Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Architecture, 2015.

Bibliographic Details
Main Author: Park, Ju Hong
Other Authors: Massachusetts Institute of Technology. Department of Architecture.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2016
Subjects:
Online Access:http://hdl.handle.net/1721.1/101544
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author Park, Ju Hong
author2 Massachusetts Institute of Technology. Department of Architecture.
author_facet Massachusetts Institute of Technology. Department of Architecture.
Park, Ju Hong
author_sort Park, Ju Hong
collection MIT
description Thesis: Ph. D., Massachusetts Institute of Technology, Department of Architecture, 2015.
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spelling mit-1721.1/1015442019-04-12T15:08:42Z Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education Park, Ju Hong Massachusetts Institute of Technology. Department of Architecture. Massachusetts Institute of Technology. Department of Architecture. Architecture. 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. 2016-03-03T21:07:57Z 2016-03-03T21:07:57Z 2015 2015 Thesis http://hdl.handle.net/1721.1/101544 940564187 eng 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 667 pages application/pdf Massachusetts Institute of Technology
spellingShingle Architecture.
Park, Ju Hong
Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education
title Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education
title_full Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education
title_fullStr Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education
title_full_unstemmed Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education
title_short Synthetic tutor : profiling students and mass-customizing learning processes dynamically in design scripting education
title_sort synthetic tutor profiling students and mass customizing learning processes dynamically in design scripting education
topic Architecture.
url http://hdl.handle.net/1721.1/101544
work_keys_str_mv AT parkjuhong synthetictutorprofilingstudentsandmasscustomizinglearningprocessesdynamicallyindesignscriptingeducation