• Title/Summary/Keyword: thinking AI

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Human Factor & Artificial Intelligence: For future software security to be invincible, a confronting comprehensive survey

  • Al-Amri, Bayan O;Alsuwat, Hatim;Alsuwat, Emad
    • International Journal of Computer Science & Network Security
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    • v.21 no.6
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    • pp.245-251
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    • 2021
  • This work aims to focus on the current features and characteristics of Human Element and Artificial intelligence (AI), ask some questions about future information security, and whether we can avoid human errors by improving machine learning and AI or invest in human knowledge more and work them both together in the best way possible? This work represents several related research results on human behavior towards information security, specified with elements and factors like knowledge and attitude, and how much are they invested for ISA (information security awareness), then presenting some of the latest studies on AI and their contributions to further improvements, making the field more securely advanced, we aim to open a new type of thinking in the cybersecurity field and we wish our suggestions of utilizing each point of strengths in both human attributions in software security and the existence of a well-built AI are going to make better future software security.

Development of SW Education Program for Data-Driven Problem Solving Using Micro:bit (마이크로비트를 활용한 데이터 기반 문제해결 SW교육 프로그램 개발)

  • Kim, JBongChul;Yu, HeaJin;Oh, SeungTak;Kim, JongHoon
    • Journal of The Korean Association of Information Education
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    • v.25 no.5
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    • pp.713-721
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    • 2021
  • As the Ministry of Education has introduced AI education in earnest in the 2022 revised curriculum, there is growing sympathy for the need for data-related education along with AI education. In order to develop the competence to understand and utilize artificial intelligence properly, the understanding and utilization competence of data must be based on it. In this study, a data-driven problem solving SW education program using microbit was developed by synthesizing the results of demand analysis and previous research analysis. The data-driven problem solving education program was developed with educational elements that can be applied to elementary school students among the contents of data science. Through the program developed in this study, education that combines various topics and subjects can be linked based on real-life data. Furthermore, based on an understanding of data, it will lay the foundation for a more substantial AI education program.

Development of an AI Education Program Converging with Korean Language Subject (국어 교과 융합 AI 교육 프로그램 개발)

  • Shin, Jineson;Jo, Miheon
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.289-294
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    • 2021
  • With the development of artificial intelligence, a wave of the 4th industrial revolution is taking place around the world. With the technologies such as big data and Internet of Things-based artificial intelligence, we are heading to a hyper-connected society where everything converges into one. Accordingly as educational talents in the era of artificial intelligence, we are pursuing the cultivation of creative convergence-type talents and emotional creative talents. With human creativity and emotion at the center, we should be able to collaborate with artificial intelligence and create new things by converging knowledge in various fields. By developing a program that combines humanities-oriented Korean language with engineering-oriented artificial intelligence, this research attempted to help students experience solving problems creatively by combining humanistic knowledge with engineering thinking skills. The educational program consists of two kinds of contents(i.e., "Books with AI" and "A Play with AI") and 15 classes that provide students with opportunities to solve humanities problems with artificial intelligence.

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The Effect of Design Thinking Based Artificial Intelligence Education Programs on Middle School Students' Creative Problem Solving Ability

  • Seung-Ju, Hong;Seong-Won, Kim;Youngjun, Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.2
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    • pp.227-234
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    • 2023
  • In this paper, we developed a design thinking-based artificial intelligence education program for middle school students and applied it to verify the impact on creative problem-solving skills. The inspection tool used the Creative Problem Solving Profile Inventory (CPSPI), an inspection tool for measuring creative thinking type ability based on the CPS theory of Hwasun Lee, Jungmin Pyo, Insoo Choe(2014). CPSPI included the steps of evaluating cognitive preferences and cognitive abilities by supplementing the limitations of existing tests, and sharing and persuading one's ideas with others. Before and after applying the design thinking-based artificial intelligence education program, as a result of analyzing the creative problem-solving ability, it increased significantly in all areas. As a result of analyzing the creative problem-solving ability of middle school students, significant results were found in the areas of Problem Detection and Analysis, Idea Generation, Action plan, Execution, Persuasion and Communication. The effect of design thinking was confirmed as a teaching and learning method to improve creative problem-solving ability in artificial intelligence education.

Development of checklist questions to measure AI capabilities of elementary school students (초등학생의 AI 역량 측정을 위한 체크리스트 문항 개발)

  • Eun Chul Lee;YoungShin Pyun
    • Journal of Internet of Things and Convergence
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    • v.10 no.3
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    • pp.7-12
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    • 2024
  • The development of artificial intelligence technology changes the social structure and educational environment, and the importance of artificial intelligence capabilities continues to increase. This study was conducted with the purpose of developing a checklist of questions to measure AI capabilities of elementary school students. To achieve the purpose of the study, a Delphi survey was used to analyze literature and develop questions. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements consisted of understanding artificial intelligence (6 elements), artificial intelligence thinking (4 elements), artificial intelligence ethics (4 elements), and artificial intelligence social-emotion (3 elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 19 questions were developed. The developed questions were verified through the first Delphi survey, and 7 questions were revised according to the revision opinions. The validity of 19 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the measurement results of competency are raised to a reliable level.

Development of checklist questions to measure AI core competencies of middle school students (중학생의 AI 핵심역량 측정을 위한 체크리스트 문항 개발)

  • Eun Chul Lee;JungSoo Han
    • Journal of Internet of Things and Convergence
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    • v.10 no.3
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    • pp.49-55
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    • 2024
  • This study was conducted with the purpose of developing a checklist of questions to measure middle school students' AI capabilities. To achieve the goal of the study, literature analysis and question development Delphi survey were used. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements are understanding of artificial intelligence (5 elements), artificial intelligence thinking (5 elements), utilization of artificial intelligence (4 elements), artificial intelligence ethics (6 elements), and artificial intelligence social-emotion (6 elements). elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 31 questions were developed. The developed questions were verified through the first Delphi survey, and 10 questions were revised according to the revision opinions. The validity of 31 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the level of reliability of measurement results increases.

An Artificial Intelligence Ethics Education Model for Practical Power Strength (실천력 강화를 위한 인공지능 윤리 교육 모델)

  • Bae, Jinah;Lee, Jeonghun;Cho, Jungwon
    • Journal of Industrial Convergence
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    • v.20 no.5
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    • pp.83-92
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    • 2022
  • As cases of social and ethical problems caused by artificial intelligence technology have occurred, artificial intelligence ethics are drawing attention along with social interest in the risks and side effects of artificial intelligence. Artificial intelligence ethics should not just be known and felt, but should be actionable and practiced. Therefore, this study proposes an artificial intelligence ethics education model to strengthen the practical ability of artificial intelligence ethics. The artificial intelligence ethics education model derived educational goals and problem-solving processes using artificial intelligence through existing research analysis, applied teaching and learning methods to strengthen practical skills, and compared and analyzed the existing artificial intelligence education model. The artificial intelligence ethics education model proposed in this paper aims to cultivate computing thinking skills and strengthen the practical ability of artificial intelligence ethics. To this end, the problem-solving process using artificial intelligence was presented in six stages, and artificial intelligence ethical factors reflecting the characteristics of artificial intelligence were derived and applied to the problem-solving process. In addition, it was designed to unconsciously check the ethical standards of artificial intelligence through preand post-evaluation of artificial intelligence ethics and apply learner-centered education and learning methods to make learners' ethical practices a habit. The artificial intelligence ethics education model developed through this study is expected to be artificial intelligence education that leads to practice by developing computing thinking skills.

A Analysis of SW Experience in AI Basic Liberal Arts Education (AI기초교양교육에서 SW경험에 따른 학습자 분석)

  • Oh, Kyungsun;Jang, Eunsill
    • Journal of The Korean Association of Information Education
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    • v.25 no.5
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    • pp.769-778
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    • 2021
  • Humanity faces the 4th industrial revolution, many countries are providing systematic and continuous SW education to foster talent with AI capabilities. On the other hand, there are high concerns that the SW gap will widen and polarize as domestic reality does not provide systematic and continuous SW education to learners. Against this background, this study started to investigate the influence of learners' SW experience on SW education. As a result of the study targeting science and engineering students, the effect of SW experience on SW education was significant. With theses results, it is expected that various discussions will be actively conducted so that systematic and continuous SW education can be provided in elementary and secondary schools.

An Analysis of differences in self-efficacy according to SW experience of learners learning AI liberal arts education (AI 기초교양에서 학습자의 SW 경험이 자기효능감에 미치는 영향)

  • Oh, Kyungsun;Jang, Eunsill
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.223-231
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    • 2021
  • Humanity faces the 4th industrial revolution, many countries are providing systematic and continuous SW education to foster talent with AI capabilities. On the other hand, there are high concerns that the SW gap will widen and polarize as domestic reality does not provide systematic and continuous SW education to learners. Against this background, this study started to investigate the influence of learners' SW experience on SW education. As a result of the study targeting science and engineering students, the effect of SW experience on SW education was significant. With theses results, it is expected that various discussions will be actively conducted so that systematic and continuous SW education can be provided in elementary and secondary schools.

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Effect of Machine Learning Education Focused on Data Labeling on Computational Thinking of Elementary School Students (데이터 라벨링 중심의 머신러닝 교육이 초등학생 컴퓨팅 사고력에 미치는 효과)

  • Moon, Woojong;Kim, Bomsol;Kim, Jungah;Kim, Bongchul;Seo, Youngho;OH, Jeongcheol;Kim, Yongmin;Kim, Jonghoon
    • 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.