Collaborative Research: Educational Data Mining Approaches for Digital Libraries

探索馆和犹他州教育技术与学习科学部之间的这一合作研究项目调查了在线评估方法以及教育数据挖掘在教育数字图书馆和服务中的应用。在过去的几十年里，许多工作都集中在开发用于在大型数据集中发现模式的算法和方法上，称为从数据中发现知识（KDD）。Webmetrics是KDD在Web使用挖掘中的应用，在电子商务等领域发展迅速。教育数据挖掘（EDM）是一种新兴的分析在线学习环境和教育数字图书馆中获取的大量纵向用户数据的工具，本项目使用EDM来分析来自探索馆学习资源库和犹他州州立大学教学架构师的数据。结果与更传统的评估数据（例如，调查，访谈）作为一个全面的战略，以了解科学教师的行为，动机和学习经验与数字图书馆资源的一部分，这项有针对性的研究的结果有望贡献新的知识，知识发现从数据和教育数据挖掘的应用，数字图书馆。该项目为用户体验设计的改进以及量身定制的教师专业发展提供了信息，为越来越多的关于使用网络支持方法进行教师学习的研究做出了贡献。

This collaborative research project between the Exploratorium and Utah State's Department of Instructional Technology and Learning Sciences investigates online evaluation approaches and the application of educational data mining to educational digital libraries and services. Much work over the past decades has focused on developing algorithms and methods for discovering patterns in large datasets, known as Knowledge Discovery from Data (KDD). Webmetrics, the application of KDD to web usage mining, is growing rapidly in areas such as e-commerce. Educational Data Mining (EDM) is just beginning to emerge as a tool to analyze the massive, longitudinal user data that are captured in online learning environments and educational digital libraries.This project uses EDM to examine data from the Exploratorium's Learning Resources Collection and the Instructional Architect at Utah State University. The results are combined with more traditional evaluation data (e.g., surveys, interviews) as part of a comprehensive strategy to understand science teachers' behaviors, motivations, and learning experiences with digital library resources The outcomes of this targeted research promise to contribute new knowledge regarding Knowledge Discovery from Data and the application of Educational Data Mining to digital libraries. The project informs improvements in the design of the user experience, as well as tailored teacher professional development, contributing to a growing body of research on teacher learning by using cyber-enabled approaches.