2026-09-19T04:31:29Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1015442026-06-17T14:46:19Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Park, Ju Hong
Massachusetts Institute of Technology. Department of Architecture.
Massachusetts Institute of Technology. Department of Architecture
2016-03-03T21:07:57Z
2016-03-03T21:07:57Z
2015
2015
http://hdl.handle.net/1721.1/101544
940564187
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Architecture, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 123-128).
Artificial intelligence is substituting human intelligence and robots are replacing human workers. Instead of settling for this competitive relationship between humans and machines, this thesis proposes a novel framework in which humans and machines work together to solve the complex problems of design-scripting education, problems which humans or machines alone cannot easily solve. In design education, there are few clear guides and pedagogies that can effectively teach students with diverse educational and professional backgrounds, some of who may need individualized tutoring. This thesis specifically explores applications of artificial intelligence (machine learning and computer vision algorithms) in which humans and machines mutually improve their learning performance. Humans can increase a machine's performance by providing training-data sets that can be a foundation for intelligent decision-making. Machines, on the other hand, can improve humans' learning performance by analyzing human study patterns and providing mass-customized instructions. This thesis illustrates that the developed Synthetic Tutor provides novice students with architectural precedents by analyzing their drawings and documents and effectively teaches these students introductory computer programming skills in the context of architectural design. Therefore, this human-machine collaboration has proven an effective framework to solve these ill-structured problems.
by Ju Hong Park.
Ph.D.
667 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.
Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education
Thesis
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