|其他题名||The promotion of frequency tree type and questioning format on causal strength estimation|
|刘雁伶1; 陈军2; 沈友田3; 胡竹菁3|
There are lots of evidences showing that participant’s performance on Bayesian inference, syllogistic reasoning and probability reasoning could be promoted by cumulative frequency tree. However, very few study focuses on the promotion effect of frequency tree on causal reasoning. This study carried out two experiments to investigate the effect of frequency tree on causal strength inference. The research hypotheses include: (a) Frequency tree featuring a explicit nest-sets structure (ENS) can improve the rationality of participant’s reasoning, while the frequency tree featuring a concealed nest-sets structure (CNS) can’t improve rationality of reasoning; (b) Participants estimate the causal strength of different contingencies by different modes in experimental treatment which used frequency tree featuring a CNS; and (c) There are more participants estimate the causal strength by Power–PC model in preventive contingency rather than in productive contingency. 2 (Frequency tree, level 1: featuring a ENS, level 2: featuring a CNS) × 2 (causal direction, level 1: productive, level 2: preventive) × 3 (contingency, level 1: P = 0.33 and Power – PC = 0.5; level 2: P = 0.33 and Power – PC = 0.83; level 3: P = 0.67 and Power – PC = 0.83) completely random design were used in two experiments. 469 undergraduate students participated in Experiment 1 which adopted counter–factual question, and 463 undergraduate students participated in Experiment 2 which adopted ability question. Contingency was offered by a booklet which contains 30 pages, and each page presents one sample related to the causality. Participant completed a frequency tree based on contingency, and estimated the causal strength of contingency individual. The frequency tree featuring a ENS consists of three types of information: the number of total samples, the number of samples in focus set, and the number of samples that represent effect emerge or not, while frequency tree featuring a CNS consists of the number of total samples and samples that represent effect emerge or not. The study found that (a) There are three common models of causal reasoning: p, Power–PC and P (E/C) for productive contingency (or P(-E/C) for preventive contingency), the most popular model changes with different experiment treatments; (b) 70.06 % of participants estimate causal strength by Power–PC model when they used frequency tree featuring a ENS, and only a few participants (about 21.28 %) estimate causal strength by Power–PC model when they used frequency tree featuring a CNS; (c) The type of frequency tree and the format of question have combining influence on causal strength evaluation, and the type of frequency tree have more influences on strength evaluation than the format of question; (d) Both contingency effect and causal direction effect are present from the experimental treatment which used frequency tree featuring a CNS. Experiment results significantly support research hypotheses (a), (b) and (c). These results indicate that frequency facilitating effect depends on supply nest-sets structure or not, whether in counter–factual question treatment or in ability question treatment. According to above two experiments, it is suggested that participant tends to make rational inference when they use frequency tree featuring a ENS or they were questioned by counter–factual format.
|关键词||因果推理 图形促进效应 频率树 提问方式|
|刘雁伶,陈军,沈友田,等. 频率树类型和提问方式对因果强度估计模式的影响[J]. 心理学报,2018,50(04):400-412.|
|MLA||刘雁伶,et al."频率树类型和提问方式对因果强度估计模式的影响".心理学报 50.04(2018):400-412.|
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