Smith Willow, Hermida Joanna, Güss Christoph Dominik
Department of Psychology, University of North Florida, Jacksonville, FL, United States.
Front Psychol. 2022 Dec 22;13:965623. doi: 10.3389/fpsyg.2022.965623. eCollection 2022.
What do people in different cultures do when they encounter complex problems? Whereas some cross-cultural research exists about complex problem-solving predictors and performance, the process has rarely been studied. We presented participants from Brazil, Germany, the Philippines, and the United States with two computer-simulated dynamic problems, one where quick action was required - the WinFire simulation - and one where cautious action was required - the Coldstore simulation. Participants were asked to think aloud in their native language while working on these two tasks. These think-aloud protocols were digitally recorded, transcribed, and coded by coders in each country in terms of the steps involved in complex problem solving and dynamic decision making. For the current study, we developed a program to calculate transition frequencies from one problem solving step to another and analyzed only those protocols with more than 15 transitions. For WinFire, these were 256 think-aloud protocols from the four countries with a total of 12,542 statement, for Coldstore, these were 247 participants with a total of 15,237 statements. Based on previous, limited cross-cultural research, we predicted that after identifying a problem, Brazilians would make emotional and self-related statements, Germans would engage primarily in planning, Filipinos would gather additional information, and Americans would primarily state solutions. Results of latent transition analysis partially support these hypotheses, but only in the highly uncertain Coldstore situation and not in the more transparent WinFire situation. Transition frequencies were then also analyzed regarding community clusters using the spinglass algorithm in R, igraph. Results highlight the importance of process analyses in different tasks and show how cultural background guides people's decisions under uncertainty.
不同文化背景的人在遇到复杂问题时会怎么做?虽然存在一些关于复杂问题解决的预测因素和表现的跨文化研究,但这个过程却很少被研究。我们让来自巴西、德国、菲律宾和美国的参与者处理两个计算机模拟的动态问题,一个需要快速行动——WinFire模拟,另一个需要谨慎行动——Coldstore模拟。参与者在处理这两项任务时被要求用他们的母语大声说出想法。这些出声思考协议被数字记录、转录,并由每个国家的编码员根据复杂问题解决和动态决策所涉及的步骤进行编码。在当前的研究中,我们开发了一个程序来计算从一个问题解决步骤到另一个步骤的转换频率,并且只分析那些有超过15次转换的协议。对于WinFire模拟,有来自四个国家的256份出声思考协议,总共12542条陈述;对于Coldstore模拟,有247名参与者,总共15237条陈述。基于之前有限的跨文化研究,我们预测在识别出问题后,巴西人会做出与情感和自我相关的陈述,德国人会主要进行规划,菲律宾人会收集更多信息,而美国人会主要陈述解决方案。潜在转换分析的结果部分支持了这些假设,但仅在高度不确定的Coldstore模拟情境中成立,在更透明的WinFire模拟情境中则不然。然后,我们还使用R语言中的igraph软件包中的spinglass算法,针对社区聚类分析了转换频率。结果突出了在不同任务中进行过程分析的重要性,并展示了文化背景如何在不确定性情况下指导人们的决策。