Psychology Department, Clemson University, Clemson, USA.
Arizona State University at Lake Havasu City, 100 University Way, Lake Havasu City, AZ, 86403, USA.
Cogn Res Princ Implic. 2020 Oct 23;5(1):49. doi: 10.1186/s41235-020-00250-5.
Research on causal reasoning often uses group-level data analyses that downplay individual differences and simple reasoning problems that are unrepresentative of everyday reasoning. In three empirical studies, we used an individual differences approach to investigate the cognitive processes people used in fault diagnosis, which is a complex diagnostic reasoning task. After first showing how high-level fault diagnosis strategies can be composed of simpler causal inferences, we discussed how two of these strategies-elimination and inference to the best explanation (IBE)-allow normative performance, which minimizes the number of diagnostic tests, whereas backtracking strategies are less efficient. We then investigated whether the use of normative strategies was infrequent and associated with greater fluid intelligence and positive thinking dispositions and whether normative strategies used slow, analytic processing while non-normative strategies used fast, heuristic processing.
Across three studies and 279 participants, uses of elimination and IBE were infrequent, and most participants used inefficient backtracking strategies. Fluid intelligence positively predicted elimination and IBE use but not backtracking use. Positive thinking dispositions predicted avoidance of backtracking. After classifying participants into groups that consistently used elimination, IBE, and backtracking, we found that participants who used elimination and IBE made fewer, but slower, diagnostic tests compared to backtracking users.
Participants' fault diagnosis performance showed wide individual differences. Use of normative strategies was predicted by greater fluid intelligence and more open-minded and engaged thinking dispositions. Elimination and IBE users made the slow, efficient responses typical of analytic processing. Backtracking users made the fast, inefficient responses suggestive of heuristic processing.
因果推理研究通常使用群体水平数据分析,这些数据淡化了个体差异和简单的推理问题,而这些问题不能代表日常推理。在三项实证研究中,我们使用个体差异方法研究了人们在故障诊断中使用的认知过程,这是一项复杂的诊断推理任务。在首先展示了高层故障诊断策略如何由更简单的因果推理组成之后,我们讨论了其中两种策略——排除和最佳解释推理(IBE)——如何允许规范性能,这最大限度地减少了诊断测试的数量,而回溯策略则效率较低。然后,我们调查了规范策略的使用是否不频繁,是否与更高的流体智力和积极思考倾向相关,以及规范策略是否使用缓慢的分析处理,而非规范策略是否使用快速的启发式处理。
在三项研究和 279 名参与者中,排除和 IBE 的使用频率较低,大多数参与者使用效率较低的回溯策略。流体智力正向预测排除和 IBE 的使用,但不预测回溯的使用。积极的思维倾向预测避免回溯。在将参与者分为一致使用排除、IBE 和回溯的小组后,我们发现使用排除和 IBE 的参与者进行的诊断测试较少,但速度较慢。
参与者的故障诊断表现显示出很大的个体差异。规范策略的使用由更高的流体智力、更开放和投入的思维倾向来预测。排除和 IBE 用户做出了缓慢、有效的分析处理反应。回溯用户做出了快速、低效的启发式处理反应。