• Journal of The Korean Association of Information Education
• /
• v.22 no.1
• /
• pp.81-89
• /
• 2018

Because the success of SW education depends on teachers' competences and understanding, many universities of education are carrying out SW education for pre-service teachers. The purpose of this research is to analyze the current status of pre-service teachers' programming learning experiences and understanding of curriculum and educational effects related to SW education. The participants were 294 junior and senior students enrolled in a university of education. In relation to 'programming learning experiences', many responded positively in terms of interest, usefulness and willingness to learn. However, many were not satisfied with their programming experiences, felt difficulty in programming, and evaluated their programming abilities as low. For the 'understanding of SW education curriculum', many recognized the necessity of SW education and understood that the allocated time was insufficient. Both positive and negative opinions were reported concerning the fact that SW education is conducted in practical arts. In comparison, many did not understand well about the concept and characteristics of SW education and the details of the curriculum. In relation to the 'understanding of SW education effects', many understood positively about all the effects presented in the questionnaire including problem solving abilities and creativity. In addition, significant differences were found among pre-service teachers' major categories regarding the programming learning experiences and the understanding of SW education curriculum and effects. Based on the results of the research, suggestions were made for the improvement of the pre-service teachers' SW education program.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.5
• /
• pp.189-195
• /
• 2021

This paper discusses choice of loans problem(CLP) that is to minimize annual payment from which bank's borrows in multi-banks multi-nations with distinct interests. For the CLP, there is impossible to obtain the optimal solution actually without the help of mathematical software package as linear programming(LP). This paper applies the method used in transportation problem(TP) that finds initial feasible solution with selects minimum interest first, least cost method(LCM), to CLP. Result of experiment, the proposed algorithm can be obtains the optimal solution with at most two exchange optimization for LCM's initial feasible solution.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.5
• /
• pp.203-211
• /
• 2024

Utilizing programming languages for data visualization can enhance the efficiency and effectiveness in handling data volume, processing time, and flexibility. However, practice is required to become proficient in programming. Therefore public data-based the problem bank was developed to practice data visualization in a programming automatic assessment system. Public data were collected based on topics suggested in the curriculum and were preprocessed to make it suitable for users to visualize. The problem bank was associated with the mathematics curriculum to learn various data visualization methods. The developed problems were reviewed to expert and pilot testing, which validated the level of the questions and the potential of integrating data visualization in math education. However, feedback indicated a lack of student interest in the topics, leading us to develop additional questions using student-center data. The developed problem bank is expected to be used when students who have learned Python in primary school information gifted or middle school or higher learn data visualization.

• Journal of The Korean Association of Information Education
• /
• v.23 no.2
• /
• pp.189-196
• /
• 2019

Artificial intelligence has begun to be used in various parts of our lives, and recently its sphere has been expanding. However, students tend to find it difficult to recognize artificial intelligence technology because education on artificial intelligence is not being conducted on elementary school students. This paper examined the teaching programming language and artificial intelligence teaching methods, and looked at the changes in students' attitudes toward artificial intelligence technology by conducting education on artificial intelligence. To this end, education on block-type programming language-based artificial intelligence technology was provided to students' level. And we looked at students' attitudes toward artificial intelligence technology through a single group pre-postmortem. As a result, it brought about significant improvements in interest in artificial intelligence, possible access to artificial intelligence technology and the need for education on artificial intelligence technology in schools.

• Water for future
• /
• v.14 no.2
• /
• pp.63-69
• /
• 1981

This Study is aimed at optimal sequencing of water supply projects for water demand from the application in water resources field of dynamic programming because a minimum present cost strategy for investment in water supply projects plays an important part of installation of some projects. In analysis, the relationships of the future water demand and numerous possible independent projects that are expected to meet water requirements up to some future data in Daegu city were used and future water demand were estimated from the exponential function method, the method used by the Water Works Bureau of Daegu City government which is a kind of geometric progression method and the mean value of these two methods. The results showed that the optimal sequencing of water supply projects using Dynamic Programming was reasonable and the changing of the estimation method of future water demand made a difference among optimal sequence of projects while the changing of annual rate of interest had influenced on present value cost only. In general, the best sequence for constructing the seven projects was the order of D-E-G-F-C-B-A, with the corresponding period for 33-38 years.

• Journal of The Korean Association of Information Education
• /
• v.22 no.6
• /
• pp.651-660
• /
• 2018

To determine the educational effects of collaborative story creation activities using the Entry programming language, we instructed first year students at the national university of education on these activities for three weeks and analyzed the changes in their software (SW) education capacity and story creating ability. The completed analysis showed no significant changes in the students' SW education capacity as related to information literacy, computational thinking, and learner competency; however, the students' ability to create stories increased significantly. Although students struggled to learn story creation using Entry, they gradually found that the activities were useful and their interest in creating stories grew. Therefore, we suggest expanding the number of subject curriculum activities using Entry in order to improve SW education capacity as well as the subject capacity for student teachers.

• Journal of The Korean Association of Information Education
• /
• v.26 no.5
• /
• pp.407-416
• /
• 2022

Although environmental education has been more important due to global extreme weather and natural desasters, environmental topics are covered by several other subjects because it is not an independent subject in elementary school and they need to distribute more class hours to cover proper amount of environmental content. This study is performed to develop method to integrate environmental education and software education in elementary school. This method helps students to learn topics about recycling by using Artificial Intelligence programming and Artificial Intelligence also helps students to practice recycling in virtual reality. A new teaching and learning module(Problem Recognition→Machine Learning↔Use of AI→Collaboration) is adopted for the learning procedure and more than 80 % of the students replied positively to the survey about the interest on integrated learning, understanding of environmental education, understanding of Artificial Intelligence, further learning on Artificial Intelligence programming.

• Structural Engineering and Mechanics
• /
• v.91 no.6
• /
• pp.643-656
• /
• 2024

The prediction of the moment rotation behavior of semi-rigid connections has been the subject of extensive research. However, to improve the accuracy of these predictions, there is a growing interest in employing machine learning algorithms. This paper investigates the effectiveness of using Multi-gene genetic programming (MGGP) to predict the moment-rotation behavior of flush-end plate connections compared to that of artificial neural networks (ANN) and previous studies. It aims to automate the process of determining the most suitable equations to accurately describe the behavior of these types of connections. Experimental data was used to train ANN and MGGP. The performance of the models was assessed by comparing the values of coefficient of determination (R²), maximum absolute error (MAE), and root-mean-square error (RMSE). The results showed that MGGP produced more accurate, reliable, and general predictions compared to ANN and previous studies with an R² exceeding 0.99, an RMSE of 6.97, and an MAE of 38.68, highlighting its advantages over other models. The use of MGGP can lead to better modeling and more precise predictions in structural design. Additionally, an experimentally-based regression analysis was conducted to obtain the rotational capacity of FECs. A new equation was proposed and compared to previous ones, showing significant improvement in accuracy with an R² score of 0.738, an RMSE of 0.014, and an MAE of 0.024.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.620-626
• /
• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• Journal of The Korean Association of Information Education
• /
• v.22 no.4
• /
• pp.419-425
• /
• 2018

The national curriculum includes the problem solving process, algorithms, and programming of SW education. The education using robots is one of attractive alternatives for students who have no interest of SW or are poor at programming. We have developed a courseware using robots for SW education based on paper art activities with narrative storytelling to enhance students' creative thinking and problem solving within limitation of class time in schools. We apply the courseware and obtained the result of pre and post-test on the creative problem solving ability of third graders in the elementary school The four factors of creative problem solving have shown significantly increase. In addition, it had an significant effects for understanding robot technology and for learning attitude using robots of SW or programming.