Teacher Development Programs in Language Education: AI-Driven Linguistic Perspectives on Effective Practices

Authors

  • Rishitha Chokkappagari India

DOI:

https://doi.org/10.61179/infact.v9i01.647

Keywords:

Teacher development program, Artificial Intelligence, Machine Learning Algorithms, Chatbots, Virtual Assistants, Accuracy

Abstract

AI today is progressing very fast in the treatment of different fields and touches almost all sectors, and education is one of them. AI is thus growing dear to language education for the ability it holds towards transforming the teaching approaches as well as the teacher training programs. This paper, Teacher Development Programs in Language Education: ‘AI-Driven Linguistic Perspectives on Effective Practices’, provides an extensive overview of the ways through which the integration of AI, into the professional development of language teachers can be successful.

The text starts the theoretical framework of language education that is the theories of language, educational psychology, and the sociocultural approach to language education. The function of AI is then brought to focus by explaining a brief history of AI use in education, a current state of integration in educational process, and its prospective advancements. This paper revolves around the concept of AI teacher development programs designs and execution. For each strategy, it provides detailed conversations on the ways in which AI can be implemented when it comes to curriculum mapping, student differentiation, and instructing. It also elaborates groundbreaking and imaginative ways of AI in pronunciation, speaking, reading, and writing improvement.

This paper provides the higher education, and private language schools’ case studies that explain how AI is implemented in practice to enhance teacher professional growth and development outcomes. Also, the paper discusses some of the core problems of big data like data privacy, algorithmic bias, and availability, and ways on how to deal with these problems responsibly are provided. Hence, the analysis and positive feedback from the programmes implementing the use of AI in the training of teachers through the rates of student performances, supplemented by the feedback from the teachers themselves, make the book informative on the impacts, as well as the shortcomings of AI in this area of practice. It ends by identifying future research directions based on the challenges raised in this paper, stressing on the roles of research, policy, and partnership to push forward language education with AI.

References

Fx. R. Baskara, “AI-Driven Dynamics: ChatGPT Transforming ELT Teacher-Student Interactions,” Lensa Kaji. Kebahasaan Kesusastraan Dan Budaya, vol. 13, no. 2, p. 261, Dec. 2023, doi: 10.26714/lensa.13.2.2023.261-275.

S. Akgun and C. Greenhow, “Artificial intelligence in education: Addressing ethical challenges in K-12 settings,” AI Ethics, vol. 2, no. 3, pp. 431–440, Aug. 2022, doi: 10.1007/s43681-021-00096-7.

P. Shah, AI and the Future of Education: Teaching in the Age of Artificial Intelligence. John Wiley & Sons, 2023.

K. Ahmad et al., “Data-Driven Artificial Intelligence in Education: A Comprehensive Review,” IEEE Trans. Learn. Technol., vol. 17, pp. 12–31, 2024, doi: 10.1109/TLT.2023.3314610.

K. Luneta, “Designing continuous professional development programmes for teachers: A literature review,” Afr. Educ. Rev., vol. 9, no. 2, pp. 360–379, Jul. 2012, doi: 10.1080/18146627.2012.722395.

H.-J. Lee, “Developing a Professional Development Program Model Based on Teachers’ Needs,” Prof. Educ., vol. 27, pp. 39–49, 2005.

H. Ji, I. Han, and Y. Ko, “A systematic review of conversational AI in language education: focusing on the collaboration with human teachers,” J. Res. Technol. Educ., vol. 55, pp. 1–16, Nov. 2022, doi: 10.1080/15391523.2022.2142873.

W. Alharbi, “AI in the Foreign Language Classroom: A Pedagogical Overview of Automated Writing Assistance Tools,” Educ. Res. Int., vol. 2023, no. 1, p. 4253331, 2023, doi: 10.1155/2023/4253331.

M. Ivanovi? et al., “Current Trends in AI-Based Educational Processes—An Overview,” in Handbook on Intelligent Techniques in the Educational Process: Vol 1 Recent Advances and Case Studies, M. Ivanovi?, A. Klašnja-Mili?evi?, and L. C. Jain, Eds., Cham: Springer International Publishing, 2022, pp. 1–15. doi: 10.1007/978-3-031-04662-9_1.

A. R. Costa, A. Balula, and S. Vasconcelos, “AI-ENHANCED LANGUAGE LEARNING IN HIGHER EDUCATION,” EDULEARN24 Proc., pp. 5594–5600, 2024, doi: 10.21125/edulearn.2024.1357.

T. Shaik et al., “A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis,” IEEE Access, vol. 10, pp. 56720–56739, 2022, doi: 10.1109/ACCESS.2022.3177752.

J. M. Gayed, M. K. J. Carlon, A. M. Oriola, and J. S. Cross, “Exploring an AI-based writing Assistant’s impact on English language learners,” Comput. Educ. Artif. Intell., vol. 3, p. 100055, Jan. 2022, doi: 10.1016/j.caeai.2022.100055.

A. Vazhayil, R. Shetty, R. R. Bhavani, and N. Akshay, “Focusing on Teacher Education to Introduce AI in Schools: Perspectives and Illustrative Findings,” in 2019 IEEE Tenth International Conference on Technology for Education (T4E), Dec. 2019, pp. 71–77. doi: 10.1109/T4E.2019.00021.

H. Fakhar, M. Lamrabet, N. Echantoufi, K. El Khattabi, and L. Ajana, “Towards a New Artificial Intelligence-based Framework for Teachers’ Online Continuous Professional Development Programs: Systematic Review,” Int. J. Adv. Comput. Sci. Appl., vol. 15, pp. 480–493, Apr. 2024, doi: 10.14569/IJACSA.2024.0150450.

G. Jugo and A. Baši?, “Opportunities for the Professional Development of Teachers in Digital Competences Related to the Use of Artificial Intelligence in Education in Croatia,” in Digital Transformation in Education and Artificial Intelligence Application, T. Volari?, B. Crnoki?, and D. Vasi?, Eds., Cham: Springer Nature Switzerland, 2024, pp. 97–109. doi: 10.1007/978-3-031-62058-4_8.

F. King, “Evaluating the impact of teacher professional development: an evidence-based framework,” Prof. Dev. Educ., vol. 40, no. 1, pp. 89–111, Jan. 2014, doi: 10.1080/19415257.2013.823099.

N. Ghamrawi, T. Shal, and N. A. R. Ghamrawi, “Exploring the impact of AI on teacher leadership: regressing or expanding?,” Educ. Inf. Technol., vol. 29, no. 7, pp. 8415–8433, May 2024, doi: 10.1007/s10639-023-12174-w.

Z. Gan, Z. An, and F. Liu, “Teacher Feedback Practices, Student Feedback Motivation, and Feedback Behavior: How Are They Associated With Learning Outcomes?,” Front. Psychol., vol. 12, Jun. 2021, doi: 10.3389/fpsyg.2021.697045.

J. Kim, “Leading teachers’ perspective on teacher-AI collaboration in education,” Educ. Inf. Technol., vol. 29, no. 7, pp. 8693–8724, May 2024, doi: 10.1007/s10639-023-12109-5.

J. H. Holloway, “Connecting Professional Development to Student Learning Gains,” Sci. Educ., vol. 15, no. 1, pp. 37–43, 2006.

K. Scalise, M. Timms, A. Moorjani, L. Clark, K. Holtermann, and P. S. Irvin, “Student learning in science simulations: Design features that promote learning gains,” J. Res. Sci. Teach., vol. 48, no. 9, pp. 1050–1078, 2011, doi: 10.1002/tea.20437.

S. Akgun and C. Greenhow, “Artificial intelligence in education: Addressing ethical challenges in K-12 settings,” AI Ethics, vol. 2, no. 3, pp. 431–440, Aug. 2022, doi: 10.1007/s43681-021-00096-7.

J. Borenstein and A. Howard, “Emerging challenges in AI and the need for AI ethics education,” AI Ethics, vol. 1, no. 1, pp. 61–65, Feb. 2021, doi: 10.1007/s43681-020-00002-7.

B. U. iu Zaman, “Transforming Education Through AI Benefits Risks and Ethical Considerations,” Jul. 10, 2024, Preprints: 2024070859. doi: 10.20944/preprints202407.0859.v1.

Rahaman M (2024) Foundations of Phishing Detection Using Deep Learning: A Review of Current Techniques. Available: https://insights2techinfo.com/foundations-of-phishing-detection-using-deep-learning-a-review-of-current-techniques/

Tabassum F, Rahaman M (2024) An Enhanced Multi-Factor Authentication and Key Agreement Protocol in Industrial Internet of Things, Available: https://insights2techinfo.com/an-enhanced-multi-factor-authentication-and-key-agreement-protocol-in-industrial-internet-of-things/

G.-J. Hwang and N.-S. Chen, “Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions,” J. Educ. Technol. Soc., vol. 26, no. 2, Apr. 2023, Accessed: Aug. 13, 2024. [Online]. Available: https://www.proquest.com/docview/3069441686/abstract/D9E3F899489E41C2PQ/1

P. Chakriswaran, D. R. Vincent, K. Srinivasan, V. Sharma, C.-Y. Chang, and D. G. Reina, “Emotion AI-Driven Sentiment Analysis: A Survey, Future Research Directions, and Open Issues,” Appl. Sci., vol. 9, no. 24, Art. no. 24, Jan. 2019, doi: 10.3390/app9245462.

F. Ouyang and L. Zhang, “AI-driven learning analytics applications and tools in computer-supported collaborative learning: A systematic review,” Educ. Res. Rev., vol. 44, p. 100616, Aug. 2024, doi: 10.1016/j.edurev.2024.100616.

H. Luan et al., “Challenges and Future Directions of Big Data and Artificial Intelligence in Education,” Front. Psychol., vol. 11, Oct. 2020, doi: 10.3389/fpsyg.2020.580820.

B. Lingard and S. Rawolle, “New scalar politics: implications for education policy,” Comp. Educ., vol. 47, no. 4, pp. 489–502, Nov. 2011, doi: 10.1080/03050068.2011.555941.

D. Hopkins and D. Stern, “Quality teachers, quality schools: International perspectives and policy implications,” Teach. Teach. Educ., vol. 12, no. 5, pp. 501–517, Sep. 1996, doi: 10.1016/0742-051X(95)00055-O.

J. Sulistiawan, M. Moslehpour, F. Diana, and P.-K. Lin, “Why and When Do Employees Hide Their Knowledge?,” Behav. Sci., vol. 12, no. 2, Art. no. 2, Feb. 2022, doi: 10.3390/bs12020056.

Downloads

Published

2025-03-17

How to Cite

[1]
R. Chokkappagari, “Teacher Development Programs in Language Education: AI-Driven Linguistic Perspectives on Effective Practices”, IIJC, vol. 9, no. 01, pp. 1–12, Mar. 2025.