Supporting Science Understanding through a Customized Learning Service for Concept Knowledge

学习研究的一个重要的教育发现是，每个学生对世界如何运作的每一个学习情况都有先入为主的看法，这些初步的理解需要明确地作为有效教学过程的一部分。本研究将设计并评估概念知识定制学习服务（CLICK）的端到端原型，通过比较学习者的概念理解（描述为概念图）与从数字图书馆资源生成的参考领域概念图，实现以学生为中心的定制。这些比较将使学习环境能够提供从数字图书馆提取的教育资源的定制检索、交付和表示。这项研究将由科罗拉多大学博尔德分校和UCAR dlesprogram Center的研究人员合作进行。一项专家研究将收集有关参考概念图生成、学生和参考概念图的比较以及为教学补救选择适当的数字图书馆资源的人类数据。这些数据将用于开发和评估自然语言处理算法，该算法将自动从dese资源和学生作业中生成概念图。专家研究的结果与以任务为中心的设计方法相结合，将为CLICK服务原型的开发提供信息。最后，学生的学习将使用行为和语言数据来评估，以解决学习过程和科学理解的潜在变化。本研究扩展了适应性学习环境的现有理论和技术。本研究的主要成果包括CLICK概念框架和CLICK服务原型。这些共同为建立基于教育数字图书馆的有效学习环境提供了一个模型。另一个重要成果是开发了一种基于自动自然语言处理的方法，用于识别和表示具有目标STEM主题深度知识特征的基本科学概念。

A key educational finding from learning research is that every student brings preconceptions about how the world works to every learning situation, and that these initial understandings need to be explicitly targeted as part of an effective instructional process. This research will design and evaluate an end-to-end prototype of a customized learning service for concept knowledge (CLICK) which will enable student-centered customizations by comparing learners' conceptual understanding, depicted as concept maps, with reference domain concept maps generated from digital library resources. These comparisons will enable learning environments to provide customized retrieval, delivery, and presentation of educational resources drawn from digital libraries.This research will be conducted by a partnership between investigators at the University of Colorado at Boulder and the DLESE Program Center at UCAR. An expert study will be conducted to gather human data on reference concept map generation, comparison of student and reference concept maps, and selection of appropriate digital library resources for instructional remediation. These data will be used for developing and evaluating natural language processing algorithms that will automatically generate concept maps from DLESE resources and student work. Results from the expert study, combined with task-centered design methods, will inform the development of the CLICK service prototype. Finally, student learning will be assessed using behavioral and verbal data to address potential changes in learning processes and science understanding.This research extends current theories and techniques in adaptive learning environments. Primary outcomes of this research include the CLICK conceptual framework and the CLICK Service prototype. Together these provide a model for building effective learning environments based on educational digital libraries. Another significant outcome is the development of an automatic natural language processing-based method for identifying and representing essential science concepts that characterize deep knowledge of a targeted STEM topic.