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Automated Monitoring and Forecasting of the Development of Educational Technologies
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Author(s): Ilya Andreyevich Kozlov (Bauman Moscow State Technical University, Russia), Ark M. Andreev (Bauman Moscow State Technical University, Russia), Dmitry Valeryevich Berezkin (Bauman Moscow State Technical University, Russia)and Marwa Ahmed Shouman (Menofiya University, Egypt)
Copyright: 2019
Pages: 20
Source title:
Handbook of Research on Engineering Education in a Global Context
Source Author(s)/Editor(s): Elena V. Smirnova (Bauman Moscow State Technical University, Russia)and Robin P. Clark (University of Warwick, UK)
DOI: 10.4018/978-1-5225-3395-5.ch027
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Abstract
This chapter will describe an approach to monitoring and forecasting the development of innovative educational technologies based on text stream analysis. The approach will involve detecting education-related events in the stream of text documents, constructing situations, determining possible scenarios of further development of situations, and generating recommendations for successful introduction of detected innovations into the educational process of the university. The authors will propose a multicriteria model of an event reflecting its key aspects. The chapter will describe an event detection method based on incremental clustering, as well as a scenario generation method based on the principle of historical analogy. The authors will discuss several experiments to evaluate the quality of the methods.
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