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• W4313582524 abstract "A key factor for successfully implementing gamified learning platforms is making students interact with the system from multiple digital platforms. Learning platforms that try to accomplish all their objectives by concentrating all the interactions from users with them are less effective than initially believed. Conversational bots are ideal solutions for cross-platform user interaction. In this paper, an open student-player model is presented. The model includes the use of machine learning techniques for online adaptation. Then, an architecture for the solution is described, including the open model. Finally, the chatbot design is addressed. The chatbot architecture ensures that its reactive nature fits into our defined architecture. The approach's implementation and validation aim to create a tool to encourage kids to practice multiplication tables playfully." @default.
• W4313582524 created "2023-01-06" @default.
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• W4313582524 date "2023-01-03" @default.
• W4313582524 modified "2023-10-10" @default.
• W4313582524 title "Personalized Gamification for Learning: A Reactive Chatbot Architecture Proposal" @default.
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• W4313582524 doi "https://doi.org/10.3390/s23010545" @default.
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