A robust classification to predict learning styles in adaptive E-learning systems

In E-Learning Systems, the automatic detection of the learners’ learning styles provides a concrete way for instructors to personalize the learning to be made available to learners. The classification techniques are the most used techniques to automatically detect the learning styles by processing d...

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Vydáno v:	Education and information technologies Ročník 25; číslo 1; s. 437 - 448
Hlavní autoři:	Azzi, Ibtissam, Jeghal, Adil, Radouane, Abdelhay, Yahyaouy, Ali, Tairi, Hamid
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.01.2020 Springer Springer Nature B.V
Témata:	Algorithms Analysis Classification Cognitive Style Computer Appl. in Social and Behavioral Sciences Computer Science Computers and Education Education Educational Technology Electronic Learning Identification Information management Information Systems Applications (incl.Internet) Integrated Learning Systems Online instruction Prediction User Interfaces and Human Computer Interaction Fuzzy C means algorithm Robust classification Felder-Silverman learning style model Learning styles Adaptive E-learning systems
ISSN:	1360-2357, 1573-7608
On-line přístup:	Získat plný text
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