• Journal of Korean Elementary Science Education
• /
• v.39 no.3
• /
• pp.369-381
• /
• 2020

This study aims to analyse the relationship between multiple intelligence and scientific creativity of science-gifted elementary students focusing on the subject of biology. For this, 37 science-gifted fifth-graders in the Science-Gifted Education Center at an Office of Education conducted a multiple intelligence test. In addition, researchers collected science-gifted students' results of scientific creativity activity at the botanical garden field trip. The main findings from this study are as follows: First, strong intelligence was logical-mathematical intelligence for gifted students, and weak intelligence was found to be naturalistic intelligence for them. Second, there was no significant correlation in the relationship between multiple intelligence and scientific creativity of science-gifted students. Third, as a result of independent two sample t-test for each intelligence and scientific creativity scores divided into the upper and lower groups, only verbal-linguistic intelligence statistically differed significantly at the level of p<.05 (t=2.13, df=35, p=0.04). Fourth, as a result of conducting a two-way analysis to see if there were any interaction effects, verbal-linguistic and visual-spatial, logical-mathematical and visual-spatial, logical-mathematical and bodily-kinesthetic, and visual-spatial and musical-rhythmic intelligence all showed significant values at the level of p<.05 level in interaction effects on originality element comprising scientific creativity. Fifth, an analysis of students with high naturalistic intelligence showed that their scores of scientific creativity tasks conducted at the botanical garden field trip were all lower. Based on the results of this study, this study discussed the implications of scientific creativity learning linking multiple intelligence in primary science education and gifted education.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.163-177
• /
• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Fisheries and Marine Sciences Education
• /
• v.12 no.1
• /
• pp.83-97
• /
• 2000

This article refers to the processions and the improvement of the 7th revised curriculum development for the Fisheries and Merchant Marine High School, published at Dec. 30, 1997. The general point of the 7th revised curriculum development was to cultivate creative Korean who will lead the epoch of globalization and information and to perform the learner-centered curriculum. Moreover, it defines the nature of Business High School not as completive but as continuing education. Based on this view, the improvment of 7th revised curriculum has been searched in varous sides. The group of general researchers and cooperators consisted of 12 members who were of university professors, teachers, related business men and executives in the administration branches, and the total researchers of 7th revised curriculum development were 90 members. The basic orientation of the research for the revised curriculum development was as following : The improvement of basic ability, job-analysis ability, integrity of theory and practice, acquisition of the certificate of national qualification, interrelation and cooperative role division between school and industrial fields, extension of self-decision ability of school and local society, protection of learner-selection right and maintaining close relations with the business-educational organization under life-long education system. Thus on the whole, the research for educational goals and contents, instructions, learning theory and evaluation is being processed with a high activity, based on the above mentioned plan of 7th revised curriculum development. At the same time, the methods and the models are being investigated. At last, it is to be noted that, in such as the 7th revised curriculum development research in this case, the effort should not be spared to harmonize the basic technological knowledge of the specialists in the Fisheries and Merchant Marine field and the cultural, liberal arts of personality education.

• The Journal of Bigdata
• /
• v.6 no.2
• /
• pp.71-84
• /
• 2021

Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

• The Journal of the Korea Contents Association
• /
• v.20 no.1
• /
• pp.233-244
• /
• 2020

The purpose of this study is to explore this music class activity and its effectiveness based on design thinking and using applications class. To this end, the effectiveness study was conducted based on the researchers' prior study of 'Development of Music learning program Using Applications Based on Design Thinking'. Under the study, two first graders who are attending P Middle School in Gyeonggi Province were selected as experimental(29) and control groups(29). The experimental group conducted the class using this program and the control group conducted a general music class. The pre-post-examination was conducted to find out the effects of this class on students' creativity, empathy, teamwork, and problem-solving skills. The course of the study was developed for seven weeks, a program pre-post-survey, and a response sample t-test was used to analyze the results. The study found that experimental groups show significant differences in creativity, empathy, cooperative spirit and problem-solving skills, while control groups that conducted general music classes had similar results in advance-postmortem. The group's students found that their ability to empathize with others in the problem situation was enhanced, their sense of rapid problem solving and achievement was high, and their ability to create creative ideas and enhance creativity in the process of solving the problem was improved. In the future, we look forward to using this music class activity in the field where new, creative, and diverse classroom models are needed.

• Geophysics and Geophysical Exploration
• /
• v.25 no.3
• /
• pp.140-161
• /
• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• Journal of Gifted/Talented Education
• /
• v.22 no.3
• /
• pp.619-637
• /
• 2012

The purpose of this study is to develop a new program for elementary math-gifted students by using 'Girih Tililng' and apply it to the elementary students to improve their math-ability. Girih Tililng is well known for 'the secrets of mathematics hidden in Mosque decoration' with lots of recent attention from the world. The process of this study is as follows; (1) Reference research has been done for various tiling theories and the theories have been utilized for making this study applicable. (2) The characteristic features of Mosque tiles and their basic structures have been analyzed. After logical examination of the patterns, their mathematic attributes have been found out. (3) After development of Girih tiling program, the program has been applied to math-gifted students and the program has been modified and complemented. This program which has been developed for math-gifted students is called 'Exploring the Secrets of Girih Hidden in Mosque Patterns'. The program was based on the Renzulli's three-part in-depth learning. The first part of the in-depth learning activity, as a research stage, is designed to examine Islamic patterns in various ways and get the gifted students to understand and have them motivated to learn the concept of the tiling, understanding the characteristics of Islamic patterns, investigating Islamic design, and experiencing the Girih tiles. The second part of the in-depth learning activity, as a discovery stage, is focused on investigating the mathematical features of the Girih tile, comparing Girih tiled patterns with non-Girih tiled ones, investigating the mathematical characteristics of the five Girih tiles, and filling out the blank of Islamic patterns. The third part of the in-depth learning activity, as an inquiry or a creative stage, is planned to show the students' mathematical creativity by thinking over different types of Girih tiling, making the students' own tile patterns, presenting artifacts and reflecting over production process. This program was applied to 6 students who were enrolled in an unified(math and science) gifted class of D elementary school in Daejeon. After analyzing the results produced by its application, the program was modified and complemented repeatedly. It is expected that this program and its materials used in this study will guide a direction of how to develop methodical materials for math-gifted education in elementary schools. This program is originally developed for gifted education in elementary schools, but for further study, it is hoped that this study and the program will be also utilized in the field of math-gifted or unified gifted education in secondary schools in connection with 'Penrose Tiling' or material of 'quasi-crystal'.

• The Journal of the Korea Contents Association
• /
• v.17 no.3
• /
• pp.305-318
• /
• 2017

The purpose of this study is improving the teachers' self-efficacy for pre-secondary music teachers. The research questions for this study were the improvement for teachers' self-efficacy for pre-secondary music teachers and the pre-secondary music teachers' perception about peer mentoring. In this study performed the interview and analyzed the in self-reflection journal in order to identify the improvement effect of teachers' self-efficacy and the participants' perception change in the peer mentoring. As the results from analyzing the change in participant's perception about peer mentoring the mentors had the opportunity to review previous learning contents and practice experiences while developing their team activity and for the mentees. Mentees said that they were given various help from the mentors' advices and their interactions and communication with mentors. From these results, it could identify that there was positive change in participant's perception about the peer mentoring. Based on these results, this study analyzed that it would need to require some chances for pre-secondary music teachers to be given some educational practice and field experience utilizing various teaching methods in order to improve their self-efficacy and the perception of peer mentoring.

• School Mathematics
• /
• v.10 no.1
• /
• pp.1-22
• /
• 2008

The purpose of this study is to search the effective teaching-learning program by considering how affect on formation of linear function using Excel. This study was based on qualitative case study. The teaching experiment using Excel executed with five 8th graders' students for second research content. Teaching experiment was performed for two classes. Collecting the data was conducted via observations and interviews with students. The data include audio and video recording of the students' work, students' worksheets and detailed field notes. The conclusions drawn from teaching experiment are as follows: First, when students explored relevancy content of function in Excel environment, formation of concept of function was facilitated by experiencing operation of algebraic formulas, tables and graphs. We could infer that formation of concept was effected by conjecture activity and iterative process of feedback through Excel environment. Second, the students explored the changes very interestingly making algebraic formulas and presenting tables and graphs. The students were familiarized with observation on algebraic formulas, graphs and tables concurrently. Also, they tried to look for general rules through inductive observation. According to this study, we noticed that exploration teaming environment using Excel could supplement paper-and-pencil environment.

• Journal of The Korean Association of Information Education
• /
• v.23 no.1
• /
• pp.55-64
• /
• 2019

Recently, entrepreneurship education has been emphasized in order to bring creative innovation to the fourth industrial revolution era. The purpose of this study is to suggest methods to promote practice by developing an educational program based on the maker education model to foster entrepreneurship of adolescents proposed in the previous study. For this purpose, we developed two kinds of programs and materials according to the subject and the level for the 3rd grader in middle school and first grader in high school. The final output was composed of the workbook for students, the guidebook for teachers, the PPT, and the worksheet for a team activity. The pilot workshop of the developed program was conducted for 14 middle school students. The final program was developed after being received advisories by three experts. This study is meaningful in that it can contribute to foster entrepreneurship education in the field by proposing specific programs required for practicing maker education for entrepreneurship.