Huey Holly, Lu Xuanchen, Walker Caren M, Fan Judith E
Department of Psychology, University of California San Diego, United States of America.
Department of Psychology, University of California San Diego, United States of America.
Cognition. 2023 Jul;236:105414. doi: 10.1016/j.cognition.2023.105414. Epub 2023 Mar 2.
Visual explanations play an integral role in communicating mechanistic knowledge about how things work. What do people think distinguishes such pictures from those that are intended to convey how things look? To explore this question, we used a drawing paradigm to elicit both visual explanations and depictions of novel machine-like objects, then conducted a detailed analysis of the semantic information conveyed in each drawing. We found that visual explanations placed greater emphasis on parts of the machines that move or interact to produce an effect, while visual depictions emphasized parts that were visually salient, even if they were static. Moreover, we found that these differences in visual emphasis impacted what information naive viewers could extract from these drawings: explanations made it easier to infer which action was needed to operate the machine, but more difficult to identify which machine it represented. Taken together, our findings suggest that people spontaneously prioritize functional information when producing visual explanations but that this strategy may be double-edged, facilitating inferences about physical mechanism at the expense of preserving visual fidelity.
视觉解释在传达关于事物如何运作的机械知识方面起着不可或缺的作用。人们认为这类图片与旨在描绘事物外观的图片有何区别呢？为了探究这个问题，我们采用了绘图范式来引出对新型机器类物体的视觉解释和描绘，然后对每幅图中传达的语义信息进行了详细分析。我们发现，视觉解释更强调机器中移动或相互作用以产生某种效果的部件，而视觉描绘则强调视觉上突出的部件，即使它们是静态的。此外，我们发现这些视觉重点的差异影响了外行观众能从这些图中提取的信息：解释使得推断操作机器所需的动作更容易，但识别它所代表的机器则更困难。综合来看，我们的研究结果表明，人们在进行视觉解释时会自发地优先考虑功能信息，但这种策略可能是一把双刃剑，在以牺牲保持视觉逼真度为代价的情况下，便于对物理机制进行推断。
