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学习分析:从源起到实践与研究

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学习分析是“大数据”在教育领域的应用,引发了教育技术发展的第三次浪潮,并获得学术界的广泛关注。本文梳理了学习分析的形成过程,然后从利益相关者、研究目标、研究对象、技术方法四个维度,回顾了近五年来国内外学者在学习分析方面的研究成果,并提出未来发展趋势和可能遇到的挑战,便于相关人员制定教育决策、优化教育管理过程以及完善学习过程。研究结果表明,学习分析研究主题主要涵盖学习者知识建模、学习情绪建模、学习行为特征抽取、学习活动跟踪、学习者建模、学位获取分析、教学资源和教学策略优化、自适应学习系统和个性化学习、在线学习影响因素分析九个方面;分析数据主要来源于集中式学习环境、分布式学习环境以及身体活动数据;常用分析方法包括统计分析、信息可视化、数据挖掘、社会网络分析、话语分析和网站分析。目前,学习分析研究遇到的挑战包括教育数据预处理难度大、数据访问权限不明确、学习分析适用性有限。虽然学习分析尚处于发展初期,但由于能够为教育系统各级决策提供科学参考,已经成为教育信息化的重要内容之一。
Learning Analytics:From the Origin to Practice
Learning analytics is a big data application in the field of education, triggering the development of the third wave in educational technology, and receiving wide attention from international and domestic academics. The ar-ticle reviews the origin of learning analytics, and then from four dimensions of whom, why, what, how, recalling the past five years relevant research results, and puts forward future development challenges that may be encountered. Spe-cifically, based on macro, meso and micro perspective, this research facilitates related personnel to make education de-cisions, optimize the educational management process and improve the learning process. <br> Research topics cover nine aspects including:learners' knowledge modeling, learners' emotion modeling, learning behavior feature extraction, learning activities tracking, the learner modeling, obtaining degree analytics, the teach-ing resources and the teaching strategy optimization, adaptive learning system and personalized learning, and online learning influence factors analysis. The data mainly comes from the centralized learning environment, distributed learning environment, and physical activity data. The common analysis methods include statistical analysis, informa-tion visualization,data mining, social network analysis, discourse analysis, and web analytics. The challenges in-clude:the difficulty of data preprocessing, the uncertainty of data accessing rights, and the limited application scope. Although the study is still in the initial stages of development, it has become an important part of educational informa-tionization as it provides scientific reference for decision-making at all levels of the education system.

learning analyticseducational data miningsocial network analysisinformation visualization

吴青、罗儒国

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武汉大学 教育科学学院,湖北武汉430072

学习分析 教育数据挖掘 社会网络分析 信息可视化

湖北省教育科学“十二五”规划2013年度课题全国教育科学“十二五”规划2013年度教育部青年课题

2013B004ECA130375

2015

开放教育研究
上海远程教育集团 上海开放大学

开放教育研究

CSTPCDCSSCICHSSCD北大核心
影响因子:9.844
ISSN:1007-2179
年,卷(期):2015.(1)
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