• Journal of Korean Elementary Science Education
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• v.26 no.1
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• pp.49-62
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• 2007

The higher cognitive functions of the human brain including teaming are hypothesized to be selectively distributed across large-scale neural networks interconnected to the cortical and subcortical areas. Recently, advances in functional imaging have made it possible to visualize the brain areas activated by certain cognitive activities in vivo. Neural substrates for teaming and motivation have also begun to be revealed. Functional magnetic resonance imaging (fMRI) provides a non-invasive indirect mapping of cerebral activity, based on the blood- oxygen level dependent (BOLD) contrast which is based on the localized hemodynamic changes following neural activities in certain areas of the brain. The fMRI method is now becoming an essential tool used to define the neuro-functional mechanisms of higher brain functions such as memory, language, attention, learning, plasticity and emotion. Further research in the field of education will accelerate the verification of the effects on loaming or help in the selection of model teaching strategies. Thus, the purpose of this study was to review brain study methods using fMRI in science education. In conclusion, a number of possible strategies using fMRI for the study of elementary science education were suggested.

• English Language & Literature Teaching
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• v.18 no.2
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• pp.45-66
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• 2012

The purpose of this study was to investigate the impact of two different SNS-based tasks on university students' English writing performance. To address our primary research question, Me2day, microblogging and Social Networking Service, was employed. 43 university students were divided into two experimental groups depending on the task types: a comparison task group and a sharing personal experiences task group. The main findings of the study were as follows: first, two different types of SNS-based tasks, 'spot the differences' and 'writing diaries', had a positive effect on learners' writing performance. The reason for this was that the succinct messages limited to 150 characters made it easier for the students to try writing in English without burden; and they may benefit from their peers by seeing their posts and interacting with each other. Yet there were no significant differences between the two groups when it came to the degree of improvement. Second, two different types of SNS-based tasks differently fostered certain aspects of the writing performance; 'contents knowledge' was supported by the 'writing diaries' task and range was supported by the 'spot the differences' task. Third, learners in the two experimental groups mostly had positive impressions regarding usage of Me2day as a new learning tool.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.21-29
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• 2024

Fueled by international efforts towards AI standardization, including those by the European Commission, the United States, and international organizations, this study introduces a AI-driven framework for analyzing advancements in drone technology. Utilizing project data retrieved from the NTIS DB via the "drone" keyword, the framework employs a diverse toolkit of supervised learning methods (Keras MLP, XGboost, LightGBM, and CatBoost) enhanced by BERTopic (natural language analysis tool). This multifaceted approach ensures both comprehensive data quality evaluation and in-depth structural analysis of documents. Furthermore, a 6T-based classification method refines non-applicable data for year-on-year AI analysis, demonstrably improving accuracy as measured by accuracy metric. Utilizing AI's power, including GPT-4, this research unveils year-on-year trends in emerging keywords and employs them to generate detailed summaries, enabling efficient processing of large text datasets and offering an AI analysis system applicable to policy domains. Notably, this study not only advances methodologies aligned with AI Act standards but also lays the groundwork for responsible AI implementation through analysis of government research and development investments.

• Korean Journal of Comparative Education
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• v.28 no.3
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• pp.291-307
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• 2018

As the value of lifelong learning becomes important, states are making efforts to build a system of lifelong learning. According to this tendency, this paper intends to compare the participation rate of lifelong learning, learning outcomes, learning support infrastructure, support of learning expenses, and recognition of lifelong learning. For the comparative pedagogical approach, Bray and Thomas' cubes such as geographical / regional level, non - geographical demographic statistics, social and educational aspects were utilized. The participation rate of lifelong learning in Korea is 34.4% in 2017, which is lower than the OECD average of 46%. The competency scores of Korean adults were lower than the OECD national averages of the PIAAC survey which measured adult competence, language ability, numeracy, and computer-based problem solving ability. In order to recognize prior learning, EU countries have developed EQFs to evaluate all non-formal and informal learning outcomes, while Korea recognizes qualification as a credit banking credit under the academic credit banking system. International comparisons of lifelong learning can be used as an important tool for diagnosing the actual conditions of lifelong learning in a country and establishing future lifelong learning policies. Therefore, it is necessary to maintain that the comparative pedagogical approach of lifelong learning differs according to the historical context, socioeconomic characteristics, and population dynamics, including the formation process and characteristics of modern countries.

• English Language & Literature Teaching
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• v.13 no.1
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• pp.87-110
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• 2007

Past studies conducted on the students' verbal participation both in and out of class have explored and identified variables affecting the process of learning to speak English. However, little is known about the causes and effects of these variables. A survey form developed from a previous study was administered to 468 university students taking English conversation classes from native speakers of English. To better understand the causes and effects of speaking barriers, path analysis was administered as the main tool of investigation. The results of the study indicate that familiarities toward NS (Native Speaker) teachers, learner faithfulness, che-myon, NS teachers' classroom management skills, and NS teacher's trustworthiness account for 50.72% of speaking grades. These factors are causally related to learner attitudes. However, with regard to speaking grades, all of the above factors except che-myon are also causally related with each other. Therefore, it was concluded that learner attitudes can be improved by minimizing che-myon, however, che-myon itself cannot be a predictor of speaking grades. To validate the findings of the study, related research work is discussed and implications are provided.

• English Language & Literature Teaching
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• v.15 no.2
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• pp.1-25
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• 2009

The purpose of this study is to explore the potential of peer coaching for EFL teachers' professional development. For this study, 12 college teachers in Korea participated in a 10-week program. They were 7 males and 5 females, ranging in age from 24 to 37 years. Data were collected through semi-structured interviews. Reflective analysis was used to analyze individual interview data. From the findings, two significant categories of peer coaching were identified: positive and negative responses to peer coaching experience. However, the overriding themes that emerged from the data were the benefits of peer coaching. The participants were almost unanimous in their acknowledgement of the advantages of peer coaching, such as reflective support through other's eyes, improved working environments, greater teaching strategies, higher professional self-esteem, and awareness of self-directed learning. Negative responses also appeared, mostly in regard to the working principles of implementation; the major issues of difficulties were time management, complexities of implementation procedure, stress and personal vulnerability, and relative lack of reflection and feedback skills. Demonstrating the participants' experiences towards the peer coaching program, this study provides EFL teachers with useful insights into peer coaching as an effective tool of their professional development.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.407-410
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• 1996

In this Paper, we propose the feedback method having neural network to control the chaotic signals to periodic signals. This controller has very simple structure, it is immune to small parameter variations, the precise access to system parameters is not required and it is possible to follow ones of its inherent periodic orbits or the desired orbits without error, The controller consist of linear feedback gain and neural network. The learning of neural network is achieved by error-backpropagation algorithm. To prove and analyze the proposed method, we construct a software tool using c-language.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.120-126
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• 2021

The importance of mathematics is emerging to create new values and secure competitiveness in an intelligent information society based on the Fourth Industrial Revolution. This study was conducted with the aim of improving the academic performance and increasing interest of electronics majors in mathematics subjects. In order to develop learners' mathematical capabilities in major fields that utilize mathematics that electronics majors do not prefer, we have proposed a new teaching method to promote employment in mathematics-based electronics fields. In addition, to enhance learners' self-directed learning, we developed teaching methods for efficient mathematics subjects with programming languages as tools in electronics engineering and applied them to real-world teaching sites to effectively cultivate academic performance improvement of majors. Finally, we conducted a survey and statistically analyze the effectiveness of the developed teaching methods to present effective operational measures for mathematics education, an essential tool in intelligent information technology.

• The Journal of Korean Association of Computer Education
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• v.16 no.4
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• pp.13-21
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• 2013

Recently, programming education is being actively performed in education field with development of educational programming language and teaching and learning methods for elementary students. However, programming education have limit to apply to the overall computer science curriculum, because it is performed by more than 5th grade and focused on the utilization of programming tools than problem-solving process. It is necessary to expand the range of students and educational content considered with problem-solving process for encouraging programming education in computer science. In this study, we suggest the easy-to-use programming tool for lower grade(1st grade) and robot programming task based on improvement of student's thinking ability. We use Tangible User Interface(TUI) for elementary student's(1st grade) convenience of programming and developed the robot programming task for improvement of logical thinking. As a result of this experiment, tangible programming tool can be used easily in elementary students(1st grade) and developed robot programming task is effective in improvement of logical thinking.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.125-144
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• 2023

Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.