A Novel Design of the Pre-Processing Stage of Data Mining for Educational Purposes

Ahrens Andreas (), Grünwald Norbert (), Zaščerinska Jeļena () and Melnikova Julija ()
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Ahrens Andreas: Hochschule Wismar, Wismar, Germany
Grünwald Norbert: Hochschule Wismar, Wismar, Germany
Zaščerinska Jeļena: Centre for Education and Innovation Research,Riga, Latvia
Melnikova Julija: Klaipeda University,Klaipeda, Lithuania

Balkan Region Conference on Engineering and Business Education, 2019, vol. 1, issue 1, 353-361

Abstract: As data sets, in education too, change in size and structure, an appropriate design of the preprocessing stage of data mining for the implementation of data mining for educational purposes is becoming a hot research topic. The aim of the present research is to carry out interdisciplinary analysis of scientific literature on pre-processing in data mining and to design a pre-processing stage of data mining for educational purposes underpinning elaboration of a new research question. The present research employs both theoretical and empirical methods. Theoretical methods include analysis of scientific literature and theoretical modelling. The theoretical findings allow identifying sub-stages of the pre-processing stage for the implementation of data mining for educational purposes. The empirical study was carried out in 2018. The study was a case study The empirical results emphasize the main areas of analysis of teachers’ behaviour in an international project. The empirical study validates the model of the pre-processing stage of data mining for educational purposes. The practical application of the model allows drawing a conclusion that the model is valid. The novel contribution of this paper is the design of the sub-stages of the preprocessing stage for the implementation of data mining techniques for educational purposes.

Keywords: Data mining; pre-processing stage; data set; teacher behaviour; international project; exploratory research; case study (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:brcebe:v:1:y:2019:i:1:p:353-361:n:42

DOI: 10.2478/cplbu-2020-0042

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