Research on Children’s Game Activity Design Strategies Based on Embodied Cognition Theory

Edutainment,in the kindergarten education stage,emphasizes the game as the basic activity and combines the content of education with the form of the game,thus it also forms the educational method of gamification teaching.Through investigation and analysis,it is found that the current kindergarten game activity design has the problem of improper combination of educational content and game form.The current kindergarten game activity design has problems such as stereotypes,children’s lack of active learning opportunities in activities,teachers’insufficient theoretical understanding,inappropriate teacher guidance methods,and so on.Embodied cognition theory attaches importance to the important role of the body in the development of cognition,provides new guidance for classroom teaching,and opens up a new path for classroom teaching reform.Based on the perspective of embodied cognition theory,the concept of body and mind integration should be adhered to in kindergarten teaching with games as the basic activity,experiential teaching situation should be created,children’s subjective experience should be respected,and games and interactions should be designed to promote children’s physical and mental participation,thus laying a foundation for the realization of children’s individual freedom,autonomy,and all-round development.Therefore,this paper aims at the existing problems in the current kindergarten gamification teaching and discusses the design strategy of children’s game activities based on embodied cognition theory.

Balance between education and game-play— A case study of design and optimization of the mini-game book classification

Purpose： Based on our experience of designing and testing a computer-based game for teaching undergraduate students information literacy （IL） concepts and skills, this paper summarizes the basic strategies for striking a balance between education and entertainment for the designers of quality IL games. Design/methodology/approach： The project team recruited 10 college students to play the game and post-game group interviews revealed problems and optimization priorities. The optimized game was tested among 50 college students. Based on a comparison of testing results of the two versions of the game, basic strategies for designing quality 1L games were summarized. Findings： The following 5 basic strategies can effectively promote combination of education and entertainment： l） using adventure games to enhance gaming experience, 2） plotting an intriguing story to attract players, 3） motivating players to engage in game play with game components such as challenge, curiosity, fantasy and control, 4） presenting learning materials through game props, and 5） assigning players tasks to be completed with subject knowledge. Research limitations： The 5 basic strategies have been tested only in the development process of one game, and the book classification knowledge in the mini-game is limited to the 22 major categories of the Chinese Library Classification. Practical implications： University libraries may refer to our experience to design and utilize educational games to promote the IL education for college students. Originality value： Few empirical studies tested and summarized strategies for combining learning and fun in the design of IL games for university students. The 5 strategies, which are summarized in the process of design and optimization of the mini-game book classification, are valuable for other designers of IL games.

Reinforcement Learning Toolkits for Gaming: A Comparative Qualitative Analysis

Historically viewed as a niche economic sector, gaming is now projected to exceed a global annual revenue of $218.7 billion in 2024, taking advantage of recent Artificial Intelligence (AI) advances. In recent years, specific AI techniques namely;Machine Learning (ML) and Reinforcement Learning (RL), have seen impressive progress and popularity. Techniques developed within these two fields are now able to analyze and learn from gameplay experiences enabling more interactive, immersive, and engaging games. While the number of ML and RL algorithms is growing, their implementations through frameworks and toolkits are also extensive too. Moreover, the game design and development community lacks a framework for informed evaluation of available RL toolkits. In this paper, we present a comprehensive survey of RL toolkits for games using a qualitative evaluation methodology.