dc.contributor.advisor | Joseph Ferreira, Jr. | en_US |
dc.contributor.author | Goodspeed, Robert (Robert Charles) | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Department of Urban Studies and Planning. | en_US |
dc.date.accessioned | 2013-10-24T18:11:10Z | |
dc.date.available | 2013-10-24T18:11:10Z | |
dc.date.copyright | 2013 | en_US |
dc.date.issued | 2013 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/81739 | |
dc.description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2013. | en_US |
dc.description | This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. | en_US |
dc.description | Cataloged from student-submitted PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (p. 240-271). | en_US |
dc.description.abstract | This dissertation examines new professional practices in urban planning that utilize new types of spatial planning support systems (PSS) based on geographic information systems (GIS) software. Through a mixed-methods research design, the dissertation investigates the role of these new technologies in planning workshops, processes, and as metropolitan infrastructures. In particular, PSS are viewed as supporting social learning in spatial planning processes. The study includes cases in Boston, Kansas City, and Austin. The findings indicate high levels of social learning, broadly confirming the collaborative planning theory literature. Participants at planning workshops that incorporated embodied computing interaction designs reported higher levels of two forms of learning drawn from Argyris and Schöns' theory of organizational learning: single and double loop learning. Single loop learning is measured as reported learning. Double loop learning, characterized by deliberation about goals and values, is measured with a novel summative scale. These workshops utilized PSS to contribute indicators to the discussion through the use of paper maps for input and human operators for output. A regression analysis reveals that the PSS contributed to learning by encouraging imagination, engagement, and alignment. Participantsʼ perceived identities as planners, personality characteristics, and frequency of meeting attendance were also related to the learning outcomes. However, less learning was observed at workshops with many detailed maps and limited time for discussion, and exercises lacking PSS feedback. The development of PSS infrastructure is investigated by conducting a qualitative analysis of focus groups of professional planners, and a case where a PSS was planned but not implemented. The dissertation draws on the research literatures on learning, PSS and urban computer models, and planning theory. The research design is influenced by a sociotechnical perspective and design research paradigms from several fields. The dissertation argues social learning is required to achieve many normative goals in planning, such as institutional change and urban sustainability. The relationship between planning processes and outcomes, and implications of information technology trends for PSS and spatial planning are discussed. | en_US |
dc.description.statementofresponsibility | by Robert Goodspeed. | en_US |
dc.format.extent | 271 p. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | 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. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Urban Studies and Planning. | en_US |
dc.title | Planning support systems for spatial planning through social learning | en_US |
dc.title.alternative | PSS for spatial planning through social learning | en_US |
dc.title.alternative | Spatial planning support systems for spatial planning through social learning | en_US |
dc.type | Thesis | en_US |
dc.description.degree | Ph.D. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Urban Studies and Planning | |
dc.identifier.oclc | 859404430 | en_US |