• Title/Summary/Keyword: 인공지능 소양능력

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Digital Content to Improve Artificial Intelligence Literacy Ability

  • Han, Sun Gwan
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.12
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    • pp.93-100
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    • 2020
  • This study aims to design and develop effective digital contents to improve the ability for artificial intelligence literacy. First, we defined AI literacy and analyzed the competencies required for artificial intelligence literacy. After selecting the educational elements for AI ability, we composed 10 educational programs. To confirm the appropriateness of designed contents, we verified through content validity test by 10 experts. The CVI value was over 0.75, which was highly valid. The developed content was installed on the online system and applied to 55 AI beginners for 4 weeks. The learners showed a positive result of at least 3.85 in the items of content difficulty, understanding, effectiveness, and learning challenge. As a result of this analysis, we can see that the developed content is positive for helping many people understand AI and improving AI literacy.

The Study on Test Standard for Measuring AI Literacy

  • Mi-Young Ryu;Seon-Kwan Han
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.7
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    • pp.39-46
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    • 2023
  • The purpose of this study is to design and develop the test standard to measure AI literacy abilities. First, we selected key areas of AI literacy through the related studies and expert FGI and designed detailed standard. The area of the test standard is divided into three categories: AI concept, practice, and impact. In order to confirm the validity of the test standard, we conducted twice expert validity tests and then modified and supplemented the test index. To confirm the validity of the test standard, we conducted an expert validity test twice and then modified and supplemented the test standard. The final AI literacy test standard consisted of a total of 30 questions. The AI literacy test standard developed in this study can be an important tool for developing self-checklists or AI competency test questions for measuring AI literacy ability.

The Effects of Artificial Intelligence Convergence Education using Machine Learning Platform on STEAM Literacy and Learning Flow

  • Min, Seol-Ah;Jeon, In-Seong;Song, Ki-Sang
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.10
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    • pp.199-208
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    • 2021
  • In this paper, the effect of artificial intelligence convergence education program that provides STEAM education using machine learning platform on elementary school students' STEAM literacy and learning flow was analyzed. A homogeneous group of 44 elementary school 6th graders was divided into an experimental group and a control group. The control group received 10 lessons of general subject convergence class, and the experimental group received 10 lessons of STEAM-based artificial intelligence convergence education using Machine learning for Kids. To develop the artificial intelligence convergence education program, the goals, achievement standards, and content elements of the 2015 revised curriculum to select subjects and class contents is analyzed. As a result of the STEAM literacy test and the learning flow test, there was a significant difference between the experimental group and the control group. In particular, it can be confirmed that the coding environment in which the artificial intelligence function is expanded has a positive effect on learners' learning flow and STEAM literacy. Among the sub-elements of convergence talent literacy, significant differences were found in the areas of personal competence such as convergence and creativity. Among the sub-elements of learning flow, significant differences were found in the areas such as harmony of challenge and ability, clear goals, focus on tasks, and self-purposed experiences. If further expanded research is conducted in the future, it will be a basic research for more effective education for the future.

Investigating the Restructuring of Artificial Intelligence Curriculum in Specialized High Schools Following AI Department Reorganization (특성화고 인공지능학과 개편에 따른 인공지능 교육과정 개편 방안 연구)

  • EunHee Goo
    • Journal of Practical Engineering Education
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    • v.16 no.1_spc
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    • pp.41-49
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    • 2024
  • The advancement of artificial intelligence on a global scale is significantly transforming life. In the field of education, there is a strong emphasis on actively utilizing AI and fostering creatively integrated talents with diverse knowledge. In alignment with this trend, there is a paradigm shift in AI education across primary, middle, high school, as well as university and graduate education. Leading AI schools and specialized high schools are dedicated to enhancing students' AI capabilities, while universities integrate AI into software courses or establish new AI departments to nurture talent. In AI-integrated education graduate programs, national efforts are underway to educate instructors from various disciplines on applying AI technology to the curriculum. In this context, specialized high schools are also restructuring their departments to cultivate technological talent in AI, tailored to students' characteristics and career paths. While the current education focuses primarily on the fundamental concepts and technologies of AI, there is a need to address the aspect of developing practical problem-solving skills. Therefore, this research aims to compare and analyze essential educational courses in AI-leading schools, AI-integrated high schools, AI high schools, university AI departments, and AI-integrated education graduate programs. The goal is to propose the necessary educational courses for AI education in specialized high schools, with the expectation that a more advanced curriculum in AI education can be established in specialized high schools through this effort.

Suggestions for Improving Computational Thinking and Mathematical Thinking for Artificial Intelligence Education in Elementary and Secondary School (초·중등 인공지능 교육에서 컴퓨팅 사고력 및 수학적 사고력 향상을 위한 제언)

  • Park, Sang-woo;Cho, Jungwon
    • 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.

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The Effect of Novel Engineering (NE) Education using VR authoring tool on STEAM literacy and Learning Immersion (VR 저작도구 기반 노벨 엔지니어링(NE) 교육이 초등학생의 융합인재소양과 학습몰입에 미치는 효과)

  • Song, Hae-nam;Kim, Tae-ryeong
    • Journal of The Korean Association of Information Education
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    • v.26 no.3
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    • pp.153-165
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    • 2022
  • This study is about the Novel Engineering(NE) education program : a class model that combines reading and engineering. By including the process of directly designing and programming a virtual reality using CospacesEdu (a VR authoring tool for the NE class), the effects of the educational program on learners' STEAM literacy and Learning immersion are demonstrated. Moreover, the subject of this education is Dokdo in South Korea. As a result, the average of STEAM literacy is increased, and a significant change is confirmed statistically in Convergence. Learning immersion shows significant improvement in Challenges-skills balance. On the other hand, some students experience difficulties due to the long research stages, from reading a book to researching for information to designing VR and rewriting a story with the collected information. In conclusion, this study will help generalise other education using NE, and this developed program will be a reference that would suggest a new way of teaching.

The Effectiveness of Collaborative Learning in SW Education based on Metaverse Platform (메타버스 기반 협력적 소통 SW 교육 프로그램의 효과)

  • Son, Jungmyoung;Lee, Sihoon;Han, Jeonghye
    • Journal of The Korean Association of Information Education
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    • v.26 no.1
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    • pp.11-22
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    • 2022
  • The educational environment, where the change to blended learning and AI convergence education through non-face-to-face is accelerating, is based on the cultivation of digital literacy. This study attempted to verify the effectiveness of future competencies by creating a collaborative SW education program on the metaverse platform that emerged by supplementing the problems through non-face-to-face. Twenty programs on how to design and create software were organized for small-scale elementary classes in the metaverse. In order to verify the effectiveness 4C competency tool presented as future educational competency was selected, and homogeneity test for the experimental group and t-test were conducted. The results showed the SW education programs based on metaverse was effective in improving collaborative communication skills, confirming the possibility of SW education through blended learning.

Research on a statistics education program utilizing deep learning predictions in high school mathematics (고등학교 수학에서 딥러닝 예측을 이용한 통계교육 프로그램 연구)

  • Hyeseong Jin;Boeuk Suh
    • 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).