• Title/Summary/Keyword: ChatGPT and Education

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Application of artificial intelligence in medical education: focus on the application of ChatGPT for clinical medical education (의학 교육에서 인공지능의 응용: 임상의학 교육을 위한 ChatGPT의 활용을 중심으로)

  • Hyeonmi Hong;Youngjoon Kang;Youngjon Kim;Bomsol Kim
    • Journal of Medicine and Life Science
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    • v.20 no.2
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    • pp.53-59
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    • 2023
  • This study explores the potential use of artificial intelligence (AI)-based services, specifically ChatGPT-3.5, in medical education. The application of this technology is acknowledged as a valuable tool for simulating authentic clinical scenarios and enhancing learners' diagnostic and communication skills. To construct a case, students received ChatGPT training using a clinical ethics casebook titled "Clinical Ethics Cases and Commentaries for Medical Students and Physicians." Subsequently, a role-play script was generated based on this training. The initial draft of the script was reviewed by two medical professors and was further optimized using ChatGPT-3.5. Consequently, a comprehensive role-play script, accurately reflecting real-world clinical situations, was successfully developed. This study demonstrates the potential for effectively integrating AI technology into medical education and provides a solution to overcome limitations in developing role-play scripts within conventional educational settings. However, the study acknowledges that AI cannot always generate flawless role-play scripts and recognizes the necessity of addressing these limitations and ethical concerns. The research explores both the potential and limitations of employing AI in the early stages of medical education, suggesting that future studies should focus on overcoming these limitations while further investigating the potential applications of AI in this field.

Generative AI as a Virtual Conversation Partner in Language Learning

  • Ji-Young Seo;Seon-Ah, Kim
    • International Journal of Advanced Culture Technology
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    • v.12 no.2
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    • pp.7-15
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    • 2024
  • Despite a recent surge in multifaceted research on AI-integrated language learning, empirical studies in this area remain limited. This study adopts a Human-Generative AI parallel processing model to examine students' perceptions, asking 182 college students to independently construct knowledge and then compare their efforts with the results generated through in-classroom conversations with ChatGPT 3.5. In questionnaire responses, most students indicated that they found these activities useful and expressed a keen interest in learning various ways to utilize generative AI for language learning with instructor guidance. The findings confirm that ChatGPT's potential as a virtual conversation partner. Identifying specific reasons for the perceived usefulness of conversation activities and drawbacks of ChatGPT, this study emphasizes the importance of teachers staying informed about both the latest advances in technology and their limitations. We recommend that teachers endeavor to creatively design various classroom activities using AI technology.

A Study on SQL Practice Model for Data Analysis Using Chat GPT in Insurance Claims Databas (보험 청구 데이터베이스에서 Chat GPT를 이용한 데이터 분석을 위한 SQL 실습 모델 연구)

  • Joon-Young Choi
    • Journal of the Health Care and Life Science
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    • v.11 no.1
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    • pp.11-23
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    • 2023
  • In this study, a practice model that can improve healthcare information management ability using Chat GPT and SQL was studied. For SQL utilization, learners were asked to use Chat GPT to easily access the database and write SQL for data extraction. For the contents analyzed in the claims database, the sum of insurance claim amount, insurance claim amount by treatment item, claim details corresponding to a specific amount, other diagnosis names of specific prescription patients, examination details of specific diagnosis names, and total amount by item were calculated. As a result of executing SQL statements written for each subject in Chat GPT, it was confirmed that the analysis contents were the same. It is believed that the use of ChatGPT as progressed in this study will contribute to improving the ability of healthcare data management to increase accuracy and efficiency in database management and analysis work, rather than simply simplifying or automating tasks.

Effective ChatGPT Prompts in Mathematical Problem Solving : Focusing on Quadratic Equations and Quadratic Functions (수학 문제 해결에서 효과적인 ChatGPT의 프롬프트 고찰: 이차방정식과 이차함수를 중심으로)

  • Oh, Se Jun
    • Communications of Mathematical Education
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    • v.37 no.3
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    • pp.545-567
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    • 2023
  • This study investigates effective ChatGPT prompts for solving mathematical problems, focusing on the chapters of quadratic equations and quadratic functions. A structured prompt was designed, following a sequence of 'Role-Rule-Example Solution-Problem-Process'. In this study, an artificial intelligence model combining GPT-4, Wolfram plugin, and Advanced Data Analysis was utilized. Wolfram was used as the primary tool for calculations to reduce computational errors. When using the structured prompt, the accuracy rate for problems from nine high school mathematics textbooks on quadratic equations and quadratic functions was 91%, showing higher performance compared to zero-shot prompts. This confirmed the effectiveness of the structured prompts in solving mathematical problems. The structured prompts designed in this study can contribute to the development of intelligent information systems for personalized and customized education.

Evaluating ChatGPT's Competency in BIM Related Knowledge via the Korean BIM Expertise Exam (BIM 운용 전문가 시험을 통한 ChatGPT의 BIM 분야 전문 지식 수준 평가)

  • Choi, Jiwon;Koo, Bonsang;Yu, Youngsu;Jeong, Yujeong;Ham, Namhyuk
    • Journal of KIBIM
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    • v.13 no.3
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    • pp.21-29
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    • 2023
  • ChatGPT, a chatbot based on GPT large language models, has gained immense popularity among the general public as well as domain professionals. To assess its proficiency in specialized fields, ChatGPT was tested on mainstream exams like the bar exam and medical licensing tests. This study evaluated ChatGPT's ability to answer questions related to Building Information Modeling (BIM) by testing it on Korea's BIM expertise exam, focusing primarily on multiple-choice problems. Both GPT-3.5 and GPT-4 were tested by prompting them to provide the correct answers to three years' worth of exams, totaling 150 questions. The results showed that both versions passed the test with average scores of 68 and 85, respectively. GPT-4 performed particularly well in categories related to 'BIM software' and 'Smart Construction technology'. However, it did not fare well in 'BIM applications'. Both versions were more proficient with short-answer choices than with sentence-length answers. Additionally, GPT-4 struggled with questions related to BIM policies and regulations specific to the Korean industry. Such limitations might be addressed by using tools like LangChain, which allow for feeding domain-specific documents to customize ChatGPT's responses. These advancements are anticipated to enhance ChatGPT's utility as a virtual assistant for BIM education and modeling automation.

Performance of ChatGPT 3.5 and 4 on U.S. dental examinations: the INBDE, ADAT, and DAT

  • Mahmood Dashti;Shohreh Ghasemi;Niloofar Ghadimi;Delband Hefzi;Azizeh Karimian;Niusha Zare;Amir Fahimipour;Zohaib Khurshid;Maryam Mohammadalizadeh Chafjiri;Sahar Ghaedsharaf
    • Imaging Science in Dentistry
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    • v.54 no.3
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    • pp.271-275
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    • 2024
  • Purpose: Recent advancements in artificial intelligence (AI), particularly tools such as ChatGPT developed by OpenAI, a U.S.-based AI research organization, have transformed the healthcare and education sectors. This study investigated the effectiveness of ChatGPT in answering dentistry exam questions, demonstrating its potential to enhance professional practice and patient care. Materials and Methods: This study assessed the performance of ChatGPT 3.5 and 4 on U.S. dental exams - specifically, the Integrated National Board Dental Examination (INBDE), Dental Admission Test (DAT), and Advanced Dental Admission Test (ADAT) - excluding image-based questions. Using customized prompts, ChatGPT's answers were evaluated against official answer sheets. Results: ChatGPT 3.5 and 4 were tested with 253 questions from the INBDE, ADAT, and DAT exams. For the INBDE, both versions achieved 80% accuracy in knowledge-based questions and 66-69% in case history questions. In ADAT, they scored 66-83% in knowledge-based and 76% in case history questions. ChatGPT 4 excelled on the DAT, with 94% accuracy in knowledge-based questions, 57% in mathematical analysis items, and 100% in comprehension questions, surpassing ChatGPT 3.5's rates of 83%, 31%, and 82%, respectively. The difference was significant for knowledge-based questions(P=0.009). Both versions showed similar patterns in incorrect responses. Conclusion: Both ChatGPT 3.5 and 4 effectively handled knowledge-based, case history, and comprehension questions, with ChatGPT 4 being more reliable and surpassing the performance of 3.5. ChatGPT 4's perfect score in comprehension questions underscores its trainability in specific subjects. However, both versions exhibited weaker performance in mathematical analysis, suggesting this as an area for improvement.

Development of university liberal arts curriculum for understanding and utilizing generative AI (생성형 AI 이해 및 활용을 위한 대학 교양교과목 교육과정 개발)

  • Jihyun Park;Jongjin Park
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.5
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    • pp.645-650
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    • 2024
  • This paper jointly designed and developed a liberal arts curriculum at two local universities for college liberal arts education using generative AI centered on ChatGPT. The developed curriculum takes into account the conceptual components for designing classes for integrated use of university ChatGPT presented in existing research, understands the language model and artificial intelligence that form the basis of ChatGPT, and applies generative AI including ChatGPT to various domains. It was developed with useful content. The developed curriculum introduces the concept and changing aspects of artificial intelligence and the natural language processing language model that is the basis of ChatGPT for students in various majors, and generates ChatGPT, a generative AI and large language model (LLM), and various open sources. The purpose was to implement my own AI service using the model and present an example of mutual collaboration between universities in Joint Education Curriculum Operation.

Design to Improve Educational Competency Using ChatGPT

  • Choong Hyong LEE
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.1
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    • pp.182-190
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    • 2024
  • Various artificial intelligence neural network models that have emerged since 2014 enable the creation of new content beyond the existing level of information discrimination and withdrawal, and the recent generative artificial intelligences such as ChatGPT and Gall-E2 create and present new information similar to actual data, enabling natural interaction because they create and provide verbal expressions similar to humans, unlike existing chatbots that simply present input content or search results. This study aims to present a model that can improve the ChatGPT communication skills of university students through curriculum research on ChatGPT, which can be participated by students from all departments, including engineering, humanities, society, health, welfare, art, tourism, management, and liberal arts. It is intended to design a way to strengthen competitiveness to embody the practical ability to solve problems through ethical attitudes, AI-related technologies, data management, and composition processes as knowledge necessary to perform tasks in the artificial intelligence era, away from simple use capabilities. It is believed that through creative education methods, it is possible to improve university awareness in companies and to seek industry-academia self-reliant courses.

The Influence of ChatGPT Literacy on Academic Engagement: Focusing on the Serial Mediation Effect of Academic Confidence and Perceived Academic Competence (챗GPT 리터러시가 학업열의에 미치는 영향: 학업자신감과 지각된 학업역량의 이중매개효과를 중심으로)

  • Eunsung Lee;Longzhe Quan
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.565-574
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    • 2024
  • ChatGPT is causing significant reverberations across all sectors of our society, and this holds true for the field of education as well. However, scholarly and societal discussions regarding ChatGPT in academic settings have primarily focused on issues such as plagiarism, with relatively limited research on the positive effects of utilizing generative AI. Additionally, amidst the educational crisis of the post-COVID era, there is a growing recognition of the need to enhance academic engagement. In light of these concerns, we investigated how academic engagement varies based on students' levels of ChatGPT literacy and examined whether students' academic confidence and perceived academic competence serve as mediators between ChatGPT literacy and academic engagement. An analysis using SPSS was conducted on the data collected from 406 college students. The results showed that ChatGPT literacy had a positive effect on academic engagement, and academic confidence mediated the relationship between ChatGPT literacy and academic engagement. Also, when the mediating effect of perceived academic competence was significant only when it was serially mediated. Based on these findings, we discussed the theoretical contributions of identifying the theoretical mechanism between ChatGPT literacy and academic engagement. In addition, practical implications regarding the importance of ChatGPT literacy education were described.

A Study on the Design and Implementation of an AI Mock Interview System for Computer Science Interview Preparation Using LLM-based ChatGPT (LLM 기반 ChatGPT를 활용한 컴퓨터 분야 면접 준비용 AI 모의 면접 시스템의 설계 및 구현에 대한 연구)

  • Jae-Sung Chun;Hee-Kwon Jang;Ji-Hye Kim;Chang-Min Bae;Dong-Gyu Lee;Il-Young Moon
    • Journal of Practical Engineering Education
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    • v.16 no.5_spc
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    • pp.643-651
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    • 2024
  • This study aims to design and implement an AI mock interview system for Computer Science (CS) interview preparation using LLM (Large Language Model) based ChatGPT. The system utilizes AI's natural language processing and speech recognition capabilities to analyze and provide real-time feedback on interview responses, helping users improve their weaknesses during the preparation process. According to a survey, 90% of users reported that the real-time feedback function provided substantial assistance in their interview preparation. Key features include GPT prompt generation and Speech-to-Text functionality, which converts voice data into text. The system received positive evaluations for its response time and feedback accuracy. Future research will explore expanding the range of question types and applying the system to various industries.