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題名 Interactive AI Application: Operant Conditioning and Adaptive Learning
作者 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
貢獻者 資管系
關鍵詞 Operant conditioning; Adaptive learning; Interactive artificial intelligence; TPACK model; System design for e-learning
日期 2024-07
上傳時間 2024-07-17
摘要 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.
關聯 Proceeding of the 28th Pacific Asia Conference on Information Systems (PACIS 2024), Association for Information Systems (AIS)
資料類型 conference
dc.contributor 資管系
dc.creator (作者) 周致遠;江尚芸
dc.creator (作者) Chou, Chih-Yuan;Chiang, Shang Yun;Huang, Jo-Mei;Sung, Yi-Chieh;Chen, Jian Ting;Wu, Ying Hsuan;Liu, Tung-Lin
dc.date (日期) 2024-07
dc.date.accessioned 2024-07-17-
dc.date.available 2024-07-17-
dc.date.issued (上傳時間) 2024-07-17-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/152357-
dc.description.abstract (摘要) 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.
dc.format.extent 127 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Proceeding of the 28th Pacific Asia Conference on Information Systems (PACIS 2024), Association for Information Systems (AIS)
dc.subject (關鍵詞) Operant conditioning; Adaptive learning; Interactive artificial intelligence; TPACK model; System design for e-learning
dc.title (題名) Interactive AI Application: Operant Conditioning and Adaptive Learning
dc.type (資料類型) conference