Open AccessExploration of learning styles by applying data mining technologies
Author(s) -
Danutė Kaklauskienė,
Sigita Turskienė
Publication year - 2014
Publication title -
lietuvos matematikos rinkinys
Language(s) - English
Resource type - Journals
eISSN - 2335-898X
pISSN - 0132-2818
DOI - 10.15388/lmr.b.2014.08
Subject(s) - personalization , learning styles , computer science , set (abstract data type) , style (visual arts) , data set , distance education , machine learning , data science , data mining , artificial intelligence , mathematics education , world wide web , psychology , archaeology , programming language , history
The article deals with the possibilities to estimate students’ learning styles by applying data mining technologies and the methods suggested by the VARK learning styles model. Using the method of communication, the VARK learning style model in a chosen respondents’ set was estimated. This enables to formulate recommendations for an author of a distance learning course concerning possibilities of personalisation of a particular distance learning course. The concept-baseddata model was chosen to model the research data. The data of the designed e-test data base was processed by applying five stages of data mining.