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

随着网络上免费提供大量的教育材料，个性化和易于获取的教育的愿景出现在我们的掌握之中。通用搜索引擎是不够的，因为它们没有侧重于教育材料、目标、先决条件关系等，也没有将多种来源结合在一起，为学生的目标和当前知识创建定制的课程。这个探索性项目的重点是建立基本结果：(1)从不同的网站中提取教育单元，并将它们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)通过新的图形模型进行多领域主题推理，以推断教育单元之间的关系；以及(3)自动课程规划，重点是根据当前技能为学生提供课程、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。本研究的目的是开发一种数据驱动的课程/课程计划器，其基于图的遍历，该图遍历丰富了备选路径、强化选项和条件分支以满足学习者的需要。本研究的更广泛的影响是两方面的：(1)开发了挖掘和遍历一般的基于网络的教育材料的方法，随后推广到多媒体课程和课程；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指导，指导如何以适合学生的学习目标、能力和技能的方式，导航和利用海量的开放式在线课程(MOOC)材料和其他教育文本、练习等。由此产生的名为教师的系统，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，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而试图参加MOOC课程但从未完成的学生的比例很大。项目网站(http://nyc.lti.cs.cmu.edu/teacher/)将用于传播成果。

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.