A Study on Design, Development, and Evaluation of the Optimal Game-Based Learning Method to Enhance Hazard Perception Skills for Adolescent Novice Moped Drivers in Vietnam (R-10435)

Adolescents aged from 15 to 18 years, considered as the future workforce to contribute to economic growth, constitute the highest proportion of traffic crashes in Vietnam, compared to other segments of students. Possibly contributing to these figures, there is no official skill-based driving training and testing in place for this group in Vietnam and they have no way to gain necessary skills, but instead need to learn from driving mistakes. Of these skills, hazard perception, a highly relevant skill due to its significant relationship to traffic crash involvement, can be trained by game-based learning (GBL) methods. Although this promising approach has been applied internationally in road safety education and training, it has never been applied to hazard perception in Vietnam. Moreover, such methods are very diverse, i.e. ranging from gamification to (serious) games, each associated with its own merits and limitations. For these reasons, the main objective of the project is to identify, develop, and evaluate the optimal GBL method to improve hazard perception skills for adolescent novice moped drivers in the context of Vietnam. To this end, hazard perception skills among Vietnamese adolescent novice drivers are identified, followed by an assessment of internationally applied GBL methods, especially related to traffic safety education and training. Then, a feasibility study on the potential GBL method in the context of Vietnam is conducted to identify the optimal GBL method. After a design phase (including the local context content), a pilot study and experimental evaluation determine the effectiveness of the application to enhance hazard perception skills among adolescent novice moped drivers in Vietnam.

Keywords:Activity-based modelling

Disciplines:Intelligent transportation systems, Transportation impact analysis, Other product development not elsewhere classified