The ability to engage and retain players is perceived as a major factor in the success of games. However, the end-goal of retention differs between entertainment and serious contexts. For an entertainment game, engagement and retention is linked to monetization; for a serious game, this needs to persist for as long as is required for learning or behavioural objectives to be met. User engagement is strongest when a balance is achieved between difficulty and skill, leading to a state of “flow”. Hence adapting difficulty could lead to increased and sustained engagement. Implementing this requires the identification of variables linked to mechanics, manipulated based upon a player performance model. In some cases, this is possible by adjusting simple properties of objects, though more comprehensive solutions require extending or adapting content applying procedural techniques. This paper proposes a six step plan, validated against two case studies: an existing serious game, with easily-manipulated parameters, and a platformer game built from scratch, where additional content is required, showing the process for different mechanics. To explore limitations, the results of two small-scale user evaluations with 45 users in total, are reported, contributing to the understanding of how adaptive difficulty might be implemented and received.
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- Artificial Intelligence
- Expert Systems
Hendrix, M., Bellamy-Wood, T., McKay, S., Bloom, V., & Dunwell, I. (2018). Implementing Adaptive Game Difficulty Balancing in Serious Games. IEEE Transactions on Games, (in press), (in press). https://doi.org/10.1109/TG.2018.2791019