• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.125-131
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• 2020

As technology advances, the importance of software education is increasing. Accordingly, interest in information subjects is increasing, but intending elementary learners to show algorithms only for specialized IT skills that could spoil the interest. In this paper for the elementary school students, through the four stages, 2015 revision curriculum analysis, creating of training program development operating plans, applying programs for the targeting students and analysis of results and evaluation, using Rich Picture technique which is various tools such as pictures and speech bubble symbols for the learners can express the intelligent CCTV algorithm freely and easily so they can understand fully about the algorithm of intelligent CCTV that uses artificial intelligence to extract faces from subjects. Suggest on this paper, the proposal of educational program can help the learner to grasp the principle of the algorithm by using the flowchart. As the result, Through the modification and development of the proposed program, we will conduct research on IT creative education that can be applied in various areas.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.61-71
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• 2021

In a situation where the online learning is expanding due to COVID-19, the current maker education has limitations in applying it to classes. This study is to design the class of online maker education using artificial intelligence tools in elementary school. Also, it is to identify the responses to it and to confirm whether it helps improve the learner's computational thinking and creative problem solving ability. The class was designed by the literature review and redesign of the curriculum. Using interveiw, the responses of instructor and learners were identified. Pre- and post-test using corresponding sample t-test was conducted. As a result, the class consisted of ten steps including empathizing, defining making problems, identifying the characteristics of material and tool, designing algorithms and coding using remixes, etc. For computing thinking and creative problem solving ability, statistically significant difference was found. This study has the significance that practical maker activities using educational artificial intelligence tools in the context of elementary education can be practically applied even in the online environment.

• Journal of Christian Education in Korea
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• v.66
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• pp.309-341
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• 2021

The purpose of this study is to develop an intelligent learning platform model for faith education in preparation for the post-corona era. This study reviewed artificial intelligence algorithms, research on learning platform development, and prior research related to faith education. The draft of the intelligent learning platform design model was developed by synthesizing previous studies. The developed draft model was validated by a Delphi survey targeting 5 experts. The content validity of the developed draft model was all 1. This is the validation of the draft model. Three revised opinions of experts were presented on the model. And the model was revised to reflect the opinions of experts. The modified final model consisted of three areas: learning materials, learning activities, learning data, and artificial intelligence. Each area is composed of 9 elements of curriculum, learning content additional learning resources, learner type, learning behavior, evaluation behavior, learner characteristic data, learning activity data, artificial intelligence data, and learning analysis. Each component has 29 sub-elements. In addition, 14 learning floors were formed. The biggest implication of this study is the first development of a basic model of an intelligent learning platform for faith education.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.227-230
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• 2022

본 연구에서는 실질적 학습자가 교수자로 착각을 한 상태에서 아바타를 학습시키는 과정을 통해 학습이 되게 하는 구조를 설계하고 제안하였다. 시스템 관리자와 교육자료 형성자를 제외하면, 교수자로 착각하고 있는 '학습자'와 학습자의 공부를 위해 노력하는 학습 가이드 역할을 '학습 관찰자', 학습이 되는 아바타로 구성된다. '학습 관찰자'는 학습 방향을 제시하여 아바타가 활동하는 방향을 지시하게 되며, 아바타는 지시된 방향에서 1:1 학습과 같은 형태로 교수자 입장 학습자에게 공부도움을 요청하게 된다. 아바타의 학습은 인공지능 지도 학습 방법을 이용하여 학습되도록 하며, 교수자로 착각하는 학습자는 아바타 학습 시 아바타에 의해 슬며시 제공되는 학습 자료를 참고하며 아바타를 공부시키게 되는 데 아바타를 공부시킨다고 노력하는 과정이 교수자로 착각된 학습자가 공부가 되는 것이다. 또한 이렇게 학습하는 과정을 거쳐 지식이 성장한 아바타는 아바타들이 경쟁하는 경진 대회에 참가하게 되며 교육자로 착각하는 학습자는 관전 또는 코치를 하며 학습을 하게 된다. 이러한 방법을 통해 교육자로 착각하는 학습자는 부모의 마음으로 적극적으로 공부를 하게 유도하며, 흥미를 갖고 공부를 하게 할 뿐 아니라, 가르치는 사람에 준하는 깊이 있는 지식을 갖도록 유도하며, 본 시스템과 온라인 오프라인을 통해 연결 되게 한 운동 기구 및 운동 환경을 이용하여 운동 하도록 유도하고 파워가 되도록 하여 운동 활동을 유도하며, 단계 마다 적당한 보상 점수들이 제공되도록 하여 지덕체가 성장되도록 하는 설계이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1055-1060
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• 2018

In the wake of the 4th Industrial Revolution, the problem of career education in schools has become a big issue. While various studies are being conducted on services or technologies to effectively handle artificial intelligence and big data, in the field of education, data on students is simply processed. Therefore, in this paper, we are going to design and present career prediction programs for students using artificial intelligence and big data. Using observational data from students at the institute, the decision tree is constructed with the C4.5 algorithm known to be most intelligent and effective in the decision tree and is used to predict students' path of hope. As a result, the coefficient of kappa exceeded 0.7 and showed a fairly low average error of 0.1 degrees. As shown in this study, a number of studies and data will be deployed to help guide students in their consultation and to provide them with classroom attitudes and directions.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.927-934
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• 2021

AI(Artificial intelligence) is gradually taking up a large part of our lives, and the pace of AI development is accelerating. It is called ACT that develop students' computational thinking in the way artificial intelligence learns. Among ACTs, pattern recognition is an essential factor in efficiently solving problems. Pattern analysis is part of the pattern recognition process. In fact, Netflix's personalized movie recommendation service and what it named Covid-19 after repeated symptoms are all the results of pattern analysis. While the importance of ACT, including pattern recognition, is highlighted, software education for kindergarten and elementary school lower grades is much insufficient compared to foreign countries. Therefore, this study aims to design and develop textbooks for the development of artificial intelligence-based computational thinking through pattern analysis for kindergarten students.

• The Mathematical Education
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• v.63 no.2
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• pp.369-385
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• 2024

With the advancement of digital technology, a variety of digital materials are being utilized in education. For their appropriate use of digital resources, teachers need to be able to evaluate the quality of digital resource and determine the suitability for teaching. This study explored how preservice teachers evaluate TocToc-Math, an Artificial Intelligence (AI)-based math support system. Based on an evaluation framework developed through prior research, preservice teachers evaluated TocToc-Math with evidence-based criteria, including content quality, pedagogy, technology use, and mathematics curriculum alignment. The findings shows that preservice teachers positively evaluated TocToc-Math overall. The evaluation tendencies of preservice teachers were classified into three groups, and the specific characteristics of each factor differed depending on the group. Based on the research results, we suggest implications for improving preservice teachers' evaluation abilities regarding the use of digital technology and AI in mathematics education.

• Journal of The Korean Association of Information Education
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• v.26 no.4
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• pp.273-284
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• 2022

The goal of this paper is to propose the use of machine learning platforms in education to train learners to recognize data biases. Learners can cultivate the ability to recognize when learners deal with AI data and systems when they want to prevent damage caused by data bias. Specifically, this paper presents a method of data bias education using MachineLearningforKids, focusing on the case of AI baseball referee. Learners take the steps of selecting a specific topic, reviewing prior research, inputting biased/unbiased data on a machine learning platform, composing test data, comparing the results of machine learning, and present implications. Learners can learn that AI data bias should be minimized and the impact of data collection and selection on society. This learning method has the significance of promoting the ease of problem-based self-directed learning, the possibility of combining with coding education, and the combination of humanities and social topics with artificial intelligence literacy.

• The Journal of Korean Association of Computer Education
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• v.22 no.4
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• pp.35-45
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• 2019

How future generations perceive coexistence with intelligent robots is an important element of how SW and artificial intelligence education should be designed and conducted. This study conducted a survey of 214 first graders in middle school and looked at differences in understanding and perception of coexistence through empathy and expected problem situations depending on the type of intelligent robot. As a result of the analysis, Firstly, if the form was not explicit, it was recognized as a top-down relationship, and Second, in the case of human form, it was ready to recognize intelligent robots and communicate with them. Third, Many people were feeling Emotion in the Robot shape AI. Fourth, there was a vague sense of uneasiness about simple mechanical robots. The study is meaningful as a case study to confirm awareness of intelligent robots and needs to consider and establish awareness of whether they can coexist and live together with robots by age group as well as middle school students.

• The Mathematical Education
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• v.63 no.2
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• pp.209-231
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• 2024

The education sector is undergoing significant changes due to the Fourth Industrial Revolution and the advancement of artificial intelligence. Particularly, the importance of education based on artificial intelligence is being emphasized. Accordingly, the purpose of this study is to develop a statistics education program using deep learning prediction in high school mathematics and to examine the impact of such statistically problem-solvingcentered statistics education programs on high school students' statistical literacy and computational thinking. To achieve this goal, a statistics education program using deep learning prediction applicable to high school mathematics was developed. The analysis revealed that students' understanding of context improved through experiencing how data was generated and collected. Additionally, they enhanced their comprehension of data variability while exploring and analyzing various datasets. Moreover, they demonstrated the ability to critically analyze data during the process of validating its reliability. In order to analyze the impact of the statistics education program on high school students' computational thinking, a paired sample t-test was conducted, confirming a statistically significant difference in computational thinking between before and after classes (t=-11.657, p<0.001).