• Title/Summary/Keyword: AI, Education

Search Result 862, Processing Time 0.033 seconds

Pattern recognition and AI education system design for improving achievement of non-face-to-face (e-learning) education (비대면(이러닝) 교육 성취도 향상을 위한 패턴인식 및 AI교육 시스템 설계)

  • Lee, Hae-in;Kim, Eui-Jeong;Chung, Jong-In;Kim, Chang Suk;Kang, Shin-Cheon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2022.05a
    • /
    • pp.329-332
    • /
    • 2022
  • This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

  • PDF

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
    • /
    • v.63 no.2
    • /
    • pp.209-231
    • /
    • 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).

Malwares Attack Detection Using Ensemble Deep Restricted Boltzmann Machine

  • K. Janani;R. Gunasundari
    • International Journal of Computer Science & Network Security
    • /
    • v.24 no.5
    • /
    • pp.64-72
    • /
    • 2024
  • In recent times cyber attackers can use Artificial Intelligence (AI) to boost the sophistication and scope of attacks. On the defense side, AI is used to enhance defense plans, to boost the robustness, flexibility, and efficiency of defense systems, which means adapting to environmental changes to reduce impacts. With increased developments in the field of information and communication technologies, various exploits occur as a danger sign to cyber security and these exploitations are changing rapidly. Cyber criminals use new, sophisticated tactics to boost their attack speed and size. Consequently, there is a need for more flexible, adaptable and strong cyber defense systems that can identify a wide range of threats in real-time. In recent years, the adoption of AI approaches has increased and maintained a vital role in the detection and prevention of cyber threats. In this paper, an Ensemble Deep Restricted Boltzmann Machine (EDRBM) is developed for the classification of cybersecurity threats in case of a large-scale network environment. The EDRBM acts as a classification model that enables the classification of malicious flowsets from the largescale network. The simulation is conducted to test the efficacy of the proposed EDRBM under various malware attacks. The simulation results show that the proposed method achieves higher classification rate in classifying the malware in the flowsets i.e., malicious flowsets than other methods.

Multi-agent Conversational AI System for Personalized Learning of Construction Knowledge.

  • Rahat HUSSAIN;Aqsa SABIR;Muahmmad Sibtain ABBAS;Nasrullah KHAN;Syed Farhan Alam ZAIDI;Chansik PARK;Doyeop LEE
    • International conference on construction engineering and project management
    • /
    • 2024.07a
    • /
    • pp.1230-1237
    • /
    • 2024
  • Personalized learning is a critical factor in optimizing performance on construction sites. Traditional pedagogical methods often adhere to a one-size-fits-all approach, failing to provide the nuanced adaptation required to cater to diverse knowledge needs, roles, and learning preferences. While advancements in technology have led to improvements in personalized learning within construction education, the crucial connection between instructors' roles and training enviornment to personalized learning success remains largely unexplored. To address these gaps, this research proposes a novel learning approach utilizing multi-agent, context-specific AI agents within construction virtual environments. This study aims to pioneer an innovative approach leveraging the Large Language Model's capabilities with prompt engineering to make domain-specific conversations. Through the integration of AI-driven conversations in a realistic 3D environment, users will interact with domain-specific agents, receiving personalized safety guidance and information. The system's performance is assessed using the five evaluation criteria including learnability, interaction, communication, relevancy and visualization. The results revealed that the proposed approach has the potential to significantly enhance safety learning in the construction industry, which may lead to improve practices and reduction in accidents on diverse construction sites.

Efficient use of artificial intelligence ChatGPT in educational ministry (인공지능 챗GPT의 교육목회에 효율적인 활용방안)

  • Jang Heum Ok
    • Journal of Christian Education in Korea
    • /
    • v.78
    • /
    • pp.57-85
    • /
    • 2024
  • Purpose of the study: In order to utilize artificial intelligence-generated AI in educational ministry, this study analyzes the concept of artificial intelligence and generative AI and the educational theological aspects of educational ministry to find ways to efficiently utilize artificial intelligence ChatGPT in educational ministry. Contents and methods of the study: The contents of this study are. First, the contents of this study were analyzed by dividing the concepts of artificial intelligence and generative AI into the concept of artificial intelligence, types of artificial intelligence, and generative language model AI ChatGPT. Second, the educational theological analysis of educational ministry was divided into the concept of educational ministry, the goals of educational ministry, the content of educational ministry, and the direction of educational ministry in the era of artificial intelligence. Third, the plan to use artificial intelligence ChatGPT in educational ministry is to provide tools for writing sermon manuscripts, preparation tools for worship and prayer, and church education, focusing on the five functions of the early church community. It was analyzed by dividing it into tools for teaching, tools for teaching materials for believers, and tools for serving and volunteering. Conclusion and Recommendation: The conclusion of this study is that, first, when writing sermon manuscripts through artificial intelligence ChatGPT, high-quality sermon manuscripts can be written through the preacher's spirituality, faith, and insight. Second, through artificial intelligence ChatGPT, you can efficiently design and plan worship services and prepare services that serve the congregation objectively through various scenarios. Third, by using artificial intelligence ChatGPT in church education, it can be used while maintaining a complementary relationship with teachers through collaboration with human and artificial intelligence teachers. Fourth, through artificial intelligence ChatGPT, we provide a program that allows members of the church community to share spiritual fellowship, a plan to meet the needs of church members and strengthen interdependence, and an attitude of actively welcoming new people and respecting diversity. It provides useful materials that can play an important role in giving, loving, serving, and growing together in the love of Christ. Lastly, through artificial intelligence ChatGPT, we are seeking ways to provide various information about volunteer activities, learning support for children and youth in the community, mentoring-related programs, and playing a leading role in forming a village community in the local community.

Design and Application of Artificial Intelligence Experience Education Class for Non-Majors (비전공자 대상 인공지능 체험교육 수업 설계 및 적용)

  • Su-Young Pi
    • Journal of Practical Engineering Education
    • /
    • v.15 no.2
    • /
    • pp.529-538
    • /
    • 2023
  • At the present time when the need for universal artificial intelligence education is expanding and job changes are being made, research and discussion on artificial intelligence liberal arts education for non-majors in universities who experience artificial intelligence as part of their job is insufficient. Although artificial intelligence education courses for non-majors are being operated, they are mainly operated as theory-oriented education on the concepts and principles of artificial intelligence. In order to understand the general concept of artificial intelligence for non-majors, it is necessary to proceed with experiential learning in parallel. Therefore, this study designs artificial intelligence experiential education learning contents of difficulty that can reduce the burden of artificial intelligence classes with interest in learning by considering the characteristics of non-majors. After, we will examine the learning effect of experiential education using App Inventor and the Orange artificial intelligence platform. As a result of analysis based on the learning-related data and survey data collected through the creation of AI-related projects by teams, positive changes in the perception of the need for AI education were found, and AI literacy skills improved. It is expected that it will serve as an opportunity for instructors to lay the groundwork for designing a learning model for artificial intelligence experiential education learning.

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
    • /
    • v.26 no.5
    • /
    • pp.417-425
    • /
    • 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.

Aviating with Multiple Intelligence

  • Anna Cybele Paschke
    • Journal of the Korean Society for Aviation and Aeronautics
    • /
    • v.31 no.2
    • /
    • pp.108-115
    • /
    • 2023
  • Alongside the rapid development of AI technology, which is stepping in to do tasks more quickly and less prone to error than humans can, the possibility for MI (multiple intelligence) development warrants equal attention and fervor. Recent theories of human intelligence point beyond standard cognitive capacity, IQ, and shine a light on the other unique potentials naturally endowed to humans. The applicability of MI to aviation is discussed, suggesting that it is important to consider ways to integrate MI development techniques into pilot education and training. Experiential starting points are discussed.

A Study on the Educational Uses of Smart Speaker (스마트 스피커의 교육적 활용에 관한 연구)

  • Chang, Jiyeun
    • Journal of the Korea Convergence Society
    • /
    • v.10 no.11
    • /
    • pp.33-39
    • /
    • 2019
  • Edutech, which combines education and information technology, is in the spotlight. Core technologies of the 4th Industrial Revolution have been actively used in education. Students use an AI-based learning platform to self-diagnose their needs. And get personalized training online with a cloud learning platform. Recently, a new educational medium called smart speaker that combines artificial intelligence technology and voice recognition technology has emerged and provides various educational services. The purpose of this study is to suggest a way to use smart speaker educationally to overcome the limitation of existing education. To this end, the concept and characteristics of smart speakers were analyzed, and the implications were derived by analyzing the contents provided by smart speakers. Also, the problem of using smart speaker was considered.

Applications and Possibilities of Artificial Intelligence in Mathematics Education (수학교육에서 인공지능 활용 가능성)

  • Park, Mangoo
    • Communications of Mathematical Education
    • /
    • v.34 no.4
    • /
    • pp.545-561
    • /
    • 2020
  • The purpose of this study is to investigate the applications and possibilities of major programs that provide services using artificial intelligence in mathematics education. For this study, related papers, reports, and materials were collected and analyzed, focusing on materials mostly published within the last five years. The researcher searched the keywords of "artificial intelligence", "artificial intelligence", "AI" and "mathematics education" independently or in combination. As a result of the study, artificial intelligence for mathematics education was mostly supporting learners' personalized mathematics learning, defining it as an auxiliary role to support human mathematics teachers, and upgrading the technology of not only cognitive aspects but also affective aspects. As suggestions, the researcher argued that followings are necessary: Research for the establishment of an elaborate artificial intelligence mathematical system, discovery of artificial intelligence technology for appropriate use to support mathematics education, development of high quality of mathematics contents for artificial intelligence, and the establishment and operation of a cloud-based comprehensive system for mathematics education. The researcher proposed that continuous research to effectively help students study mathematics using artificial intelligence including students' emotional or empathetic abilities, and collaborative learning, which is only possible in offline environments. Also, the researcher suggested that more sophisticated materials should be developed for designing mathematics teaching and learning by using artificial intelligence.