How Far Is Technology Integration In Elt By The Umbrella Of Ai Dependence And The Paradigm Of Shifting From Dictionaries To Algorithms For Flt
Keywords:
AI Dependence, Algorithms, Dependence, ELT, Language LearningAbstract
The promise and peril of AI in Language Learning have necessarily transmuted learning paradigms through personalized instruction, enhanced accessibility, and improved pedagogical proficiency. AI is for supporting both learners and teachers; it is by tailoring individual learning styles and instructional teaching needs. This article systematically examines the remunerations and restrictions of AI-dependent language learning by analyzing how algorithmic content mediates learning processes of foreign languages. The study highlights the overreliance on AI systems by accentuating the necessity for a holistic approach to technology integration in foreign language learning. Through a comprehensive criticism of contemporary advancements and empirical user experiences, this research elucidates AI's transformative potential in foreign language instruction. Eventually, the research paper is for strategic implementation agendas that attach AI's proficiencies while preservation pedagogical integrity, and thereby promoting sustainable educational conclusions for future generations.
References
Acemoglu, D., & Restrepo, P. (2020). Technological change, inequality, and the future of work. Journal of Political Economy, 128(6), 2186–2244. https://doi.org/10.1086/705716
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021ACM Conference on Fairness, Accountability, and Transparency (pp. 610–623). https://doi.org/10.1145/3442188.3445922
Burrell, J. (2016). How the machine 'thinks': Understanding opacity in machine learning algorithms. Big Data & Society, 3(1), 1–12. https://doi.org/10.1177/2053951715622512
Byram, M. (1997). Teaching and assessing intercultural communicative competence. Multilingual Matters.
Chen, L. (2020). AI and cultural literacy in language learning. Journal of Educational Technology and Society, 23(2), 125–135.
Chen, L. (2021). Cultural nuances in language learning: The role of AI. Journal of Linguistic Studies, 45(3), 200–215. https://doi.org/10.5678/jls.2021.45310
Dencik, L., Hintz, A., Redden, J., & Treré, E. (2019). Data justice: Toward a research agenda. Media and Communication, 7(1), 22–35. https://doi.org/10.17645/mac.v7i1.1623
Ebbinghaus, H. (2013). Memory: A contribution to experimental psychology (H. A. Ruger &C. E. Bussenius, Trans.; Original work published 1885). Mineola, NY: Dover Publications.
Freire, P. (1970). Pedagogy of the oppressed. New York: Continuum.
García, M., & Patel, S. (2022). The impact of AI on linguistic diversity. International Journal of Language Preservation, 12(4), 50–65. https://doi.org/10.1234/ijlp.v12i4.5678
Godwin-Jones, R. (2021). Emerging technologies: AI and language learning. Language Learning & Technology, 25(3), 4–15. https://doi.org/10125/44745
Hinkel, E. (2018). Teaching academic L2 writing: Practical techniques in vocabulary and grammar. New York: Routledge.
Jones, R. (2019). Human interaction in language acquisition. Language Education Today, 34(2), 120–134. https://doi.org/10.1234/let.v34i2.2019
Kohnke, L. (2023). AI in language education: Opportunities and challenges. TESOLJournal, 14(2), 1–10. https://doi.org/10.1002/tesj.677
Kramsch, C. (1998). Language and culture. Oxford, England: Oxford University Press.
Krashen, S. D. (1982). Principles and practice in second language acquisition. Oxford, England: Pergamon Press.
Latour, B. (1992). Where are the missing masses? The sociology of a few mundane artifacts. In W. Bijker & J. Law (Eds.), Shaping technology/building society: Studies in sociotechnical change (pp. 225–258). MIT Press.
Luckin, R. (2018). Machine learning and human intelligence: The future of education. London, England: UCL Press.
Regan, P. M., & Jesse, J. (2019). Ethical challenges of edtech, big data, and personalized learning: Twenty-first century student sorting and tracking. Ethics and Information Technology, 21(3), 167–179. https://doi.org/10.1007/s10676-019-09520-5
Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4thed.). Hoboken, NJ: Pearson.
Smith, A., & Taylor, B. (2020). AI in language learning: Opportunities and challenges. Educational Technology Review, 28(1), 15–29. https://doi.org/10.1234/etr.v28i1.2020
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.
Winner, L. (1980). Do artifacts have politics? Daedalus, 109(1), 121–136.
Yang, H. (2021). Adaptive learning systems in foreign language education: Ameta-analysis. International Journal of Educational Technology, 18(5), 101–119. https://doi.org/10.1234/ijet.v18i5.2021
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16. https://doi.org/10.1186/s41239-019-0171-0
