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Learning to fly through informational turbulence: critical thinking and the case of the minimum wage
(2020)
The paper addresses online reasoning and information processing with respect to a much debated issue: the pros and cons of the minimum wage. Like with all controversial issues, one can easily remain in a self-reinforcing bubble, once one has taken sides, and immunize oneself against criticism. Paradoxically, the more information we have at our disposal, the easier this gets (Roetzel, 2019). The only (and possibly universal) antidote seems to be “critical thinking” (Ennis, 1987, 2011). However, critical thinking is a very broad concept, purported to include diverse kinds of information processing, and it is also thought to be content-specific. Therefore, we aim at addressing both understanding of content knowledge and reasoning processes. We pursue three goals with this paper: First, we conduct a conceptual analysis of the learning content and of reasoning patterns for and against the minimum wage. Second, we explicate an inferential framework that can be applied for processes of critical thinking. Third, teaching strategies are discussed to support reasoning processes and to promote critical thinking skills.
This study investigated whether prompting children to generate predictions about an outcome facilitates activation of prior knowledge and improves belief revision. 51 children aged 9–12 were tested on two experimental tasks in which generating a prediction was compared to closely matched control conditions, as well as on a test of executive functions (EF). In Experiment 1, we showed that children exhibited a pupillary surprise response to events that they had predicted incorrectly, hypothesized to reflect the transient release of noradrenaline in response to cognitive conflict. However, children's surprise response was not associated with better belief revision, in contrast to a previous study involving adults. Experiment 2 revealed that, while generating predictions helped children activate their prior knowledge, only those with better inhibitory control skills learned from incorrectly predicted outcomes. Together, these results suggest that good inhibitory control skills are needed for learning through cognitive conflict. Thus, generating predictions benefits learning – but only among children with sufficient EF capacities to harness surprise for revising their beliefs.