Open AccessAn Authoring Tool for Generating Context Awareness Mobile Game Based Learning
Author(s) -
Lamyae Bennis,
Khalid Kandali,
Hamid Bennis
Publication year - 2022
Publication title -
international journal of emerging technologies in learning/international journal: emerging technologies in learning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 24
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v17i02.25943
Subject(s) - computer science , context (archaeology) , adaptation (eye) , multimedia , context awareness , adventure , process (computing) , human–computer interaction , mobile device , field (mathematics) , mobile technology , artificial intelligence , world wide web , paleontology , linguistics , philosophy , physics , mathematics , phone , pure mathematics , optics , biology , operating system
Game-Based Learning (GBL) has become extensively used in Technology-Enhanced Learning (TEL) as a substitute for traditional education methods. Moreover, research has been done in this field proves that it’s very interesting for Learning Game (LG) designers to integrate the latest technologies in order to augment GBL efficiency and to reach more learners. On the other hand, context awareness and adaptation are a crucial aspect in mobile game-based learning. It is thus necessary to place at the disposal of the learner player an adaptive mobile game based learning according to the context. However, the contextualisation in the training is not easy to reach. The diversity of mobile technologies and dynam-ics in mobile environments complicate the process of contextualisation. Further-more, migration and implementation of these novel technologies can be very pricey and require more informatics knowledge and time, which can lead to a huge loss. Thus, the main purpose of this article is to present the proposed e-Adventure architecture using the ZeroCouplage multi-platform Framework that was introduced to solve this problem. We code once and the context awareness for mobile game-based learning is automatically generated.