• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.43-54
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• 2019

Currently, a majority of artificial intelligence is used to secure big data; however, it is concentrated in a few of major companies. Therefore, automatic data augmentation and efficient learning algorithms for small-scale data will become key elements in future artificial intelligence competitiveness. In addition, it is necessary to develop a technique to learn meanings, correlations, and time-related associations of complex modal knowledge similar to that in humans and expand and transfer semantic prediction/knowledge inference about unknown data. To this end, a neural memory model, which imitates how knowledge in the human brain is processed, needs to be developed to enable knowledge expansion through modality cooperative learning. Moreover, declarative and procedural knowledge in the memory model must also be self-developed through human interaction. In this paper, we reviewed this essential methodology and briefly described achievements that have been made so far.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.589-594
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the losed loop problem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and efficiently. This algorithm is a hybrid type of using both declarative description (constraint represention) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• Management Science and Financial Engineering
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• v.5 no.1
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• pp.27-49
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• 1999

WebME is an Web-based integrated modeling environment that implements a multi-facetted modeling approach to mathematical model representation and management. Key features of WebME include the following: (i) sharing of modeling knowledge on the Web, (ii) a user-friendly interface for creating, maintaining, and solving models, (iii) independent management of mathematical models from conceptual models, (iv) object-oriented conceptual blackboard concept, (v) multi-facetted mathematical modeling modeling, and (vi) declarative representation of mathematical knowledge. This paper presents details of design and implementation issues that were encountered in the development of WebME.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.116-123
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• 1997

We have already presented the constraint satisfaction algorithm which could solve the closed loop porblem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and effi- ciently. This algorithm is a hybrid type of using both declarative description (constraint representation) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• Journal of The Korean Association For Science Education
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• v.18 no.2
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• pp.149-160
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• 1998

The purpose of this study was to analyze the 6th national secondary science curriculum and classroom practices to collect the basic data for developing secondary science program focusing on creative problem-solving ability. The creative problem-solving ability was conceptualized as an active process of producing new solutions to problems and consisted of five components: general knowledge, domain-specific knowledge, motivation, divergent thinking and critical thinking. The research questions were generated as follows: (1) Whether creative problem-solving elements-domain specific knowledge(declarative knowledge and inquiry methods) were included or not in the 6th secondary science curriculum, textbooks and teacher's guide? If so, how are they represented? (2) Whether the teachers tried to enhance divergent and critical thinking of their students. Through content analyses, observations and interviews, these research questions were answered as follows: (1) Inquiry methods, which are important to develop creative problem-solving abilities in science, were underestimated in comparison with declarative knowledge. In other words. inquiry methods were regarded only as tools to understand the scientific concepts and principles. (2) It was hard to find the situations which teachers provided opportunities for divergent and critical thinking to their students. Based on these results, the followings were recommended: (1) Inquiry methods should be regarded as a goal not as a tool and be used to acquire inquiry methods themselves. (2) Teachers should not stick to the prescribed inquiry methods prescribed in the textbook, but to give opportunities for thinking various kinds of inquiry methods to improve divergent and critical thinking.

• Journal of Korean Elementary Science Education
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• v.38 no.3
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• pp.395-405
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• 2019

The purpose of this study is to analyze the process of creative science problem solving (CSPS) in elementary school students. To do this, 6 graders (n=9) at a elementary school in Seoul were participated. In this study, fixed eye-tracker with 250 Hz sampling and observation camera were used. The results of this study, the students with higher ability to solve creative science problems had a slower saccade, and had more visual attention on core clues and a greater number of eye changes. Therefore, students with higher ability to solve creative science problems showed more effective eye movement and faster information processing to solve problems. The CSPS types of elementary students were classified as 'declarative knowledge type', 'procedural knowledge type', 'conditional knowledge type', 'knowledge lack type'. Because each type appears to be complementary, CSPS process for elementary students who have integrated the four types was devised. The results of this study can be used as basic data for understanding elementary school students' CSPS and will help to develop and guide creative science teaching and learning programs useful to elementary school students and science gifted students.

• Journal of The Korean Association For Science Education
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• v.14 no.2
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• pp.143-158
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• 1994

This study aims to identify the characteristics of gas phase problem solving of college freshmen. Four students were participated in this study and solved the problem by using think-aloud method. The thinking processes were recorded and transferred into protocols. Problem solving stage, the ratio spended in each solving stage, solving strategy, misconceptions, and errors were identified and discussed. The relationships between students' belief system about chemistry problem solving and problem solving characteristics were also investigated. The results were as follows: 1. Students felt that chemical equation problem was easier than word problem or pictorial problem. 2. When students had declarative knowledge and procedural knowledge required by given problem, their confidence level and formula selection were not changed by redundunt information in the problem. 3. When the problem seemed to be difficult, students tended to use the Means-End or Random strategy. 4. In complicated problems, students spent longer time for problem apprehension and planning. In familiar problems, students spent rather short time for planning. 5. Students spent more time for overall problem solving process in case of using Means-End or Random strategy than using Knowledge-Development strategy.

• Journal of Korean Elementary Science Education
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• v.35 no.2
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• pp.253-264
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• 2016

The purpose of this study was to investigate implications of self-directed learning experiments in elementary science education through understanding elementary school students' awareness of their experiences in self-directed learning experiments. Twenty students joined the school science club voluntarily and conducted self-directed learning experiments. We collected data through observation of the experiments, interviews, and questionnaires. The students who participated in the club showed high satisfaction with self-directed learning experiments. The participants were aware that their scientific interest and knowledge, and the confidence in conducting experiments were increased. The students felt positive about the inquiry process of conducting self-directed learning experiments with their own subjects. They also felt a sense of achievement in attempting their experiments in defiance of several failures. The participants realized that the self-directed inquires led to increased declarative and procedural knowledge of science. The students stated that they had some difficulties in coping with the different results contrary to expectations and preparing laboratory materials and instruments. Nonetheless, they showed the promotion of their scientific literacy during overcoming those difficulties. We suggest that self-directed learning experiments can be a more effective way in science learning to make students experience the nature of science than existing school experiments. This can be implemented through a creative experience activities such as science clubs.

• Journal of the Korean Society of Earth Science Education
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• v.3 no.1
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• pp.18-27
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• 2010

The purpose of this study is to investigate effects of instruction with stories on elementary school students' science learning and memory. For the purpose, this researcher sampled 3 classes in their 3th grade from an elementary school. Out of the three classes, two were designated as the comparative group consisting of 70 students and the other, the experimental group, 32 students. The former group was applied instruction treatment under the 7th national curriculum of education. The other group was instructed with a story book that contained stories students already knew which were somewhat rearranged to comply with contents of a relevant curricular course. Results of the study can be described as follows. First, academic achievement test was made immediately after the treatment to show that the experimental group was significantly higher in scores for memory and understanding in the section of 'Finding Constellations' that the other group. Second, the two groups' academic achievements in relation to the section, 'Finding Constellations' were tested 3 months after the treatment to show that the experimental group was significantly higher in scores for memory and understanding than the comparative group. Such achievements within the groups were tested 3 months after the treatment to find that both of the two groups didn't show statistically significant differences.

• Journal of the Korean earth science society
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• v.24 no.6
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• pp.524-532
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• 2003

The purpose of the present study was to test the hypothesis that student's abductive reasoning skills play an important role in the generation of hypotheses on pendulum motion tasks. To test the hypothesis, a hypothesis-generating test on the pendulum motion and a prior knowledge test about the length of the pendulum motion were developed and administered to a sample of 5th grade children. A significant number of subjects who have the prior knowledge about the length of the pendulum motion failed to apply that prior knowledge to generate a hypothesis on a swing task. These results showed that students' failure in hypothesis-generating was related to their deficiency in abductive reasoning ability, rather than the simple lack of prior knowledge. Furthermore, children's successful generating hypothesis should be required their abductive reasoning skills as well as prior knowledge. Therefore, this study supports the notion that abductive reasoning ability beyond prior knowledge plays an important role in the process of hypothesis-generation. This study suggests that science education should provide teaching about abdctive reasoning as well as scientific declarative knowledge for developing children's hypothesis-generating skills.