{"title":"基于增量网络的持续行动迭代困境下的教师引导式同伴学习","authors":"Can Qiu;Dengxiu Yu;Zhen Wang;C. L. Philip Chen","doi":"10.1109/TCSS.2023.3335162","DOIUrl":null,"url":null,"abstract":"This article proposes a teacher-guided peer learning approach that employs a continuous action iterated dilemma (CAID) model based on an incremental network. Traditional peer learning approaches often assume static communication relationships between students, which is not consistent with actual society, and this affects the effectiveness of peer learning. Additionally, every student is a highly unique individual, and using a single mathematical model to mimic their behavior would result in research findings with limited applicability. Therefore, this article presents several innovations. First, we propose an incremental network generation algorithm that generates an effective communication network to improve classroom efficiency by enhancing the convergence of information between classmates. Second, considering the multiple unknown nonlinear environmental impacts, we design a student dynamic model based on CAID with multiple layers of nonlinearity to fit the different environmental impacts that different students receive. Finally, based on the incremental network and student dynamic model, we design the Lyapunov function to prove the convergence of the proposed model. This mathematical proof ensures that the proposed model is stable and unaffected by parameters, making it more applicable.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Teacher-Guided Peer Learning With Continuous Action Iterated Dilemma Based on Incremental Network\",\"authors\":\"Can Qiu;Dengxiu Yu;Zhen Wang;C. L. Philip Chen\",\"doi\":\"10.1109/TCSS.2023.3335162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article proposes a teacher-guided peer learning approach that employs a continuous action iterated dilemma (CAID) model based on an incremental network. Traditional peer learning approaches often assume static communication relationships between students, which is not consistent with actual society, and this affects the effectiveness of peer learning. Additionally, every student is a highly unique individual, and using a single mathematical model to mimic their behavior would result in research findings with limited applicability. Therefore, this article presents several innovations. First, we propose an incremental network generation algorithm that generates an effective communication network to improve classroom efficiency by enhancing the convergence of information between classmates. Second, considering the multiple unknown nonlinear environmental impacts, we design a student dynamic model based on CAID with multiple layers of nonlinearity to fit the different environmental impacts that different students receive. Finally, based on the incremental network and student dynamic model, we design the Lyapunov function to prove the convergence of the proposed model. This mathematical proof ensures that the proposed model is stable and unaffected by parameters, making it more applicable.\",\"PeriodicalId\":13044,\"journal\":{\"name\":\"IEEE Transactions on Computational Social Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computational Social Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10404003/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10404003/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
Teacher-Guided Peer Learning With Continuous Action Iterated Dilemma Based on Incremental Network
This article proposes a teacher-guided peer learning approach that employs a continuous action iterated dilemma (CAID) model based on an incremental network. Traditional peer learning approaches often assume static communication relationships between students, which is not consistent with actual society, and this affects the effectiveness of peer learning. Additionally, every student is a highly unique individual, and using a single mathematical model to mimic their behavior would result in research findings with limited applicability. Therefore, this article presents several innovations. First, we propose an incremental network generation algorithm that generates an effective communication network to improve classroom efficiency by enhancing the convergence of information between classmates. Second, considering the multiple unknown nonlinear environmental impacts, we design a student dynamic model based on CAID with multiple layers of nonlinearity to fit the different environmental impacts that different students receive. Finally, based on the incremental network and student dynamic model, we design the Lyapunov function to prove the convergence of the proposed model. This mathematical proof ensures that the proposed model is stable and unaffected by parameters, making it more applicable.
期刊介绍:
IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.