Abstract
The Smart e-Learning System (SeLS) should be designed and developed as a smart student-centered biotechnical system with certain features of smart systems (sensing, transmission, big data processing, activation of actuators) and levels of “smartness” (adaptation, sensing, inferring, learning, anticipation, self-organization). In order to provide higher efficiency of learning process in general, and, SeLS, in particular, SeLS should use multiple parameters of student psychophysiological state.
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References
Yau, S., Guppta, S., et al.: Smart classroom: enhancing collaborative learning using pervasive computing technology. In: Proceedings of the 2003 ASEE Annual Conference and Exposition, Nashville, TN, 23–25 June 2003
O’Driscoll, C., Mithileash, et al.: Deploying a context aware smart classroom. In: International Technology, Education and Development Conference INTED (2008)
Yue Suo, Y., Miyata, N., et al.: Open smart classroom: extensible and scalable learning system in smart space using Web service technology. IEEE Trans. Knowl. Data Eng. 21(6), 814–828 (2009)
Shi, Y., Xie, W., et al.: The smart classroom: merging technologies for seamless tele-education. Pervasive Comput. 2(2), 45–55 (2003). IEEE
Das, S.K., Cook, D.J.: Designing and modeling smart environments. In: World of Wireless. Mobile and Multimedia Networks, WoWMoM (2006)
Akhras, G.: Smart materials and smart systems for the future. Can. Mil. J. http://www.revue.forces.gc.ca/vo1/no3/doc/25-32-eng.pdf
Derzko, W.: Smart Technologies (2006). http://archives.ocediscovery.com/discovery2007/presentations/Session3WalterDrezkoFINAL.pdf
Lisitsyna, L., Lyamin, A., Skshidlevsky, A.: Estimation of student functional state in learning management system by heart rate variability method. In: Proceedings of the First International Conference on Smart Technology Based Education and Training, Crete, Greece, June 2014
Maraes, V., Carreiro, D., Barbosa, N.: Study of heart rate variability of university trained at rest and exercise. In: 2013 Pan American Health Care Exchanges (PAHCE), Medellin (2013)
Karthikeyan, P., Murugappan, M., Yaacob, S.: A study on mental arithmetic task based human stress level classification using discrete wavelet transform. In: Proceedings of the 2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT), Kuala Lumpur, pp. 77–81, October 2012
Wu, W., Lee, J.: Improvement of HRV methodology for positive/negative emotion assessment. In: Proceedings of the 5th International Conference on Collaborative Computing: Networking, Applications and Worksharing, Washington, DC, 11–14 Nov 2009
Uskov, V., Uskova, M.: Reusable learning objects approach to web-based education. In: Proceedings of the 5th International Conference on Computers and Advanced Technology in Education CATE-2002, Cancun, Mexico, 20–22 May, pp. 165–170 (2002)
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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Uskov, V., Lyamin, A., Lisitsyna, L., Sekar, B. (2014). Smart e-Learning as a Student-Centered Biotechnical System. In: Vincenti, G., Bucciero, A., Vaz de Carvalho, C. (eds) E-Learning, E-Education, and Online Training. eLEOT 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 138. Springer, Cham. https://doi.org/10.1007/978-3-319-13293-8_21
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DOI: https://doi.org/10.1007/978-3-319-13293-8_21
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