Assistance in Building Student Models Using Knowledge Representation and Machine Learning

机译：使用知识表示和机器学习协助建立学生模型

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We propose a method and a first authoring tool to assist the design and implementation of diagnostic techniques. This method is independent from the domain and allows building more than one technique at once. The method is based on knowledge representation and a semi-automatic machine learning algorithm. We tested the method in two domains, surgery and reading English. Techniques built with our method beat the majority class in terms of accuracy.

机译：我们提出了一种方法和第一个创作工具来协助诊断技术的设计和实现。此方法独立于域，并允许一次构建多个技术。该方法基于知识表示和半自动机器学习算法。我们在两个领域（手术和阅读英语）中测试了该方法。用我们的方法构建的技术在准确性方面超过了大多数同类产品。

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《International conference on artificial intelligence in education》|2013年|754-757|共4页
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作者
Sebastien Lalle; Vanda Luengo; Nathalie Guin;
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Knowledge diagnostic; authoring tool; machine learning;

机译：知识诊断;创作工具;机器学习;

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2. Comparing machine learning to knowledge engineering for student behavior modeling: a case study in gaming the system [J] . Paquette Luc, Baker Ryan S. Interactive Learning Environments . 2019,第5a8期

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4. Assistance in Building Student Models Using Knowledge Representation and Machine Learning [C] . Sébastien Lallé, Vanda Luengo, Nathalie Guin International Conference on Artificial Intelligence in Education . 2013

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5. Using Machine Learning Models to Predict Student Retention: Building a State-Wide Early Warning System [D] . Muncie, Travis. 2020

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6. Building a Normalized Conceptual Representation of Medical Language: A Semantic Composition Method Driven by Domain Knowledge Models [O] . J. Bouaud, P. Zweigenbaum, B. Bachimont 1997

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7. Machine Learning and Knowledge Representation in the LaboUr Approach to User Modeling [O] . Wolfgang Pohl, Achim Nick 1999

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8. Research on knowledge representation, machine learning, and knowledge acquisition [R] . Buchanan, Bruce G. 1987

机译：研究知识表示，机器学习和知识获取

Assistance in Building Student Models Using Knowledge Representation and Machine Learning

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