Abstract
Critical thinking requires knowledge about the diversity of viewpoints on controversial issues. However, the diversity of perspectives often remains unexploited: Learners prefer preference-consistent over preference-inconsistent information, a phenomenon called confirmation bias. This chapter attempts to introduce how recommender systems can be used to stimulate unbiased information selection, elaboration and unbiased evaluation. The principle of preference-inconsistency and its role in supporting critical thinking is explained. We present our empirical approach, the experimental paradigm and a summary of our main findings. Taken together, the results indicate that preference-inconsistent recommendations are an effective approach for stimulating unbiased information selection, elaboration and evaluation. In conclusion, implications for research and practice are discussed.
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Schwind, C., Buder, J. (2014). The Case for Preference-Inconsistent Recommendations. In: Manouselis, N., Drachsler, H., Verbert, K., Santos, O. (eds) Recommender Systems for Technology Enhanced Learning. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0530-0_7
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DOI: https://doi.org/10.1007/978-1-4939-0530-0_7
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