Geographic Information Systems and Social Learning in Participatory Spatial Planning

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The presentation from my dissertation proposal defense.

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  • Point out axes
  • Applied previous slides to this particular tool
  • Be sure to walk through the four categories
  • Images larger
  • Macro on the top
  • Wenger – explain constructsMethodology – link to specific cases – terms in actual cases
  • Connect the theory with this photo – Workshop dimension from WengerQuestion 1SurveysQuestion 2participation/reification differs among attendeesLow negotiability for othersUnknown identificationQuestion 3Design and emergentRobustness - sufficient links between system and environmentLimited at this meetingQuestion 4Institutional capital?- First time the town has used something like this
  • Geographic Information Systems and Social Learning in Participatory Spatial Planning

    1. 1. Geographic Information Systems and SocialLearning in Participatory Spatial PlanningRobert Goodspeed Committee Members:MIT Department of Urban Studies and Planning • Prof. Joseph Ferreira, Jr. (chair)Dissertation Colloquium • Prof. Brent Ryan30 May 2012 • Prof. Annette M. Kim Reviewer: • Prof. Eran Ben-Joseph
    2. 2. Overview1. Introduction2. Theoretical Framework3. Research Questions and Hypotheses4. Previous Research a) Spatial Planning b) Computer Modeling for Planning c) Social Learning in Policy and Planning5. Case Selection and Research Design6. Anticipated Challenges, Works Cited & Discussion 2
    3. 3. 1-Slide Dissertation Proposal Planning Processes: A B How do participants‘ knowledge, views, and attitudes change after participating in workshops with/without the GIS tool, or different types of tools and workshops? Does the GIS tool, and the way it is used, affect the type of discussion that happens in planning workshops? How can specific projects using GIS tools result in knowledge that continues beyond the process? 3
    4. 4. 1. Introduction
    5. 5. Spatial Planning Projects are IncreasingSource: Bartholomew (2007) 5
    6. 6. An Increasing Number use GIS Support Tools Galveston, Texas South Holland, Netherlands Cape Cod, Mass. Meridian, Idaho Marshfield, Mass. Medford, Mass.Sources: Medford (MAPC), Marshfield (author), allothers from CommunityViz case studies 6
    7. 7. Maturing Research and Practice Around the Tools 2012 2011 2009 2008 2001 ―Open Scenario Planning Tools Ecosystem‖ group working on standards, interoperability, techniquesProfessional technical assessment reports/memos:• ICF/Montgomery County (Grant, Rooney, and Assasie 2010)• UBC/Lincoln Institute (Condon, Cavens and Miller 2009)• Portland Metro (Hoglund 2011)Drivers• Technology: desktop GIS, web-based geoprocessing, open source software• Public Policy: HUD Sustainable Communities Initiative, Climate change/Calif. S.B. 375• Urban Change: Shifting preferences, demographics, travel patterns, etc. 7
    8. 8. ToolsRetail Tools (ArcGIS Extensions)• CommunityViz 1,2• Index 1• Envision Tomorrow 1,2• What If?Emerging (web-based)• IPLACE3S 1• MetroQuestProprietary/Prototypes (various)• Urban Footprint/Rapid Fire (Calthorpe)• Decision Commons 2• Urban Vision/UrbanSim1Assessed for Metropolitan Area Planning Council inJanuary 2011 (Goodspeed, R. MAPC Memorandum:Software evaluation for local scenario planning project,Part 1 and 2. January 2011.)2 Used by proposed dissertation cases. 8
    9. 9. Diverse Modeling Systems …Products Definition GIS Tool GIS Tool Examples in Examples in INDEX Examples Examples CommunityViz (technical) (content)Instantiation Realization of - Specific model with Marshfield Specific INDEX Project the artifact in data Buildout Analysis the environmentMethod Algorithm or Analysis Indicator estimation Set of ―wizards‖ Fixed methods associated guideline functions Build-out analysis or methods for with indicators ArcMap Functions common tasksModel Relation Data model Land uses Flexible Fixed relations between between composed of layers, allowable constructs development/buildi manipulations ng typesConstructs Domain-specific Data constructs Development/Land Flexible, some Required data layers, conceptualizatio Use Types methods require fixed set of indicators ns Development certain constructs Attributes • An ―indicator‖ can be a primitive data construct, or also the result of a specific method of calculation or estimation. • Ambiguity and conflict over constructs, methods, and models are partly the explanation why these have resisted commercialization.After March and Smith (1995) 9
    10. 10. … Used for Interaction and Representation Source: MacEachren (1994) 10
    11. 11. … Used in Social Contexts Individual GIS Artifact Social Context 11
    12. 12. Characterizing the Tool for the StudyGIS-based modeling systems used for:• Interactive Representation Used in specific sociocultural practices• Rule Extrapolation (planning)• Indicator Construction and Calculation 12
    13. 13. 2. Theoretical Framework
    14. 14. What scale and unit of analysis?What is the practice?Which theories of social learning? 14
    15. 15. Which scales? Knowledge Infrastructure Macro Longer Scales of Space & Time Modeling System Meso Planning Process Interacti Interacti on on Opportu Opportu Micro nities nities Individual interactionAfter Edwards (2003) 15
    16. 16. What is the practice? Strategic spatial planning is a ―public-sector-led sociospatial process through which a vision, actions, and means for implementation are produced that shape and frame what a place is and may become‖ that is characterized by multiple forms of rationality: • Value (design of alternative futures) • Strategic (addressing power relationships) • Communicative (understanding from deliberation) • Instrumental (identifying optimal means for achieving goals) Source: Albrecht (2004) 16
    17. 17. Spatial Planning is a ‗Wicked Problem‘ (Rittel and Webber 1973)Decisions require Participant Solutions require weighing value Many stakeholders preferences design and analysis trade-offs involved poorly defined; (instrumental) (value) (strategic) interests differ (communicative) Yet consensus(?) plans are produced. Possible Explanations: • Structured coercion (Peattie 1987; Arnstein 1969; McCullum et al 2004) • Social choice or negotiation (Dutton and Kraemer 1985; Arrow 1965) • Social learning (Healey 1998; Schon 1996; Wenger 1998) 17
    18. 18. What is (Social) Learning?• Historical Views • Behaviorism (Skinner 1974) • Constructionism (Piaget 1963) • Psychological Social Learning (Bandura 1977)• Individual development in an environment (Vygotsky, from Rogoff 1990) • Phylogenic – slowly changing species history (genes) • Sociocultural – changing cultural history, artifacts & norms • Ontogenetic – Changes in individuals over their life history, such as childhood or educational experiences • Microgenetic – ―moment-to-moment learning by individuals‖ built on specific genetic and sociocultural backgrounds.• ―Social‖ perspectives emphasize the importance of social context in understanding individual development 18
    19. 19. Social Learning Theories• Macro (Sociocultural) • ―Knowledge Infrastructure‖ (Healey 1998) • Civic Capacity (Stone 2001; Briggs 2008)• Meso (Ontogenetic and collective) • Organizational Learning (single/double loop) (Argyris and Schön 1978, 1996) • Wenger (1998)• Micro (Microgenetic) • Wenger‘s ―social theory of learning‖ (1998) • Three infrastructures for design: imagination, alignment, and engagement • Design for learning: • participation/reification • designed/emergent • local/global • identification/negotiability 19
    20. 20. Framework OverviewQuestion Scale Description Primary Theories Alternative Theories Q4 Macro Infrastructure • Institutional Capital • Institutional Social Choice Modeling • Organizational Learning Q3 Meso system • Sociotechnical Systems • Hidden Process Q2 Meso Participation design • Social Learning (Hanna 2000) (Wenger) • Social Choice Q1 Micro Interactions • Structured Coercion 20
    21. 21. Meso and Micro Social Learning Measures Spatial Planning PracticeForms of Rationality Measures related to interactive representation, rule extrapolation, indicator construction and calculation 21
    22. 22. Macro Social Learning Measures• Institutional capacity (Healey 1998) • Knowledge resources • Data infrastructure • Metropolitan indicators • Tool capacity • Relational resources • Capacity for mobilization 22
    23. 23. 3. Research Questions
    24. 24. Question 1 – Workshop Design (micro)Design variables (engagement, imagination, alignment) are associated withdifferent types of microgenetic learning (instrumental, strategic, etc), but alsorepresent trade-offs given time and resource constraints. In addition, Wengerand the psychological theorists argue individual background is an importantintermediate variable. 24
    25. 25. Question 2 – Process Design (meso) Source: Faga 2006Models developed with participation (negotiation) are more effective. However,it also speculates that choices for the nature of the model affects the learningoutcomes you get. Ways of addressing the tension in Wenger‘s learningarchitecture: participation/reification, designed/emergent, local/global,identification/negotiability. 25
    26. 26. Question 3 – Modeling System Design (meso)System characteristics (modularity, robustness) will be linked to collectivelearning outcomes (single or double loop learning). 26
    27. 27. Question 4 – Infrastructure Development (macro)What are the characteristics of various paths to develop sociotechnicalinfrastructures (data, indicators, tool capacity) for social learning in spatialplanning? 27
    28. 28. 4. Previous Research• Spatial planning research and practice• GIS modeling in participatory planning• Social learning in policy and planning
    29. 29. Models of Professional Practice• ―Land Use Planning‖ • In the Anglo-American planning tradition • Internally problematic (Webber 1964), unitary projections, insufficient topical scope • Shift to alternate ―land use-transportation‖ or ―scenario‖ planning • Both have strengths, but under-specify participation• ―Spatial planning‖ • Euro-English invention to describe planning activities across cultures • Used by various factions in different ways (An ―empty signifier‖?) (Inch 2012) • Albrecht (2004) has proposed a theoretical framework 29
    30. 30. Spatial Planning• Useful Priors • Klosterman‘s economic ―arguments‖: public goods, externalities, prisoner‘s dilemma conditions, distributional questions (1985) • Wicked Problems – can be addressed but never ―solved‖ (Rittel and Webber 1973)• Spatial Planning (Albrechts 2004) • Products • Vision • Short- and Long-term steps • Contact with stakeholders • Participation • Rationality • Value • Communicative • Instrumental • Strategic 30
    31. 31. Spatial Planning PracticeParadigm Value Strategic Instrumental Communicativ Example Rationality Rationality Rationality e RationalityPlanning as Self-evident Implementation Plan of ChicagoDesign Public Interest concern (1909)Planning as Determined by Application of KentExpert Practice elected officials expert knowledgePlanning As Informs Contributed by Source of value Davidoff,Negotiation selection of planner or legitimacy Susskind ―stakeholders‖ consultantPlanning as Pluralism; Explicitly Expert Under-specified SchoemakerFutures choices considered models/analysisAnalysis 31
    32. 32. Source: Albrecht (2004) 32
    33. 33. (GIS) Modeling in Planning Large-scale models can capture second-order effects, critiqued for lack of practical usefulness (Lee 1973; 1996) Research PracticeResearch Models Rule-based models with practical• e.g., UrbanSim (Waddell 2002) focus • See slide 8Experimental Prototypes• e.g., Ben-Joseph (2001) More sophisticated techniques in domain-specific applications Discussions about Role • e.g., transportation planning • Planning support systems (Klosterman 1997) • Shift to communicative rationality (Guhathakurta 1999) • Utility of new web-based technology (Ferreira 2008) Empirical Studies • Emerging literature using experimental methods to investigate GIS planning tools: Smith (2012), Salter (2009), Arciniegas (2012), Jankowski (2011). • Perspectives: human-computer interaction, landscape visualization, information systems 33
    34. 34. Recent ResearchStudy/Journal/Fram Research Design Assessment ResultsingArciniegas, Janssen Complete a multicriteria analysis: Perceived and observed Digital maps linked with higherand Rietveld(2012) - on paper effectiveness: intensity of use (qualitative) and[in press] in - qualitative on single digital map - Usefulness negotiation (quantitative)Environmental (CommunityViz) - Clarity Paper maps had higher time usingModeling & Software - quantitative on digital map - Impact tool and performance conflict- Spatial decision Digital map had highest perceivedsupport systems Both individual and groups of three, effectiveness. student subjects, n=30Salter, Campbell, - Explore 3D visualizations and Before and after: Indicators and non-visual data ratedJourneay, and quantitative indicators (from - Level of knowledge as very helpfulSheppard (2009) in community) for a draft plan by real- - Level of supportJ. Environmental world stakeholders - Whether the plan will Limited participant time for discussionManagement result in sustainability and interactive exploration (21- Landscape - Three site-scale proposals created. Video analysis methods minutes and 26 minutes)visualization - Two 3-hour workshops, n=14.Jankowski and Small group site selection problem, Convening, process, and Used maps for visualizing results andNyerges (2011) in n=100, 20 groups of 5, student outcome analytic-integrating phaseAnnals of AAG participants.- Enhanced AdaptiveStructuration Custom group decision software withTheory/HCI a ArcMap-based GIS interface.Smith, Bishop, Evaluation of forest management Interaction logs Differences in individual uses of theWilliams and scenarios using an interactive web- Usefulness of information interface and preferences forFord(2012) [in press] based interface. Preference rankings visual/nonvisual informationin Landscape andUrban Planning Individual tasks, n=45 34Landscape vis./HCI
    35. 35. Recent ResearchStudy/Journal/Fram Research Design Assessment ResultsingArciniegas, Janssen Complete a multicriteria analysis: Perceived and observed Digital maps linked with higherand Rietveld(2012) - on paper effectiveness: intensity of use (qualitative) and[in press] in - qualitative on single digital map - Usefulness negotiation (quantitative)Environmental Take-Away: (CommunityViz) - Clarity Paper maps had higher time usingModeling & Software- Spatial decision • Recent studies analyze professional - quantitative on digital map - Impact techniques and performance conflict tool and Digital map had highest perceivedsupport systems Both individual andexperimental methods tools using groups of three, effectiveness. • Focus on the micro scale student subjects, n=30Salter, Campbell, • - Generally opt to stay in laboratoryafter: Explore 3D visualizations and Before and context, although and non-visual data rated IndicatorsJourneay, and quantitative indicators (from - Level of knowledge as very helpfulSheppard (2009) in some links a draft plan by real- - Level(Salter 2009) community) for to ‗natural‘ contexts of supportJ. Environmental • Findings support my hypotheses, although often not world stakeholders - Whether the plan will Limited participant time for discussionManagement result in sustainability and interactive exploration (21- Landscape - directly designed to address them Three site-scale proposals created. Video analysis methods minutes and 26 minutes)visualization - Two 3-hour workshops, n=14.Jankowski and • Small group site selection problem, these approaches, and: maps for visualizing results and My research builds on Convening, process, and UsedNyerges (2011) in n=100, 20 groups of 5, student outcome analytic-integrating phaseAnnals of AAG • shifts to real-world contexts participants.- Enhanced Adaptive • a focus on for collective, higher-level cognitionStructuration Custom group decision software withTheory/HCI • explicit links to a ArcMap-based GIS interface. social theorySmith, Bishop, Evaluation of forest management Interaction logs Differences in individual uses of theWilliams and scenarios using an interactive web- Usefulness of information interface and preferences forFord(2012) [in press] based interface. Preference rankings visual/nonvisual informationin Landscape andUrban Planning Individual tasks, n=45 35Landscape vis./HCI
    36. 36. Social Learning Theories• Older Concepts • Stimulus-response behaviors • Container metaphor • Innate cognitive skills (IQ)• ‗Social‘ Perspective • Knowledge acquired and utilized in social contexts • Knowledge and skills not disconnected and ―cold‖ but ―situated‖ in skilled cultural practices • Specific mental skills, such as ability to memorize disconnected facts, vary according to cultural contexts (Rogoff 1990) • Theorists developed a set of ‗apprenticeship‘ models: • Cognitive conflict between peers (Piaget 1963) – mental models • The zone of proximal development (Vygotsky) – skills • Legitimate peripheral participation (Lave and Wenger 1991) - skills • Guided Participation (Rogoff 1990) – cultural variation • Theory of skilled cultural (professional) practice involving artifacts and an apprenticeship model (Wenger 1998) 36
    37. 37. Social Learning in Policy and Planning Planning Natural Resources/EnvironmentSocial learning as social change (Friedmann1987). Holden (2008) describes severalapproaches:• Organizational learning• Communicative action theory• Pragmatism as planning theory The ―Diversity, Interdependence, Authentic Dialogue‖ (DIAD) model presented in Innes and Booher (2010, 35) Compound social learning model from literature review (Muro and Jeffrey 2008) 37
    38. 38. 5. Case Selection and Research Design
    39. 39. Case Selection Factors• Planning activity • Standard steps • Learn context • Develop vision • Design actions/scenarios • Evaluate actions/scenarios • Multiple forms of rationality • Scale• Character of GIS tool • Interactive representation • Rule extrapolation • Indicator construction and calculation• Planner-participant gap • Projects sponsored by regional planning agencies• Contextual factors • Participant attitudes (Schön and Argyris 1996) • Cultural variation in learning styles (Rogoff 1990) 39
    40. 40. Cases Primary Cases Secondary Cases Boston (MAPC) Kansas City Tacoma Singapore Others? Macro Metro Boston Metro Kansas City Marshfi Meso eld Hingha Buildout New No m Corridor 1 Corridor 2 Tacoma and GIS Master (GIS) (No GIS) Urban EIS Alternati Project? Plan ve Singapore Micro FuturesNature of CommunityViz and/or Decision CommunityViz Tool Envision Tomorrow Commons 40
    41. 41. Data Collection Plans Primary Cases Secondary Cases Context Context Process/Case Process/Case Process-level data collected through structured interviews and participant Workshop observation Workshop surveys used to evaluate specific workshops, as well as process characteristics 41
    42. 42. Measurement and Data Analysis Techniques• Question 1 • Paired pre- and post-surveys using Likert scales • Difference of means or ANOVA • Plan to develop and test survey this summer, starting with students or MAPC employees• Questions 2 and 3 • Observation and recording • Develop personal instrument for observations, coding and analysis of transcripts as well as observation data • Case analysis methods: explanation building, pattern matching (Yin 2009)• Question 4 • Interviews • Case analysis methods: process tracing, historical analysis (Yin 2009)• COUHES approval for semi-structured interviews 3/23/12 (#1203004956) 42
    43. 43. 6. Anticipated Challenges & Discussion
    44. 44. Anticipated Challenges• Theoretical • Wenger‘s theory too abstract• Methodological • Control over cases for experiment • Obtaining valid natural control case/counterfactual • Project timing • Measurement construct validity 44
    45. 45. Empirical Challenges Town Planner Planning BoardMAPC Staff Citizens Housing PartnershipMarshfield Town HallPlanning Board MeetingMarshfield Buildout and Alternative Futures Project 458:43 PM, May 14, 2012
    46. 46. Discussion and Questions• Topic • Professional context • GIS tools• Theoretical Framework • Appropriate theories • Alternative perspectives• Research Design • Case selection • Data collection • Analysis Robert Goodspeed MIT Department of Urban Studies and Planning Dissertation Colloquium rgoodspe@mit.edu 202-321-2743 46
    47. 47. Works Cited (A-F)Albrechts, L. 2004. Strategic (spatial) planning reexamined. Environment and Planning B 31:743-758.Arciniegas, Gustavo, Ron Janssen, and Piet Rietveld. 2012. Effectiveness of collaborative map-based decision support tools: Results of an experiment. Environmental Modelling & Software (0).Argyris, Chris, and Donald A. Schön. 1978. Organizational learning. 2 vols, Addison-Wesley OD series. Reading, Mass.: Addison-Wesley Pub. Co.———. 1996. Organizaitonal Learning II: Theory, Method, and Practice. 2 vols. Vol. 2, Addison-Wesley OD series. Reading, Mass.: Addison- Wesley Pub. Co.Arnstein, Sherry R. 1969. A ladder of citizen participation. Journal of the American Planning Association 35 (4):216-224.Arrow, Kenneth Joseph. 1951. Social choice and individual values. New York: Wiley.Bandura, Albert. 1977. Social learning theory. Englewood Cliffs, N.J.: Prentice Hall.Bartholomew, K. 2007. Land use-transportation scenario planning: promise and reality. Transportation 34 (4):397-412.Ben-Joseph, E., H. Ishii, J. Underkoffler, B. Piper, and L. Yeung. 2001. Urban Simulation and the Luminous Planning Table. Journal of Planning Education and Research 21 (2):196-203.Brail, Richard K. 2008. Planning support systems for cities and regions. Cambridge, Mass.: Lincoln Institute of Land Policy.Brail, Richard K., and Richard E. Klosterman. 2001. Planning support systems : integrating geographic information systems, models, and visualization tools. Redlands, Calif.: ESRI Press.Briggs, Xavier de Souza. 2008. Democracy as problem solving : civic capacity in communities across the globe. Cambridge, Mass.: MIT Press.Burby, Raymond J. 2003. Making plans that matter: Citizen involvement and government action. Journal of the American Planning Association 69 (1):33-49.Condon, Patrick, Duncan Cavens, and Nicole Miller. 2009. Urban Planning Tools for Climate Change Mitigation. In Policy Focus Report. Cambridge: Lincoln Institute of Land Policy.Dutton, William H., and Kenneth L. Kraemer. 1985. Modeling as negotiating : the political dynamics of computer models in the policy process, Communication and information science. Norwood, N.J.: Ablex Pub. Corp.Edwards, P.N. 2003. Infrastructure and modernity: force, time, and social organization in the history of sociotechnical systems. In Modernity and technology, edited by T. J. Misa, P. Brey and A. Feenberg. Cambridge, Mass.: MIT Press.Faga, Barbara. 2006. Designing public consensus : the civic theater of community participation for architects, landscape architects, planners, and urban designers. Hoboken, N.J.: John Wiley.Ferreira, Joseph. 2008. Comment on Drummond and French: GIS Evolution: Are We Messed Up by Mashups? Journal of the American Planning Association 74 (2):177 - 179.Friedmann, J. 1987. Planning in the Public Domain. Princeton, NJ: Princeton University Press. 47
    48. 48. Works Cited (G-M)Geertman, Stan, and John C. H. Stillwell. 2009. Planning support systems best practice and new methods, The GeoJournal library. Dordrecht: Springer.Grant, Michael, Kathleen Rooney, and Kojo Assasie. 2010. WA 4-55 Smart Growth and Climate Protection Policy Analysis, Task 3 - Assessment of Tools. ICF International, for U.S. EPA.Guhathakurta, S. 1999. Urban modeling and contemporary planning theory: Is there a common ground? Journal of Planning Education and Research 18 (4):281-292.Hanna, K.S. 2000. The paradox of participation and the hidden role of information. Journal of the American Planning Association 66 (4):389- 410.Healey, P. 1998. Building institutional capacity through collaborative approaches to urban planning. Environment and Planning A 30:1531-1546.Hoglund, Mike. 2011. Memorandum to the Oregon Modeling Steering Committee on Climate Smart Communities Scnearios: Portland Metro Greenhouse Gas Scenario Planning (House Bill 2001) - Requirements & Technical Approach. Portland, OR: Metro.Holden, M. 2008. Social learning in planning: Seattles sustainable development codebooks. Progress in Planning 69 (1):1-40.Holway, Jim, C.J. Gabbe, Frank Hebbert, Jason Lally, Robert Matthews, and Ray Quay. 2012. Opening Access to Scenario Planning Tools. In Policy Focus Report. Cambridge, Mass.: Lincoln Institute of Land Policy.Inch, Andy. 2012. Deconstructing Spatial Planning: Re-interpreting the Articulation of a New Ethos for English Local Planning. European Planning Studies:1-19.Innes, Judith E., and David E. Booher. 2010. Planning with Complexity: An Introduction to Collaborative Rationality for Public Policy. London and New York: Routledge.Jankowski, Piotr, and Timothy Nyerges. 2001. GIS-Supported Collaborative Decision Making: Results of an Experiment. Annals of the Association of American Geographers 91 (1):48-70.Klosterman, R. E. 1985. Arguments for and against Planning. Town Planning Review 56 (1):5-20.Klosterman, Richard E. 1997. Planning Support Systems: A New Perspective on Computer-Aided Planning. Journal of Planning Education and Research 17 (1):45-54.Lave, Jean, and Etienne Wenger. 1991. Situated learning : legitimate peripheral participation, Learning in doing. Cambridge England ; New York: Cambridge University Press.Lee, Douglass B. 1973. Requiem for Large-Scale Models. Journal of the American Planning Association 39 (3):163.———. 1994. Retrospective on Large-Scale Urban Models. Journal of the American Planning Association 60 (1):35.March, S. T., and G. F. Smith. 1995. Design and Natural-Science Research on Information Technology. Decision Support Systems 15 (4):251- 266.McCullum, C., D. Pelletier, D. Barr, J. Wilkins, and J.P. Habicht. 2004. Mechanisms of power within a community-based food security planning process. Health education & behavior 31 (2):206-222.Muro, M., and P. Jeffrey. 2008. A critical review of the theory and application of social learning in participatory natural resource management processes. Journal of Environmental Planning and Management 51 (3):325-344. 48
    49. 49. Works Cited (P-Y)Peattie, Lisa Redfield. 1987. Planning: Rethinking Ciudad Guayana. Ann Arbor: University of Michigan Press.Piaget, Jean. 1963. The origins of intelligence in children, Norton library. New York: W.W. Norton.Rittel, HWJ, and MM Webber. 1973. Dilemmas in a general theory of planning. Policy sciences 4 (2):155-169.Rogoff, Barbara. 1990. Apprenticeship in thinking : cognitive development in social context. New York: Oxford University Press.Salter, J.D., C. Campbell, M. Journeay, and S.R.J. Sheppard. 2009. The digital workshop: Exploring the use of interactive and immersive visualisation tools in participatory planning. Journal of environmental management 90 (6):2090-2101.Skinner, B. F. 1974. About behaviorism. [Book Club ed. New York: Knopf.Smith, Eric Legge, Ian D. Bishop, Kathryn J. H. Williams, and Rebecca M. Ford. 2012. Scenario Chooser: An interactive approach to eliciting public landscape preferences. Landscape and Urban Planning (0).Waddell, P. 2002. UrbanSim - Modeling urban development for land use, transportation, and environmental planning. Journal of the American Planning Association 68 (3):297-314.Walker, Doug, and Thomas L. Daniels. 2011. The planners guide to CommunityViz : the essential tool for a new generation of planning. Chicago: Planners Press, American Planning Association.Webber, Melvin M. 1964. Explorations into urban structure. Philadelphia,: University of Pennsylvania Press.Wenger, Etienne. 1998. Communities of practice : learning, meaning, and identity, Learning in doing. Cambridge, U.K. ; New York, N.Y.: Cambridge University Press.Yin, Robert K. 2009. Case study research : design and methods. Thousand Oaks, Calif.: Sage Publications. 49

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