Abstract
This article deals with the methods of classifying communicative competence. Finding effective ways to evaluate the level of intending primary school teachers’ foreign language communicative competence is becoming increasingly relevant today, as objectifying the measurement process through feedback provides an opportunity to coordinate the developing that competence components (motivational, cognitive, communicatively active, reflexive) and further improving the students’ levels of foreign language communicative competence.
In order to effectively evaluate developing the foreign language communicative competence, it is necessary to focus not only on explicitly expressed, but also on implicitly expressed traits and qualities of an intending professional. It means that the assessment, in addition to traditional parameters, should determine those personal qualities that are hidden for direct observation and which are only indirectly manifested in the professionally oriented communicative activity of the individual.
All above mentioned information necessitate the development of a special assessment scale, the creation of which is objectively difficult due to the complexity of identifying and describing implicit parameters of professionally relevant components of communicative competence. During this process it is important to use the more sophisticated mathematical methods and information technologies.
The minimax classifications, method of k-means, Bayesian classification are proposed with the aim to assess the levels of students’ (intending primary school teachers’) foreign language communicative competence. Students’ ratings were determined by the hierarchy analysis method. Decision-making procedures are used to select one of two or four possible options.
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Pashko, A., Pinchuk, I. (2021). Methods of Classifying Foreign Language Communicative Competence Using the Example of Intending Primary School Teachers. In: Babichev, S., Lytvynenko, V., Wójcik, W., Vyshemyrskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2020. Advances in Intelligent Systems and Computing, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-54215-3_7
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