Reasoning Through the Application of Crystallized and Fluid Intelligence in a Causal Inference Task

Abstract: The aim of the study was to find out how well individuals perform when solving hypothetical causally related problems, and further understand what intelligence factors interact with this. This was done via a survey that consisted of hypothetical, linear relation, causal scenarios. Two experiments were conducted to ensure that no validity issues confounded the results. Experiment 1 consisted of 77 participants who performed unexpectedly well across all conditions. This may have been due to a later identified heuristic simplifying the level of reasoning required, hence Experiment 2 was conducted. Only 19 participants were used for the follow up experiment, thus may need to be further replicated with a larger sample size. The results however have shown that negative-negative-negative condition was the most challenging among the others presented, resulting in the lowest overall mean (M = 0.8). Causal reasoning in the context of this study shows that most individuals are able to correctly infer the relationship A to C when B is an intermediate cause, and A to D when B and C are intermediate causes. Future studies should focus on validity concerns and explore more controlled conditions for the current paradigm.