Use of neural networks for adaptive e-learning: A preliminary study

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F17%3AA1801QY3" target="_blank" >RIV/61988987:17310/17:A1801QY3 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Use of neural networks for adaptive e-learning: A preliminary study

Original language description

Neural Computing, e.g. Artificial Neural Networks, is one of the most interesting and rapidly growing areas of research, attracting researchers from a wide variety of scientific disciplines. Starting from the basics, Neural Computing covers all the major approaches, putting each in perspective in terms of their capabilities, advantages, and disadvantages. Their use primarily focuses on predicting future behaviour of the given area, e.g. stock market. Adaptive system is able to react to changes from the outside aiming at minimizing the deviation from the required values that characterise the required state or behaviour of the system. Current adaptive systems take advantage of the use of expert systems. Unlike expert systems that use a predefined knowledge base of rules, neural networks learn from a set of examples thus creating their own unique configuration. The aim of this paper is to consider the use of neural networks in an existing e-learning system featuring adaptive characteristics based on a fuzzy expert system. Neural networks are used as a classifier, which generates personal study plans of students and are able to replace the previously used expert system. Nowadays, the experimental study of the whole proposed classifier is in a testing phase. Neural networks should then replace the fuzzy expert system with the goal to outperform it and to provide more accurate and suitable outputs. The final structure of the system should be simplified as the tool in the form of a series of neural networks. The proposed system should act as the only mediator between the tutor and the student in the process of creating a personalised study plan.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10200 - Computer and information sciences

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the European Conference on e-Learning, ECEL

ISBN

978-191121859-3

ISSN

2048-8637

e-ISSN

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Number of pages

7

Pages from-to

78-84

Publisher name

Academic Conferences Limited

Place of publication

UK

Event location

Porto; Portugal

Event date

Oct 27, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000457842600011