Motivation for Learning - Adaptive Gamification for Web-based Learning Environments

Baptiste Monterrat, Élise Lavoué, Sébastien George

Abstract

Many learning environments are deserted by the learners, even if they are effective in supporting learning. Gamification is becoming a popular way to motivate users and enhance their participation on web-based activities, by adding game elements to the learning environment. But it still pays little attention to the individual differences among learners’ preferences as players. This paper presents a generic and adaptive gamification system that can be plugged on various learning environments. This system can be automatically personalised, based on an analysis of the interaction traces. We first present the architecture of the proposed system to support the genericity of the game elements. Then, we describe the user model supporting the adaptivity of the game elements.

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Paper Citation


in Harvard Style

Monterrat B., Lavoué É. and George S. (2014). Motivation for Learning - Adaptive Gamification for Web-based Learning Environments . In Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-020-8, pages 117-125. DOI: 10.5220/0004848101170125


in Bibtex Style

@conference{csedu14,
author={Baptiste Monterrat and Élise Lavoué and Sébastien George},
title={Motivation for Learning - Adaptive Gamification for Web-based Learning Environments},
booktitle={Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2014},
pages={117-125},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004848101170125},
isbn={978-989-758-020-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - Motivation for Learning - Adaptive Gamification for Web-based Learning Environments
SN - 978-989-758-020-8
AU - Monterrat B.
AU - Lavoué É.
AU - George S.
PY - 2014
SP - 117
EP - 125
DO - 10.5220/0004848101170125