Exergaming and education: a relational model for games selection and evaluation.

Area of Science:

• Kinesiology
• Educational Technology
• Rehabilitation Science

Background:

• Exergaming (technology-driven physical exercise) is increasingly used in education, health, and rehabilitation.
• While beneficial, exergaming's effectiveness varies across different populations.
• Inconsistent outcomes may stem from mismatched exergame demands and user capabilities.

Purpose of the Study:

• To propose a theoretical framework for matching exergames with users.
• To enhance the effective application of exergaming for diverse populations.
• To guide future research in exergame design and effectiveness.

Main Methods:

• Developed a relational model integrating Bloom's taxonomy of learning domains.
• Incorporated performance components of exergames into the model.
• Proposed a matrix for matching exergame physical demands with user abilities.

Main Results:

• The proposed model facilitates appropriate matching between exergames and individuals.
• This matching is crucial for optimizing benefits across various user groups.
• The model addresses the need for a structured approach to exergame application.

Conclusions:

• A theory-based model can improve exergame effectiveness for students, older adults, and rehabilitation patients.
• Matching game demands to user capabilities enhances physical, developmental, and psychosocial outcomes.
• This model offers a foundation for future exergame research and development.