• Journal of Gifted/Talented Education
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• v.22 no.3
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• pp.575-596
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• 2012

Students' perception on a science program for gifted was investigated. The whole program was designed in consistency and integrity based on the Autonomous Learner Model suggested by Betts & Kercher(1999). 7th, 8th and 9th grade students were enrolled in this program, offered by G Education Institute for Gifted(GEI) located in Seoul. A survey was done to ask students' perception regarding the effect of the program. The survey consisted of statements about the expected effects of the program and students were asked if they agreed with the statements. Most students strongly agreed that GEI's program has positive effects. Students replied that they learned useful and interesting science contents, enjoyed meaningful experience of cooperating with members in small groups, and were challenged by the inquiry tasks. They recognized that they were being trained to become autonomous learners. They also said that their choices and decisions were respected, which resulted in positive effects on their ability to negotiate or to inquire actively. These implies that Autonomous Learner Model had been successfully applied. Although it was not clear autonomy of students was fully grown, the possibility of becoming an autonomous learner was evident. Satisfaction level is higher for the older students, implying that the integrity in the program gave accumulating effect. Students response showed that three sub-programs of GEI, the classes of each subject, conference at the end of the year and autonomous learner training played equally important role for students to learn the process of scientific inquiry and autonomous learning. This was a positive sign that the strategies for scientific inquiry and autonomous learning were embedded and integrated deeply in the program. The results of current research suggests that the integrity of a program based on a specific education model for the gifted could provide better education environment for the gifted students.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.13-22
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• 2024

In the current epoch of educational technology (EdTech), the realization of a personalized learning system has become increasingly important. This is due to the growing diversity of today's learners in terms of backgrounds, learning styles, and abilities. Traditional educational methods that deliver the same content to all learners often fail to take this diversity into account. This paper identifies models that comprehensively analyze learners' characteristics, interests, and learning histories to meet the growing demand for learner-centered education. Based on these models, we have designed a personalized learning system. This system is structured to support autonomous learning tailored to the learner's current level and goals by identifying strengths and weaknesses based on the learner's learning history. In addition, the system is designed to extend necessary learning elements without changing its architecture. Through this research, we can identify the essential foundations for constructing a user-tailored learning system and effectively develop a system architecture to support personalized learning.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.110-115
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• 2021

With the era of the 4th Industrial Revolution, education on artificial intelligence is one of the important topics. However, since existing education is aimed at knowledge, it is not suitable for developing the active problem-solving ability and AI utilization ability required by artificial intelligence education. To solve this problem, we proposes PBL-based education method in which learners learn in the process of solving the presented problem. The problem presented to the learner is a completed project. This project consists of three types: a classification model, the training data of the classification model, and the block code to be executed according to the classified result. The project works, but each component is designed to perform a low level of operation. In order to solve this problem, the learners can expect to improve their computational thinking skills by finding problems in the project through testing, finding solutions through discussion, and improving to a higher level of operation.