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

随着大量的教育材料在网络上免费提供，个性化和易于获取的教育的愿景似乎在我们的掌握之中。通用的搜索引擎是不够的，因为它们不关注教材、目标、先决条件关系等，也不能根据学生的目标和现有知识将多个资源拼接在一起来创建定制的课程。本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，并将其表示为一个大的有向图，其节点是内容描述符，其边编码先决条件和其他关系；(2)通过一组新的图形模型进行多领域主题推理，推断教育单元之间的关系；(3)自动化课程规划，侧重于根据学生当前的技能，为学生提供一系列的课程、课程、练习和其他教育单元，以实现他或她的教育目标。目标是根据需要开发一个数据驱动的课程/课程规划器，基于图形遍历，其中包含丰富的替代路径，强化选项和条件分支，以匹配学习者的需求。本研究的广泛影响是双重的：(1)开发了一般的基于网络的教育材料的挖掘和浏览方法，后来推广到多媒体课程和课程；(2)个性化课程规划，使任何地方的任何学生都能根据自己的学习目标、能力和技能，以定制的方式，指导他们如何驾驭和利用海量的MOOC （open online course，开放网络课程）材料和其他教育文本、练习等。由此产生的系统名为TEACHER，可以用于学习特定的工作技能，加强课堂教学，或者作为独立的学术支持来解决，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，大量学生试图参加mooc，但从未完成课程。项目网站（http://nyc.lti.cs.cmu.edu/teacher/）将用于传播结果。

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.