A Strategy for Incorporating Learning Analytics into the Design and Evaluation of a K-12 Science Curriculum
A Strategy for Incorporating Learning Analytics into the Design and Evaluation of a K-12 Science Curriculum
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将学习分析纳入 K-12 科学课程设计和评估的策略
DOI：
10.18608/jla.2014.12.6
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Reid Whitaker
中科院分区：
文献类型：
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作者：
Carlos Monroy;V. Rangel;Reid Whitaker
在本文中，我们讨论了一种将学习分析集成到在线 K-12 科学课程中的可扩展方法。在描述课程和基本教学框架之后，讨论了作为这种整合的一部分需要解决的挑战。我们包括基于教师使用数据的数据可视化示例以及用于检查基于探究的科学项目的方法。超过一百万学生和五万名教师使用该课程，海量丰富的数据集不断更新。该存储库描述了教师和学生的使用情况，并提供了利用数据改善教学的令人兴奋的机会。在本文中，我们使用了一个中型学区的数据，该学区包括 53 所学校、1,026 名教师，以及 2012-2013 学年 100 万次课程访问中的近三分之一。这一不断增长的数据集也带来了技术挑战，例如数据存储、复杂聚合以及对教育学、大数据和学习具有更广泛影响的分析。
In this paper, we discuss a scalable approach for integrating learning analytics into an online K–12 science curriculum. A description of the curriculum and the underlying pedagogical framework is followed by a discussion of the challenges to be tackled as part of this integration. We include examples of data visualization based on teacher usage data along with a methodology for examining an inquiry-based science program. With more than one million students and fifty thousand teachers using the curriculum, a massive and rich dataset is continuously updated. This repository depicts teacher and student usage, and offers exciting opportunities to leverage data to improve both teaching and learning. In this paper, we use data from a medium-sized school district, comprising 53 schools, 1,026 teachers, and nearly one-third of a million curriculum visits during the 2012–2013 school year. This growing dataset also poses technical challenges such as data storage, complex aggregation, and analyses with broader implications for pedagogy, big data, and learning.