Building Cognitive Tutors with Programming by Demonstration: When Simulated Students help Cognitive Modeling and Educational Studies

通过演示编程培养认知导师：当模拟学生帮助认知建模和教育研究时

• 批准号: 0537198
• 负责人: William Cohen
• 金额: --
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0537198&HistoricalAwards=false
• 关键词: Building; Cognitive; Tutors; Programming; Demonstration

This project will develop a novel design for an Intelligent Authoring System for Cognitive Tutors. The system includes a machine learning facility - called the Simulated Student - that generates a "cognitive model" which can perform the subject task just as students do. The Simulated Student learns the production rules in the cognitive model much like a human student: by observing examples of worked-out problem solutions, reading associated instructions, and getting feedback on solution attempts. The author provides the examples, English instructions, and solution feedback, and thus acts more like a teacher than a programmer. In this way, the Simulated Student allows authors to bypass the time-consuming and difficult-to-learn programming that is currently required to build the Cognitive Model component of a Cognitive Tutor. The key technology behind Simulated Students is programming by demonstration, in which machine learning is integrated tightly into a user interface. We plan to use learning methods based on Inductive Logic Programming and Statistical Relational Learning. With the proposed Intelligent Authoring System, an author will perform the following steps to build a tutor: (1) build a graphic user interface (GUI) for the tutor; (2) demonstrate solutions, by solving problems with the GUI and annotating steps with instructional messages, thus providing training data for the Simulated Student to learn production rules that replicate the demonstrations; and (3) test the production rules and giving the Simulated Student feedback on its solutions for another set of problems.This effort builds upon a suite of Cognitive Tutor Authoring Tools (CTAT), which includes a built-in GUI builder, a facility to demonstrate solution steps and recode them, and facilities to write and test production rules. The proposed Intelligent Authoring System will be implemented by integrating the Simulated Student into CTAT, so all three authoring steps will be a natural extension of existing authoring tools. This project has broader impacts in advancing intelligent systems technology and in providing better cognitive tutors by allowing teachers to be authors.

本项目将为认知导师的智能创作系统开发一种新颖的设计。该系统包括一个名为“模拟学生”的机器学习设备，它可以生成一个“认知模型”，可以像学生一样执行主题任务。模拟学生像人类学生一样学习认知模型中的生产规则：通过观察解决问题的示例，阅读相关说明，并获得解决方案尝试的反馈。作者提供了示例、英文说明和解决方案反馈，因此更像一个老师而不是程序员。通过这种方式，模拟学生允许作者绕过耗时且难以学习的编程，这些编程目前需要构建认知导师的认知模型组件。模拟学生背后的关键技术是通过演示编程，其中机器学习紧密集成到用户界面中。我们计划使用基于归纳逻辑规划和统计关系学习的学习方法。使用建议的智能创作系统，作者将执行以下步骤来构建导师：(1)为导师构建图形用户界面（GUI）；(2)演示解决方案，通过使用GUI解决问题并用教学消息注释步骤，从而为模拟学生提供培训数据，以学习复制演示的生产规则；(3)测试生成规则，并对另一组问题的解决方案给予模拟学生反馈。这项工作建立在一套Cognitive Tutor Authoring Tools （CTAT）之上，它包括一个内置的GUI构建器、一个演示解决方案步骤并对其进行重新编码的工具，以及编写和测试生产规则的工具。拟议的智能创作系统将通过将模拟学生集成到CTAT中来实现，因此所有三个创作步骤都将是现有创作工具的自然扩展。该项目在推进智能系统技术和通过允许教师成为作者提供更好的认知导师方面具有更广泛的影响。