LAUSR

During the last years, gamification has been used to engage students in more attractive educational activities in different Computer Science subjects at the university level, thereby improving their motivation and learning outcomes. This work continues a research that initially proposed a gamified design for the course “Distributed Artificial Intelligence”, an optional undergraduate course of the Computer Engineering degree. Specifically, we focused on reinforcing subjects related to Multi-Agent Systems (MAS) by means of fun hands-on activities to experiment theoretical concepts in practice. A first iteration of the design was deployed during two consecutive academic years, with good results in terms of students’ perceived learning, engagement and commitment during the class. Nevertheless, a posterior analysis of the design showed that the proposed mechanics did not consider some types of players such as disruptors -, and some of the learning profiles such as theoretical and reflexive -. Then, we proposed a card-based game to redesign the learning experience, using a LEarner-centered GAmification Design Framework (LEGA) that aligns both educational and gamification approaches. This paper focuses on this second iteration of the design, which has been deployed and evaluated during the last semester. The obtained results show that students liked the card game, were engaged and motivated during the gamified class, as well as they perceived an increased learning in the subject.