• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.185-187
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• 2022

Because of the rapid change in the educational paradigm in the Fourth Industrial Revolution Era, Artificial Intelligence (AI) Education is becoming increasingly important today. The 2022 Revised Curriculum focuses on AI Education that can cultivate the fundamental skills and competencies needed in the future society. The following are the directions presented in this study for improving computational thinking and mathematical thinking in AI Education in elementary and secondary schools. First, studying teaching principles that allow students to understand AI concepts and principles and develop their ability to solve real-life problems is necessary in terms of computational thinking skills education. Second, an educational program is required for students to acquire algorithms using formulas and learn principles in the process of computers thinking like humans as part of their mathematical thinking ability to understand AI. A study on expectations through the analysis of competent learning effects that may arise from the relationship between instructors and learners was proposed as a future research project.

• Journal of The Korean Association of Information Education
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• v.22 no.6
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• pp.689-699
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• 2018

The purpose of this study was to investigate the prediction of self-regulated learning, GRIT and parents support on computational thinking and learning satisfaction in online software education. The participants were 71 elementary students who attended to an online software education which K university offered in Spring 2018. The 63 of cases were used to analyze by SPSS. The key findings were as follows: First, self-regulated learning and GRIT significantly predicted computational thinking. Second, self-regulated learning and GRIT significantly predicted learning satisfaction. This research suggested the implications for computational thinking and learning satisfaction in online software education.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.751-759
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• 2021

This study developed an artificial intelligence education program using localized public data as an educational method for improving computing thinking skills of elementary school students. According to the ADDIE model, the program design was carried out based on the results of pre-requisite analysis for elementary school students, and textbooks and education programs were developed. Based on localized public data, the training program was constructed to learn the principles of artificial intelligence using machine learning for kids and scratches and to solve problems and improve computational thinking through abstracting public data for purpose. It is necessary to put this training program into the field through further research and verify the change in students' computational thinking as a result.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.327-335
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• 2021

This study verified the effectiveness of machine learning education programs focused on data labeling as an educational method for improving computational thinking of elementary school students. The education program was designed and developed based on the results of a preliminary demand analysis conducted on 100 elementary school teachers. In order to verify the effectiveness of the developed education program, 17 sixth-grade students attending K Elementary School were given 2 classes per day for a total of 6 weeks. In order to measure the effect of the training on improving computational thinking, the educational effects were analyzed by conducting pre-post-inspection using the "Beaver Challenge". According to the analysis, machine learning education focused on data labeling contributed to improving computational thinking of elementary school students.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.315-320
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• 2021

In order to prepare for future social changes, SW·AI education is essential. In this paper, after conducting non-face-to-face SW·AI education for pre-service teachers, the effectiveness of SW education before and after education was measured using the measurement tool on the software educational effectiveness. As a result of the analysis, the overall average and the average of the 'computational thinking' and 'SW literacy' domains increased significantly, and the difference between the averages before and after education was statistically significant in decomposition, pattern recognition, abstraction, and algorithm, which are sub domains of 'computational thinking'. Through SW·AI education, students not only recognize the necessity of SW education and the importance of computational thinking, but also understand the process of decomposing information, recognizing and extracting patterns, and expressing problem-solving processes. It can be seen that non-face-to-face SW·AI education has the effect of improving computational thinking and SW literacy beyond recognizing the importance of SW.

• Proceedings of The KACE
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• 2017.08a
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• pp.107-109
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• 2017

다가올 미래 사회와 4차 산업혁명 시대에는 창의성(Creation)과 융합(Convergence)을 기반으로 다양한 분야에서의 문제해결력이 요구되며, 컴퓨팅 사고력(CT, Computational Thinking)은 문제 해결을 위한 필수 사고로 인식되고 있다. 이러한 시대적 흐름에 발맞춰, 성균SW교육원(SSEN)에서는 다른 전공을 가진 학생에게도 컴퓨팅 사고력 중심의 SW기초교육을 실시하고 있다. 본 논문에서는 성균SW교육원에서 시행하는 비전공자를 위한 컴퓨팅사고력 중심의 SW기초교육 체계에 대해 소개하고, 비전공자 SW교육에 대해 앞으로 나아갈 방향을 제시한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.209-210
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• 2017

본 연구에서는 초등에서 알고리즘 교육의 방법으로 사용되는 언플러그드 활동에 순서도를 활용하는 방안을 제안한다. 소프트웨어 교육의 기본적인 방향은 컴퓨팅 사고력을 기반으로 문제를 해결하는 역량을 기르고자 하는 것[1]이지만, 현재는 교육용 프로그래밍 언어의 학습에 치우쳐 있거나 알고리즘 교육이 제대로 이루어지고 있지 않다. 언플러그드 활동에 순서도를 활용함으로써 알고리즘 영역의 교육을 강화하고 균형 잡힌 컴퓨팅 사고력 함양에 도움이 될 것이다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.223-226
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• 2018

2015 개정 교육과정은 바른 인성을 갖춘 창의융합형 인재를 양성하는 데에 교육과정 구성의 중심을 두고, 교육과정 구성에 다양한 학생 참여형 수업을 활성화하여 자기주도적 학습능력을 기르고 학습의 즐거움을 경험하도록 하고 있다. 소프트웨어 교육을 통해 이를 실현할 수 있는 방법은 재미있고 흥미를 끄는 학습내용의 구성과 학습 방법이라 본다. 이에 학습자들의 흥미를 끄는 앱을 제작함에 유대인의 교육방식인 하브루타를 적용하여, 학습자 참여 중심의 자기주도 학습을 설계하고 이를 통해 컴퓨팅 사고력을 신장시키고 바른 인성을 갖춘 창의 융합형 인재를 양성할 수 있는 하나의 방법을 제안하고자 한다.

• The Journal of Korean Association of Computer Education
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• v.22 no.6
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• pp.43-55
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• 2019

In the Fourth Industrial Revolution, a super-intelligent and super-connected society has arrived. Software is an important part of the core technologies of the Fourth Industrial Revolution. The ability to solve problems through software requires software education in that it is a core competency that everyone should have. Software education aims to improve Computational Thinking, which is the ability to solve problems through programming. Until now, most problem-solving programming learning models follow the traditional method of development: Waterfall model (Analysis-Design-Development-Test). In this model, if there is a problem in the preceding step, That could be found in the test phase. This takes a considerable amount of time and effort to find a solution to the problem and can be a burden on the programming learning. In this study, we proposed a Test-Driven Problem-Solving learning model using TDD (Test Driven Development) as Agile development method, and reviewed the appropriateness of the model through experts review. The verification results of the model showed positive evaluation results. In particular, the learning phase configuration of the model, helping in programming learning, helping of Computational Thinking improvement showed high rating, it is determined that there will be positive effects on Computational Thinking improvement through problem-solving programming learning when applying future learning.

• The Journal of Korean Association of Computer Education
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• v.20 no.2
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• pp.13-21
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• 2017

The purpose of this study is to verify the effect of the design - oriented model (NDIS) for enhancing learner's computing thinking in SW education. NDIS is a project-based learning model in which learners find real-life problems, analyze their needs, and design and implement them. In order to verify the effectiveness of NDIS, we experimented with middle level G education university students who had previously experienced SW education class. The traditional project model was applied to the control group and the NDIS model based on CT was applied to the experimental group. The experimental group showed a higher CT narrative performance evaluation score than the comparative group, which showed a significant difference. In addition, students showed a positive perception of self-confidence and CT improvement in solving real-life problems using computing.