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The purpose of this study is to present the classification criteria for disabled Go. Since Go uses brains unlike other physical exercises, a method different from the classification method of disabled players based on physical exercise needs to be applied. For this purpose, experiences of participation and organization of Go competitions and player training and education need to be reflected. Since the International Association of disabled Go has not yet been established, and therefore there is no official classification standard for Go only, the current regulations of disabled chess apply mutatis mutandis. Although chess is a board game that uses brains like Go, the classification system does not properly reflect the characteristics of board games, so it is insufficient to continue to apply it to Go. Therefore, this study will examine the purpose of classification and the current regulations, etc., and consider which characteristics of Go should be reflected in the regulations. Through this study, it is expected that disabled Go associations will be formed in various countries and an international disability classification standard for Baduk will be established with their agreement. Go is a strong sport in East Asia, especially in Korea, China, and Japan, so unlike Western chess, this region has no choice but to lead the association and establish various standards. Through this, we hope that more domestic and foreign Go competitions will be held for the disabled, so that Go can continually participate in the Asian Para Games in the future.

This article explores the application of artificial intelligence (AI) technology in Go level examinations and its impact on Go education and evaluation systems. With the advancement of science and technology, especially the rapid development of AI technology, Go, as an ancient strategic game, has experienced revolutionary changes in its competitive scenes and learning methods. After AlphaGo defeated world Go champion Lee Sedol in 2016, the application of AI in the field of Go received widespread attention. AI has not only demonstrated capabilities beyond humans in high-level Go games, but has also played an increasingly important role in Go teaching and training. The global spread of the COVID-19 epidemic has forced Go level examinations to find new ways to adapt. The Go online intelligent test came into being, providing a new, efficient and objective assessment method. Although the introduction of online intelligent examinations has brought convenience, it has also raised issues in organizational structure adjustment, revenue distribution, and examination fairness. Challenges faced by the Go online intelligence examination in terms of fairness, including lack of face-to-face supervision, possible cheating, etc., pose new challenges to the fairness and authority of the Go level examination. This article compares the differences between intelligent Go exams and traditional exams, including assessment format, exam content and passing rate. The online intelligent examination has added test questions and raised the requirements for candidates’ computing power. It also shows a higher passing rate than traditional methods. However, the authenticity and fairness of online intelligent examinations have been challenged, including the adaptability of AI game difficulty and the lack of examination supervision, leading to the emergence of cheating. The positive impacts of implementing online smart exams include improving the convenience and efficiency of exams, simplifying event organization, and promoting the development of Go players’ skills. But at the same time, this new form has had an impact on the original Go organizational structure and benefit distribution, causing concerns and adjustments from local associations. In order to solve these problems, this article puts forward a series of suggestions, including setting up a supervision mechanism for intelligent examinations, optimizing the assessment system, and adjusting the revenue distribution ratio to ensure the long-term sustainable development of online intelligent examinations. In summary, the use of artificial intelligence in Go level examinations not only reflects the persistence of the interaction between technology and traditional cultural activities, but also poses ongoing challenges to the fairness and validity of education and assessment methods. By deeply understanding these impacts and taking corresponding countermeasures, we can find a balance between innovation and tradition, and provide support for the development of Go education and evaluation systems.

Go books have played an important role in the spread of Go for thousands of years. However, looking at the existing research in the academic community, there is a lack of interpretation of contemporary Chinese Go books from a macro perspective. This study fills this gap and reveals the development process and characteristics of contemporary Go books in China.

The purpose of this study is to analyze Baduk technique books, derive the factors of Baduk strength in the endgame, and structurize these factors. In order to achieve the purpose of the study, an analysis was conducted on the content presented in 12 Baduk technical books. We selected and conducted interviews with eight Baduk professional players from Korea, Japan and Taiwan. In order to demonstrate multiple factors, we presented situations that require the consideration of multiple factors. Through an analysis of game records, we examined how these factors are utilized in professional games. Additionally, by utilizing AI, we conducted an analysis to discern the differences between AI and professional players. The results of the study are as follows. First, through the analysis of content included in Baduk technical books, we derived 18 subfactors for consideration. Second, as a result of the expert interviews, although there are differences in the number of factors used by each expert, it was proved that all 18 subfactors were used. There were also differences in classifying types, and 18 subfactors could be classified into several endgame factors. As for the factors that experts consider the most important in the endgame, seven experts answered ‘positional judgment’ and one expert responded ‘size’, indicating that they regard positional judgment and size as important. Third, as a result of structuring the factors of Baduk strength in the endgame, it was found that the endgame ability consists of three common factors, ‘knowledge,’ ‘reading,’ ‘value judgment’, and five endgame factors, ‘size of endgame move’, ‘sente & gote’, ‘stability’, ‘surrounding position’, ‘positional judgment’ and 18 sub-considerations. Fourth, in the endgame, there are complex situations that require considering multiple endgame factors for successful resolution. In order to substantiate the evidence of the multifaceted situation of endgame factors, 26 examples of compound factors were provided. Fifth, as a result of analyzing the end stage of actual games, it was found that moves were related to the endgame factors and the subfactors, and the difference between the AI Baduk program and the professional Baduk player is that the AI seems to find better moves regarding the endgame factors ‘size’, ‘sente & gote’, ‘stability’, ‘surrounding position’, and ‘positional judgment’. Implications were derived from the results obtained in this study. First, it was the first study to suggest that the factors at the end stage consist of three common factors, five endgame factors, and 18 subfactors, and showed that much more diverse factors play a role than the current technical factors at the endgame. Second, the endgame ability is a very important part for professional Baduk players. Only when you have the endgame ability, you can finish the game stably or turn the tables. The results obtained from this study will serve as the basis for developing an endgame training program for professional Baduk players in the future. Third, the method of AI Baduk programs is still a field that requires a lot of research. The results of this study will be helpful in analyzing and supplementing the weaknesses and strengths of the endgame of AI Baduk programs.

This study examines the educational benefits and challenges of using small Go boards to teach beginners. Through a thematic analysis of interviews with 13 experienced Go teachers, it discusses the advantages, disadvantages, and practical strategies for integrating small boards into Go education. It emphasizes how small boards make the game more accessible and less intimidating, promoting a quicker understanding of basic rules and enjoyment in the learning process. While noting great benefits such as increased engagement and simplified teaching, the study also acknowledges challenges like limited strategic development and the lack of teaching materials and guidelines regarding transitioning to the 19x19 board. The research contributes to a better understanding of effective approaches to introducing beginners to the game of Go in a more straightforward and enjoyable manner.