• Journal of the Daesoon Academy of Sciences
• /
• v.44
• /
• pp.141-175
• /
• 2023

This comparative study combines the methodologies of comparative research and literature review to examine Daesoon Thought. Comparative religious analysis in the social sciences, does not presuppose an a priori framework of the essence of religion because it targets various aspects of religion which are revealed within a historical field. However, it does not decompose and return to psychological or social phenomena like social sciences. In addition, with the emergence of religious pluralism, the climate of focusing on similarities between religions has already been accomplished to some degree. Furthermore, it is worth noting that many spiritual movements in modern spirituality reveal mixed or amorphous characteristics without being restricted by specific religious membership. It is time to overcome instrumentation and restore the transcendence of its original appearance even in secular humanist reasoning. It can be said that this reveals the perception that the ills and crises of modern civilization should be overcome in connection with the opening of the acquired world of Daesoon Thought. It could further be said that the main culprit of evil behavior is instrumental reason or degenerated reason rather than spirituality. Religion is the intellectual crystalline body of humankind and aims at human perfection and salvation. However, extremists in previous times amplified conflicts between religions and formed ideas suitable for their specific regions through different experiences. This generated mental rifts that proved greatly influential. At the time of initial inception, each religion confronted and fought other ideologies, but when the era of religious pluralism began, the necessity for inter-spiritual communication became urgent. It could be said that happiness is the realization of human spirituality by exploring the vision of humanism. In that case, the combined methodologies of comparative research and literature review reveal that the spirituality of Daesoon Thought would enable a humanism based on human dignity. This would be a path for seeking spirituality through human life and living as a true human being. Spiritual humanism as discussed through this study aims to share the problems of modern civilization and provide a critical view of modern civilization that shows the roots of prevailing thought are stuck in a Cartesian dualistic view of humanity and the world. The type of spiritual humanism to examined here focuses on a cosmotheandric vision by considering the spiritual return to Daoism via Daesoon Thought. This would treat human beings like heaven in alignment with Donghak ideology and honor the human dignity proposed by Daesoon Thought. It would also deliver sentient beings from suffering and to bliss in accordance with the aims of faith in Maitreya Buddha, and it would implement the Resolution of Grievances for Mutual Beneficence in fulfillment of Daesoon Thought.

• Journal of the Korean Society of Earth Science Education
• /
• v.16 no.2
• /
• pp.302-318
• /
• 2023

The purpose of this study was to study to the effect of presenting SBF questions on the level of conceptual achievement and eye movement of elementary students in seasonal constellation learning that requires systems thinking. In this study, the effectiveness of SBF questions was divided into experimental groups and comparison groups, and scientific texts with different question types were presented to analyze the level of conceptual achievement and differences in eye movement of sixth-grade elementary students. Data analysis quantitatively analyzed the pre- and post-test results of the developed concept test paper and the eye movement data when learning scientific texts related to seasonal constellations. As a result of the study, first, the SBF question was a valid learning strategy for learning seasonal constellations. The SBF question showed a statistically significant difference (p<0.05) in the pre- and post-test between groups, and a statistically significant difference (p<0.001) in the pre- and post-test within the group. Second, SBF questions had a positive effect on students' learning by inducing learners with low preconceptions to area of interest that help them achieve concepts. In other words, when presenting SBF questions with visual data from a space-based perspective, it was confirmed based on the results of eye movement analysis that there was a significant difference in total fixation count (p<0.01) of learners. On the other hand, for learners with high scientific preconceptions, the effect of exploration was not significant because the preconceptions of the learners themselves acted as a hard core rather than the effect of SBF questions. This study is different from existing seasonal constellation learning studies in that it provides quantitative data through pre- and post-test and eye movement analysis in the seasonal constellation learning process, and can help elementary students learn seasonal constellations.

• Journal of Ethics
• /
• no.77
• /
• pp.73-112
• /
• 2010

This study aims to explore the character and problem of multicultural society in Korea in terms of the concept of moral panics. Its major issues are dealt with as follows: Firstly, this essay will apply two concepts of culture in multiculturalism - the pattern of meaning and a study of perfection- to three degrees of multicultural members: by individual, by groups and by a society as a whole. In this approach, moral panics of multicultural society in Korea have been manipulated by the secondary definitions like Korean government and media. In this study, however, the resource of the panics would be seen as nationalism in Korean history. To remove it in this essay, the conception of the pattern of meaning, which makes members understand others outer their norms, should be harmonized with that of a study of perfection by which they have identities. Secondly, the main subject of multiculturalism in Korea should at least be majority (groups)-Korean, not minority (groups)-foreigners. A stereotype of foreigners by majority is an image distorted by nationalities and races. People, for example, with the white skin from advanced countries are recognized as superior, while those born in the countries of Southeast Asia are, consciously or unconsciously, discriminated and have low positions due to socio-economic stratification in Korea. In this sense, a study of multicultural society in Korea should go forward to the inner direction to majority, because it is one of the real moral panics in Korea. In conclusion, it is important that there must be a study of identity which we can have of others in multicultural studies of Korea. It enables us to meet the conception of diversity. In that Korean government and media have neglected the danger of nationalism, it is also necessary that this study have any foundation of morality in ethics, which can give useful alternatives to the given polices of the secondary definitions.

• (The) Research of the performance art and culture
• /
• no.22
• /
• pp.371-411
• /
• 2011

In the twenty first century of rapid cultural change performing art requires new mode of expression based on imaginative power and creativity as well as establishing its own identity. The modern technological environment support this with advanced technology and bring about the expansion of reason from new experience. The introduction of digital media on artistic expression in particular, expands the physical ability of human body which is the main subject of performing art. A virtual body from digital technology is freed from physical boundaries and goes over space and time. It also suggests the possibility of new mode of communication with audience. This study aims at examining the subject of performing art and its digitalized movement focusing on EveR, the world's first professional robot actor. The robot actor which came on stage according to the new expression medium, a digital body, stands in need not only of technological value but also of cultural and artistic application for expression in art. In this endeavor to meet the demand, this study examines the development process and function of 'EveR' the robot actor. Also it searches into the performance of Ever which replaced human being as well as the historical significance of the title:the world's first. To be more specific, there is a example research on two performances:a pansori play "EveR is simply stunning(2009)" and children's play "The Robot Princess and Seven Dwarfs(2009)." Through this example research, it is enabled to anticipate the influence of robot actors on performing arts and to search for the better way of them to evolve. Furthermore, it aims at finding ways to create high value through promoting robot actors to be familiar to the public as well as supporting them to become active cultural contents. The performance with robotic technology is one of the artistic experiment that may cause the change of the future of performing art by actualizing technological imagination together with human body and machinery. As a consequence, it is expected that the meeting of performing art and robotic technology gives positive influence on activating performing art as one of the integrated cultural phenomenon which satisfies the taste of modern era. Moreover, this study may also be the beginning of the expansion of performing art to stretch to diverse field.

• Journal of Science Education
• /
• v.47 no.3
• /
• pp.225-237
• /
• 2023

The purpose of this study is to explore the perceptions of elementary pre-service teachers regarding their interest in science. A survey was conducted among 187 elementary pre-service teachers enrolled at Non-Metropolitan Area A University of Education. Data collection was carried out concurrently with three elementary pre-service teachers who agreed to participate in online interviews. The survey responses provided by the elementary pre-service teachers were analyzed using a qualitative text analysis method. Interest in science was observed to decrease during middle school, followed by the upper grades of elementary school and then the lower grades. The reasons for the decline in interest in science were interpreted as stemming from negative experiences with science education within the context of individual circumstances in the school setting. Strategies to address the decline and enhance interest in science were discussed across individual, family, school, teacher, local community, and national levels, considering both short-term and long-term perspectives. These strategies encompassed various inquiry activities and experiences related to the field of science, engagement in science-related activities, student-centered instruction, teacher professional development, support for elementary students and teachers, and policy measures. The multifaceted approach and efforts aimed to open avenues for positive feedback regarding science on an individual level and foster experiences related to science were interpreted as part of an effort to counteract the decline in interest in science. Lastly, given the current situation of declining interest in science and the need to enhance students' interest, it was implicitly and explicitly discussed that pre-service teachers should focus on improving their expertise in curriculum instruction. This research, by exploring the conceptual characteristics of interest in science, perceptions of changes, and educational needs related to interest in science among elementary pre-service teachers, is expected to have academic significance as foundational research data for the current status of declining interest in science.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.95-108
• /
• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.