形成性评估和学习分析

Dirk T. Tempelaar, A. Heck, H. Cuypers, H. V. D. Kooij, E. V. D. Vrie
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引用次数: 70

摘要

学习分析旨在通过系统地测量与学习相关的数据,并将这些测量结果告知学习者和教师,从而加强学习过程,从而支持对学习过程的控制。学习分析有各种各样的信息源,两种主要类型是意图和学习者活动相关的元数据[1]。这一贡献旨在提供Shum和Crick的学习分析基础设施理论框架[1]的实际应用,该框架将学习倾向数据与从基于计算机的形成性评估中提取的数据相结合。后一个数据组件来自ONBETWIST的一个教育项目,是SURF项目“测试和测试驱动学习”的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Formative assessment and learning analytics
Learning analytics seeks to enhance the learning process through systematic measurements of learning related data, and informing learners and teachers of the results of these measurements, so as to support the control of the learning process. Learning analytics has various sources of information, two main types being intentional and learner activity related metadata [1]. This contribution aims to provide a practical application of Shum and Crick's theoretical framework [1] of a learning analytics infrastructure that combines learning dispositions data with data extracted from computer-based, formative assessments. The latter data component is derived from one of the educational projects of ONBETWIST, part of the SURF program 'Testing and Test Driven Learning'.
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