Policy Innovations in Language Education: Leveraging Digital Technologies for Personalized Learning Experiences
DOI:
https://doi.org/10.52152/3130Ključne besede:
personalized learning; visual analytics; CiteSpace; knowledge graphsPovzetek
In the context of digital transformation, the increasingly mature digital technology has accelerated the change of education and learning mode. As an important means of cultivating talents, personalized learning, empowered by digital technology, is highly compatible with the requirements of the strategy of “developing the country through science and education” and the goal of digital transformation of education. The study takes 1,651 documents included in the CNKI database from 1999 to 2024 as the research samples, and with the help of the visual analysis software CiteSpace, analyzes them in terms of keyword co-occurrence, core authors, and research institutes, and draws out the related knowledge maps. The study outlines the overall evolution of personalized learning under the collaboration of digital technology, and reveals the specific mechanism of digital technology to promote personalized learning experience. The study finds that personalized learning research in China has experienced three stages of slow development (1999-2009), rapid development (2010-2018), and stable development (2018-present). The process of digital technology for personalized learning experience mainly involves six aspects: educational concept, learning resource recommendation, openness and flexibility, personalization and customization, intelligent assessment and feedback, and outcome visualization. The latest frontiers of future research include the application of digital technologies such as artificial intelligence and smart education in personalized learning in language education.
Literatura
Chen, X., Zou, D., Xie, H., & Cheng, G. (2021). Twenty years of personalized language learning. Educational Technology & Society, 24(1), 205-222.
Lai, C., & Zheng, D. (2018). Self-directed use of mobile devices for language learning beyond the classroom. ReCALL, 30(3), 299-318.
Walkington, C., & Bernacki, M. L. (2020). Appraising research on personalized learning: Definitions, theoretical alignment, advancements, and future directions. Journal of research on technology in education, 52(3), 235-252.
Zhang, L., Basham, J. D., & Yang, S. (2020). Understanding the implementation of personalized learning: A research synthesis. Educational research review, 31, 100339.
Yeşildağ, C., & Sadik, O. (2021). Applying the personalization principle of multimedia learning theory in second language listening classes. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 22(2), 1036-1070.
Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning—Are they really useful? A systematic review of chatbot‐supported language learning. Journal of Computer Assisted Learning, 38(1), 237-257.
Li, X., & Zhang, B. (2024). Personalized Learning Path Recommendation Algorithm for English Listening Learning. Journal of Electrical Systems, 20(6s), 2188-2199.
Wyatt, S., & Redmon, M. (2022). Personalized adaptive learning technology: Supercharging second language learning. In ICERI2022 Proceedings (pp. 3744-3748). IATED.
Pardo, A., Bartimote, K., Shum, S. B., Dawson, S., Gao, J., Gašević, D., ... & Vigentini, L. (2018). Ontask: Delivering data-informed, personalized learning support actions. Journal of Learning Analytics, 5(3), 235-249.
Pérez-Paredes, P., Ordoñana Guillamón, C., & Aguado Jiménez, P. (2018). Language teachers’ perceptions on the use of OER language processing technologies in MALL. Computer Assisted Language Learning, 31(5-6), 522-545.
Huang, X., Zou, D., Cheng, G., Chen, X., & Xie, H. (2023). Trends, research issues and applications of artificial intelligence in language education. Educational Technology & Society, 26(1), 112-131.
Park, M., Kim, S., Lee, S., Kwon, S., & Kim, K. (2024, May). Empowering personalized learning through a conversation-based tutoring system with student modeling. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-10).
Ma, Q. (2017). A multi-case study of university students’ language-learning experience mediated by mobile technologies: A socio-cultural perspective. Computer assisted language learning, 30(3-4), 183-203.
Cattelan, R. G., Araújo, R. D., Ferreira, H. N., Brant-Ribeiro, T., & Dorça, F. A. (2024). Classroom eXperience: from automated multimedia capture to personalized learning. Multimedia Tools and Applications, 1-37.
Boninger, F., Molnar, A., & Saldaña, C. M. (2019). Personalized Learning and the Digital Privatization of Curriculum and Teaching. National Education Policy Center.
Shemshack, A., & Spector, J. M. (2020). A systematic literature review of personalized learning terms. Smart Learning Environments, 7(1), 33.
Maheswara, A., & Rifai, I. (2023). To Learn, Unlearn, and Relearn with Personalized Language Learning and Educational Technology. In E3S Web of Conferences (Vol. 388, p. 04029). EDP Sciences.
Karoui, A., Alvarez, L., Goffre, T., Dherbey Chapuis, N., Rodi, M., & Ramalho, M. (2021, June). Adaptive pathways within the european platform for personalized language learning PEAPL. In Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (pp. 90-94).
Ovezova, G. (2024). PERSONALIZED LEARNING PATHS, INTELLIGENT TUTORING SYSTEMS, AND ADAPTIVE LANGUAGE ASSESSMENT: A SYNERGISTIC APPROACH. Вестник науки.
Yeung, C. Y., & Lee, J. S. (2018, August). Personalized text retrieval for learners of chinese as a foreign language. In Proceedings of the 27th international conference on computational linguistics (pp. 3448-3455).
Chen, X., Zou, D., Cheng, G., & Xie, H. (2021, July). Artificial intelligence-assisted personalized language learning: systematic review and co-citation analysis. In 2021 international conference on advanced learning technologies (ICALT) (pp. 241-245). IEEE.
Dong, W., Pan, D., & Kim, S. (2024). Exploring the integration of IoT and Generative AI in English language education: Smart tools for personalized learning experiences. Journal of Computational Science, 82, 102397.
Barrot, J. S. (2024). ChatGPT as a language learning tool: An emerging technology report. Technology, Knowledge and Learning, 29(2), 1151-1156.
Dhananjaya, G. M., Goudar, R. H., Govindaraja, K., Kaliwal, R. B., Rathod, V. K., Deshpande, S. L., ... & Hukkeri, G. S. (2024). Enhancing Education with ChatGPT: Revolutionizing Personalized Learning and Teacher Support. EAI Endorsed Transactions on Internet of Things, 10.
Thanyaluck Ingkavara,Wararat Wongkia & Patcharin Panjaburee. (2023). Trends of Adaptive/Personalized Learning and Intelligent Tutoring Systems in Mathematics: A Review of Academic Publications from 2010 to 2022 .Engineering Proceedings(1),34-.
Hongyu Mai & Xiaoying Li .(2024). Design of an AI-based Personalized English Self-learning System. Journal of Higher Education Teaching(5).
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Avtorske pravice (c) 2025 Lex localis - Journal of Local Self-Government
To delo je licencirano pod Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 mednarodno licenco.
