Abstract
The exploration of the application of information technology in the fields of General English and Business English has emerged as a crucial area of research. This systematic literature review examined 32 indexed research articles published between 2021 and 2024, focusing on the application of machine learning, deep learning, ChatGPT, and other algorithms in these domains. The main aim of this review is to assess the current academic development in the optimization of General English and Business English learning in the context of AI technology The findings underscored that the utilization of information technology was minimal in listening. In contrast, significant and effective applications of deep learning, machine learning, ChatGPT, and other algorithms were observed in speaking, writing, and translation works. Notably, the highest level of interest was noted by researchers in China, with Asian researchers accounting for 91% of the contributions. In contrast, General English exhibited broader applicability, encompassing a diverse target population. This research ultimately provides valuable insights for researchers and educators, guiding the development of innovative educational practices in the context of language learning in the AI era in line with SDG 4 that focusses on Quality Education.
References
Chen, Z., Lian, Y., & Lin, Z. (n.d.). Research on business English autonomous learning based on artificial intelligence and improved BP network model.
Darwin, Rusdin, D., Mukminatien, N., Suryati, N., Laksmi, E. D., & Marzuki. (2024). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations. Cogent Education, 11(1), 2290342. https://doi.org/10.1080/2331186X.2023.2290342
Dhivya, D. S., Hariharasudan, A., Ragmoun, W., & Alfalih, A. A. (2023). ELSA as an Education 4.0 Tool for Learning Business English Communication. Sustainability, 15(4), 3809. https://doi.org/10.3390/su15043809
Drajati, N. A., Rochsantiningsih, D., & Agung, S. (2023). Intertextuality in Pre-service Teachers’ Argumentative Essay in Raising AI: Practices and Beliefs. REGISTER JOURNAL, 16(2).
Duan, W. (2022). Research on Scoring of Business English Oral Training Based on Deep Neural Network. Scientific Programming, 2022, 1–8. https://doi.org/10.1155/2022/9193454
Ghio, A. (2024). Democratizing academic research with Artificial Intelligence: The misleading case of language. Critical Perspectives on Accounting, 98, 102687. https://doi.org/10.1016/j.cpa.2023.102687
Hou, R. (2022). Application of Decision Tree Algorithm Based on Data Mining in English Teaching Evaluation. Wireless Communications and Mobile Computing, 2022, 1–10. https://doi.org/10.1155/2022/5717895
Hu, B. (2021). English Listening Teaching Model in Flipped Classroom Based on Artificial Intelligence Fusion Control Algorithm. Mathematical Problems in Engineering, 2021, 1–14. https://doi.org/10.1155/2021/6005359
Hu, R., & Wu, K. (n.d.). Edge computing and 5G based low‐delay business English translation framework.
Liu, L. (n.d.). Classification of English Educational Resources Information Based on Mobile Learning Using Cognitive Web Service. 19(2).
Liu, Q. (2023). Text Complexity Analysis of Chinese and foreign academic English writing via mobile devices based on neural network and deep learning. Library Hi Tech, 41(5), 1317–1332. https://doi.org/10.1108/LHT-11-2021-0383
Luo, X. (2022). Practice of Artificial Intelligence and Virtual Reality Technology in College English Dialogue Scene Simulation. Wireless Communications and Mobile Computing, 2022, 1–9. https://doi.org/10.1155/2022/4922675
Nazari, N., Shabbir, M. S., & Setiawan, R. (2021). Application of Artificial Intelligence powered digital writing assistant in higher education: Randomized controlled trial. Heliyon, 7(5), e07014. https://doi.org/10.1016/j.heliyon.2021.e07014
Nugroho, A., Andriyanti, E., Widodo, P., & Mutiaraningrum, I. (2024). Students’ appraisals post-ChatGPT use: Students’ narrative after using ChatGPT for writing. Innovations in Education and Teaching International, 1–13. https://doi.org/10.1080/14703297.2024.2319184
Peres, F. (2024). Health literacy in ChatGPT: Exploring the potential of the use of artificial intelligence to produce academic text. Ciência & Saúde Coletiva, 29(1), e02412023. https://doi.org/10.1590/1413-81232024291.02412023en
Sel, İ., & Hanbay, D. (2022). Fully Attentional Network for Low-Resource Academic Machine Translation and Post Editing.
Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: Assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in Psychology, 14, 1260843. https://doi.org/10.3389/fpsyg.2023.1260843
Tang, J. (2023). Artificial intelligence-based needs analysis for english specific purposes in digital environment. Learning and Motivation, 83, 101914. https://doi.org/10.1016/j.lmot.2023.101914
Taskiran, A., & Goksel, N. (2022). AUTOMATED FEEDBACK AND TEACHER FEEDBACK: WRITING ACHIEVEMENT IN LEARNING ENGLISH AS A FOREIGN LANGUAGE AT A DISTANCE. Turkish Online Journal of Distance Education, 23(2), 120–139. https://doi.org/10.17718/tojde.1096260
Wang, R. (2023). RETRACTED ARTICLE: Research on effectiveness of college english blended teaching mode under small private online course based on machine learning. SN Applied Sciences, 5(2), 55. https://doi.org/10.1007/s42452-023-05278-y
Wang, Y. (2023). Artificial Intelligence Technologies in College English Translation Teaching. Journal of Psycholinguistic Research, 52(5), 1525–1544. https://doi.org/10.1007/s10936-023-09960-5
Wiwanitkit, S., & Wiwanitkit, V. (2024). Correspondence on ‘Is ChatGPT a “Fire of Prometheus” for Non-Native English-Speaking Researchers in Academic Writing?’ Korean Journal of Radiology, 25(1), 120. https://doi.org/10.3348/kjr.2023.0971
Wu, M., Subramaniam, G., Zhu, D., Li, C., Ding, H., & Zhang, Y. (2024). Using Machine Learning-based Algorithms to Predict Academic Performance—A Systematic Literature Review. 2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM), 1–8. https://doi.org/10.1109/ICIPTM59628.2024.10563566
Xu, X., & Xiao, K. (2022). Oral Business English Recognition Method Based on RankNet Model and Endpoint Detection Algorithm. Journal of Sensors, 2022, 1–13. https://doi.org/10.1155/2022/7426303
Xu, Y. (2021). Research on Business English Translation Architecture Based on Artificial Intelligence Speech Recognition and Edge Computing. Wireless Communications and Mobile Computing, 2021(1), 5518868. https://doi.org/10.1155/2021/5518868
Yang, Q. (2022). Analysis of English Cultural Teaching Model Based on Machine Learning. Computational Intelligence and Neuroscience, 2022, 1–9. https://doi.org/10.1155/2022/7126758
Yang, X., & Qi, S. (2022). Interactive Design of Business English Learning Resources Based on EDIPT Multimodal Model. Computational Intelligence and Neuroscience, 2022, 1–9. https://doi.org/10.1155/2022/1264847
Yu, Y., Han, L., Du, X., & Yu, J. (2022). An Oral English Evaluation Model Using Artificial Intelligence Method. Mobile Information Systems, 2022, 1–8. https://doi.org/10.1155/2022/3998886
Zenni, R. D., & Andrew, N. R. (2023). Artificial Intelligence text generators for overcoming language barriers in ecological research communication. Austral Ecology, 48(7), 1225–1229. https://doi.org/10.1111/aec.13417
Zhao, B. (2022). A Design Model of English Auxiliary Teaching System Using Artificial Neural Networks. Mobile Information Systems, 2022, 1–11. https://doi.org/10.1155/2022/8694532
Zheng, P. (2022). Multisensor Feature Fusion-Based Model for Business English Translation. Scientific Programming, 2022, 1–10. https://doi.org/10.1155/2022/3102337
Zheng, Z., & Na, K. S. (2021). A Data-Driven Emotion Model for English Learners Based on Machine Learning. International Journal of Emerging Technologies in Learning (iJET), 16(08), 34. https://doi.org/10.3991/ijet.v16i08.22127
Zhu, Y. (2021). Off-Topic Detection of Business English Essay Based on Deep Learning Model. Mobile Information Systems, 2021, 1–9. https://doi.org/10.1155/2021/5051667
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