On a Design Approach for Collaborative Decision Making Games: A Preliminary Validation Study

This preliminary validation study evaluates a five-step, iterative design approach for Collaborative Decision Making Games (CDMGs), a genre where players, whether co-located or distributed, build consensus and work toward a shared goal during gameplay. The approach draws on Collaboration Engineering principles and the concept of patterns, and it combines ideas from game design, software design, and collaboration research. Its steps are capturing game activities, considering collaboration patterns, creating game elements, allocating game mechanics, and validating game activities. The authors position the work as a response to the limited literature available to guide the systematic design of serious games aimed at complex decision-making skills.

The evaluation was small and exploratory. Two groups of four third-year undergraduate Computing or Game Technology students, none of whom had prior exposure to complex decision-making topics or CDMG design, took part in a two-hour workshop. Participants received a training presentation and booklet, then designed a collaborative management game for a football scenario called Ultra League Football. Data came from a questionnaire of 17 Likert-scale items plus one open question, supplemented by qualitative observation of discussions, decisions, and obstacles.

Participants rated the approach highly for analysability, adoptability, and effectiveness, particularly in decomposing game objectives, mechanics, and elements into manageable parts. They found the supporting material comprehensive and useful. Learnability was the main weakness: novice users found the approach hardest to apply, while hard-core players and expert designers found it less challenging. Prior game development experience appeared to strongly influence how quickly participants could learn and apply the method, and the group with more such experience produced a notably collaborative preliminary design. The authors acknowledge the study's limitations, including its small, self-selected sample, and plan larger observational studies with senior undergraduates, graduate students, and industry professionals.