APPLYING RECOMMENDER SYSTEMS AND ADAPTIVE HYPERMEDIA FOR E-LEARNING PERSONALIZATION

被引：2

作者：

Vesin, Boban ^{[1
]}

Klasnja-Milicevic, Aleksandra ^{[1
]}

Ivanovic, Mirjana ^{[2
]}

Budimac, Zoran ^{[2
]}

机构：

[1] Higher Sch Profess Business Studies, Novi Sad 21000, Serbia

[2] Univ Novi Sad, Fac Sci, Dept Math & Informat, Novi Sad 21000, Serbia

来源：

COMPUTING AND INFORMATICS | 2013年 / 32卷 / 03期

关键词：

e-learning; recommendation; personalization; adaptive hypermedia; ontology; semantic web; tutoring system; WEB; INTEGRATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Learners learn differently because they are different and they grow more distinctive as they mature. Personalized learning occurs when e-learning systems make deliberate efforts to design educational experiences that fit the needs, goals, talents, and interests of their learners. Researchers had recently begun to investigate various techniques to help teachers improve e-learning systems. In this paper we present our design and implementation of an adaptive and intelligent web-based programming tutoring system - Protus, which applies recommendation and adaptive hypermedia techniques. This system aims at automatically guiding the learner's activities and recommend relevant links and actions to him/her during the learning process. Experiments on real data sets show the suitability of using both recommendation and hypermedia techniques in order to suggest online learning activities to learners based on their preferences, knowledge and the opinions of the users with similar characteristics.

引用

页码：629 / 659

页数：31

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