Show simple item record

dc.contributor.advisorPattie Maes.en_US
dc.contributor.authorXia, Cassandraen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Architecture. Program in Media Arts and Sciences.en_US
dc.date.accessioned2014-11-04T21:35:09Z
dc.date.available2014-11-04T21:35:09Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/91416
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014.en_US
dc.description50en_US
dc.descriptionTitle 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.en_US
dc.descriptionIncludes bibliographical references (pages 48-50).en_US
dc.description.abstractProbability 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.en_US
dc.description.statementofresponsibilityby Cassandra Xia.en_US
dc.format.extent55 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectArchitecture. Program in Media Arts and Sciences.en_US
dc.titleA game-based intervention for the reduction of statistical cognitive biasesen_US
dc.title.alternativeProbability playground : a set of games for statical intuitionen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Architecture. Program in Media Arts and Sciences.en_US
dc.identifier.oclc893607430en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record