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This work demonstrates the potentials of procedural content generation (PCG) for games, focusing on the generation of specific graphic props (reefs) in an explorer game. We briefly portray the state-of-the-art of PCG and compare various methods to create random patterns at runtime. Taking a step towards the game industry, we describe an actual game production and provide a detailed pseudocode implementation showing how Perlin or Simplex noise can be used efficiently. In a comparative study, we investigate two alternative implementations of a decisive game prop: once created traditionally by artists and once generated by procedural algorithms. 41 test subjects played both implementations. The analysis shows that PCG can create a user experience that is significantly more realistic and at the same time perceived as more aesthetically pleasing. In addition, the ever-changing nature of the procedurally generated environments is preferred with high significance, especially by players aged 45 and above.
We present the design outline of a context-aware interactive system for smart learning in the STEM curriculum (science, technology, engineering, and mathematics). It is based on a gameful design approach and enables "playful coached learning" (PCL): a learning process enriched by gamification but also close to the learner's activities and emotional setting. After a brief introduction on related work, we describe the technological setup, the integration of projected visual feedback and the use of object and motion recognition to interpret the learner's actions. We explain how this combination enables rapid feedback and why this is particularly important for correct habit formation in practical skills training. In a second step, we discuss gamification methods and analyze which are best suited for the PCL system. Finally, emotion recognition, a major element of the final PCL design not yet implemented, is briefly outlined.
We present the design of a system combining augmented reality (AR) and gamification to support elderly persons’ rehabilitation activities. The system is attached to the waist; it collects detailed movement data and at the same time augments the user’s path by projections. The projected AR-elements can provide location-based information or incite movement games. The collected data can be observed by therapists. Based on this data, the challenge level can be more frequently adapted, keeping up the patient’s motivation. The exercises can involve cognitive elements (for mild cognitive impairments), physiological elements (rehabilitation), or both. The overall vision is an individualized and gamified therapy. Thus, the system also offers application scenarios beyond rehabilitation in sports. In accordance with the methodology of design thinking, we present a first specification and a design vision based on inputs from business experts, gerontologists, physiologists, psychologists, game designers, cognitive scientists and computer scientists.