• Title/Summary/Keyword: SW.AI education

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Development and Validation of Data Science Education Instructional Model (데이터 과학 교육을 위한 수업모형 개발 및 타당성 검증)

  • Bongchul Kim;Bomsol Kim;Jonghoon Kim
    • Journal of The Korean Association of Information Education
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    • v.26 no.5
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    • pp.417-425
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    • 2022
  • The 'Comprehensive Plan for Nurturing Digital Talents' reported at the Cabinet meeting of the Ministry of Education in August 2022 focuses on qualitative and quantitative expansion of informatics education centered on SW, AI education. With the advent of the era of artificial intelligence, data science education is also drawing attention as a field of informatics education. Data science is originally a field where various studies are fused, and advanced technologies are being used for data analysis, modeling, and machine learning. This study devised a draft of the instructional model of data science education through literature research and analysis of previous studies, and developed a final instructional model through usability test and expert validation.

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.

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.

A Case Study of Educational Effectiveness by Software Subjects for Humanities College Students

  • Seo, Joo-Young;Shin, Seung-Hun
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.9
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    • pp.267-277
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    • 2022
  • Recently, the topics of SW liberal-arts education are diversifying, from 'Computational Thinking(CT)' to 'Programming, Data Analysis and Artificial Intelligence(AI)' in universities. We expect that the diversification of SW liberal-arts subjects does not just mean that the learning contents are different, but also differentiates the educational goals and educational effects of each subject. In this paper, we conducted a case study to analyze the educational effect according to the educational goals of two SW liberal-arts subjects, CT and Data Analysis Fundamentals(DA), for humanities college students. We confirmed that the educational effect of 'CT Efficacy' increased significantly in accordance with the common educational goal of 'Improving CT-based SW convergence competency' in both subjects. However, we also analyzed the difference in the educational effects of 'CT(the goal of basic SW education)' and 'DA(the goal of major-friendly SW education)', which have different subject goals. 'CT' mainly showed an educational effect on how to solve general daily problems, and 'DA' showed confidence in how to solve major problems along with general problems.

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 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.

Analyzing the effects of artificial intelligence (AI) education program based on design thinking process (디자인씽킹 프로세스 기반의 인공지능(AI) 교육 프로그램 적용 효과분석)

  • Lee, Sunghye
    • The Journal of Korean Association of Computer Education
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    • v.23 no.4
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    • pp.49-59
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    • 2020
  • At the beginning of the discussion of AI education in K-12 education, the study was conducted to develop and apply an AI education program based on Design Thinking and analyze the effects of the AI education programs. In the AI education program, students explored and defined the AI problems they were interested in, gathered the necessary data to build an AI model, and then developed a project using scratch. In order to analyze the effectiveness of the AI education program, the change of learner's perception of the value of AI and the change of AI efficacy were analyzed. The overall perception of the AI project was also analyzed. As a result, AI efficacy was significantly increased through the experience of carrying out the project according to the Design Thinking process. In addition, the efficacy of solving problems with AI was influenced by the level of use of programming languages. The learner's overall perception of the AI project was positive, and the perceptions of each stage of the AI project (AI problem understanding and problem exploration, practice, problem definition, problem solving idea implementation, evaluation and presentation) was also positive. This positive perception was higher among students with high level of programming language use. Based on these results, the implications for AI education were suggested.

Effectiveness analysis based on PJBL of Liberal Arts Computing (PJBL기반의 교양컴퓨터 수업의 효과성 분석)

  • Jin-Ah, Yoo
    • Journal of Integrative Natural Science
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    • v.15 no.4
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    • pp.163-169
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    • 2022
  • Currently, many universities are implementing software-oriented universities and artificial intelligence-oriented universities to foster software-oriented manpower. We are educating students to design and produce computational thinking and coding directly with their major knowledge. However, computer education is not easy for non-majors, and there are many difficulties in coding. The results of responses from 104 students from the College of Health Sciences and College of Social Management who took the liberal arts computer at University H were analyzed using SPSS 26.0 version. In the liberal arts computer class for non-majors, a PJBL-based class plan was proposed. The effectiveness of PJBL-based classes was confirmed through a questionnaire for the improvement of artificial intelligence liberal arts courses. As a result, PJBL-based education showed statistically significant results in terms of satisfaction, effectiveness, and self-efficiency of classes regardless of major.

A Study on ARCS-DEVS-based Programming Learning Methods for SW/AI Basic Liberal Arts Education for Non-majors (비전공자 대상 SW/AI 기초 교양 교육을 위한 ARCS-DEVS 모델 기반의 프로그래밍 학습방법 연구)

  • Han, Youngshin
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.311-324
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    • 2022
  • In this paper, we adjusted the feedback and learning materials for each learning based on ARCS motivation which applied DEVS methodology. We designed the ARCS professor-student model that expresses the continuous change in the student's attitude toward the class according to the student's attention, relevance, confidence, and satisfaction. It was applied to computational thinking and data analysis classes Based on the designed model. Before and after class, the students were asked the same question and then analyzed for each part of the ARCS. It was observed that students' perceptions of Attention, Relevance, and Satisfaction were improved except for Confidence. we observed that the students themselves felt that they lacked a lot of confidence compared to other ARS through the analysis. Although, Confidence showed a 13.5% improvement after class but it was about 33% lower than the average of other ARS. However, when it was observed that students' self-confidence was 30% lower than other motivational factors it was confirmed that the part that leads C to a similar level in other ARS is necessary.