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dc.contributor.advisorD. Fox Harrell.en_US
dc.contributor.authorKao, Dominicen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2018-05-23T15:05:33Z
dc.date.available2018-05-23T15:05:33Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/115631
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages [245]-319).en_US
dc.description.abstractWith the current proliferation of educational games, MOOCs, and with the pervasive use of virtual identities such as avatars in systems ranging from online forums to virtual reality simulations, it is increasingly important to understand the impacts of avatars. Over two years, I led an initiative in MIT's Imagination, Computation, and Expression (ICE) Laboratory conducting experiments involving > 10,000 participants to understand the impacts of virtual identities on users in virtual environments. Using a computer science learning platform and game of our own creation as an experimental setting, we have been studying the impacts of avatar use on users' performance and engagement in computer science learning environments. This is a topic of increasing importance in human-computer interaction [69, 130, 132, 310, 452, 549]. While a great deal of work focuses on procedural thinking and problem solving, we argue that attending to learners' identities and their engagement to be equally important. We systematically explored the impacts of different avatar types on users, beginning with distinctions between anthropomorphic vs. non-anthropomorphic avatars, user likeness vs. non-likeness avatars, and other conditions informed by insights from the learning sciences and sociology. Our studies have revealed that avatars can support, or harm, performance and engagement. Several notable trends are: 1) simple abstract avatars (such as geometric shapes) are especially effective when the player is experiencing failure, e.g., while debugging, 2) likeness avatars (avatars in a user's likeness) are not always effective, 3) role model avatars (in particular scientist avatars) are often effective, and 4) successful likeness avatars that are a user's likeness when doing well and otherwise abstract are effective. We describe our studies leading to these findings and end with a follow-up study.en_US
dc.description.statementofresponsibilityby Dominic Kao.en_US
dc.format.extent319 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleResearching and developing the impacts of virtual identity on computational learning environmentsen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1036987393en_US


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