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首页> 外文会议>International Conference of the System Dynamics Society >Providing structural transparency when exploring a model's behavior: Effects on performance and knowledge acquisition
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Providing structural transparency when exploring a model's behavior: Effects on performance and knowledge acquisition

机译：在探索模型行为时提供结构透明度：对性能和知识获取的影响

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摘要

Prior exploration is an instructional strategy which has improved performance and knowledge acquisition in system-dynamics based learning environments, but only to a limited degree. This study investigates whether model transparency, showing users the internal structure of models, can extend the prior exploration strategy and improve learning even more. In an experimental study, participants in a web-based simulation learned about and managed a small developing nation. All participants were provided the prior exploration strategy but only half received prior exploration embedded in a structure-behavior diagram intended to make the underlying model's structure more transparent. Participants provided with the more transparent strategy demonstrated better knowledge acquisition of the underlying model on an objective measure (multiple-choice posttest) but no difference on a subjective measure (open-ended verbal protocols based on short essay questions). Furthermore, their performance (managing the nation) was the equivalent to those in the less transparent condition. Combined with our previous studies, the results suggest that while prior exploration is a beneficial strategy for both performance and knowledge acquisition, making the model structure transparent in this way (with structure-behavior diagrams) is more limited in its effect.
机译：事先探索是一种教学策略，它在基于系统动态的学习环境中提高了性能和知识获取，但仅限于有限的程度。本研究调查了模型透明度，展示了用户模型内部结构，可以扩展先前的探索策略，并提高学习更多。在一个实验研究中，参与者在基于网络的模拟中了解并管理了一个小型发展中国家。提供了所有参与者的先前探索策略，但只收到了嵌入的结构 - 行为图中的现有探索的一半，旨在使潜在的模型结构更加透明。随着更透明的战略提供的参与者表明了更好的知识获取了对客观措施（多项选择后期）的潜在模型的知识获取，但对主观措施（基于短文问题的开放式口头协议）没有差异。此外，它们的表现（管理国家）相当于透明条件不太透明的人。结合我们以前的研究，结果表明，虽然先前的探索是表现和知识获取的有益策略，使模型结构以这种方式透明（具有结构 - 行为图）的效果更大。

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