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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/152357


    Title: Interactive AI Application: Operant Conditioning and Adaptive Learning
    Authors: 周致遠;江尚芸
    Chou, Chih-Yuan;Chiang, Shang Yun;Huang, Jo-Mei;Sung, Yi-Chieh;Chen, Jian Ting;Wu, Ying Hsuan;Liu, Tung-Lin
    Contributors: 資管系
    Keywords: Operant conditioning;Adaptive learning;Interactive artificial intelligence;TPACK model;System design for e-learning
    Date: 2024-07
    Issue Date: 2024-07-17
    Abstract: The motivation behind this research project stems from concerns regarding the disparity of mathematical abilities between students in Taiwan, which is the largest among all participating countries, according to the 2022 PISA assessment. Therefore, leveraging technology to provide adaptive learning for students and enhance their autonomous learning abilities is an important and urgent educational issue that needs to be addressed. In order to address the problem above, this research will utilize large language models (LLMs) to generate interactive AI tutors featuring personalized interaction and personalized difficulty adjustments as their characteristics, providing students with customized adaptive learning. Additionally, operant conditioning theory will be employed to practice interactive AI tutoring and voice interactions as reinforcement, thereby increasing the frequency and willingness of students to learn mathematics. It is expected that by integrating educational theory and information technology into practical applications through this research, highly personalized adaptive learning can be achieved.
    Relation: Proceeding of the 28th Pacific Asia Conference on Information Systems (PACIS 2024), Association for Information Systems (AIS)
    Data Type: conference
    Appears in Collections:[Department of MIS] Proceedings

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