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’. 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).
Highlights
Distance teaching and learning environment provide certain opportunities for instructors to observe students’ learning behaviour
The group of authors (Sun et al 2008) proposed a useful grouping method to help teachers improve group-learning in e-learning by first establishing effective groups with rules based on data mining, and facilitating student interaction using a system that monitors members’ communication status
System administrators can accumulate and analyse data using this tool. They can observe students’ work, and make suggestions to course instructors and scientific personnel of an education institution working on research of offering and supporting areas of the distance learning course
Summary
Distance teaching and learning environment provide certain opportunities for instructors to observe students’ learning behaviour. Questionnaires are avoided using the second method and the student’s learning behaviour is studied, analyzing and comparing similarities and differences between learners‘ behaviour Later on, these data are analyzed and recommendations are developed according to the results observed. VLE are widely used for reporting of learning materials as well as for discussions among the learners This tool enables a teacher to report learning materials in a flexible way and to provide a possibility for learners to participate in common discussions, synchronic chats, create their blogs, review video files of the lectures, use e-mail, etc. This is a powerful tool for tracking students‘ activities and interpreting these results
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
