Abstract
It is already commonly accepted, that blended learning seems to be one of the modern and promising approaches to teaching and learning. Blended learning aims to integrate traditional learning with innovative means, such as e-learning, analytics, game-based learning, and open educational resources, in order to create a new learning environment aiming to enhance learning effectiveness, and enrich learning experience. In the meantime, as one important and applicable output of the smart environments research, the concept of smart learning environments has evolved with a number of successful applications. The aim of this paper is to argue, that blended learning concept can be viewed as a promising perspective for affective learning strategies inclusion into recently more and more popular smart learning environments.
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Ducatel, K., Bogdanowicz, M., Scapolo, F., Leijten, J., Burgelman, J.C.: Scenarios for ambient intelligence 2010. Institute for Prospective Technological Studies, Seville, November 2001 (2001). ftp://ftp.cordis.lu/pub/ist/docs/istagscenarios2010.pdf
Mikulecký, P.: Smart environments for smart learning. In: DIVAI 2012 (2012)
Bureš, V., Tučník, P., Mikulecký, P., Mls, K., Blecha, P.: Application of ambient intelligence in educational institutions: visions and architectures. Int. J. Ambient Comput. Intell. (IJACI) 7(1), 94–120 (2016)
Kinshuk, Chen, N.S., Cheng, I.L., Chew, S.W.: Evolution is not enough: revolutionizing current learning environments to smart learning environments. Int. J. Artif. Intell. Educ. 26(2) 561–581 (2016)
Koper, R.: Conditions for effective smart learning environments. Smart Learn. Environ. 1(1), 5 (2014)
Hwang, G.J.: Definition, framework and research issues of smart learning environments: a context-aware ubiquitous learning perspective. Smart Learn. Environ. 1(1), 1–14 (2014)
Libbrecht, P., Müller, W., Rebholz, S.: Smart learner support through semi-automatic feedback. In: Chang, M., Li, Y. (eds.) Smart Learning Environments. LNET, pp. 129–157. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-44447-4_8
Spector, J.M.: Conceptualizing the emerging field of smart learning environments. Smart Learn. Environ. 1(1), 1–10 (2014)
Picard, R.W., Papert, S., Bender, W., Blumberg, B., Breazeal, C., Cavallo, D., Machover, T., Resnick, M., Roy, D., Strohecker, C.: Affective learning: a manifesto. BT Technol. J. 22(4), 253–269 (2004)
Minsky, M.: The emotion machine: commonsense thinking, artificial intelligence, and the future of the human mind. Simon and Schuster (2007)
Daradoumis, T., Arguedas, M., Xhafa, F.: Current trends in emotional e-learning: new perspectives for enhancing emotional intelligence. In: 2013 Seventh International Conference on Complex, Intelligent, and Software Intensive Systems, pp. 34–39. IEEE (2013)
Cabada, R.Z., Estrada, M.L.B., Hernández, F.G., Bustillos, R.O., Reyes-García, C.A.: An affective and web 3.0-based learning environment for a programming language. Telematics Inform. 35(3) 611–628 (2018)
Wiggins, J.B., et al.: JavaTutor: an intelligent tutoring system that adapts to cognitive and affective states during computer programming. In: Proceedings of the 46th ACM Technical Symposium on Computer Science Education, p. 599. ACM (2015)
Mikulecky, P.: User adaptivity in smart workplaces. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ACIIDS 2012. LNCS (LNAI), vol. 7197, pp. 401–410. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28490-8_42
Mikulecký, P.: Smart learning environments - a multi-agent architecture proposal. In: DIVAI 2014, 10th International Scientific Conference on Distance Learning in Applied Informatics. Wolters Kluwer (2014)
Ma’arop, A.H., Embi, M.A.: Implementation of blended learning in higher learning institutions: a review of the literature. Int. Educ. Stud. 9(3), 41–52 (2016)
Arguedas, M., Daradoumis, T., Xhafa, F.: Analyzing the effects of emotion management on time and self-management in computer-based learning. Comput. Hum. Behav. 63, 517–529 (2016)
Acknowledgment
The research has been partially supported by the Faculty of Informatics and Management UHK specific research project 2107 Computer Networks for Cloud, Distributed Computing, and Internet of Things II. Thanks goes also to Mr. Martin Kulhanek, a diploma student, for some preparatory help in writing the paper.
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Mikulecky, P. (2019). Blended Learning in Smart Learning Environments. In: Moura Oliveira, P., Novais, P., Reis, L. (eds) Progress in Artificial Intelligence. EPIA 2019. Lecture Notes in Computer Science(), vol 11805. Springer, Cham. https://doi.org/10.1007/978-3-030-30244-3_6
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DOI: https://doi.org/10.1007/978-3-030-30244-3_6
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