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Pattie Maes. Xia, Cassandra Massachusetts Institute of Technology. Department of Architecture. Program in Media Arts and Sciences. Program in Media Arts and Sciences (Massachusetts Institute of Technology) 2014-11-04T21:35:09Z 2014-11-04T21:35:09Z 2014 2014 http://hdl.handle.net/1721.1/91416 893607430 Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014. 50 Title as it appears in MIT commencement exercises program, June 6, 2014: Probability playground: a set of games for statical intuition Cataloged from PDF version of thesis. Includes bibliographical references (pages 48-50). Probability and statistics is perhaps the area of mathematics education most directly applicable to everyday life. Yet, the methodologies traditionally used to cover these topics in school render the material formal and difficult to apply. In this thesis, I describe a game design that develops probabilistic concepts in real-life situations. Psychologists have coined the term cognitive bias for instances in which the intuition of the average person disagrees with the formal mathematical analysis of the problem. This thesis examines if a one-hour game-based intervention can enact a change in the intuitive mental models people have for reasoning about probability and uncertainty in real-life. Two cognitive biases were selected for treatment: overconfidence effect and base rate neglect. These two biases represent instances of miscalibrated subjective probabilities and Bayesian inference, respectively. Results of user tests suggest that it is possible to alter probabilistic intuitions, but that attention to the transitions from the current mental constructs must be carefully designed. Prototyping results suggest how some elements of game design may naturally lend themselves to deep learning objectives and heuristics. by Cassandra Xia. S.M. 55 pages eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Architecture. Program in Media Arts and Sciences. A game-based intervention for the reduction of statistical cognitive biases Probability playground : a set of games for statical intuition Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="e102907b-9a67-412c-aa6f-1015e8353bef"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>A game-based intervention for the reduction of statistical cognitive biases</Title> <Subtitle>Probability playground : a set of games for statical intuition</Subtitle> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2014</PublicationDate> <Authors> <Author> <DisplayName>Xia, Cassandra</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Architecture. Program in Media Arts and Sciences.</Keyword> <Abstract>Probability and statistics is perhaps the area of mathematics education most directly applicable to everyday life. Yet, the methodologies traditionally used to cover these topics in school render the material formal and difficult to apply. In this thesis, I describe a game design that develops probabilistic concepts in real-life situations. Psychologists have coined the term cognitive bias for instances in which the intuition of the average person disagrees with the formal mathematical analysis of the problem. This thesis examines if a one-hour game-based intervention can enact a change in the intuitive mental models people have for reasoning about probability and uncertainty in real-life. Two cognitive biases were selected for treatment: overconfidence effect and base rate neglect. These two biases represent instances of miscalibrated subjective probabilities and Bayesian inference, respectively. Results of user tests suggest that it is possible to alter probabilistic intuitions, but that attention to the transitions from the current mental constructs must be carefully designed. Prototyping results suggest how some elements of game design may naturally lend themselves to deep learning objectives and heuristics.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>