摘要
全球的MOOC浪潮推动了在线课程大规模传播和发展,由此产生了海量多样的数据。"大数据"分析技术加速应用到教育领域,评估、分析和利用这些数据对于学习效果的提升有着重要的影响。当前,各类学习系统和学习工具都按其自有的格式存储和传输数据,造成其数据通用性差,而且难以被分享和深度利用。标准化组织IMS针对目前学习系统难以跨平台收集学习数据以及数据标准不一的问题,制定了一项学习分析数据互操作规范——Caliper Analytics,试图解决学习分析中有关以统一的形式收集并分析数据的关键问题。该规范通过"计量组谱"构建记录和存储分析数据的通用格式,并通过"Sensor API"捕获和传递散落在各个平台中的分析数据。这将有利于学习分析的数据交换和跨平台使用,从而让有价值的学习分析数据得以更好地利用。这个统一的标准能促使更有效地实现对在线课程质量、效果及性能的分析;帮助院校、教师和教学设计师等数字化教学内容的开发者测量、修改及迭代教育产品;帮助学习者更好地使用学习分析结果持续提升学习绩效。该规范应用前景广泛,但还将面临数据源的呈现方式、数据自有的目标用途、教育机构的组织文化、分析技术的实施效果以及商业模式上的潜在风险等方面的挑战。
The global wave of MOOC has promoted the dissemination and development of online courses,which generates massive and diversified data, and thus accelerates the application of ＂big data＂ analysis technologyin education. The assessment, analysis and use of the data have an important influence on learning. Nowadays, Allthe LMS and learning tools have their own formats to store and transfer data, resulting in difficulties in collectingand analyzing cross-platform data with a unified format. IMS GLC developed the Caliper Analytics specification,built up an data inter-operation framework, and tried to resolve the key relevant issues. This specificationestablishes a common format for analyzing and recording data by ＂metric profile＂, and with ＂sensor API＂ capturesand delivers analytical data from different platforms, which will facilitate the exchange and cross-platform use oflearning analytics data, so that valuable learning data can be used better. This unified standard can promote moreeffective analysis on quality, effectiveness and performance of online courses; help colleges, teachers, instructionaldesigners and other digital teaching content developers to measure, modify and iterate education products; helplearners to improve learning performance with analysis results. Although, this standard has good applicationprospects, it will still face a lot of challenges： such as the way to present the data sources, its own intended usage ofdata, organizational culture of institutions, the implementation effectiveness of analytical techniques, and thepotential risks of the business model.
出处
《现代远程教育研究》
CSSCI
2016年第2期98-106,共9页
Modern Distance Education Research
基金
中国博士后科学基金第八批特别资助项目“泛在学习环境下基于情境感知的协同认知空间建构研究”(2015T80049)
