Abstract
In the current world, performance is one of the most important issues concerning work and competition. Performance is strongly connected with learning and when it comes to acquiring new knowledge, attention is one the most important mechanisms as the level of the learner’s attention affects learning results. When students are doing learning activities using new technologies, it is extremely important that the teacher has some feedback from the students’ work in order to detect potential learning problems at an early stage. The goal of this research is to propose a system that measures the level of attentiveness in real scenarios, and detects patterns of behavior associated to different attention levels among different students. This system measures attention and uses this information for training a decision support system that shows the level of attention of a group of students in real time.
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References
Carroll, J.M.: Human-computer interaction: psychology as a science of design. Ann. Rev. Psychol. 48, 61–83 (1997). doi:10.1146/annurev.psych.48.1.61
Clark, R.E.: The transfer of technology between nations. Interaction 1(3), 185–203 (1983)
Milrad, M., Wong, L.H., Sharples, M., Hwang, G.-J., Looi, C.–.K., Ogata, H.: Seamless learning: an international perspective on next generation technology enhanced learning. In: Berge, Z.L., Muilenburg, L.Y. (eds.) Handbook of Mobile Learning, pp. 95–108. Routledge, New York (2013)
Pimenta, A., Gonçalves, S., Carneiro, D., Riverola, F., Novais, P.: Mental Workload Management as a Tool in e-Learning Scenarios (2014)
Hwang, K., Yang, C.: Automated inattention and fatigue detection system in distance education for elementary school students. J. Educ. Technol. 12, 22–35 (2009)
Mancas, M.: Computational Attention – Toward Attentive Computers. Press Universitaire de Louvain, Louvain-la-Neuve (2007)
James, W.: Principles of Psychology, vol. 1, pp. 255–260. Dover Publications Inc., New York (1890)
Durães, D., Carneiro, D., Bajo, J., Novais, P.: Using computer peripheral devices to measure attentiveness. In: Advances in Intelligent System and Computing, pp. 147–155 (2016)
Acknowledgment
This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.
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Durães, D., Gonçalves, S., Carneiro, D., Bajo, J., Novais, P. (2017). Detection of Behavioral Patterns for Increasing Attentiveness Level. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_58
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DOI: https://doi.org/10.1007/978-3-319-53480-0_58
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