• Title/Summary/Keyword: SW.AI교육

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An Analysis of the Influence big data analysis-based AI education on Affective Attitude towards Artificial Intelligence (빅데이터 기반의 AI기초교양교육이 학부생의 정의적 태도에 미치는 영향)

  • Oh, Kyungsun;Kim, Hyunjung
    • 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.

The Artificial Intelligence Literacy Scale for Middle School Students

  • Kim, Seong-Won;Lee, Youngjun
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.3
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    • pp.225-238
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    • 2022
  • Although the importance of literacy in Artificial Intelligence (AI) education is increasing, there is a lack of testing tools for measuring such competency. To address this gap, this study developed a testing tool that measures AI literacy among middle school students. This goal was achieved through the establishment of an expert group that was enlisted to determine the relevant factors and items covered by the proposed tool. To verify the reliability and validity of the developed tool, a field review, exploratory factor analysis, and confirmatory factor analysis were conducted. These procedures resulted in a testing tool comprising six domains that encompass 30 items. The domains are the social impact of AI (eight items), the understanding of AI (six items), AI execution plans (five items), problem solving with AI (five items), data literacy (four items), and AI ethics (two questions). The items are to be rated using a five-point Likert scale. The internal consistency of the tool was .970 (total), while that of the domains ranged from .861 to .939. This study can serve as reference for developing the analysis of AI literacy, teaching and learning, and evaluation in AI education.

A Study of the Definition and Components of Data Literacy for K-12 AI Education (초·중등 AI 교육을 위한 데이터 리터러시 정의 및 구성 요소 연구)

  • Kim, Seulki;Kim, Taeyoung
    • 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.

Development and application of supervised learning-centered machine learning education program using micro:bit (마이크로비트를 활용한 지도학습 중심의 머신러닝 교육 프로그램의 개발과 적용)

  • Lee, Hyunguk;Yoo, Inhwan
    • Journal of The Korean Association of Information Education
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    • v.25 no.6
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    • pp.995-1003
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    • 2021
  • As the need for artificial intelligence (AI) education, which will become the core of the upcoming intelligent information society rises, the national level is also focusing attention by including artificial intelligence-related content in the curriculum. In this study, the PASPA education program was presented to enhance students' creative problem-solving ability in the process of solving problems in daily life through supervised machine learning. And Micro:bit, a physical computing tool, was used to enhance the learning effect. The teaching and learning process applied to the PASPA education program consists of five steps: Problem Recoginition, Argument, Setting data standard, Programming, Application and evaluation. As a result of applying this educational program to students, it was confirmed that the creative problem-solving ability improved, and it was confirmed that there was a significant difference in knowledge and thinking in specific areas and critical and logical thinking in detailed areas.

Exploring AI-based Teaching and Learning Activities for Software Education in Kindergarteners to the Second Graders (유치원 및 초등학교 1-2학년을 위한 AI 기반 교수학습활동 탐색)

  • Kim, Sohee;Jeong, Youngsik
    • Journal of The Korean Association of Information Education
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    • v.24 no.5
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    • pp.413-421
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    • 2020
  • AI(Artificial intelligence) has brought many changes to our living in the Fourth Industrial Revolution. In our daily lives, we can easily access unmanned automatic systems using AI such as unmanned cameras and unmanned delivery boxes. Therefore, AI education has become an important part of daily life in the future. Currently, however, we have very few cases of AI education for young students, such as kindergarten and lower grades in elementary schools. Based on the software education curriculum of kindergarteners and lower graders previously studied, we presented the examples of AI-based teaching and learning activities and presented related AI-based computational thinking by each topic. However, in order for these teaching and learning activities to be applied to public education, it is necessary to secure sufficient class time, improve the educational environment, and actively support teaching activities.

Analysis of the Current Status of the AI Major Curriculum at Universities Based on Standard of AI Curriculum

  • Kim, Han Sung;Kim, Doohyun;Kim, Sang Il;Lee, Won Joo
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.3
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    • pp.25-31
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    • 2022
  • The purpose of this study is to explore the implications for the systematic operation of the AI curriculum by analyzing the current status of the AI major curriculum in universities. To this end, This study analyzed the relevant curriculum of domestic universities(a total of 51 schools) and overseas QS Top 10 universities based on the industry demand-based standard of AI major curriculum developed through prior research. The main research results are as follows. First, in the case of domestic universities, Python-centered programming subjects were lacking. Second, there were few subjects for advanced learning such as AI application and convergence. Third, the subjects required to perform the AI developer job were insufficient. Fourth, in the case of colleges, the ratio of AI mathematics-related subjects was low. Based on these results, this study presented implications for the systematic operation of the AI major education.

Effectiveness Analysis of AI Maker Coding Education (AI 메이커 코딩 교육의 효과성 분석)

  • Lee, Jaeho;Kim, Daehyun;Lee, Seunghun
    • 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.

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A Study on Comparing the Computer Science Education Hours between Public and Private Elementary Schools (공립초등학교와 사립초등학교의 정보교육 시수 비교 연구)

  • Choi, Moonseok;Shin, Seungki
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.107-112
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    • 2021
  • This study tried to analyze the hours for computer science education in private elementary schools located in Seoul, in order to find out how many lesson hours are required. According to online discussion participation in the 2022 revised curriculum survey results, it was found that students and parents wanted computer science education to be strengthened. Information education in public elementary schools consists of a separate unit in the practical subject based on the 2015 revised curriculum and is to be implemented for more than 17 hours. As a result of surveying the average hours of computer science education based on school reminder of 28 private elementary schools in Seoul, it was found that about 152 hours of information education were being operated for 6 years. This is about 9 times the gap in education hours compared to public elementary schools. Artificial intelligence is emerging as important, so the lesson hours of information education must be secured to strengthen students' future competency in morden society. Therefore, informatics curriculum should be independent as a subject and secure the number of hours in the elementary school level.

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A Study on the Evaluation Direction of AI Education through the Analysis of SW Education Learner-centered Assessment Cases (SW교육 학습자 중심 평가 사례 분석을 통한 인공지능교육의 평가 방향 고찰)

  • Shin, Heenam;Ann, SungHun
    • Journal of The Korean Association of Information Education
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    • v.24 no.5
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    • pp.511-518
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    • 2020
  • Preparing for the Fourth Industrial Revolution and Corona-19, our education is expanding a new chapter of learning to the era of AI education that incorporates software technology beyond software education. In this study, we will analyze the case of learner-centered assessment in software education and examine the assessment direction of artificial intelligence education through its effectiveness. Through the case of applying learner-centered assessment to non-computer subjects including computer subjects, we sought the effects on learners' learning, environmental conditions and assessment models of learner-centered evaluation, and through the case of applying the learner-centered assessment model to software education, we wanted to find out what the learner-centered assessment in artificial intelligence education suggests to the educational site. According to the analysis, the learner-centered assessment had a significant effect on the learner's achievement goal, and it is expected that the learner-centered assessment in artificial intelligence education will be carried out smoothly when an objective evaluation system and objective evaluation model are designed to help the learner's assessment, building digital environment conditions based on intelligent information technology.

Development and Application of Artificial Intelligence Education Program for Secondary School Students using Self-Driving Cars (자율주행 자동차를 이용한 중등 학생 대상 인공지능 교육 프로그램 개발 및 적용)

  • Ryu, Hyein;Lee, Jeonghun;Cho, Jungwon
    • Journal of Digital Convergence
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    • v.19 no.7
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    • pp.227-236
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    • 2021
  • This study aims to develop an AI education program for secondary school students to help understand AI and to provide an experience of solving real-life problems by using AI, and to analyze the effectiveness of education. The education program based on the AI education system for K-12 developed in the previous study was composed of a total of 12 lessons by selecting the self-driving cars, which is emerging as a recent issue among real life problems, as the main topic. Classes were conducted for secondary school students who had experience in software education, and the effectiveness of education and class satisfaction were analyzed. As a result of the analysis, it was confirmed that the understanding of AI and the sense of AI efficacy were improved, and the class satisfaction was high in all items such as educational content, fun in class, difficulty of class, and interest in AI. Based on these results, implications for AI education for secondary students were proposed.