2026-09-19T21:26:59Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/284392022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Harold Abelson and Dick K.P. Yue.
Lin, Thomas, 1981-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-09-26T20:28:37Z
2005-09-26T20:28:37Z
2004
2004
http://hdl.handle.net/1721.1/28439
57003369
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 77-78).
This thesis considers the design of automated tutoring systems that customize teaching material to accommodate individual student learning styles. In particular, we consider the following problem: Begin with one or more presentations of a subject, and break them into fragments ("atoms") each expressing a single idea. Given information about an individual student's learning style, how can one select the optimal choice and sequence of atoms ("path of atoms") to create the most effective presentation for that student? We have implemented several algorithms that automatically create such paths, and we investigate the tradeoff between number of constraints imposed by the algorithms and the number of paths they can find. We have tested one of these algorithms ("partition search") in an experiment where student volunteers in computer science studied material about planning and artificial intelligence. The results of the experiment indicate that the algorithms can produce presentations that are effectively tailored to the different learning styles.
by Thomas Lin.
M.Eng.
90 p.
5831991 bytes
5842017 bytes
application/pdf
application/pdf
en_US
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.
APOT : automatic path optimizing for traits
Automatic path optimizing for traits
Thesis
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<Abstract>This thesis considers the design of automated tutoring systems that customize teaching material to accommodate individual student learning styles. In particular, we consider the following problem: Begin with one or more presentations of a subject, and break them into fragments ("atoms") each expressing a single idea. Given information about an individual student's learning style, how can one select the optimal choice and sequence of atoms ("path of atoms") to create the most effective presentation for that student? We have implemented several algorithms that automatically create such paths, and we investigate the tradeoff between number of constraints imposed by the algorithms and the number of paths they can find. We have tested one of these algorithms ("partition search") in an experiment where student volunteers in computer science studied material about planning and artificial intelligence. The results of the experiment indicate that the algorithms can produce presentations that are effectively tailored to the different learning styles.</Abstract>
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