Adaptive game-based e-leaming using semantic web technologies

Technology has played a vital role in education and significant amount of research have been performed in e-learning field to allow users to learn beyond the traditional class rooms. In this work, we have developed a novel adaptive quiz/ game-based e-learning tool using Semantic Web technologies which re-uses knowledge from DBpedia. Although there are works on game/quiz-based e-learning using Semantic Web, none of the previous works have applied personalization, which is the key novelty of our approach. In particular, we developed a novel user ontology to represent information about users and apply semantic rules to adapt the game to different users based on their knowledge. In the quiz, users can test their knowledge in Physics, Chemistry, and Geography domains that are extracted from DBpedia. In order to test the effectiveness of the proposed adaptive quiz-based e-learning system, we carried out user evaluations and compare our system with a baseline system (non-adaptive Semantic Web based version). Evaluations show that users improved their performances better with the adaptive game-based e-learning system and completed the quiz faster comparing to the baseline e-learning system without adaptation.