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[英文摘要] :
Teaching material sharing (TMS) networks enrich teachers in their teaching capacity and provisioning of high-quality education services through sharing among peers. However, a TMS network needs proper incentives to be sustainable. By analyzing the empirical behavior data of elementary school teachers on TMS networks, we develop prescriptive behavior models that describe the relationship among the membership join and leave, and material upload and richness of teaching materials, individual altruism and rewards. We first model individual behaviors by probability distributions and the Bass model after identification of key factors that affect teachers' behaviors. Then, we model the collective behaviors and interacting dynamics. On top of these models, we adopt an agent-based simulation to evaluate the TMS behaviors under different conditions of content richness, altruism level and rewards.
Keywords—Teaching Material Sharing, Join, Leave, Upload, Content Richness, Altruism, Reward, Collective Behavior, Agent-based Simulation