This research develops computational models of teaching and learning and combines these models with machine learning algorithms to interpret learners’ actions and customize instruction based on these interpretations. This approach results in frameworks that can be adapted to a variety of educational domains, with the frameworks clearly separating components that can be shared across tasks and components that are customized based on the educational content. Using this approach, this dissertation addresses three major questions: (1) How can one diagnose learners’ knowledge from their behavior in games and virtual laboratories? (2) How can one predict whether a game will be diagnostic of learners’ knowledge? and (3) How can one customize instruction in a computer-based tutor based on a model of learning in a domain?

关键词：知识诊断；教育游戏；教育游戏设计；概率模型

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