Abstract
The demand for distance learning is increasing due to the recent expansion of the COVID-19 pandemic. In distance learning, less communication level has been pointed out that it would reduce student’s concentration level in the study. However, these were subjective evaluations based on questionnaires, therefore, there was a lack of criteria to evaluate this problem. In this work, we propose a method to objectively evaluate distance learning using the biometric information to understand the difference of the student’s concentration level during the study. We measure the student’s electroencephalography (EEG) and heart rate variability (HRV) to evaluate the change of student’s emotion based on different communication condition during distance learning. In the experiment, we measured EEG and HRV of the students, while turning on and off face-to-face video camera. The analysis of results show that different communication condition effect student’s concentration level. We found that it could be due to their preferences of the subject.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
The Third Basic Plan for the Promotion of Education of the Ministry of Education, Culture, Sports, Science and Technology. Decided by the Cabinet in June 2018 [Translated from Japanese]. https://www.mext.go.jp/content/1406127_002.pdf
Ministry of Education, Culture, Sports, Science and Technology. Policy for the Promotion of Distance Education [Translated from Japanese] https://www.mext.go.jp/a_menu/shotou/zyouhou/detail/__icsFiles/afieldfile/2018/09/14/1409323_1_1.pdf
Tagami, H.: Necessity of eyes correspondence in remote teaching and a solution of the problem. J. JSiSE 25(4), 394–402 (2008)
Croft, N., Dalton, A., Grant, M.: Overcoming isolation in distance learning: building a learning community through time and space. J. Educ. Built Environ. 5(1), 27–64 (2010)
Kudo, N., et al.: Building interaction support system for participants in the Internet based distance class. In: Internet Conference, pp. 97–104 (2003)
Taura, K.: Introduction of questionnaire results regarding online classes (2020) [Translated from Japanese]. https://www.nii.ac.jp/event/upload/20200904-06_Taura.pdf
Ohkura, M., et al.: Measurement of Wakuwaku feeling of interactive systems using biological signals. In: Fukuda, S. (ed.) Emotional Engineering, pp. 327–342. Springer, London (2011)
Sakamoto, Y., et al.: Comparative analysis of state thinking by learning a simple electroencephalograph. In: Multimedia, Distributed, Collaborative and Mobile (DICOMO2012) Symposium, pp. 724–729 (2012)
Urabe, N., Sugaya. M.: An emotion classification method for individuals using EEG and heart rate data and deep learning. In: Proceedings of the Annual Conference of JSAI, vol. JSAI2020, 34th Annual Conference, J2F6GS1302–2F6GS1302 (2020)
Ohnishi, T., et al.: Development of a remote consultation system using avatar technology. EEJ Trans. Electr. Inf. Syst. 129(7), 1408–1415 (2009)
Shiraiwa, G., Sugaya. M.: Verification of learning motivation, improvement by voice of robot -quantitative evaluation by EEG analysis [Transrated from Japanese]. IEICE Technical Report, pp. 1–6. 119, 446, CNR2019–45 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Nakagawa, Y., Sripian, P., Sugaya, M. (2021). Evaluation of Distance Learning Effects on Concentration and Relaxed States by EEG and HRV. In: Nazir, S., Ahram, T.Z., Karwowski, W. (eds) Advances in Human Factors in Training, Education, and Learning Sciences. AHFE 2021. Lecture Notes in Networks and Systems, vol 269. Springer, Cham. https://doi.org/10.1007/978-3-030-80000-0_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-80000-0_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-79999-1
Online ISBN: 978-3-030-80000-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)