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

Angela Pasqualotto1, Marios Fanourakis1, Zeno Menestrina1

  • 1Faculty of Psychology and Education Sciences (FPSE), University of Geneva.

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Summary
This summary is machine-generated.

This study presents a new video game framework for cognitive control training. Its dynamic difficulty adjustment system personalizes gameplay, enhancing skill acquisition and transfer for diverse users.

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Human-Computer Interaction

Background:

  • Cognitive control training is crucial for various cognitive functions.
  • Existing training methods often lack personalization and engagement.
  • Action video games show potential for enhancing brain plasticity.

Purpose of the Study:

  • To introduce a novel methodological framework for cognitive control training.
  • To develop a video game with a multidimensional dynamic difficulty adjustment (DDA) system.
  • To provide a blueprint for designing effective computerized cognitive training tools.

Main Methods:

  • A modular video game architecture with configurable cognitive training modules.
  • An action-based central hub for seamless module transitions.
  • A multidimensional DDA system adapting in real-time to player performance.

Main Results:

  • Players reached their zone of proximal development within 30-45 minutes per module.
  • The DDA system maintained gameplay variability for skill transfer.
  • The system accommodated a wide range of skill levels, ensuring smooth onboarding.

Conclusions:

  • The proposed framework offers a rigorous methodology for cognitive training tool design.
  • The DDA system enhances personalized learning and engagement.
  • This approach supports the development of effective computerized cognitive interventions.