Video Education through the Lens of Educational Neuroscience: A Concise Review
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11528-024-00946-1.pdf
Reference129 articles.
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2. Alimardani, M., van den Braak, S., Jouen, A., Matsunaka, R., & Hiraki, K. (2021). Assessment of Engagement and Learning During Child-Robot Interaction Using EEG Signals. In H. Li, S. S. Ge, Y. Wu, A. Wykowska, H. He, X. Liu, D. Li, & J. Perez-Osorio (Eds.), Social Robotics. ICSR 2021. Lecture Notes in Computer Science (pp. 671–682). Springer International Publishing. https://doi.org/10.1007/978-3-030-90525-5_59
3. Balters, S., Baker, J. M., Hawthorne, G., & Reiss, A. L. (2020). Capturing Human Interaction in the Virtual Age: A Perspective on the Future of fNIRS Hyperscanning. Frontiers in Human Neuroscience, 14, 558494. https://doi.org/10.3389/fnhum.2020.588494
4. Bevilacqua, D., Davidesco, I., Wan, L., Chaloner, K., Rowland, J., Ding, M., Poeppel, D., & Dikker, S. (2019). Brain-to-brain synchrony and learning outcomes vary by student–teacher dynamics: Evidence from a real-world classroom electroencephalography study. Journal of Cognitive Neuroscience, 31(3), 401–411. https://doi.org/10.1162/jocn_a_01274
5. Biard, N., Cojean, S., & Jamet, E. (2018). Effects of segmentation and pacing on procedural learning by video. Computers in Human Behavior, 89, 411–417. https://doi.org/10.1016/j.chb.2017.12.002
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