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Predictive artificial intelligence and pedagogical agent modeling in the cognitive imprinting of knowledge and skill domains

机译:知识和技能领域的认知烙印中的预测人工智能和教学代理建模

摘要

System and methods for predicting and dynamically adapting the most appropriate content and teaching strategies that aid individual student learning. System and methods are based on a cognitive model that integrates new information with what the student already knows. A program of study is predicted by the unique cognitive needs of the individual student correlated with aggregated student data history using an Artificial Intelligence Engine (AI Engine). Said system and methods then dynamically adapt the initial cognitive model to the student's ongoing progress using personalized software Agents. Said system and methods include a computer network that incorporates a server-side AI Engine and a collection of client-side software Agents embodied as animated characters. The program connects new information to prior knowledge and then strengthens these connections through dedicated learning Activities, customized to the student, to ensure that effective, and real, learning occurs.
机译:用于预测和动态适应最适合学生个人学习的内容和教学策略的系统和方法。系统和方法基于认知模型,该模型将新信息与学生已经知道的信息整合在一起。通过使用人工智能引擎(AI Engine),通过与汇总的学生数据历史相关的单个学生的独特认知需求,可以预测学习计划。然后,所述系统和方法使用个性化软件代理将初始认知模型动态地适应于学生的正在进行的进度。所述系统和方法包括计算机网络,该计算机网络结合了服务器端AI引擎和体现为动画角色的客户端软件代理的集合。该计划将新信息与先验知识联系起来,然后通过针对学生量身定制的专门学习活动来加强这些联系,以确保进行有效而真实的学习。

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