EAGER: TEACHER: A Pilot Study on Mining the Web for Customized Curriculum Planning

EAGER：老师：挖掘网络进行定制课程规划的试点研究

• 批准号: 1350364
• 负责人: Jaime Carbonell
• 金额: $ 24.96万
• 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: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1350364&HistoricalAwards=false
• 关键词: EAGER; TEACHER; Pilot; Study; Mining

With massive quantities of educational materials freely available on the web, the vision of personalized and readily accessible education appears within our grasp. General-purpose search engines are insufficient as they do not focus on educational materials, objectives, pre-requisite relations, etc., nor do they stitch together multiple sources to create customized curricula for students' goals and current knowledge. This exploratory project focuses on establishing fundamental results in: (1) extracting educational units from diverse web sites and representing them in a large directed graph, whose nodes are content descriptors and whose edges encode pre-requisite and other relations; (2) conducting multi-field topic inference via a new family of graphical models to infer relations among educational units; and (3) automated curricular planning, focusing on providing sequences of lessons, courses, exercises and other education units for a student to achieve his or her educational goals, conditioned on current skills. The objective is to develop a data-driven course/curriculum planner on demand, based on a graph traversal that is enriched with alternate paths, reinforcement options, and conditional branches to match the learner's needs.The broader impact of this research is two-fold: (1) developing methods for mining and traversing web-based educational materials in general, later generalizing to multi-media lessons and courses; and (2) individualized curricular planning, so any student anywhere can be provided with guidance on how to navigate and exploit the vast ocean of massive open online course (MOOC) materials and other educational texts, exercises, etc. in a manner customized to the student's learning objective, capabilities and skills. The resulting system, named TEACHER, can be applied to learning specific job skills, to reinforce classroom instructions, or as stand-alone academic support to address, for instance, the huge percentage of students who attempt taking MOOCs but never complete them due to lack of requisite skills and lack of guidance on how to acquire them. Project web site (http://nyc.lti.cs.cmu.edu/teacher/) will be used to disseminate results.

随着大量的教育材料在网上免费提供，个性化和容易获得的教育的愿景似乎在我们的掌握。通用搜索引擎是不够的，因为它们不关注教育材料、目标、先决条件关系等，他们也没有将多个资源整合在一起，为学生的目标和现有知识创建定制的课程。这个探索性项目的重点是建立以下方面的基本成果：（1）从不同的网站中提取教育单元，并将其表示在一个大的有向图中，其节点是内容描述符，其边编码先决条件和其他关系;（2）通过一个新的图形模型家族进行多领域主题推理，以推断教育单元之间的关系;以及（3）自动化课程规划，集中于为学生提供课程、课程、练习和其他教育单元的序列，以实现他或她的教育目标，以当前技能为条件。本研究的目标是开发一个基于数据驱动的课程/课程计划器，该课程/课程计划器基于图遍历，该图遍历富含替代路径、强化选项和条件分支以匹配学习者的需求。以及（2）个性化的课程规划，因此任何地方的任何学生都可以被提供关于如何以针对学生的学习目标、能力和技能定制的方式导航和利用海量开放式在线课程（MOOC）材料和其他教育文本、练习等的指导。由此产生的系统名为TEACHER，可用于学习特定的工作技能，加强课堂教学，或作为独立的学术支持，以解决例如，由于缺乏必要的技能和缺乏如何获得这些技能的指导，试图参加MOOC但从未完成的学生的巨大比例。将利用项目网站（http：//nyc.lti.cs.cmu.edu/teacher/）传播成果。