• Journal of the Daesoon Academy of Sciences
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• v.37
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• pp.297-328
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• 2021

This paper aims to find out from what perspective Joseon Dynasty Confucian scholars evaluated and understood Yang Xiong's guiding principles and literature at the micro level and to reveal the academic trends of Joseon Dynasty Confucian scholars. This topic is approached as follows: first, an evaluation of Yang Xiong's way of living as a 'senior state official of Wang Mang (the controversial Emperor of the short-lived Xin Dynasty)'; second, Yang Xiong's literary character and his literary works; third, Yang Xiong's writing style; and fourth, Yang Xiong's view of good and evil. These can be summarized in three main ways: One is to agree with Zhu Xi's criticism of Yang Xiong as a 'senior state official of Wang Mang' and dismiss his guiding principles, academic achievements, literature, and other accomplishments. Most of these negatives have been found in Confucian scholars who are especially enthusiastic about theology. Examples include Hong Jikpil, Wi Baekgyu, Kim Wonhaeng, and Lee Sangjeong. In the case of kings such as King Yeong-Jo, the assessment of Yang Xiong is quite similar. The following assessments of Yang Xiong are positive though. Positive assessments are presented from two different views. One is a balanced approach that covers both the positive and negative aspects of Yang Xiong. For example, Heo-Kyun's understanding. Another positive view can be analyzed from three perspectives. The first case is when the scholars assessing Yang Xiong were not deeply influenced by Zhu Xi's criticism of him. Seo Geojeong and Seong-Hyeon are examples. The second case are those that broke away from theology or adhered to Silhak [Practical Studies]. Yi-Ik is an example. Third, assessments from scholars who posited that truth was of a pluralistic nature. Jang-Yu is an example of such scholars. Regarding theories of human nature; however, there was consensus among Confucian scholars that Mengzi held that human nature is good, and thereby it was common to criticize Yang Xiong's theory that human nature was a mixture of good and evil. From an ideal micro perspective, Joseon Dynasty Confucian scholars' different assessments of Yang Xiong show that their understanding and evaluation of Yang Xiong differed in accordance with their own differing worldviews and ideas.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.