Educational Data Mining: User Categorization in Virtual Learning Environments

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’. 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).

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Exploring Self-Regulation Based Virtual Learning Environments Using Diary

Neuroscience and Biomedical Engineering ◽

10.2174/2213385203666150828233907 ◽

2015 ◽

Vol 3 (2) ◽

pp. 66-75

Author(s):

Mahmoud Mohamed Hussien Ahmed ◽

Chaklam Silpasuwanchai ◽

Naglaa Mohammed Fares ◽

Zeinab Mohamed Amin ◽

Abd El-Rahem Ahmed Ahmed Salama

Keyword(s):

Learning Environments ◽

Self Regulation ◽

Virtual Learning ◽

Virtual Learning Environments

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Developing information literacy courses for students through virtual learning environments in Tanzania: Prospects and challenges

IFLA Journal ◽

10.1177/03400352211018231 ◽

2021 ◽

pp. 034003522110182

Author(s):

Evans F Wema

Keyword(s):

Learning Environments ◽

Information Literacy ◽

Teaching And Learning ◽

Virtual Learning ◽

Higher Learning ◽

Virtual Learning Environments ◽

Web Based ◽

Face To Face ◽

Institutions Of Higher Learning ◽

The Face

This article reviews literature on the use of virtual learning environments by highlighting their potential and the challenges of introducing the same in Tanzania. It introduces the concept of virtual learning environments by demonstrating their applications to support teaching and learning. The article discusses the use of virtual learning environments in teaching information literacy courses by highlighting the success of using such tools in facilitating the teaching of information literacy courses to library users. In this review, special emphasis is placed on attempts by Tanzanian institutions of higher learning to introduce web-based teaching of information literacy and the challenges faced. The review reveals the need for Tanzanian institutions of higher learning to develop virtual learning environments to facilitate the teaching of information literacy courses to students and faculty so as to reach many of those who may not manage to attend the face-to-face information literacy sessions that are offered by librarians on a regular basis.

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