EMPOWERING TEACHERS: AI TOOLS FOR ENHANCING ENGLISH EDUCATION IN PONTIANAK URBAN SCHOOLS
DOI:
https://doi.org/10.26418/jefle.v5i2.89288Abstract
This research examines the integration of AI tools in English language education within urban schools in Pontianak, focusing on teachers' perceptions, benefits, and challenges. The study aims to understand how English teachers view the effectiveness of AI tools and the obstacles they encounter. Using a descriptive research approach, data were collected through surveys completed by 4 English teachers from four urban schools. Results indicate that teachers generally find AI tools beneficial for student engagement and classroom management, yet express concerns regarding role replacement and technical support. The insights gathered will support educational stakeholders in formulating policies and developing AI tools that align with teachers"™ practical needs and enhance the quality of English education in similar contexts.
Keywords: AI tools, English education, teacher perceptions, educational technology, teacher empowerment
References
Behrens, J. T. (2018). Adaptive learning in educational technology: Approaches and future directions. Educational Researcher, 47(4), 259-269. https://doi.org/10.3102/0013189X18771017
Erickson, F., & Kaplan, A. (2020). AI in education: Implications for teacher autonomy and learning effectiveness. Educational Technology Research and Development, 68(6), 3451-3464. https://doi.org/10.1007/s11423-020-09812-5
Godfrey, K., Zhang, Y., & Wang, Z. (2020). Natural language processing in classroom assessments. Language Learning and Technology, 24(2), 85-103.
Godwin-Jones, R. (2018). Learning languages with AI: Applications and effectiveness. Language Learning & Technology, 22(1), 4-14.
Hew, K. F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educational Technology Research and Development, 55(3), 223-252. https://doi.org/10.1007/s11423-006-9022-5
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Kukulska-Hulme, A., Norris, L., & Donohue, J. (2017). Mobile and AI learning in language acquisition: A systematic review. Educational Technology & Society, 20(2), 45-59.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
Moussa-Inaty, J., & Mohamed, E. (2019). Challenges in implementing AI in low-resource educational settings: Perspectives from urban schools. Journal of Educational Technology Development, 6(3), 201-215.
Reinders, H., & White, C. (2011). Learner-centered approaches in AI-based language learning systems. Language Learning and Technology, 15(3), 12-27.
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197-221. https://doi.org/10.1080/00461520.2011.611369
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Warschauer, M. (2011). Learning in the cloud: How (and why) to transform schools with digital media. Teachers College Press.
Wang, S., & Vasquez, C. (2012). Web 2.0 and second language learning: What does the research tell us? CALICO Journal, 29(3), 412-430.
Zawacki-Richter, O., MarÃn, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education: Challenges and opportunities. International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0177-2
Downloads
Published
Issue
Section
License
- Author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-ShareAlike 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal
- Author is able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgment of its initial publication in this journal.
- Author is permitted and encouraged to post his/her work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work (See The Effect of Open Access).