混合学习设计的学科差异:一项网络分析研究

A. Whitelock-Wainwright, Yi-Shan Tsai, Kayley M. Lyons, Svetlana Kaliff, Mike Bryant, K. Ryan, D. Gašević
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引用次数: 10

摘要

学习设计研究主要依赖于基于调查和访谈的方法,这两种方法都受到社会期望和回忆的限制。本文提供了另一种方法,即使用认知网络分析分析物理和在线学习活动数据。本文以10个学院在4年期间(2016- 2019)提供的6040门课程为样本,说明了网络在理解学习设计方面的效用。具体而言,通过采用网络分析方法,我们发现:大学显然致力于混合式学习,但学科之间和学科内部都存在相当大的差异。
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Disciplinary differences in blended learning design: a network analytic study
Learning design research has predominately relied upon survey- and interview-based methodologies, both of which are subject to limitations of social desirability and recall. An alternative approach is offered in this manuscript, whereby physical and online learning activity data is analysed using Epistemic Network Analysis. Using a sample of 6,040 course offerings from 10 faculties across a four year period (2016--2019), the utility of networks to understand learning design is illustrated. Specifically, through the adoption of a network analytic approach, the following was found: universities are clearly committed to blended learning, but there are considerable differences both between and within disciplines.
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