MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Doctoral Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Doctoral Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

[I³] imitation, iteration and improvisation : embodied interaction in computational making and learning

Author(s)
El-Zanfaly, Dina Ezz ElDin
Thumbnail
DownloadFull printable version (28.54Mb)
Alternative title
Embodied interaction in computational making and learning
Other Contributors
Massachusetts Institute of Technology. Department of Architecture.
Advisor
Terry W. Knight.
Terms of use
MIT 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. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Despite advances in digital design and fabrication technologies, creative design practices still follow Alberti's separation of the design phase from the construction phase. This separation causes a reliance on digital fabrication machines that pushes human agency to the periphery of the making process. The interfaces of these technologies and their linear process of production create cognitive and perceptual obstacles, making it difficult for non-experts to create and improvise independently. Design and the ability to make are often thought to be intuitive, yet significant research has suggested that intuition is developed through skilled practice, interaction with materials, tools, and machines. Existing pedagogical approaches to design focus on outcomes and instructors' feedback to the students, neglecting the importance of the tools and the process itself. How, then, do we learn to make something? What are the potential roles of computational tools, theories, and practices in understanding, describing, and enriching the making and learning process? What can we learn from machines, and what can machines learn from us? Finally, what do we learn from making? Here, I introduce l³, a computational making methodology that enables emerging designers and makers to improvise and create on their own. I call this method F for its three-layer operation of Imitation, Iteration and Improvisation. Drawing upon research from other fields, this methodology for human-machine making and learning is based on a recursive process of embodied, situated interaction between learners, machines, materials, and the things-in-the-making. I describe the continuous process of developing and testing 1³ through experiments I conducted during the teaching of three courses for graduate and undergraduate students. The qualitative research I conducted shows that through using the 1³ methodology, students develop their spatial reasoning and decision-making skills while at the same time learning to use digital technologies as design companions.
Description
Thesis: Ph. D. in Architecture: Design and Computation, Massachusetts Institute of Technology, Department of Architecture, 2018.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 122-127).
 
Date issued
2018
URI
http://hdl.handle.net/1721.1/118695
Department
Massachusetts Institute of Technology. Department of Architecture
Publisher
Massachusetts Institute of Technology
Keywords
Architecture.

Collections
  • Doctoral Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.