• International conference on construction engineering and project management
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• 2024.07a
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• pp.1256-1263
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• 2024

In the realm of Architecture, Engineering, and Construction (AEC) education, various factors play a crucial role in shaping students' acceptance of the learning environments facilitated by visualization technologies, such as virtual reality (VR). Works on leveraging the heterogeneous educational information (i.e., pedagogical data, student performance data, and student survey data) to identify essential factors influencing students' learning experience and performance in virtual environments are still insufficient. This research proposed KnowLearn, an interactive learning assistant system, to integrate an educational knowledge graph (KG) and a locally deployed large language model (LLM) to generate real-time personalized learning recommendations. As the knowledge base of KnowLearn, the educational KG accommodated multi-faceted educational information from twelve perspectives, such as the teaching content, students' academic performance, and their perceived confidence in a specific course from the AEC discipline. A heterogeneous graph attention network (HAN) was utilized to infer the latent information in the KG and, thus, identified the perceived confidence, intention to use, and performance in a relevant quiz as the top three indicators that significantly influenced students' learning outcomes. Based on the information preserved in the KG and learned from the HAN model, the LLM enhanced the personalization of recommendations concerning adopting virtual learning environments while protecting students' privacy. The proposed KnowLearn system is expected to feasibly provide enhanced recommendations on the teaching module design for educators from the AEC domain.

• Journal of Elementary Mathematics Education in Korea
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• v.19 no.4
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• pp.609-624
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• 2015

It is well-known that every learner has his/her own learning style and the learning style has a great effect on his/her learning characteristics, processes and achievements. This study aims to induce some implications for designing the gifted mathematics programs which go with gifted students' learning styles. To do this, we applied the gifted mathematics program of nine lessons to 52 third grade gifted students and examined the characteristics of the programs according Kolb's learning style. To investigate the effect of the program, the pretest and posttest for applying the programs were taken and the results of two tests were analysed by t-test. As a result, the students of diverging style increased and the ones of converging style decreased, while there is little change in the accommodating style and the assimilating style. It was also shown that the average of the concrete experience(CE) of the subjects has increased significantly. This study also contains some pedagogical implications based on discussing about the results of analysis.

• Korean Journal of Applied Biomechanics
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• v.32 no.1
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• pp.1-8
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• 2022

Objective: This study proposes a methodology to analyze important variables that have a significant impact on the putting direction prediction using a machine learning-based putting direction prediction model trained with IMU sensor data. Method: Putting data were collected using an IMU sensor measuring 12 variables from 6 adult males in their 20s at K University who had no golf experience. The data was preprocessed so that it could be applied to machine learning, and a model was built using five machine learning algorithms. Finally, by comparing the performance of the built models, the model with the highest performance was selected as the proposed model, and then 12 variables of the IMU sensor were applied one by one to analyze important variables affecting the learning performance. Results: As a result of comparing the performance of five machine learning algorithms (K-NN, Naive Bayes, Decision Tree, Random Forest, and Light GBM), the prediction accuracy of the Light GBM-based prediction model was higher than that of other algorithms. Using the Light GBM algorithm, which had excellent performance, an experiment was performed to rank the importance of variables that affect the direction prediction of the model. Conclusion: Among the five machine learning algorithms, the algorithm that best predicts the putting direction was the Light GBM algorithm. When the model predicted the putting direction, the variable that had the greatest influence was the left-right inclination (Roll).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.272-275
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• 2022

Large-scale online platforms such as MOOCs-Massive Open Online Courses, which provide a variety of educational contents, have provided a learning environment that allows students to freely access and learn anytime and anywhere. Currently, the proportion of online lectures and home-based learning is increasing, and portfolio or experience-based learning such as bootcamp, field activities, and team project-based group learning are also being actively carried out for educational outcomes. At present, interest in nano or microdegree focused on core technology in units of hours or credits is increasing significantly because such strategic intensive education enables effective learning in terms of continuity and efficiency of education. In an era of large changes in job market due to the reorganization of the industrial structure by new technologies, intensive education in specialized new technology fields such as smart mobility, big data, and artificial intelligence is much more conducive to finding a job. With this reason it is attracting attention as an alternative to lifelong learning are receiving In this paper we propose an educational platform that can efficiently and effectively support the purpose learning for the personalized microdegree education in the online learning era.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.278-290
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• 2020

This study evaluated college students' virtual academic experience due to COVID-19. Based on Colaizzi's analysis method, data from advanced interviews with 15 students were analyzed. The results were as follows. The participants showed a desire for eye-level learning, frustration on unsatisfactory academic factors, gratefulness for the factors that enhance academic satisfaction, lonely fight with the shortcomings of online lectures, and the factors predicted by COVID-19, and aim to seek balance through health care. Based on the results, the students should be prepared to learn at an appropriate academic level. Second, the change should be sought to increase delivery and concentration in class. Third, students are motivated by the professor's efforts to communicate in class and their sincerity and passion. Fourth, cooperation between professors and learners is needed to develop a sympathetic and supportive classroom atmosphere. Fifth, until the cessation of COVID-19, the principle of virtual education should persist unless there are exceptional circumstances. These results, which suggested specific ways to increase satisfaction with virtual learning lectures, can be used as basic data for establishing effective virtual teaching directions.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.223-231
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• 2021

Humanity faces the 4th industrial revolution, many countries are providing systematic and continuous SW education to foster talent with AI capabilities. On the other hand, there are high concerns that the SW gap will widen and polarize as domestic reality does not provide systematic and continuous SW education to learners. Against this background, this study started to investigate the influence of learners' SW experience on SW education. As a result of the study targeting science and engineering students, the effect of SW experience on SW education was significant. With theses results, it is expected that various discussions will be actively conducted so that systematic and continuous SW education can be provided in elementary and secondary schools.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.417-426
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• 2024

In general, the implementation of machine learning requires prior knowledge and experience with deep learning models, and substantial computational resources and time are necessary for data processing. As a result, machine learning encounters several limitations when deployed on embedded processors. To address these challenges, this paper introduces a novel approach where a genetic algorithm is applied to the convolution operation within the machine learning process, specifically for performing a selective convolution operation.In the selective convolution operation, the convolution is executed exclusively on pixels identified by a genetic algorithm. This method selects and computes pixels based on a ratio determined by the genetic algorithm, effectively reducing the computational workload by the specified ratio. The paper thoroughly explores the integration of genetic algorithms into machine learning computations, monitoring the fitness of each generation to ascertain if it reaches the target value. This approach is then compared with the computational requirements of existing methods.The learning process involves iteratively training generations to ensure that the fitness adequately converges.

• Journal of Korean Elementary Science Education
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• v.40 no.3
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• pp.407-419
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• 2021

This study investigated the perception of science philosophy education targeting 150 elementary school teachers in metropolitan cities and provinces. The questionnaire survey on the perception of the philosophy of science education was composed of a 5-point Likert scale based on the interest and experience of the philosophy of science, the reason for difficulty in using it, and the introduction method, the expected effect. As a result of the survey, elementary school teachers' awareness of the interest and necessity of the philosophy of science was generally high, while the experience of learning and teaching the philosophy of science was low. In addition, to the reason why it was difficult to utilize the philosophy of science, teachers answered that there was insufficient teacher training and development of teaching and learning methods. As a way to introduce the philosophy of science in science education, it was thought that it was necessary to combine the concept learning and inquiry method, and elementary school teachers' perception of the expected effect of using the philosophy of science was generally high. The results of this study are meaningful in that they provide basic data on the direction of the introduction of the philosophy of science in elementary science education.

• The Journal of Korean Philosophical History
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• no.56
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• pp.209-238
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• 2018

The purpose of this research is to analyze characteristics of the method of education or learning reflected in the teacher-student relationship in On Haeng Lok By Toe-gye and explore their relevance to modern education. By writing various works and conversing with his students, Toe-gye devoted himself in the education of the traditional Confucian principles. Specially, he taught his students based on two Confucian educative principles, namely Shim Deuk(心得) and Goong Haeng(躬行). Judging from this, Toe-gye can be seen as someone who tries to fulfill the role of teacher as dictated in the educative principles of the Confucianism. In Confucianism, teacher is responsible for forming a well-rounded view on life in student, rather than simply transmitting knowledge. As such, the teacher was supposed to find a harmonious way to create something new based on what was inherited from the past generation and try to do his best in learning new things himself and teaching his students. These Toe-gye managed to do successfully, earning his students' trust and respect. Being moved and inspired by their teacher, the students continued their intellectual pursuit. This relationship between Toe-gye and his students can be analyzed from the perspective of education method and discussed in terms of cognitive learning and adult learning. In terms of cognitive learning, the education method reflected in the relationship is similar to potential learning, insight learning, and imitation learning. In terms of adult learning, it is similar to self-directed learning and communicative learning.!

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.425-432
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• 2020

This study was to identify the educational needs for mental health nursing among undergraduate nursing students, prioritizing the areas where require extensive convergence learning via simulation. One hundred and forty students completed the survey where data accrued from between March-May 2020. The educational needs for mental health nursing and nursing care schizophrenia patients were assessed using a self-reporting questionnaire, which included 19 and 15 items, respectively. Additional three essay questions were used to obtain information regarding previous simulation education experience. Higher educational needs in nursing care for schizophrenia were identified and the highest-priority need is communication skills. Factors, including realistic experience with standardized patients, teamwork, and feedback from the lecturers, affect positive experiences in mental health nursing simulation. The findings suggest that educational programs to improve communication skills are necessary for better mental health nursing competency. Well-designed and convergence based simulation programs providing real-like clinical experience would ensure optimal learning outcomes.