“宽墙”如何提高参与度:来自Scratch自然实验的证据

Sayamindu Dasgupta, Benjamin Mako Hill
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引用次数: 18

摘要

设计建构主义学习系统和工具包的一个核心目标是实现“宽墙”——一个用来描述支持各种创造性成果的比喻。确保通过工具包为学习者提供广泛的设计空间是实现宽墙的常用方法。我们使用计量经济学方法,通过Scratch在线社区的自然实验,对宽墙理论进行了实证检验。我们估计了政策变化的因果效应,该政策变化使大量Scratch用户能够访问更强大版本的Scratch数据结构,有效地拓宽了学习者的界限。我们表明,访问和使用这些更强大的新数据结构会使学习者更频繁地使用数据结构。我们的研究结果为宽墙可以提高参与度和学习能力的理论提供了支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How “Wide Walls” Can Increase Engagement: Evidence From a Natural Experiment in Scratch
A core aim for designing constructionist learning systems and toolkits is enabling "wide walls"-a metaphor used to describe supporting a diverse range of creative outcomes. Ensuring that a broad design space is afforded to learners by a toolkit is a common approach to achieving wide walls. We use econometric methods to provide an empirical test of the wide walls theory through a natural experiment in the Scratch online community. We estimate the causal effect of a policy change that gave a large number of Scratch users access to a more powerful version of Scratch data structures, effectively widening the walls for learners. We show that access to and use of these more powerful new data structures caused learners to use data structures more frequently. Our findings provide support for the theory that wide walls can increase engagement and learning.
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