The Role of Deep Learning in Intelligent Assistance for Second Language Learners
DOI:
https://doi.org/10.54097/snmqay54Keywords:
Deep Learning, SLA, Intelligent Tutoring SystemsAbstract
The advent of Artificial Intelligence (AI) is instigating substantial changes in educational paradigms. Its incorporation into SLA provides a tailored, effective, and wholly novel educational experience. AI technologies, including adaptive learning systems, intelligent tutoring systems, and natural language processing tools, are transforming conventional SLA by offering customized instruction and immediate feedback. Within deep learning frameworks, AI can proficiently distinguish student behaviors in the classroom, systematically gather and analyze data, and assist educators in comprehending learner performance in SLA environments. This, consequently, enables more informed pedagogical judgments and enhances teaching efficiency. Conventional language education predominantly relies on teachers and textbooks, with instructors acting as the principal source of information. In SLA situations, educators frequently bear the weight of comprehensive explanation and instruction, sometimes constraining learners’ options for practical language application. This may lead to a passive learning environment, markedly diminishing student participation, initiative, and drive. In contrast, deep learning frameworks enable personalized learning models and adaptive systems to efficiently address individual learner requirements, accommodate distinct learning styles, and adjust to diverse learning speeds. These technologies offer substantial assistance for SLA, markedly improving learning outcomes. Moreover, the integration of AI with gamification in blended learning settings has demonstrated an enhancement in student motivation and engagement, thereby leading to improved outcomes in SLA.
Downloads
References
[1] Alhijaj, J.A. and Khudeyer, R.S., 2023. Techniques and applications for deep learning: A review. Journal of Al-Qadisiyah for Computer Science and Mathematics, 15(2), p.114.
[2] Assogba, Y., Pearce, A. and Elliott, M., 2023. Large scale qualitative evaluation of generative image model outputs. arXiv preprint arXiv:2301.04518.
[3] Becker, G.S. and Lewis, H.G., 1973. On the interaction between the quantity and quality of children. Journal of Political Economy, 81(2, Part 2), pp.S279-S288.
[4] Betal, A., 2023. Enhancing second language acquisition through artificial intelligence (AI): Current insights and future directions. Journal for Research Scholars and Professionals of English Language Teaching, 7, p.39.
[5] Braun, V. and Clarke, V., 2006. Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), pp.77-101.
[6] Brinkmann, S., 2014. Unstructured and semi-structured interviewing. In: P. Leavy, ed. The Oxford Handbook of Qualitative Research. 2nd ed. Oxford: Oxford University Press, pp.277-299.
[7] Cao, Y. and Sun, Y., 2024. The Research on the Application of Deep Learning in Education. IETI Transactions on Data Analysis and Forecasting, 2(3), pp.4-11.
[8] Chapelle, C.A., 2005. Computer-assisted language learning. In: Handbook of Research in Second Language Teaching and Learning. Routledge, pp.743-755.
[9] Cloete, F., 2007. Data analysis in qualitative public administration and management research. Journal of Public Administration, 42(6), pp.512-527.
[10] Curry, L.A., Nembhard, I.M. and Bradley, E.H., 2009. Qualitative and mixed methods provide unique contributions to outcomes research. Circulation, 119(10), pp.1442-1452.
[11] Eslit, E.R., 2023. Elevating language acquisition through deep learning and meaningful pedagogy in an AI-evolving educational landscape. Preprints.org.
[12] Greeni, A., Chitkara, P., Pathak, P., Orosoo, M., Rengarajan, M. and Bala, B.K., 2024, July. Advancing Adaptive Assessment in English Language Teaching: A Deep Learning-based Approach within Intelligent Tutoring Systems. In: 2024 Third International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT), pp.1-7. IEEE.
[13] Heift, T. and Chapelle, C.A., 2013. Language learning through technology. In: The Routledge Handbook of Second Language Acquisition, pp.555-569. Routledge.
[14] Hernández-Blanco, A., Herrera-Flores, B., Tomás, D. and Navarro-Colorado, B., 2019. A systematic review of deep learning approaches to educational data mining. Complexity, 2019(1), p.1306039.
[15] Kallio, H., Pietilä, A.M., Johnson, M. and Kangasniemi, M., 2016. Systematic methodological review: Developing a framework for a qualitative semi-structured interview guide. Journal of Advanced Nursing, 72(12), pp.2954-2965.
[16] Koceva, V., 2017. Krashen’s theory of second language acquisition. Knowledge International Journal, 22(6), pp.1507-1514.
[17] Kukulska-Hulme, A. and Lee, H., 2020. Intelligent assistants in language learning: An analysis of features and limitations.
[18] Lacey, A. and Luff, D., 2001. Qualitative data analysis. Trent Focus Group, pp.320-357.
[19] Lee, J., Huang, J.X., Cho, M., Roh, Y.H., Kwon, O.W. and Lee, Y., 2024, June. Developing Conversational Intelligent Tutoring for Speaking Skills in Second Language Learning. In: International Conference on Intelligent Tutoring Systems, pp.131-148. Cham: Springer Nature Switzerland.
[20] Leech, N.L. and Onwuegbuzie, A.J., 2008. A typology of mixed methods research designs.
[21] Mokhtar, F.A., 2016. Rethinking conventional teaching in language learning and proposing Edmodo as intervention: A qualitative analysis. Malaysian Online Journal of Educational Technology (MOJET), 4(2), pp.22-37.
[22] Oba, M., Kuribayashi, T., Ouchi, H. and Watanabe, T., 2023. Second language acquisition of neural language models. arXiv preprint arXiv:2306.02920.
[23] Rost, M., 2014. Listening in a multilingual world: The challenges of second language (L2) listening. International Journal of Listening, 28(3), pp.131-148.
[24] Sale, J.E., Lohfeld, L.H. and Brazil, K., 2002. Revisiting the quantitative-qualitative debate: Implications for mixed-methods research. Quality and Quantity, 36, pp.43-53.
[25] Samarajeewa, C. and Mohammed, L.A., 2025. Obstacles in second language acquisition: Linguistic, psychological, social, cultural, and pedagogical challenges with a focus on secondary ESL Education in Sri Lanka.
[26] Shafiabady, A. and Abdullah, S.M., 2018, November. Qualitative Evaluation on Software Maintainability Prediction Models. In 2018 IEEE Student Conference on Research and Development (SCOReD) (pp. 1-6). IEEE.
[27] Sgier, L., 2012. Qualitative data analysis. An Initiat. Gebert Ruf Stift, 19, pp.19-21.
[28] Son, J.B., Ružić, N.K. and Philpott, A., 2023. Artificial intelligence technologies and applications for language learning and teaching. Journal of China Computer-Assisted Language Learning, (0).
[29] Soomro, B.A. and Shah, N., 2022. Entrepreneurship education, entrepreneurial self-efficacy, need for achievement and entrepreneurial intention among commerce students in Pakistan. Education+ Training, 64(1), pp.107-125.
[30] Tafazoli, D. and Golshan, N., 2014. Review of computer-assisted language learning: History, merits & barriers. International Journal of Language and Linguistics, 2(5), pp.32-38.
[31] Tafazoli, D., Huertas-Abril, C.A. and Gomez-Parra, M.E., 2019. Technology-based review on Computer-Assisted Language Learning: A chronological perspective. Píxel-Bit. Revista de Medios y Educación, (54), pp.29-43.
[32] Torfi, A., Shirvani, R.A., Keneshloo, Y., Tavaf, N. and Fox, E.A., 2020. Natural language processing advancements by deep learning: A survey. arXiv preprint arXiv:2003.01200.
[33] Ulfa, K., 2023. The transformative power of artificial intelligence (AI) to elevate English language learning. Majalah Ilmiah METHODA, 13(3), pp.307-313.
[34] Wu, Z., Saad, M.R.M. and Halim, H.A., 2024. Self-Determination Theory in Blended Learning: Fostering Motivation and Language Outcomes in Primary EFL Learners. International Journal of Advanced Research in Education and Society, 6(4), pp.247-259.
[35] Xiong, L., Teng, C.L., Li, Y.Q., Lee, Y.Z., Zhu, B.W. and Liu, K., 2019. A qualitative-quantitative evaluation model for systematical improving the creativity of students’ design scheme. Sustainability, 11(10), p.2792.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 International Journal of Education and Humanities

This work is licensed under a Creative Commons Attribution 4.0 International License.







