Artificial neural network for learning personalisation - Berniukevičius, Andrius; Kurilovas, Eugenijus (Lietuvos matematikos rinkinys, 2017)
The paper aims to suggest a method of using artificial neural for learning personalisation. Learning personalisation consists form learning style identification then linking it to learning activities and objects which correspond to learning style. But the problem is that learning style identified by questionnaire cannot guarantee adequacy and objectivity. In order to overcome this issue we can use artificial neural network which could analyse learner in learning activities and interaction with learning objects and correct learning style and scenarios characteristics according to collected information.