Abstract
Learning activities using technologies is one of the common education methods. Its advantages allow that students can learn with concepts more practical’s. However in this environment not all the students can be attentive. In this research an Ambient Intelligent System has been designed using biometrics behaviors for detecting learner inattentiveness. The learning attentiveness of a student can be determined precisely and the teacher has access to these results and might improve news strategies.
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
References
Carroll, J.M.: Human-computer interaction: psychology as a science of design. Annu. Rev. Psychol. 48, 61–83 (1997). doi:10.1146/annurev.psych.48.1.61
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)
Durães, D., Jiménez, A., Bajo, J., Novais, P.: Monitoring level attention approach in learning activities. Adv. Intell. Syst. Comput. 478, 33–40 (2016). doi:10.1007/978-3-319-40165-2_4
McNeely, B.: Using Technology as a Learning Tool, Not Just the Cool New Thing. Educating the Net Generation, pp. 4.1–4.10 (2005)
Muir-Herzig, R.: Technology and Its Impact in the Classroom (2003). doi:10.1016/S0360-1315(03)00067-8
Weber, W., Rabaey, J.M., Aarts, E.: Ambient Intelligence, pp. 1–2. Springer (2005)
Neto, W. B., Gauthier, F., Nassar, S.M.: An adaptive e-Learning model for the semantic web. In: International Workshop on Applications of Semantic Web technologies for E-Learning, pp. 63–64. Banff, Canada (2005)
Khan, F.A., Grap, S., Weippl, E.R., Tjoa, A.M.: Identifying and incorporating affective sate and learning styles in web-based learning management systems. Interact. Des. Archit. (s) J.—IXD&A 9–10, 85–103 (2010)
Durães, D., Carneiro, D., Bajo, J., Novais, P.: Using computer peripheral devices to measure attentiveness. Adv. Intell. Syst. Comput. 147–155 (2016)
Acknowledgements
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Durães, D., Castro, D., Bajo, J., Novais, P. (2017). Modelling an Intelligent Interaction System for Increasing the Level of Attention. In: De Paz, J., Julián, V., Villarrubia, G., Marreiros, G., Novais, P. (eds) Ambient Intelligence– Software and Applications – 8th International Symposium on Ambient Intelligence (ISAmI 2017). ISAmI 2017. Advances in Intelligent Systems and Computing, vol 615. Springer, Cham. https://doi.org/10.1007/978-3-319-61118-1_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-61118-1_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-61117-4
Online ISBN: 978-3-319-61118-1
eBook Packages: EngineeringEngineering (R0)