Bridging STEM Education and Ubiquitous Learning: A Case Study on Developing a LINE Chatbot with Google's Gemini for Virtual Peer Collaboration
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-65884-6_25
Reference28 articles.
1. Lee, H.-Y., Chang, W.-C., Huang, Y.-M.: Combining deep learning and computer vision techniques for automatic analysis of the learning process in STEM education. In: Huang, Y.-M., Cheng, S.-C., Barroso, J., Sandnes, F.E. (eds.) Innovative Technologies and Learning: 5th International Conference, ICITL 2022, Virtual Event, August 29–31, 2022, Proceedings, pp. 22–32. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-15273-3_3
2. Wang, W.-S., Lin, C.-J., Lee, H.-Y., Wu, T.-T., Huang, Y.-M.: Feedback mechanism in immersive virtual reality influences physical hands-on task performance and cognitive load. Int. J. Human–Comput. Interact. 1–13 (2023)
3. Lee, H.-Y., Cheng, Y.-P., Wang, W.-S., Lin, C.-J., Huang, Y.-M.: Exploring the learning process and effectiveness of STEM education via learning behavior analysis and the interactive-constructive- active-passive framework. J. Educ. Comput. Res. 61, 951–976 (2023)
4. Kelley, T.R., Knowles, J.G.: A conceptual framework for integrated STEM education. Int. J. STEM Educ. 3, 11 (2016)
5. Lee, H.-Y., Wu, T.-T., Lin, C.-J., Wang, W.-S., Huang, Y.-M.: Integrating computational thinking into scaffolding learning: an innovative approach to enhance science, technology, engineering, and mathematics hands-on learning. J. Educ. Comput. Res. 62, 431–467 (2023)
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