An Intelligent Learning Support System

Mariia Gavriushenko, Oleksiy Khriyenko, Ari Tuhkala

2017

Abstract

Fast-growing technologies are shaping many aspects of societies. Educational systems, in general, are still rather traditional: learner applies for school or university, chooses the subject, takes the courses, and finally graduates. The problem is that labor markets are constantly changing and the needed professional skills might not match with the curriculum of the educational program. It might be that it is not even possible to learn a combination of desired skills within one educational organization. For example, there are only a few universities that can provide high-quality teaching in several different areas. Therefore, learners may have to study specific modules and units somewhere else, for example, in massive open online courses. A person, who is learning some particular content from outside of the university, could have some knowledge gaps which should be recognized. We argue that it is possible to respond to these challenges with adaptive, intelligent, and personalized learning systems that utilize data analytics, machine learning, and Semantic Web technologies. In this paper, we propose a model for an Intelligent Learning Support System that guides learner during the whole lifecycle using semantic annotation methodology. Semantic annotation of learning materials is done not only on the course level but also at the content level to perform semantic reasoning about the possible learning gaps. Based on this reasoning, the system can recommend extensive learning material.

Paper Citation

in Harvard Style

Gavriushenko M., Khriyenko O. and Tuhkala A. (2017). An Intelligent Learning Support System . In Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-239-4, pages 217-225. DOI: 10.5220/0006252102170225

in Bibtex Style

@conference{csedu17,
author={Mariia Gavriushenko and Oleksiy Khriyenko and Ari Tuhkala},
title={An Intelligent Learning Support System},
booktitle={Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2017},
pages={217-225},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006252102170225},
isbn={978-989-758-239-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - An Intelligent Learning Support System
SN - 978-989-758-239-4
AU - Gavriushenko M.
AU - Khriyenko O.
AU - Tuhkala A.
PY - 2017
SP - 217
EP - 225
DO - 10.5220/0006252102170225