| Title |
Pagrindinės tendencijos taikant edukacinių duomenų gavybą mokymuisi personalizuoti / |
| Translation of Title |
Resource description framework based methodology to personalise learning. |
| Authors |
Krikun, Irina ; Kurilov, Jevgenij |
| DOI |
10.15388/LMR.B.2016.05 |
| Full Text |
|
| Is Part of |
Lietuvos matematikos rinkinys. Ser. B.. Vilnius : Matematikos ir informatikos institutas. 2016, t. 57, p. 25-30.. ISSN 0132-2818. eISSN 2335-898X |
| Keywords [eng] |
educational data mining ; learning analytics ; learning personalisation ; systematic literature review ; personalised recommendations |
| Abstract [eng] |
The paper aims to analyse Educational Data Mining/Learning Analytics application trends to personalise learning. First of all, systematic literature review was performed. Based on the systematic review analysis, the main trends on applying educational data mining methods to personalise learning were identified. Second, three main tendencies on educational data mining/learning analytics application in education were formulated. They are: (a) Educational Data Mining/Learning Analytics support self-directed autonomous learning; (b) Educational Data Mining/Learning Analytics systems become essential tools of educational management; and (c) most teaching is delegated to computers, and Educational Data Mining/Learning Analytics based recommendations become better and more reliable than those that can be produced by even the best-trained teachers. |
| Published |
Vilnius : Matematikos ir informatikos institutas |
| Type |
Journal article |
| Language |
Lithuanian |
| Publication date |
2016 |
| CC license |
|
