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Training Elementary Teachers in Vietnam by Blended Learning Model

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Proceedings of 3rd International Conference on Mathematical Modeling and Computational Science (ICMMCS 2023)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1450))

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Abstract

This study focuses on determining the ratio between face-to-face learning and online learning and points out the main factors affecting the training process of primary school teachers in Vietnam according to the teaching model combined blended learning. The authors conducted a survey using a questionnaire and conducted in-depth interviews with lecturers who are teaching at universities that train primary school teachers in many provinces and cities across the country. The results show that the views on the ratio between face-to-face and online learning in training units are different. Many lecturers believe that face-to-face teaching is favorable for training professional skills for primary school teachers, so the online learning should be limited in the training process. However, some lecturers believe that information technology is becoming increasingly important in education. Therefore, blended learning is an inevitable trend in teacher training. When discussing the factors affecting the teaching process by blended learning model, most of the lecturers think that technological factors and the skills of teachers and learners in using information technology are important roles. Finally, the study shows the most suitable ratio between face-to-face and online learning to make the process of training primary teachers under the blended teaching model more effective and, at the same time, offers a few suggestions to help lecturers improve the effectiveness of the blended learning process.

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Correspondence to Tiep Quang Pham .

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Pham, T.Q., Dang, T.M., Van Nguyen, H., Nguyen, H.T. (2023). Training Elementary Teachers in Vietnam by Blended Learning Model. In: Peng, SL., Jhanjhi, N.Z., Pal, S., Amsaad, F. (eds) Proceedings of 3rd International Conference on Mathematical Modeling and Computational Science. ICMMCS 2023. Advances in Intelligent Systems and Computing, vol 1450. Springer, Singapore. https://doi.org/10.1007/978-981-99-3611-3_18

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