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Analysis of students’ study activities in virtual learning environments using data mining methods

    Saulius Preidys Affiliation
    ; Leonidas Sakalauskas Affiliation

Abstract

This article deals with application of data mining methods’ to analysis of learners’ behaviour using the distance learning platform BlackBoard Vista (BlackBoard 2008). Before planning a distance learning course, instructors have to pay attention to the fact that there exist different study methods: some students start reading learning materials from the very beginning to the end, some students look at unclear topics only, some start with the discussions, etc. Therefore after analyzing the learning factors and identifying learner's style, it is possible to prepare individualized learning materials and to choose a proper way of course presentation. Such a way of study organization would improve the quality of studies and make it possible to reach better results. The research was performed by observing the behaviour and results achieved by 528 students in 15 distance learning courses and, using the clustering method, 3 learner's styles using virtual learning environments (VLE) have been identified and work methods proposed for students with regard to those learners’ styles. Besides, the research aims to find out the factors that influence final evaluations of students’.


Article in English.


Studentų, besimokančių virtualaus mokymo aplinkoje, veiklos analizė taikant duomenų gavybos metodus


Santrauka. Prieš planuodami rengti ir teikti nuotolinio mokymosi kursą, rengėjai turi atsižvelgti į tai, kad žmonės studijuoja skirtingais metodais: vieni pradeda skaityti pateiktą medžiagą iš eiles, kiti peržiūri tik nesuprantamas vietas, treti persikelia į virtualias diskusijas ir pan. Todėl, išanalizavus mokymosi veiksmus ir nustačius studento stilių, vėliau galima pateikti suasmenintą mokymosi medžiagą, parinkti geresnius kurso pateikimo metodus. Toks mokymo organizavimas pagerintų studijų kokybę ir leistų pasiekti geresnių rezultatų. Šiame straipsnyje nagrinėjamas duomenų gavybos metodu taikymas, analizuojant studentų elgseną, naudojantis virtualaus mokymo terpe BlackBoard Vista (BlackBoard 2008).


Reikšminiai žodžiai: virtualaus mokymo aplinkanuotolinis mokymasduomenu gavybaklasterizavimasnuotoliniu studiju vartotoju elgsena.


First published online: 21 Oct 2010

Keyword : distance education, data mining, e‐learning, virtual learning environments, clustering, online learners’, behaviour

How to Cite
Preidys, S., & Sakalauskas, L. (2010). Analysis of students’ study activities in virtual learning environments using data mining methods. Technological and Economic Development of Economy, 16(1), 94-108. https://doi.org/10.3846/tede.2010.06
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Mar 31, 2010
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