Improving Game-Based Learning Experience Through Game Appropriation

Abstract

Computational Thinking is an essential concept in this technological age. Several countries have included this subject as part of their educational program, and many others intend to do it. However, this is not a regular subject like maths or history; it needs more training (to increase the capabilities/skills) than studying and memorizing concepts. So it comes clear that the introduction of Computational Thinking to students requires the choice of the most suitable learning resources. Game-Based Learning was proven to be an effective teaching method. Therefore, we elected games as our learning resources. Nonetheless, we believe that the learning experience and motivation of students when playing games can be improved by choosing the most suitable game for each student. So, this paper focuses on the adaptation of Game-Based Learning to each student to develop Computational Thinking. We will argue that this adaptation can be done in a computer supported systematic way. To make that possible, on one hand, it will be necessary to classify games - an original ontology was used for that. On the other hand, it is crucial to establish the students' profile, having into consideration sociodemographic factors, personality, level of education, among others. Then, resorting to a similarity evaluation process it is feasible to choose the games that best fit the players, augmenting the effectiveness of the learning experience. We intend to start applying our approach - training Computational Thinking - to young students, since the first scholar years. However, we are also considering its application to adults starting programming studies.