| تعداد نشریات | 24 |
| تعداد شمارهها | 916 |
| تعداد مقالات | 8,202 |
| تعداد مشاهده مقاله | 15,918,403 |
| تعداد دریافت فایل اصل مقاله | 13,468,789 |
Exploring the Efficacy of ChatGPT in Personalized Language Learning: An Intervention Study in Iranian ESL Classrooms | ||
| Teaching English as a Second Language Quarterly | ||
| دوره 43، شماره 3، 2024، صفحه 1-26 اصل مقاله (502.88 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22099/tesl.2024.49390.3260 | ||
| نویسنده | ||
| Forough Amirjalili* | ||
| Department of Language and Literature, Yazd University, Yazd, Iran | ||
| چکیده | ||
| With the advent of artificial intelligence (AI) tools, language teachers are presented with new possibilities for addressing challenges in language education. This intervention study aimed to investigate views from ESL teachers on the benefits and challenges of integrating ChatGPT, An artificial intelligence (AI) language model created by OpenAI in 2023, into ESL classrooms for personalized language learning. The study carried out in two upper-secondary schools, combines teacher questionnaires and interviews with a personalized learning intervention based on ChatGPT. The primary focus was on understanding the effect of ChatGPT-based personalized learning assignments on learners’ grammatical knowledge in a local classroom setting. Through the questionnaire, initial teacher concerns regarding the precision, dependability, and helpful application of AI tools were investigated. Despite these reservations, the intervention demonstrated a notable decrease in grammatical errors in student writing. Subsequent interviews revealed a positive shift in teacher perceptions, indicating increased receptivity to AI-based approaches after witnessing positive outcomes. The study highlights the importance of teacher training and hands-on experience in overcoming initial hesitations associated with AI tool adoption in pedagogical practices. Moreover, the promising results suggest that AI-powered instruments, like ChatGPT, have the potential to enhance personalized language learning. This underscored the significance of educators cultivating their Technological Pedagogical Content Knowledge (TPACK) to overcome hesitations and effectively harness the potential of ChatGPT for augmenting individualized learning. The study’s findings provided evidence supporting the utilization of ChatGPT-based personalized learning assignments to meet the specific requirements of the schools in question. | ||
| کلیدواژهها | ||
| AI-powered tools؛ ChatGPT؛ Customized tasks؛ ESL classroom؛ Personalized language learning | ||
| مراجع | ||
|
Ahmad, M. F., & Ghapar, W. R. G. W. A. (2019). The era of artificial intelligence in Malaysian higher education: Impact and challenges in tangible mixed-reality learning system toward self-exploration education (SEE). Procedia Computer Science, 163, 2-10.
AL-Qadri, A. H., & Ahmed, S. A. (2023). Assessing the ChatGPT accuracy through principles of statistics exam: A performance and implications. Retrieved from
Ayanawale, A. B., Aladejana, A. O., & Adewale, O. S. (2022). Teachers’ readiness and intention to teach Artificial Intelligence in schools. International Journal of Technology and Educational Marketing, 12(2), 52-64.
Baker, R. S. (2016). Stupid tutoring systems, intelligent humans. International Journal of Artificial Intelligence in Education, 26(2), 600-614.
Bansla, A., & Bansla, N. (2012, January 01). Artificial intelligence. Journal of Artificial Intelligence, 7, 1724-1727.
Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. International Journal of Information Management, 62, 102529.
Budzianowski, P., & Vulić, I. (2019). Hello, it’s GPT-2 - how can I help you? Towards the use of pre-trained language models for task-oriented dialogue systems. In Proceedings of the 3rd Workshop on Neural Generation and Translation, (pp.15–22). https://doi.org10.18653/v1/D19-5602
Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate Artificial Intelligence (AI)-based tools into education. Computers in Human Behavior, 138, 107468. https://doi.org10.1016/j.chb.2022.107468/.
Chatterjee, S., & Bhattacharjee, K. (2020). Adoption of artificial intelligence in higher education: A quantitative analysis using structural equation modeling. Education and Information Technologies, 25. https://doi.org/10.1007/s10639-020-10159-7
Cheng, E. C., & Wang, T. K. (2021). An Investigation of barriers to Hong Kong K-12 schools incorporating Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 2, 100031. https://doi.org/10.1016/j.caeai.2021.100031 Top of Form
Chen, D., & Wu, J. (2018). Leveraging digital storytelling for critical thinking: A knowledge forensics approach. Ed Media and Innovative Learning Conference, Amsterdam, Netherlands, (pp.52–60).
Chiu, T.K.F., Xia, Q., Zhou, X., Chai, C.S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2022.100118. Top of Form
Cook, C. R., Kilgus, S. P., & Burns, M. K. (2018). Advancing the science and practice of precision education to enhance student outcomes. Journal of School Psychology, 66, 4-10. https://doi.org/10.1016/j.jsp.2017.11.004
Desmarais, M. C., & Baker, R. S. (2012). A review of recent advances in learner and skill modeling in intelligent learning environments. User Modeling and User-Adapted Interaction, 22(1-2), 9-38. https://link.springer.com/article/10.1007/s11257-011-9106
Field, A. P. (2005). Is the meta-analysis of correlation coefficients accurate when population correlations vary? Psychological Methods, 10(4), 444–455. https://doi.org10.1037/1082-989X.10.4.444.
Ferguson, C., van den Broek, E. L., & van Oostendorp, H. (2022). AI-induced guidance: Preserving the optimal Zone of Proximal Development. Computers and Education: Artificial Intelligence, 3(21). https://www.sciencedirect.com/science/article/pii/S2666920X22000443
Kalla, D., & Smith, N. (2023). Study and analysis of chat GPT and its impact on different fields of study. International Journal of Innovative Science and Research Technology, 8(3). Retrieved from https://ssrn.com/abstract=4402499
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103(45).
https://doi.org10.1016/j.lindif.2023.102274
Khan, H. (2021). Types of AI: Different types of artificial intelligence systems. Journal of AI Research, 9(50). https://artificialintelligenceact.com/
Kim, S., Jang, Y., Choi, S., Kim, W., Jung, H., Kim, S., & Kim, H. (2021). Analyzing teacher competency with TPACK for K-12 AI education. KI-Künstliche Intelligenz, 35(2), 139-151. https://doi.org/10.1007/s13218-021-00731-9
Knox, J. (2020). Artificial intelligence and education in China. Learning, Media and Technology, 45(3), 298-311.
Kvale, S. (2007) Doing interviews (1st.ed). Sage Publications, Thousand Oaks. http://dx.doi.org/10.4135/9781849208963 Lindner, A., Romeike, R., Jasute, E., & Pozdniakov, S. (2019). Teachers’ perspectives on artificial intelligence. In 12th International Conference on Informatics in Schools, Situation, Evaluation and Perspectives, (pp.22 – 29).
Lee, D., Kim, H. H., & Sung, S. H. (2022). Development research on an AI English learning support system to facilitate learner-generated-context-based learning. Educational Technology Research and Development, 70(1), 287-310.
Li, W., & Zhang, L. (2019). Personalized learning path generation based on network embedding and learning effects. 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS) (pp. 316-319). IEEE. https://doi.org/10.1109/ICSESS47205.2019.9040721
Minn, S. (2022). AI-assisted knowledge assessment techniques for adaptive learning environments. Computers and Education: Artificial Intelligence, 3, 100050.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers’ College Record, 108(6), 1017-1054.
Nushi, M., & Momeni, A. (2020). Educational technologies in textbooks: The case of Iranian EAP context. Teaching English with Technology, 20(5), 65-86.
Rožman, M., Oreški, D., & Tominc, P. (2023). Artificial-intelligence-supported reduction of employees’ workload to increase the company’s performance in today’s VUCA Environment. Sustainability, 15(6). https://doi.org/10.3390/su15065019
Tang, Y., Liang, J., Hare, R., & Wang, F. Y. (2020). A personalized learning system for parallel intelligent education. IEEE Transactions on Computational Social Systems, 7(2), 352-361. https://doi.org/10.1109/TCSS.2020.2965198
Vygotsky, L. S., & Cole, M. (1978). Mind in society: Development of higher psychological processes. Harvard University Press.
Wang, X., Liu, Q., Pang, H., Tan, S. C., Lei, J., Wallace, M. P., & Li, L. (2023). What matters in AI-supported learning: A study of human-AI interactions in language learning using cluster analysis and epistemic network analysis. Computers & Education, 194, 104703. https://doi.org/10.1016/j.compedu.2022.104703
Wang, Y., Liu, C., & Tu, Y. F. (2021). Factors affecting the adoption of AI-based applications in higher education. Educational Technology & Society, 24(3), 116-129.
Yonezawa, S., McClure, L., & Jones, M. (2012). Personalization in schools. The Education Digest, 78(2), 41-47. https://eric.ed.gov/?id=EJ1002828 | ||
|
آمار تعداد مشاهده مقاله: 1,410 تعداد دریافت فایل اصل مقاله: 1,299 |
||