2026-09-19T07:27:40Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/854182026-06-06T00:49:26Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Henry Lieberman.
Fleisher, Tamara
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-03-06T15:40:38Z
2014-03-06T15:40:38Z
2013
2013
http://hdl.handle.net/1721.1/85418
870528645
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 36-37).
Justify is a high-functionality web application that helps users clearly state arguments and organize them in a meaningful structure, however due to its complicated user interface and abundance of point types, it is extremely difficult and frustrating to learn and use. Research shows that when presented with an abundance of choices, users are less likely to think through their decision rationally and more likely to regret any decision they make. This thesis proposes that reducing the amount of point types initially provided to the user, grouping them by similarity, and then utilizing "just in time" learning to dynamically introduce them to the user with interactive tutorials will dramatically increase the learnability of Justify, and thus also increase user retention and satisfaction. User testing indicated that these changes in Justify made it easier to learn and more enjoyable to use, when compared to both the older version of Justify and to alternative methods of decision making.
by Tamara Fleisher.
M.Eng.
37 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
Electrical Engineering and Computer Science.
Improving learnability of high functionality user interfaces through simplification without loss of functionality
Thesis
application/pdf
Publication
unknown
unknown
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<Abstract>Justify is a high-functionality web application that helps users clearly state arguments and organize them in a meaningful structure, however due to its complicated user interface and abundance of point types, it is extremely difficult and frustrating to learn and use. Research shows that when presented with an abundance of choices, users are less likely to think through their decision rationally and more likely to regret any decision they make. This thesis proposes that reducing the amount of point types initially provided to the user, grouping them by similarity, and then utilizing "just in time" learning to dynamically introduce them to the user with interactive tutorials will dramatically increase the learnability of Justify, and thus also increase user retention and satisfaction. User testing indicated that these changes in Justify made it easier to learn and more enjoyable to use, when compared to both the older version of Justify and to alternative methods of decision making.</Abstract>
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