Visualization, Serious Games and Decision Making

"Visualization, Serious Games and Decision Making" examines whether visual data support can enhance student learning and decision-making within a logistics serious game. The work centers on the Data Hound and Visualizations (DHV) dashboard, designed as a companion to the LOST logistics business simulator, with the explicit aim of helping students comprehend complex supply-chain systems without dictating the choices they make. The authors situate their approach within broader research on serious games and data visualization, acknowledging that well-designed visualizations can support decision-making while poorly designed ones risk misleading users.

The study was conducted in two stages with student participants. A pilot involving 33 students found that 69.7% considered LOST helpful for learning, rising to 78% when intermediate responses were included, with DHV receiving somewhat lower but comparable perceived benefit. Usability ratings favored LOST, with 36.4% rating it highly usable compared with 21.2% for DHV. A second stage involving 36 students used pre- and post-testing and reported mean gains of 40% in tool functionality, 0.44 normalized points in data processing, and 0.44 normalized points in user interface assessment. From these results the authors conclude that visualization support improves data analysis and decision-making within the game.

The evidence base warrants careful interpretation. The findings rest largely on self-reported perceptions from small samples at a single institutional context, and the gains are not accompanied by strong controls or larger-scale replication. The accompanying bibliography draws on prior work concerning in-game data collection, higher-education applications of simulations, and meta-analyses of serious games in education, providing a theoretical grounding that the empirical component extends but does not fully confirm.