Using AI Techniques in a Serious Game for Socio-Moral Reasoning Development
Abstract
We present a serious game designed to help players/learners develop socio-moral reasoning (SMR) maturity. It is based on an existing computerized task that was converted into a game to improve the motivation of learners. The learner model is computed using a hybrid deep learning architecture, and adaptation rules are provided by both human experts and machine learning techniques. We conducted some experiments with two versions of the game (the initial version and the adaptive version with AI-Based learner modeling). The results show that the adaptive version provides significant better results in terms of learning gain.
Cite
Text
Tato et al. "Using AI Techniques in a Serious Game for Socio-Moral Reasoning Development." AAAI Conference on Artificial Intelligence, 2020. doi:10.1609/AAAI.V34I09.7066Markdown
[Tato et al. "Using AI Techniques in a Serious Game for Socio-Moral Reasoning Development." AAAI Conference on Artificial Intelligence, 2020.](https://mlanthology.org/aaai/2020/tato2020aaai-using/) doi:10.1609/AAAI.V34I09.7066BibTeX
@inproceedings{tato2020aaai-using,
title = {{Using AI Techniques in a Serious Game for Socio-Moral Reasoning Development}},
author = {Tato, Ange and Nkambou, Roger and Dufresne, Aude},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2020},
pages = {13420-13427},
doi = {10.1609/AAAI.V34I09.7066},
url = {https://mlanthology.org/aaai/2020/tato2020aaai-using/}
}