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Feedback Influences Syllogistic Strategy: An Analysis based on Joint Nonnegative Matrix Factorization

Mr. Nicolas Oliver Riesterer
University of Freiburg ~ Cognitive Computation Lab
Mr. Daniel Brand
University of Freiburg ~ Cognitive Computation Lab
Prof. Marco Ragni
University Freiburg ~ University Freiburg

Feedback for drawn inferences can lead to an adaption of future responses and underlying cognitive mechanisms. This article presents a reanalysis of recent hypothesis-driven experiments in syllogistic reasoning in which participants were presented with different feedback conditions (no feedback, 1s, 10s). We extend the original analysis, which only focused on no feedback vs. 1s feedback, by including the additional 10s condition. For our analysis, we rely on the data-driven theory- and hypothesis-agnostic Joint Nonnegative Matrix Factorization which allows us to contrast datasets based on the extraction of response patterns reflecting common and distinct response behavior. Our results support the previous claims that feedback does not generally boost logical reasoning ability but reduces the influence of biases against the response indicating that nothing logically follows from the premises.


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