Résumés
Abstract
Learners might have several challenges while attempting to learn a second/foreign language. Learners of Chinese face linguistic, psychological, and educational challenges. The integration of technology, especially artificial intelligence (AI), into teaching foreign languages is a blessing for teachers and learners. This study delved into the auxiliary role of AI-powered applications in mitigating the linguistic, psychological, and educational challenges which non-Chinese learners face while learning Chinese/Mandarin language. Qualitative research was employed, and 20 teachers of Chinese language were selected through theoretical sampling. In-depth interviews were used for collecting data, and MAXQDA was used for thematic analysis. Findings revealed that AI-powered educational applications are useful for helping language learners overcome the commonly reported linguistic, psychological, and educational challenges which non-Chinese learners and teachers of Mandarin might encounter. Findings verify the effectiveness of AI-powered applications, such as ChatGPT, Poe, Brainly, and so forth, in helping teachers and learners of Chinese language learn grammar, structure, idioms, and cultural issues of Chinese language. Findings have implications for foreign language (Chinese) learners and teachers, educational technologists, as well as syllabus designers.
Keywords:
- AI-powered application,
- auxiliary role of AI,
- AI,
- Chinese language,
- challenges of learning,
- Chinese language learner,
- Chinese language teacher
Veuillez télécharger l’article en PDF pour le lire.
Télécharger
Parties annexes
Bibliography
- Agarwal, M., Saba, L., Gupta, S. K., Carriero, A., Falaschi, Z., Paschè, A., Danna, P., El-Baz, A., Naidu, S., & Suri, J. S. (2021). A novel block imaging technique using nine artificial intelligence models for COVID-19 disease classification, characterization, and severity measurement in lung computed tomography scans on an Italian cohort. Journal of Medical Systems, 45, Article 28. https://www.doi.org/10.1007/s10916-021-01707-w
- Ajabshir, Z. F. (2023). A review of the affordances and challenges of artificial intelligence technologies in second language learning. Technology Assisted Language Education, 1(4), 96-115. DOI: 10.22126/TALE.2024.10104.1028
- Alibakhshi, G. (2013). Construction and validation of self-assessment inventory for English for academic purposes: A case of Iranian tertiary students. Journal of Research in Applied Linguistics, 4(2), 93–109.
- Alibakhshi, G., & Nezakatgoo, B. (2019). Construction and validation of Iranian EFL teachers’ teaching motivation scale. Cogent Education, 6(1), Article 1585311. https://www.doi.org/10.1080/2331186X.2019.1585311
- Bogdan, R. C., & Biklen, S. K. (2007). Qualitative research for education: An introduction to theory and methods (5th ed.). Allyn & Bacon.
- Cheng, C. T., Chen, C. C., Fu, C. Y., Chaou, C. H., Wu, Y. T., Hsu, C. P., Chang, C. C., Chung, I. F., Hsieh, C. H., Hsieh, M. J., & Liao, C. H. (2020, November 23). Artificial intelligence-based education assists medical students’ interpretation of hip fractures. Insights Imaging, 11(1), Article 119. https://doi.org/10.1186/s13244-020-00932-0
- Chen, M., Mao, S., Zhang, Y., & Leung, V. C. (2014). Big data: Related technologies, challenges and future prospects (Vol. 100). Heidelberg: Springer.
- Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education. Routledge.
- Cox, S. E. (2020). Perceptions and influences behind teaching practices: Do teachers teach as they were taught? [Master’s thesis, Brigham Young University]. BYU Scholars Archive. https://scholarsarchive.byu.edu/etd/5301
- Creswell, J. W. (2014). Research design: Qualitative, quantitative and mixed methods approaches (4th ed.). Sage.
- Derun, P., Genggeng, Q., & Weiguo, C. (2019). Application progress of artificial intelligence technology based on deep learning in breast cancer screening and imaging diagnosis. International Journal of Medical Radiology, 42(01), 15–18. https://inis.iaea.org/search/search.aspx?orig_q=RN:54023411
- Everson, M. (2008). Issues in Chinese literacy learning and implications for teacher development. In P. Duff & P. Lester (Eds.), Issues in Chinese language education and teacher development (pp. 70–78). University of British Columbia, Centre for Research in Chinese Language and Literacy Education. https://www.academia.edu/9682120/Issues_in_Chinese_Language_Education_and_Teacher_Development_2008
- Gao, L. X., & Zhang, L. J. (2020). Teacher learning in difficult times: Examining foreign language teachers’ cognitions about online teaching to tide over COVID-19. Frontiers in Psychology, 11, Article 549653. https://doi.org/10.3389/fpsyg.2020.549653
- Gligorea, I., Cioca, M., Oancea, R., Gorski, A. T., Gorski, H., & Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: A literature review. Education Sciences, 13(12), 1216.
- Graham, S., Depp, C., Lee, E. E., Nebeker, C., Tu, X., Kim, H. – C., & Jeste, D. V. (2019). Artificial intelligence for mental health and mental illnesses: An overview. Current Psychiatry Reports, 21, Article 116. https://www.doi.org/10.1007/s11920-019-1094-0
- Guo, Y., Ren, X., Chen, Y.-X., & Wang, T.-J. (2019). Artificial intelligence meets Chinese medicine. Chinese Journal of Integrative Medicine, 25(9), 648–653. https://www.doi.org/10.1007/s11655-019-3169-5
- Hartig, F. (2015). Chinese public diplomacy: The rise of the Confucius Institute. Routledge.
- Hirschmann, A., Cyriac, J., Stieltjes, B., Kober, T., Richiardi, J., & Omoumi, P. (2019, June). Artificial intelligence in musculoskeletal imaging: Review of current literature, challenges, and trends. Seminars in Musculoskeletal Radiology, 23, (3), 304–311. https://www.doi.org/10.1055/s-0039-1684024
- Jiang, Y., Chen, Y., Lu, J., & Wang, Y. (2021). The effect of the online and offline blended teaching mode on English as a foreign language learners’ listening performance in a Chinese context. Frontiers in Psychology, 12, 742742. DOI: 10.3389/fpsyg.2021.742742
- Jin, Q. (Ed.). (2011). Intelligent learning systems and advancements in computer-aided instruction: Emerging studies. IGI Global.
- Johnson, K. W., Torres Soto, J., Glicksberg, B. S., Shameer, K., Miotto, R., Ali, M., Ashley, E., & Dudley, J. T. (2018). Artificial intelligence in cardiology. Journal of the American College of Cardiology, 71(23), 2668–2679. https://www.doi.org/10.1016/j.jacc.2018.03.521
- Kang, B., & Kang, S. (2023). Construction of a Chinese language teaching system model based on deep learning under the background of artificial intelligence. Scientific Programming, 2022, Article 3960023. https://doi.org/10.1155/2022/3960023
- Li, H. (2018). Deep learning for natural language processing: Advantages and challenges. National Science Review, 5(1), 24–26. https://doi.org/10.1093/nsr/nwx110
- Lu, X., Ai, W., Liu, X., Li, Q., Wang, N., Huang, G., & Mei, Q. (2016, September). Learning from the ubiquitous language: an empirical analysis of emoji usage of smartphone users. In Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing (pp. 770-780). https://doi.org/10.1145/2971648.2971724
- Makhambetova, A., Zhiyenbayeva, N., & Ergesheva, E. (2021). Personalized learning strategy as a tool to improve academic performance and motivation of students. International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 16(6), 1-17. DOI:10.4018/IJWLTT.286743
- Miao, S., Xu, T., Wu, Y., Xie, H., Wang, J., Jing, S., Zhang, Y., Zhang, X., Yang, Y., Zhang, X., Shan, T., Wang, L., Xu, H., Wang, S., & Liu, Y. (2018). Extraction of BI-RADS findings from breast ultrasound reports in Chinese using deep learning approaches. International Journal of Medical Informatics, 119, 17–21. https://www.doi.org/10.1016/j.ijmedinf.2018.08.009
- Orton, J. (2011). Educating Chinese language teachers—Some fundamentals. In L. Tsung & K. Cruickshank (Eds.), Teaching and learning Chinese in global contexts: Multimodality and literacy in the new media age (pp. 151–164). Continuum.
- Peng, H., Ma, S., & Spector, J. M. (2019). Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6(1), 1-14. https://slejournal.springeropen.com/articles/10.1186/s40561-019-0089-y
- Pérez-Milans, M. (2015). Mandarin Chinese in London education: Language aspirations in a working-class secondary school. Language Policy, 14, 153–181. https://doi.org/10.1007/s10993-014-9345-8
- Wang, R. (2021). Research on the application of deep learning in artificial intelligence courses. Journal of Electronic Research and Application, 5(6), 14–18. https://www.doi.org/10.26689/jera.v5i6.2760
- Wang, X. (2004). Encouraging self-monitoring in writing by Chinese students. ELT Journal, 58(3), 238–246. https://doi.org/10.1093/elt/58.3.238
- Wang, Y., & Lemmer, V. (2015). Teaching Chinese as a foreign language in higher education in China and South Africa: Lecturers’ views. Per Linguam, 31(2), 35–52. https://doi.org/10.5785/31-2-608
- Wu, W. J., & Mareya, I. A. (2022). Benefits and challenges faced by foreign students of Chinese language after graduation. Journal of Applied Linguistics and Language Learning, 5(1), 12–18. https://doi.org/10.5923/j.jalll.20220501.02
- Xiao, Y., & Liu, S. (2019). Collaborations of industry, academia, research and application improve the healthy development of medical imaging artificial intelligence industry in China. Chinese Medical Sciences Journal, 34(2), 84–88. https://doi.org/10.24920/003619
- Yalun, A. (2019). International promotion of Chinese language in the new era. International Education Studies, 12(7), 67–79. https://www.doi.org/10.5539/ies.v12n7p67
- Ye, L. (2013). Shall we delay teaching characters in teaching Chinese as a foreign language? Foreign Language Annals, 46(4), 610–627. https://doi.org/10.1111/flan.12049
- Yi, T., Lin, C., En-Ci, J., & Ji-Zhong, Y. (2020). Application and prospects of hyperspectral imaging and deep learning in traditional Chinese medicine in context of AI and industry 4.0. Zhongguo Zhong yao za zhi= Zhongguo Zhongyao Zazhi= China Journal of Chinese Materia Medica, 45(22), 5438-5442.https://www.doi.org/10.19540/j.cnki.cjcmm.20200630.603
- Yue, Y. (2017). Teaching Chinese in K-12 schools in the United States: What are the challenges? Foreign Language Annals, 50(3), 601–620. https://doi.org/10.1111/flan.12277
- Zhu, Z., Shan, J., & Yan, H. (2019). International investigation and development strategy for artificial intelligence maker education. Open Education Research, 25(1), 47–54. https://doi.org/10.1155/2022/3960023