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◆ Psychological Methods2026-04-23· Computer science

A novel multidimensional dynamic difficulty adjustment algorithm: Use case in a cognitive training video game.

Angela Pasqualotto, Marios Fanourakis, Zeno Menestrina, Friedhelm C. Hummel, Elmārs Rancāns, Frank Padberg, Omer Bonne, Amit Lotan, Esther Bukowski, Lena Lipskaya‐Velikovsky, Mor Nahum, Daphné Bavelier

原始摘要(英文原文)· Original abstract
This study introduces a novel methodological framework for cognitive control training, embedded in a video game that incorporates action-based gameplay and a multidimensional dynamic difficulty adjustment (DDA) system. This system adapts to individual player performance in real time, ensuring a personalized and engaging experience. The game architecture is modular, including a configurable set of cognitive training modules that are tailored according to one's training goals. Transitioning between modules occurs through an action-based central hub following the literature on action video games and their positive impact on brain plasticity. Analysis of data from 34 players demonstrates how they progress through each module, with most players reaching their zone of proximal development after approximately 30-45 min of playing a module. Once players stabilize in their skill progression, the DDA system maintains variability in gameplay, a feature that has been suggested to promote the transfer of skills to novel situations. This analysis also highlights how our novel multidimensional DDA system accommodates to a wide range of skill levels, offering a seamless onboarding experience across a variety of players. Together, this novel architecture and DDA framework provide a new, rigorous methodological blueprint for the design of computerized cognitive training tools. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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A novel multidimensional dynamic difficulty adjustment algorithm: Use case in a cognitive training video game. — 科研速览 Science Skim