Description | Agenda | Instructors & Participants | Travel & Accommodations

Spatial Analysis for the Undergraduate Social Science Curriculum

July 18-23, 2005: Santa Barbara, CA

Participants should arrive in Santa Barbara on Sunday, July 17th. The first class is in Ellison Hall, Room 2620 at 9:00am on Monday, July 18th. [Campus Map] [Graphic Agenda]

Meals
8-8:45am	Breakfast - Carrillo Dining Commons
12-1:00pm	Lunch - De La Guerra Dining Commons (DLG)
5:30-6:30pm	Dinner - Carrillo Dining Commons (Friday July 22 @ DLG, 5:45-7:15pm)

Monday, July 18: Introduction, Motivation, and Project Planning
9:00	Welcome and Introduction (2.4MB)	D. Janelle
9:30	Integrating Spatial Perspectives into Undergraduate Social Science Education	S. Sweeney
10:30	Break
10:45	Undergraduate Instruction Principles and Implementation Techniques General Assessment Ideas (14MB) The Role of Prior Knowledge (28kb)	F. Goodchild, S. Rebich
11:45	Lunch
1:15	Project Planning*	F. Goodchild, S. Rebich, S. Sweeney
2:15	Break
2:30	Computer Lab (laptop software checks, data checks, lab logistics) Small-Group Pedagogy Discussion (F. Goodchild, S. Rebich, D. Janelle, S. Sweeney)
3:30	Introducing GIS and Peer Interaction (S. Battersby, J. Hemphill, E. Yoo) *Background Reading* (password protected): Data Classification (2.1MB) Exercises: Introduction to ArcGIS
5:30	Reception, Introductions and Poster Session (UCSB Faculty Club)+

Tuesday, July 19: Spatial Social Science and GIScience
9:00	Geographic Information Systems/Science: Basic Concepts of GIS (3.4MB) Nature of spatial processes and their representation in GIS *Background Reading* (password protected): Representing geography (12.7MB) The nature of geographic data (19.3MB) Georeferencing (11MB) Uncertainty (8.9MB) Query, measurement, and transformation (14MB) Descriptive summary, design, and inference (14MB) Spatial modeling with GIS (8MB)	M. Goodchild
10:00	Break
10:15	The Challenge of Spatial Social Science GIS methods in social science research and education. Thinking spatially in the social sciences. Integration and Discussion * (M. Goodchild, F. Goodchild, S. Rebich)	M. Goodchild
12:00	Lunch
1:15	Structured Lab: ArcGIS I: Data Structures / Data Sources / Mapmaking (S. Battersby, J. Hemphill, E. Yoo) ESRI Shape files and data structures Easy Access Data for Social Science Apps. (ESRI Data Package, ESRI WWW, Census archives) Rudiments of computer cartography in ArcGIS
3:45	Break
4:00	Parallel Electives * Open Computer Lab (S. Battersby, J. Hemphill, E. Yoo) Proportional Symbol Maps Advanced Topics in GIS Data Structures (Sweeney) External data management with SAS Pitfalls with ESRI ID fields / merging external data Area unit misalignment / census geography / MAUP Spatial Thinking and Student Assessment (Stacy Rebich)

Wednesday, July 20: Spatial Analytic Methods in Social Science Instruction
6:00am	Hike with Mike - Foothills of Santa Ynez Mountains
9:00	Reflection and Goal Setting *	F. Goodchild, S. Rebich, S. Sweeney
9:30	Spatial Analytic Methods (exploratory / descriptive / inferential) Point data: SS methods / applications Area data: SS methods / applications Interaction data: SS methods / applications *Background Reading* (password protected): GeoDa: An Introduction to Spatial Data Analysis (522kb) Under the Hood. Issues in the Specification and Interpretation of Spatial Regression Models (172kb) *Materials* (password protected): Animations (5.2MB)	S. Sweeney
10:30	Break
10:45	Spatial Analytic Methods (exploratory / descriptive / inferential) Spatial analytic methods in social science research and education. Added-value from spatial analytic methods Spatial autocorrelation and relation to social science theories Classroom demos versus student assignments / labs Integration and Discussion * (Sweeney, F. Goodchild, S. Rebich)	S. Sweeney
12:00	Lunch
1:15	Structured Lab: GeoDA: Exploratory Spatial Data Analysis Reading ESRI Shape files and variable construction EDA and ESDA utility and interpretation Inferential pattern analysis / spatial autocorrelation.	S. Sweeney, K. Grace, E. Yoo
3:45	Break
4:00	Parallel Electives * Open Computer Lab (staffed by S. Battersby, J. Hemphill, E. Yoo) Choropleth Maps with ArcGIS Spatial Regression in GeoDA (Sweeney, K. Grace) *Background Reading* (password protected): Spatial Dependence in Linear Regression Models (2.1MB) Spatial econometric theory; Spatial error and spatial lag models Specification tests and model interpretation GeoDA application: Hedonic real estate model

Thursday, July 21: Cartography / Visualization in Social Science Instruction
6:00am	Surf with Stuart
9:00	Cartographic Visualization in Social Science Instruction Symbolizing point, line, and area features (13MB) *Background Reading* (password protected): Sample evaluation criteria for maps (20kb) The Selection of Class Intervals (1.5MB) On Grouping for Maximum Homogeneity (593kb) Map Making for Social Scientists (9.1MB) Geographical Movement (1.6MB) Computer Cartograms (219kb) A Continuous Transformation Useful for Districting (225kb) Geographic Area and Map Projections (518kb) Pseudo-Cartograms (305kb)	S. Fabrikant
10:30	Break
10:45	Structured Lab: ArcGIS II: Topics in Cartographic Communication Classification *Data Sources: US Census FactFinder (census data) ESRI Census Watch (census data portal and information) ESRI Geography Network (tiger line data and tons of other spatial data) Exercise Material: Example table Selecting good color schemes for maps cart/viz links by Slocum et al. (2004) Mapping Exercises* (password protected): Downloading map data, processing and classifying (70kb) Choropleth mapping with GIS (207kb)	S. Fabrikant, S. Battersby, J. Hemphill, E. Yoo
12:15	Lunch
Afternoon	Free Time - Spatial events in Santa Barbara (depending on interest) or Santa Ynez Valley wine tasting (Stacy Rebich)

Friday, July 22: Spatial Interaction, Pedagogy, and Project Development
9:00	Issues in Teaching and Learning Chair: Fiona Goodchild Panel: Claude Barnes, Mike Goodchild, Brian Lee, Diana Sinton
10:30	Break
10:45	Movement and Flows Flow representation and mapping Gravity & entropy models The transportation problem, linear and quadratic Integration and Discussion* *Background Reading* (password protected): Migration (970kb) Links: Tobler's Reprinted Articles on Migration	W. Tobler
12:00	Lunch
1:15	Structured Lab: Flowmapper Integration with other software	W. Tobler, S. Battersby, J. Hemphill, K. Grace, E. Yoo
2:15	Open Computer Lab	S. Battersby, K. Grace, J. Hemphill, E. Yoo

Saturday, July 23: Project Presentations / Closing Session
9:00	Participant Presentations and Peer Feedback 10 minute presentation, 5 minute discussion (maximum of 10 PowerPoint slides) Peer review for each participant
12:00	Lunch
1:15	Participant Presentations and Peer Feedback 10 minute presentation, 5 minute discussion. Peer review for each participant
3:15	Break
3:30	Participant Presentations and Peer Feedback 10 minute presentation, 5 minute discussion. Peer review for each participant
4:30	Closing Comments	D. Janelle, S. Sweeney, F. Goodchild
6:00	BBQ Dinner and workshop Awards (Goleta Beach)

Sunday, July 24: Participants Depart Santa Barbara

* Definitions

Project Planning / Goal Setting - Workshop participants are expected to work on a project related to their curriculum and course development. This will be the basis of a final presentation from each participant towards the end of the workshop.
Poster Session - Describe who you are and your role at your home institution. Discuss your interest in spatial analysis and provide examples of how you may have or would like to incorporate spatial analytic perspectives in the undergraduate curriculum. Posters will be the focus for participant and instructor interaction at the reception on the first day of the workshop.
Reflection and Goal Setting - The early morning reflection sessions are opportunities to raise any issues and questions that are of concern to participants and instructors. Participants may also discuss their goals for the day and for project completion.
Integration / Discussion - An opportunity to clarify the pedagogic implications of the preceding presentations.
Parallel Electives - Participants may choose options that best reflect their interests and needs. Topics for parallel sessions are flexible and may be suggested by participants at any time during the workshop. These will allow for small-group and more in-depth treatment of topics than would be possible in larger groups.

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