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    인공지능 기술을 이용한 알고리즘 코딩학습 성취도 개선에 대한 연구 = A Study on Algorithm Coding Learning Improvement with Artificial Intelligence Technology

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    https://www.riss.kr/link?id=A108847645

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    The advancement of artificial intelligence technology, especially LLMs (large language models), created high expectations for the practicality of AI technology. In various areas, research to increase the practical applicability of AI technology is being actively conducted and some areas are showing success cases. Among them, the education area, especially coding education, has long been expected to show innovations in educational methods and improving learning outcomes through AI technology.
    This paper explores how various AI technologies that have emerged so far can be utilized in the field of coding education to improve efficiency of education and learning outcomes. This paper mainly explores the applicability of generative AI and existing KT (Knowledge Tracing) technology in the field of coding education and presents a case where DKT (Dynamic Knowledge Tracing) is applied to actual algorithm coding learning. We study on the effect of applying AI technology to algorithm coding learing.
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    The advancement of artificial intelligence technology, especially LLMs (large language models), created high expectations for the practicality of AI technology. In various areas, research to increase the practical applicability of AI technology is bei...

    The advancement of artificial intelligence technology, especially LLMs (large language models), created high expectations for the practicality of AI technology. In various areas, research to increase the practical applicability of AI technology is being actively conducted and some areas are showing success cases. Among them, the education area, especially coding education, has long been expected to show innovations in educational methods and improving learning outcomes through AI technology.
    This paper explores how various AI technologies that have emerged so far can be utilized in the field of coding education to improve efficiency of education and learning outcomes. This paper mainly explores the applicability of generative AI and existing KT (Knowledge Tracing) technology in the field of coding education and presents a case where DKT (Dynamic Knowledge Tracing) is applied to actual algorithm coding learning. We study on the effect of applying AI technology to algorithm coding learing.

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    참고문헌 (Reference)

    1 이영석, "예비 교사의 인공지능 리터러시 향상을 위한 교양교육의 효과 분석에 관한 연구" 한국컴퓨터교육학회 26 (26): 73-81, 2023

    2 J. Leinonen, "Using Large Language Models to Enhance Programming Error Messages" 2023

    3 M. Kazemitabaar, "Tovi : Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming" 1-23, 2023

    4 J. Finnie-Ansley, "The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming" 2022

    5 B. A. Becker, "Programming Is Hard – Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generation" ACM 2023

    6 G. Abdelrahman, "Knowledge tracing : A survey" 55 (55): 1-37, 2023

    7 R. Balse, "Investigating the Potential of GPT-3 in Providing Feedback for Programming Assessments" 1 : 292-298, 2023

    8 Y. Liu, "Improving knowledge tracing via pre-training question embeddings"

    9 GitHub, "GitHub Copilot: Your AI Pair Programmer"

    10 B. Puryear, "Gina : Github Copilot in the Classroom : Learning to Code with AI Assistance" 38 (38): 37-47, 2022

    1 이영석, "예비 교사의 인공지능 리터러시 향상을 위한 교양교육의 효과 분석에 관한 연구" 한국컴퓨터교육학회 26 (26): 73-81, 2023

    2 J. Leinonen, "Using Large Language Models to Enhance Programming Error Messages" 2023

    3 M. Kazemitabaar, "Tovi : Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming" 1-23, 2023

    4 J. Finnie-Ansley, "The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming" 2022

    5 B. A. Becker, "Programming Is Hard – Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generation" ACM 2023

    6 G. Abdelrahman, "Knowledge tracing : A survey" 55 (55): 1-37, 2023

    7 R. Balse, "Investigating the Potential of GPT-3 in Providing Feedback for Programming Assessments" 1 : 292-298, 2023

    8 Y. Liu, "Improving knowledge tracing via pre-training question embeddings"

    9 GitHub, "GitHub Copilot: Your AI Pair Programmer"

    10 B. Puryear, "Gina : Github Copilot in the Classroom : Learning to Code with AI Assistance" 38 (38): 37-47, 2022

    11 C. Zastudil, "Generative AI in Computing Education: Perspectives of Students and Instructors"

    12 T. Phung, "Generative AI for Programming Education : Benchmarking ChatGPT, GPT-4, and Human Tutors" 2 : 2023

    13 C. Bull, "Generative AI Assistants in Software Development Education:A vision for integrating Generative AI into educational practice, not instinctively defending against it" 2023

    14 R. Huang, "GPTutor: A ChatGPT-Powered Programming, in Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky" 2023

    15 C. A. Philbin, "Exploring the Potential of Artificial Intelligence Program Generators in Computer Programming Education for Students" 14 (14): 30-38, 2023

    16 M. Chen, "Evaluating Large Language Models Trained on Code" abs/2107.03374 : 2021

    17 D. Baidoo-Anu, "Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning"

    18 C. Piech, "Deep knowledge tracing" 28 : 2015

    19 P. Denny, "Computing Education in the Era of Generative AI"

    20 S. Sarsa, "Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models" 2022

    21 C. Helen, "Artificial intelligence in higher education : the state of the field" 22 : 2023

    22 C. K. Yeung, "Addressing two problems in deep knowledge tracing via prediction-consistent regularization" 1-10, 2018

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