Support : Références scientifiques
Auteur(s) : Jina Kang, Sa Liu and Min Liu
Editeur : Learning and Knowledge Analytics in Open Education pp 125-137
Date : 2017
A Serious Game (SG) is a virtual process designed for the purpose of real-world problem-solving. In SG analytics studies, learning processes are tracked using diverse techniques to support the personalization of instruction. However, it is a challenge to find potential meanings of each parameter of the tracking logs and define an appropriate indicator for a user’s behavior. Game tracking logs often only provide limited information regardless of a game context. Therefore, research such as combining game data analysis with visualization techniques is needed to provide a holistic view of the gaming process and player behaviors. This study focused on the learning analytics of students’ activities in a 3D immersive SG environment called Alien Rescue (AR, http://alienrescue.edb.utexas.edu), which is designed for middle school science learning. The goal of this study was to understand the relationship between students’ activities—as shown in log data—and their performance in the environment. Students’ activity logs and their performance scores were analyzed using both statistics and visualization techniques. The findings on SG tracking variables, learning paths based on different performance groups, and the most frequent learning path are reported in this paper.
Mots-clés : Serious games analytics, Visualization, Learning path