Research Article
Automatic Extraction of Gameplay Design Expertise: An Approach Based on Semantic Annotation
@INPROCEEDINGS{10.1007/978-3-319-51055-2_8, author={Kaouther Raies and Maha Khemaja and Yemna Mejbri}, title={Automatic Extraction of Gameplay Design Expertise: An Approach Based on Semantic Annotation}, proceedings={Serious Games, Interaction and Simulation. 6th International Conference, SGAMES 2016, Porto, Portugal, June 16-17, 2016, Revised Selected Papers}, proceedings_a={SGAMES}, year={2017}, month={1}, keywords={GBLS Gameplay Automatic knowledge extraction Ontology learning}, doi={10.1007/978-3-319-51055-2_8} }- Kaouther Raies
Maha Khemaja
Yemna Mejbri
Year: 2017
Automatic Extraction of Gameplay Design Expertise: An Approach Based on Semantic Annotation
SGAMES
Springer
DOI: 10.1007/978-3-319-51055-2_8
Abstract
A Game Based Learning System (GBLS) constitutes an interesting learning environment. However, many problems are facing the general adoption of learning approaches based on this system. For instance, complexity of GBLS design process and problems of integrating learning outcomes with fun aspects constitute the major challenges. Therefore, novice game designer have not only to acquire specific skills and expertise but also to acquire them in an efficient and active pedagogical manner. For that aim, extraction and representation of knowledge related to GBLSs design become necessary to render possible accessibility and transfer of that knowledge to novice actors and further to meet aforementioned challenges. In this context the use of learning ontology techniques based on semantic annotation of gameplay description seems promising as it facilitates knowledge extraction, elicitation process, and grants more formal knowledge representation which allows answering to growing needs of sharing data within and across organizations and actors.
