• Journal of Integrative Natural Science
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• v.12 no.4
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• pp.122-126
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• 2019

In this paper, we propose a simple and efficient retrieval technique using the feature value of the corner region, which is one of the shape information attributes of images. The proposed algorithm extracts the edges and corner points of the image and rearranges the feature values of the corner regions doubly, and then measures the similarity with the image in the database using the correlation of these feature values as the feature vector. The proposed algorithm is confirmed to be more robust to rotation and size change than the conventional image retrieval method using the corner point.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.459-469
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• 2021

In this paper, a case study of basic data science practice education for field teachers and pre-service teachers was studied. In this paper, for basic data science education, spreadsheet software was used as a data collection and analysis tool. After that, we trained on statistics for data processing, predictive hypothesis, and predictive model verification. In addition, an educational case for collecting and processing thousands of public big data and verifying the population prediction hypothesis and prediction model was proposed. A 34-hour, 17-week curriculum using a spreadsheet tool was presented with the contents of such basic education in data science. As a tool for data collection, processing, and analysis, unlike Python, spreadsheets do not have the burden of learning program- ming languages and data structures, and have the advantage of visually learning theories of processing and anal- ysis of qualitative and quantitative data. As a result of this educational case study, three predictive hypothesis test cases were presented and analyzed. First, quantitative public data were collected to verify the hypothesis of predicting the difference in the mean value for each group of the population. Second, by collecting qualitative public data, the hypothesis of predicting the association within the qualitative data of the population was verified. Third, by collecting quantitative public data, the regression prediction model was verified according to the hypothesis of correlation prediction within the quantitative data of the population. And through the satisfaction analysis of pre-service and field teachers, the effectiveness of this education case in data science education was analyzed.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.691-704
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• 2021

The development of AI technology has brought about a big change in our lives. The importance of AI and data education is also growing as AI's influence from life to society to the economy grows. In response, the OECD Education Research Report and various domestic information and curriculum studies deal with data literacy and present it as an essential competency. However, the definition of data literacy and the content and scope of the components vary among researchers. Thus, we analyze the semantic similarity of words through Word2Vec deep learning natural language processing methods along with the definitions of key data literacy studies and analysis of word frequency utilized in components, to present objective and comprehensive definition and components. It was revised and supplemented by expert review, and we defined data literacy as the 'basic ability of knowledge construction and communication to collect, analyze, and use data and process it as information for problem solving'. Furthermore we propose the components of each category of knowledge, skills, values and attitudes. We hope that the definition and components of data literacy derived from this study will serve as a good foundation for the systematization and education research of AI education related to students' future competency.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.1
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• pp.76-84
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• 2009

This paper proposes a SOC platform which is eligible for education and application SOC design. The platform, fully synthesizable and reconfigurable, includes the OpenRISC embedded processor, some basic peripherals such as GPIO, UART, debug interlace, VGA controller and WISHBONE interconnect. The platform uses a set of development environment such as compiler, assembler, debugger and RTOS that is built for HW/SW system debugging and software development. Designed SOC, IPs and Testbenches are described in the Verilog HDL and verified using commercial logic simulator, GNU SW development tool kits and the FPGA. Finally, a multimedia SOC derived from the SOC platform is implemented to ASIC using the Magnachip cell library based on 0.18um 1-poly 6-metal technology.

• The Journal of Korean Association of Computer Education
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• v.22 no.4
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• pp.11-20
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• 2019

This research aims to investigate elementary school teacher's perception and needs of computer and information literacy education to provide basic materials so that computer and information literacy education converges with related subject and can be done in various educational contexts. In order to achieve the goal for this research, we conducted an online questionnaire survey on the current status of teachers, the perception and status of convergence education for computer and information literacy, and the needs for convergence education for computer and information literacy. As a result of the analysis, when the teacher majored in computer and information education or had experience in software education, the percentage of respondents who said that it is possible to converge for computer and information literacy is high. Also, It was found that the burden of following the class progress according to the curriculum was high. In the school environment, preparation for software tool was found to be insufficient. we suggested the strategic implications in terms of education direction, teacher training, education program, and learning tool based on the analysis results.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.53-60
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• 2018

In this study we have developed a Python education program that can be applied to students who have studied block-based coding. We have developed a Python education program based on the extracted the learners' level of block-based coding by analyzing the programs and the textbooks. We extracted the grammar of the block-based coding and constructed the curriculum. Then, the Python education program was composed by 16 hours. After reviewing the appropriateness of the education program through expert validation, it was concluded that the developed Python education program is suitable for applying to learners of block-based coding. We expect that proposed program will be effectively applied as basic resources to learn script coding in class.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.77-84
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• 2021

The purpose of this study is to propose AI maker coding education as a way to improve computational thinking(CT), which is an essential competence for problem-solving capability in modern society, and to analyze the effectiveness of this education on improving CT in elementary school students. For the research, 5 students from 4th graders and 5 students from 6th graders were recruited, and AI maker coding education was planned in 8 sessions to form classes from basic block coding and maker education to real-life problem solving. To analyze the effectiveness of AI maker coding education, pre- and post-CT examinations were performed. The test results confirmed that AI maker coding education had a significant effect on "abstraction", "algorithm", and "data processing" in the five CT components, and confirmed that there was no correlation in "problem resolution" and "automation". Overall, the average score of all students increased, and the deviation between students decreased, confirming that AI maker coding education was effective in improving CT.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.441-449
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• 2019

With the introduction of the 2015 revised curriculum, software education became mandatory in elementary school. The practical subject in the content for the software education consists of information ethics, algorithms, programming, and computer science. Especially, elementary school encourages the unplugged activities. Unplugged activities are preferred among the teachers in the education field as a teaching-learning method. However, those teachers pointed out that the lack of suitable unplugged activity materials was the biggest challenge. In addition, it was pointed out that the existing materials were not suitable for achievement standards, and there are many simple playing-oriented educations that are not linked to computing activities. In this study, we developed an unplugged activity-oriented robot that can be used for the elementary students to learn the basic control structure suggested in the achievement criteria SW education and to develop creative problem solving ability through various activities using sensors. The effectiveness was verified through the software class using the developed robot in this study.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.463-471
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• 2020

Humanity faces the fourth industrial revolution, a time of technological revolution by the collaboration of various industries including the fields of artificial intelligence(AI) and big data. Many countries are focused on fostering AI talent to prevail in the coming technological revolution. While Korea also provides some strategies to enhance the cultivation of AI talent, it is still difficult for Korean undergraduate students to get involved in AI studies. Through on the implementation of 'Big data analysis based AI education', which allows an easier approach to AI education, this paper examined the changes in the attitudes of undergraduate students regarding general AI education. 'Big data analysis based AI education' was provided at undergraduate level for 5.5 weeks (15 hours). The attitudes of undergraduate students were analyzed by pre-postmortem. The results showed there was a significant improvement in confidence and self-directed in regard to receiving AI education. With these results, further active research to develop basic AI education that also increases confidence and self-initiative can be expected.

• Journal of Integrative Natural Science
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• v.12 no.4
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• pp.105-115
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• 2019

In this paper, a prediction system is proposed to control the brightness of smart street lamps by predicting the moving path through the reduction of consumption power and information of pedestrian's past moving direction while meeting the function of existing smart street lamps. The brightness of smart street lamps is adjusted by utilizing the walk tracking vector and soft hand-off characteristics obtained through the motion sensing sensor of smart street lamps. In addition, the motion vector is used to analyze and predict the pedestrian path, and the GPU is used for high-speed computation. Pedestrians were detected using adaptive Gaussian mixing, weighted difference imaging, and motion vectors, and motions of pedestrians were analyzed using the extracted motion vectors. The preprocessing process using linear interpolation is performed to improve the performance of the proposed prediction system. Fuzzy prediction system and neural network prediction system are designed in parallel to improve efficiency and rough set is used for error correction.