Random Reward Mechanisms (RRMs) in video games are systems in which rewards are issued probabilistically upon certain trigger conditions, such as completing gameplay tasks, exceeding a playtime quota, or making in-game purchases. We investigated the relationship between RRM implementations and user experience. Video analysis of 35 RRM systems allowed for the creation of a classification system based on contrasting observed dimensions. Interviews with 14 video game players provided insights into how factors such as the affordances of non-optimal rewards and the trade-off between random luck and skill impact player perception and interaction with RRMs. We additionally investigated the relationship between auditory, visual, and gameplay design decisions and player expectations for RRM reward presentations, finding that the resources required to obtain the reward and the relative value of the reward impact its expected presentation. Finally, we applied our findings to propose design methodologies for creating engaging and significant RRM systems.
https://dl.acm.org/doi/abs/10.1145/3491102.3517642
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)