3166769

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., & Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901.

Cárdenas, R., Arroba, P., & Risco Martin, J. L. (2021). Bringing AI to the edge: A formal M&S specification to deploy effective IoT architectures. Journal of Simulation, 1-18. https://doi.org/10.1080/17477778.2020.1863755

Castells, N., Minguela, M., Solé, I., Miras, M., Nadal, E., & Rijlaarsdam, G. (2022). Improving Questioning-Answering Strategies in Learning from Multiple Complementary Texts: An Intervention Study. Reading Research Quarterly, 57(3), 879-912. https://doi.org/10.1002/rrq.451

Chen, Y., Smith, T. J., York, C. S., & Mayall, H. J. (2020). Google Earth Virtual Reality and expository writing for young English Learners from a Funds of Knowledge perspective. Computer Assisted Language Learning, 33(1-2), 1-25. https://doi.org/10.1080/09588221.2018.1544151

Chien, S. Y., Hwang, G. J., & Jong, M. S. Y. (2020). Effects of peer assessment within the context of spherical video-based virtual reality on EFL students' English-Speaking performance and learning perceptions. Computers & Education, 146, 103751. https://doi.org/10.1016/j.compedu.2019.103751

Couto, S. M. (2016). Foreign Language Anxiety Levels in Second Life oral interaction. ReCALL Journal, 27(3).

Cowie, N., & Alizadeh, M. (2022). The affordances and challenges of virtual reality for language teaching. International Journal of TESOL Studies, 4(3), 50-56.

Deriu, J., Rodrigo, A., Otegi, A., Echegoyen, G., Rosset, S., Agirre, E., & Cieliebak, M. (2021). Survey on evaluation methods for dialogue systems. Artificial Intelligence Review, 54(1), 755-810. https://doi.org/10.1007/s10462-020-09866-x

Dowling, M. (2022). Is non-fungible token pricing driven by cryptocurrencies?. Finance Research Letters, 44, 102097. https://doi.org/10.1016/j.frl.2021.102097

Ebadi, S., & Ebadijalal, M. (2020). The effect of Google Expeditions virtual reality on EFL learners' willingness to communicate and oral proficiency. Computer Assisted Language Learning, 1-25. https://doi.org/10.1080/09588221.2020.1854311

Fernández-Río, J. (2016). Student-teacher-content-context: Indissoluble ingredients in the teaching-learning process. Journal of Physical Education, Recreation & Dance, 87(1), 3-5. https://doi.org/10.1080/07303084.2016.1110476

Gill, S. S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., ... & Uhlig, S. (2022). AI for next-generation computing: Emerging trends and future directions. Internet of Things, 19, 100514. https://doi.org/10.1016/j.iot.2022.100514

Gladence, L. M., Anu, V. M., Rathna, R., & Brumancia, E. (2020). Recommender system for home automation using IoT and artificial intelligence. Journal of Ambient Intelligence and Humanized Computing, 1-9. https://doi.org/10.1007/s12652-020-01968-2

Gong, C., Lin, F., Gong, X., & Lu, Y. (2020). Intelligent cooperative edge computing in the internet of things. IEEE Internet of Things Journal, 7(10), 9372-9382. https://doi.org/10.1109/JIOT.2020.2986015

Guo, K., Wang, J., & Chu, S. K. W. (2022). Using chatbots to scaffold EFL students' argumentative writing. Assessing Writing, 54, 100666. https://doi.org/10.1016/j.asw.2022.100666

Guo, Q., Feng, R., & Hua, Y. (2021). How effectively can EFL students use automated written corrective feedback (AWCF) in research writing?. Computer Assisted Language Learning, 1-20. https://doi.org/10.1080/09588221.2021.1879161

Hamad, S., Tairab, H., Wardat, Y., Rabbani, L., AlArabi, K., Yousif, M., & Stoica, G. (2022). Understanding science teachers' implementations of integrated STEM: Teacher perceptions and practice. Sustainability, 14(6), 3594. https://doi.org/10.3390/su14063594

Haristiani, N. (2019, November). Artificial Intelligence (AI) chatbot as language learning medium: An inquiry. In Journal of Physics: Conference Series, 1387(1), 012020. IOP Publishing. https://doi.org/10.1088/1742-6596/1387/1/012020

Hong, Z. W., Huang, Y. M., Hsu, M., & Shen, W. W. (2016). Authoring robot-assisted instructional materials for improving learning performance and motivation in EFL classrooms. Journal of Educational Technology & Society, 19(1), 337-349.

Hwang, W. Y., Hoang, A., & Lin, Y. H. (2021). Smart mechanisms and their influence on geometry learning of elementary school students in authentic contexts. Journal of Computer Assisted Learning, 37(5), 1441-1454. https://doi.org/10.1111/jcal.12584

Hwang, W. Y., Nguyen, V. G., & Purba, S. W. D. (2022). A systematic survey of anything-to-text recognition and constructing its framework in language learning. Education and Information Technologies, 1-27. https://doi.org/10.1007/s10639-022-11112-6

Jiang, R. (2022). How does artificial intelligence empower EFL teaching and learning nowadays? A review on artificial intelligence in the EFL context. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1049401

Kim, N. Y. (2016). Effects of voice chat on EFL learners' speaking ability according to proficiency levels. Multimedia-Assisted Language Learning, 19(4), 63-88.

Kim, N. Y., Cha, Y., & Kim, H. S. (2019). Future English learning: Chatbots and artificial intelligence. Multimedia-Assisted Language Learning, 22(3), 32-53.

Lai, K. W. K., & Chen, H. J. H. (2021). A comparative study on the effects of a VR and PC visual novel game on vocabulary learning. Computer Assisted Language Learning, 1-34. https://doi.org/10.1080/09588221.2021.1928226

Lan, Y. J., Fang, W. C., Hsiao, I. Y., & Chen, N. S. (2018). Real body versus 3D avatar: The effects of different embodied learning types on EFL listening comprehension. Educational Technology Research and Development, 66(3), 709-731. https://doi.org/10.1007/s11423-018-9569-y

Lotze, N. (2018). Goodbye to classroom teaching. Artificial intelligence in language learning. Translation: Chris Cave. Copyright: Goethe-Institut e. V., Redaktion Magazin Sprache.

Luck, M., & Aylett, R. (2000). Applying artificial intelligence to virtual reality: Intelligent virtual environments. Applied artificial intelligence, 14(1), 3-32. https://doi.org/10.1080/088395100117142

Lu, O. H., Huang, A. Y., Tsai, D. C., & Yang, S. J. (2021). Expert-Authored and Machine-Generated Short-Answer Questions for Assessing Students' Learning Performance. Educational Technology & Society, 24(3), 159-173.

Matuk, C., & Linn, M. C. (2018). Why and how do middle school students exchange ideas during science inquiry? International Journal of Computer-Supported Collaborative Learning, 13(3), 263-299. https://doi.org/10.1007/s11412-018-9282-1

Messaoud, S., Bradai, A., Bukhari, S. H. R., Quang, P. T. A., Ahmed, O. B., & Atri, M. (2020). A survey on machine learning in the internet of things: algorithms, strategies, and applications. Internet of Things, 12, 100314. https://doi.org/10.1016/j.iot.2020.100314

Mohamed, H., and Lamia, M. (2018). Implementing flipped classroom that used an intelligent tutoring system into the learning process. Computers & Education, 124, 62-76. https://doi.org/10.1016/j.compedu.2018.05.011

Mohammadzadeh, A., and Sarkhosh, M. (2018). The Effects of Self- regulatory Learning Through Computer-assisted Intelligent Tutoring System on the Improvement of EFL Learners' Speaking Ability. International Journal of Instruction, 11(2), 167-184. https://doi.org/10.12973/iji.2018.11212a

Nagro, S. A. (2021). The Role of Artificial Intelligence Techniques in Improving the Behavior and Practices of Faculty Members When Switching to E-Learning in Light of the Covid-19 Crisis. International Journal of Education and Practice, 9(4), 687-714. https://doi.org/10.18488/journal.61.2021.94.687.714

Nguyen, T. H., Hwang, W. Y., Pham, X. L., & Pham, T. (2020). Self-experienced storytelling in an authentic context to facilitate EFL writing. Computer Assisted Language Learning, 1-30. https://doi.org/10.1080/09588221.2020.1744665

Nobrega, F. A., & Rozenfeld, C. C. D. F. (2019). Virtual reality in the teaching of FLE in a Brazilian public school. Languages, 4(2), 36. https://doi.org/10.3390/languages4020036

Obari, H. (2020). The integration of AI and virtual learning in teaching EFL under COVID-19. In ICERI2020 Proceedings, 7866-7872. IATED. https://doi.org/10.21125/iceri.2020.1740

Radanliev, P., & De Roure, D. (2022). New and emerging forms of data and technologies: Literature and bibliometric review. Multimedia Tools and Applications, 1-25. https://doi.org/10.1007/s11042-022-13451-5

Radanliev, P., & De Roure, D. (2022). Advancing the cybersecurity of the healthcare system with self-optimizing and self-adaptative artificial intelligence (part 2). Health and Technology, 12(5), 923-929. https://doi.org/10.1007/s12553-022-00691-6

Rao, A. R., & Clarke, D. (2020). Perspectives on emerging directions in using IoT devices in blockchain applications. Internet of Things, 10, 100079. https://doi.org/10.1016/j.iot.2019.100079

Rau, P. L. P., Zheng, J., Guo, Z., & Li, J. (2018). Speed reading on virtual reality and augmented reality. Computers & Education, 125, 240-245. https://doi.org/10.1016/j.compedu.2018.06.016

Repetto, C. (2014). The use of virtual reality for language investigation and learning. Frontiers in Psychology, 5, 1280. https://doi.org/10.3389/fpsyg.2014.01280

Silvestru, C. I., Firulescu, A. C., Iordoc, D. G., Icociu, V. C., Stoica, M. A., Platon, O. E., & Orzan, A. O. (2022). Smart Academic and Professional Education. Sustainability, 14(11), 6408. https://doi.org/10.3390/su14116408

Sohag, M. U., & Podder, A. K. (2020). Smart garbage management system for a sustainable urban life: An IoT-based application. Internet of Things, 11, 100255. https://doi.org/10.1016/j.iot.2020.100255

Sun, Z., Yu, H., Song, X., Liu, R., Yang, Y., & Zhou, D. (2020). Mobilebert: a compact task-agnostic bert for resource-limited devices. arXiv preprint arXiv:2004.02984. https://doi.org/10.18653/v1/2020.acl-main.195

Tai, T. Y., Chen, H. H. J., & Todd, G. (2020). The impact of a virtual reality app on adolescent EFL learners' vocabulary learning. Computer Assisted Language Learning, 1-26. https://doi.org/10.1080/09588221.2020.1752735

Tulba, M. F. (2000). Computer and artificial intelligence, Modern Egyptian Office Press, Cairo.

Wang, C. P., Lan, Y. J., Tseng, W. T., Lin, Y. T. R., & Gupta, K. C. L. (2020). On the effects of 3D virtual worlds in language learning-a meta-analysis. Computer Assisted Language Learning, 33(8), 891-915. https://doi.org/10.1080/09588221.2019.1598444

Wang, Y. F., & Petrina, S. (2013). Using learning analytics to understand the design of an intelligent language tutor-Chatbot lucy. Editorial Preface, 4(11), 124-131. https://doi.org/10.14569/IJACSA.2013.041117

Xie, Y., Chen, Y., & Ryder, L. H. (2021). Effects of using mobile-based virtual reality on Chinese L2 students' oral proficiency. Computer Assisted Language Learning, 34(3), 225-245.https://doi.org/10.1080/09588221.2019.1604551

Xu, Z. Kausalai (Kay) Wijekumar, Gilbert Ramirez, Xueyan Hu, und Robin Irey. 2019.The Effectiveness of Intelligent Tutoring Systems on K-12 Students' Reading Comprehension: A Meta-Analysis. British Journal of Educational Technology, 50(6), 3119-37. https://doi.org/10.1111/bjet.12758

Yin, W. (2022). An artificial intelligent virtual reality interactive model for distance education. Journal of Mathematics, Vol. 2022. pages 1-7. https://doi.org/10.1155/2022/7099963

York, J., Shibata, K., Tokutake, H., & Nakayama, H. (2021). Effect of SCMC on foreign language anxiety and learning experience: A comparison of voice, video, and VR-based oral interaction. ReCALL, 33(1), 49-70. doi:10.1017/S0958344020000154

Authors

Abdalilah. G. I. Alhalangy
Mohammed AbdAlgane
Mo.mohammed@qu.edu.sa (Primary Contact)
Author Biographies

Abdalilah. G. I. Alhalangy , Assistant Professor of Information Systems Department of Computer Science, College of Science and Arts, Ar Rass, Qassim University, Saudi Arabia

Dr. ABDALILAH ALHALANGY is an assistant professor of information systems. He got a bachelor’s degree in information technology from Al-Sharq Private College, a master’s in information technology, and a Ph.D. in information systems from Al-Neelain University in Sudan. He has taught at the level of higher education in Sudan (the University of Kassala, Faculty of Computer Science and Information Technology) and Saudi Arabia (Qassim University) since 2006. At the University of Kassala, Sudan, he held several positions. He taught courses in the departments of computer science, information technology, and information systems.

Mohammed AbdAlgane, Department of English & Translation, College of Science and Arts, Ar Rass, Qassim University

Dr. MOHAMMED ABDALGANE is an assistant professor of Applied Linguistics and has been awarded an MA in ELT and a Ph.D. in Applied Linguistics from the University of Gezira, Sudan. He has been teaching English at the tertiary level in Sudan as well as Saudi Arabia since 2006. He taught the four skills, Linguistics, Phonetics & Phonology, Morphology, etc. His research interests are EFL speech production and perception, vocabulary teaching, reading, readability,  Phonetics, Phonology and teacher education, teaching methodologies, education technology, etc.

Alhalangy , A. G. I., & AbdAlgane, M. (2023). Exploring the Impact of AI on The EFL Context: A Case Study of Saudi Universities. Journal of Intercultural Communication, 23(2), 41–49. https://doi.org/10.36923/jicc.v23i2.125

Article Details

Smart Citations via scite_
Views
  • Abstract 5866
  • Download PDF 1490
  • XML 0