Inconsistencies Among Beliefs as a Basis for Learning via Thought Experiments
- Igor Bascandziev, Rutgers University, Newark, New Jersey, United States
AbstractAlthough many studies have shown that being exposed to empirical data that contradict one’s beliefs can lead to learning, it is not clear whether calling attention to inconsistencies among beliefs without the provision of new data, leads to learning. The present study asked whether calling attention to inconsistent beliefs via thought experiments leads to belief revision. Five-hundred-seventy-five participants were assigned to three different conditions in a pre-training, training, post-training design. We found that participants generated inconsistent beliefs between pre-training and training, but they did not spontaneously revise them at post-training (Baseline Condition). They did revise them, however, when they were asked to reason about the implications of the training thought experiments (Warning Condition) and when they saw an explicit inference drawn from the training thought experiments (Explicit Inference Condition). These results show that, with prompting, scientifically naïve adults can learn from thought experiments.