• English Language & Literature Teaching
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• v.15 no.4
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• pp.137-156
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• 2009

This case study examines language learners' oral interactive practices and what they learn along with these practices. Language learners who study abroad take on the challenge of living in a foreign place and undergo difficulties in communicating and interacting with people in their new country. These difficulties, caused by cultural differences, are experienced most particularly in their daily interactions. Language learners' trials and efforts to learn English while dealing with a different culture and the difficulties are mainly observed for this paper. The process of learning a second culture is closely related to the process of learning a second language. Oral interactive practices can give the study abroad language learners opportunities to learn their target culture. Therefore, the purpose of this paper is to discuss how participating in interactive practices assists the learners in understanding their target culture while they deal with their difficulties inherent in studying abroad. This study adds weight to the notion that culture is an essential and major factor in learning a language, and that only active participation in interactions can be effective in learning both a language and its culture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2831-2845
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• 2022

Compared to the significant approach of project-based learning research, a data-driven design project-based learning has not reached a meaningful consensus regarding the most valid and reliable method for assessing design creativity. This article proposes an advanced information data-interactive learning system for creative design using a service design process that combines a design thinking. We propose a service framework to improve the convergence design process between students and advanced information data analysis, allowing students to participate actively in the data visualization and research using patent data. Solving a design problem by discovery and interpretation process, the Advanced information-interactive learning framework allows the students to verify the creative idea values or to ideate new factors and the associated various feasible solutions. The student can perform the patent data according to a business intelligence platform. Most of the new ideas for solving design projects are evaluated through complete patent data analysis and visualization in the beginning of the service design process. In this article, we propose to adapt advanced information data to educate the service design process, allowing the students to evaluate their own idea and define the problems iteratively until satisfaction. Quantitative evaluation results have shown that the advanced information data-driven learning system approach can improve the design project - based learning results in terms of design creativity. Our findings can contribute to data-driven project-based learning for advanced information data that play a crucial role in convergence design in related standards and other smart educational fields that are linked.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.90-104
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• 2020

It is difficult for non-experts to build machine learning (ML) models at the level that satisfies their needs. Deep learning models are even more challenging because it is unclear how to improve the model, and a trial-and-error approach is not feasible since training these models are time-consuming. To assist these novice users, we examined how interactive and explainable feedback while training a deep learning network can contribute to model performance and users' satisfaction, focusing on the data preparation process. We conducted a user study with 31 participants without expertise, where they were asked to improve the accuracy of a deep learning model, varying feedback conditions. While no significant performance gain was observed, we identified potential barriers during the process and found that interactive and explainable feedback provide complementary benefits for improving users' understanding of ML. We conclude with implications for designing an interface for building ML models for novice users.

• Journal of Christian Education in Korea
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• v.66
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• pp.343-382
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• 2021

This study is a case study in which the interactive non-face-to-face classes using Edutech were applied to the Department of Christian Education. The subjects were 20 students from the Christian education department of A University located in the metropolitan area. The course was 'Instructional Methods and Educational Technology' in the first semester of 2020. In theory, I studied non-face-to-face classes and interaction, and edutech and interaction. Afterward, it designed and developed interactive non-face-to-face classes using edutech. The interactive non-face-to-face classes using edutech were developed as a process of applying Flipped-PBL based interactive edutech. In addition, Edutech was selected for active interaction according to the Flipped-PBL process to be carried out in a non-face-to-face situation. In particular, in the process of developing the problem of PBL, it was built around the situation of the church. As a result of applying the class, first, learners showed high satisfaction and interest in the class. Second, positive transference appeared in the space of learning and the space of living. Third, interactive non-face-to-face classes using Edutech have generated active interaction. In particular, interactive edutech and learning methods have become the main factors enabling active interaction. Through this, learners have improved learning efficiency, immersion, and satisfaction. Also, as an alternative to face-to-face classes, I was able to experience online classes. In other words, the satisfaction and interest of learning, and the transference of learning space, were also possible through active interactions generated through learning methods using interactive Edutech used in class. Furthermore, disabilities in the online communication(Internet) environment and learners' unfamiliarity with the online environment have been found as factors that hinder learning satisfaction and interaction. During learning, obstacles to the online communication environment hinder the utilization of interactive Edutech, preventing active interactions from occurring. This results in diminishing satisfaction and interest in learning. Therefore, we find that designing interactive non-face-to-face classes using Edutech requires sufficient learner learning and checking of the online communication(Internet) environment in advance for Edutech and learning methods. In response, this study confirmed the possibility by applying interactive non-face-to-face classes using Edutech to Christian education classes as an alternative method of education that allows active interaction and consistent transference of learning and life. Although it is a case study with limited duration and limitations of the number of people, I would like to present the possibility as an alternative Christian education method of an era where the direction of online classes should be presented as an alternative to a face-to-face class.

• Educational Technology International
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• v.7 no.1
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• pp.1-20
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• 2006

This paper describes practical research on the improvement of teaching and learning process by integrating Web Bulletin Board (WBB) and mobile phone. This paper addresses three topics; A) the interactive lecture with topics-based discussions using the Web Bulletin Board (WBB) as a tool for assisting discussion, B) the introduction of peer evaluation among students to develop their problem-solving and cognitive skills, C) the use of mobile phones for promoting interactive lectures, keeping class attendance, conducting assignments, and providing notices for the next class. Results indicated the following research-findings: (1) WBB plays a role in facilitating positive participation in classes. (2) In contrast to the scenario of the traditional mode of instruction (without the usage of WBB), students were able to deepen their understanding of the theme by accessing the WBB before and after classes. (3) Peer evaluation highly promoted students' motivation to learn, and was effective in cultivating meta-cognition through modeling. (4) Mobile phone was identified as a highly effective tool for keeping class attendance, realizing interactive classes by generating discussions, and managing assignments and homework.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.236-242
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• 2003

This paper presents a cooperation strategy between a human operator and autonomous robots for an interactive robot soccer game, The interactive robot soccer game has been developed to allow humans to join into the game dynamically and reinforce entertainment characteristics. In order to make these games more interesting, a cooperation strategy between humans and autonomous robots on a team is very important. Strategies can be pre-programmed or learned by robots themselves with learning or evolving algorithms. Since the robot soccer system is hard to model and its environment changes dynamically, it is very difficult to pre-program cooperation strategies between robot agents. Q-learning - one of the most representative reinforcement learning methods - is shown to be effective for solving problems dynamically without explicit knowledge of the system. Therefore, in our research, a Q-learning based learning method has been utilized. Prior to utilizing Q-teaming, state variables describing the game situation and actions' sets of robots have been defined. After the learning process, the human operator could play the game more easily. To evaluate the usefulness of the proposed strategy, some simulations and games have been carried out.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.816-821
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• 2003

Researchers have utilized artificial evolution techniques and learning techniques for studying the interactions between learning and evolution. Adaptation in dynamic environments gains a significant advantage by combining evolution and learning. We propose an on-line, realtime evolutionary learning mechanism to determine the structure and the synaptic weights of a neural network controller for mobile robot navigations. We support our method, based on (1+1) evolutionary strategy which produces changes during the lifetime of an individual to increase the adaptability of the individual itself, with a set of experiments on evolutionary neural controller for physical robots behaviors. We investigate the effects of learning in evolutionary process by comparing the performance of the proposed realtime evolutionary learning method with that of evolutionary method only. Also, we investigate an interactive evolutionary algorithm to overcome the difficulties in evaluating complicated tasks.

• International Journal of Contents
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• v.15 no.4
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• pp.1-7
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• 2019

As the recent developments of artificial intelligence, particularly machine-learning, impact every aspect of society, they are also increasingly influencing creative fields manifested as new artistic tools and inspirational sources. However, as more artists integrate the technology into their creative works, the issues of diversity and fairness are also emerging in the AI-based creative practice. The data dependency of machine-learning algorithms can amplify the social injustice existing in the real world. In this paper, we present an interactive visualization system for raising the awareness of the diversity and fairness issues. Rather than resorting to education, campaign, or laws on those issues, we have developed a web & ML-based interactive data visualization system. By providing the interactive visual experience on the issues in interesting ways as the form of web content which anyone can access from anywhere, we strive to raise the public awareness of the issues and alleviate the important ethical problems. In this paper, we present the process of developing the ML-based interactive visualization system and discuss the results of this project. The proposed approach can be applied to other areas requiring attention to the issues.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.145-150
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• 2023

The main purpose of the study is to identify the key aspects of modern innovative research in the field of education. In the modern informatized world, education is becoming a decisive factor in social development and an important component in the development of the human personality, increasing respect for human rights and freedoms. Today it is quite obvious that without the necessary education a person will not be able to provide himself with proper living conditions and realize himself as a person. The high level of education of the population is an important factor that positively influences the creation of favorable conditions for the full realization of the rights and freedoms of man and citizen. Today, active and interactive teaching methods are widely used. The use of interactive teaching methods ensures complete immersion of students in the learning process and is the main source of learning. The radical difference between traditional and interactive learning is that the student not only replenishes and strengthens his knowledge, but also complements and constructs new ones. The methodology includes a number of theoretical methods. As a result of the study, current trends and prerequisites of modern innovative research in the field of education were investigated.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.264-272
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• 2022

Human-robot cooperative tasks are increasingly required in our daily life with the development of robotics and artificial intelligence technology. Interactive reinforcement learning strategies suggest that robots learn task by receiving feedback from an experienced human trainer during a training process. However, most of the previous studies on Interactive reinforcement learning have required an extra feedback input device such as a mouse or keyboard in addition to robot itself, and the scenario where a robot can interactively learn a task with human have been also limited to virtual environment. To solve these limitations, this paper studies training strategies of robot that learn table balancing tasks interactively using deep reinforcement learning with human's facial expression feedback. In the proposed system, the robot learns a cooperative table balancing task using Deep Q-Network (DQN), which is a deep reinforcement learning technique, with human facial emotion expression feedback. As a result of the experiment, the proposed system achieved a high optimal policy convergence rate of up to 83.3% in training and successful assumption rate of up to 91.6% in testing, showing improved performance compared to the model without human facial expression feedback.