学习分析技术的发展和挑战——第四届学习分析与知识国际会议评析  

Learning Analytics Development and Challenges—— A Review on the Fourth International Conference on Learning Analytics and Knowledge

作　　者：吴永和[1] 曹盼[2] 邢万里[3] 马晓玲[4] 

机构地区：[1]华东师范大学开放教育学院及上海数字化教育装备工程技术研究中心,上海200062 [2]华东师范大学教育信息技术学系,上海200062 [3]密苏里大学哥伦比亚分校信息科学与学习技术系,美国65201 [4]华东师范大学信息学系,上海200062

出　　处：《开放教育研究》2014年第6期72-80,共9页Open Education Research

基　　金：上海市浦江人才计划项目"基于教育大数据的学习分析教育应用创新研究"(14PJC034);上海市科委"科技创新行动计划"项目"面向移动互联网的自主学习系统研制及应用示范"(1451109300);重点科技攻关专项"上海数字化教育装备工程技术研究中心持续研发项目"(13DZ2280300)

摘　　要：第四届学习分析与知识国际会议于2014年3月24-28日在美国印第安纳州波利斯成功举行,会议以探讨学习分析研究、理论和实践的交叉点为主题,涵盖了学习分析技术在教育学、教育心理学、教育管理学、工程学中的运用,以及教育数据挖掘、计算机算法和数据可视化等方面的发展。文章首先说明了此次会议的背景,从研究、理论和实践三方面阐析学习分析主题之间的关系,简述了来自孟菲斯大学的格莱赛教授(Art Graesser)、香港大学的罗陆慧英(Nancy Law)教授和加州大学圣地亚哥分校的克莱默教授(Scott Klemmer)三位专家所作的主题报告;然后从学习分析与课程教学设计、教与学过程挖掘和评价、学习分析与学习资源、文本挖掘与语义分析、学习分析与数学教育、学习分析与教育一体化、学习分析多元化等七个方面对分论坛报告及会议进行系统综述;文章最后指出未来学习分析研究和发展的五个方向:逐步明晰学习分析系统概念与理论、研究通用性的算法和模型、研制学习分析技术标准、支撑数据驱动的学习和评估、融入教育信息化应用与实践、推进教育的深度发展和加快多元化进程,期望能够推动学习分析系统化研究和在教育中的深度应用。The Fourth International Conference on Learning Analytics and Knowledge （ LAK 14 ） was successfully held on March 24 -28, 2014 in Indianapolis, Indiana, the United States of America. The conference focuses on the intersection of research, theory, and practice on learning analysis related on learning technologies in educational psy-chology, educational management, education, engineering, education data mining, computerized algorithms, data visualization and its research development and their intersection. This paper introduces the background of the confer-ence, and then describes the keynotes presentations by Art Graesser, Nancy Law and Scott Klemmer. Next, the authors reviewed and analyzed those reports and papers systematically from the aspects of mathematics education, curriculum and instructional design, mining and evaluation of teaching and learning process, learning resources, text mining and semantic analysis, integration of education, as well as learning analysis diversification. At the end,the authors conclude and point out the hot research and development directions of learning analytics in the future such as gradual-ly clearing analysis system concepts and theories of learning, research versatility of algorithms and models, develop-ment of technical standards on learning analytics, supporting data-driven learning and assessment, application of in-formation technology in the education and practice, promoting the deep development of education and accelerating di-versified process. We hope that this article can promote systematic research of learning analytics and deep application in education.

关 键 词：学习分析 数据挖掘 算法 可视化 教育理论 教学设计 

分 类 号：G434[文化科学—教育学]