Công nghệ low-code/no-code tạo chatbot thông minh: một hướng tiếp cận nâng cao năng lực trí tuệ nhân tạo cho giáo viên tiểu học
Tóm tắt
Digital transformation in education requires the integration of Artificial Intelligence (AI) technology; however, primary school teachers often lack programming skills. Low-code/no-code (LCNC) technology has opened opportunities for teachers to create chatbots that support teaching without requiring specialized programming knowledge. This study proposes a process for creating intelligent chatbots based on LCNC platforms for primary school teachers in Vietnam. Drawing upon the ADDIE model (Analysis, Design, Development, Implementation, Evaluation) and Agile software development philosophy, this paper presents a five-step process: (1) identifying objectives, scope, and constructing chatbot personas; (2) preparing knowledge data sources and selecting AI chatbot creation platforms; (3) designing and configuring; (4) testing and refinement; (5) deployment and evaluation. The paper provides detailed guidance and concrete applications of AI chatbots using Google Gemini for primary school sexuality education. The paper concludes that LCNC technology is not only feasible but sustainable, helping enhance Artificial Intelligence capabilities for primary school teachers in Vietnam.
Tài liệu tham khảo
Abuhassna, H., Alnawajha, S., Awae, F., Adnan, M. A. B. M., & Edwards, B. I. (2024). Synthesizing technology integration within the Addie model for instructional design: A comprehensive systematic literature review. Journal of Autonomous Intelligence, 7(5), 1-28. https://doi.org/10.32629/jai.v7i5.1546
Alfarwan, A. (2025). Generative AI use in K-12 education: a systematic review. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1647573
Chu, S. T., Hwang, G. J., & Tu, Y. F. (2022). Artificial intelligence-based robots in education: A systematic review of selected SSCI publications. Computers and education: Artificial intelligence, 3, 100091. https://doi.org/10.1016/j.caeai.2022.100091
Highsmith, J., Cockburn, A., Cunningham, W., Fowler, M., Beedle, M., Jeffries, R., & Sutherland, J. (2001). Manifesto for Agile Software Development. https://agilemanifesto.org/
How, M.-L. (2021). Artificial Intelligence for Social Good in Responsible Global Citizenship Education: An Inclusive Democratized Low-Code Approach. Proceedings of the 3rd World Conference on Teaching and Education. https://doi.org/10.33422/2nd.worldcte.2021.01.08
Kling, N., Runte, C., Kabiraj, S., Schumann, C. A. (2022). Harnessing Sustainable Development in Image Recognition Through No-Code AI Applications: A Comparative Analysis. International Conference on Recent Trends in Image Processing and Pattern Recognition. Springer. https://doi.org/10.1007/978-3-031-07005-1_14
Sufi, F. (2023). Algorithms in Low-Code-No-Code for Research Applications: A Practical Review. Algorithms, 16(108). https://doi.org/10.3390/a16020108
Sundberg, L., & Holmström, J. (2023). Democratizing artificial intelligence: How no-code AI can leverage machine learning operations. Business Horizons, 66(6), 777-788. https://doi.org/10.1016/j.bushor.2023.04.003
Sundberg, L., & Holmström, J. (2024). Using No-Code AI to Teach Machine Learning in Higher. Journal of Information Systems Education, 35(1), 56-66. https://doi.org/10.62273/CYPL2902
Tlili, A., Saqer, K., Salha, S., & Huang, R. (2025). Investigating the effect of artificial intelligence in education (AIEd) on learning achievement: A meta-analysis and research synthesis. Information Development, 41(3), 825-842. https://doi.org/10.1177/02666669241304407
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