Blended Course Map: ECON 690 — GIS Analysis and Big Data

Blended Learning

This blended course map was created by a participant of the Blend@UW Course Design Series. It represents an example of how activities could be designed for one unit of a course to achieve the course and unit outcomes.

Example of a blended course map from ECON 690 — GIS Analysis and Big Data

Name: Matthew Friedman
SCID: College of Letters & Science
Department: Economics
Course Name: ECON 690 — GIS Analysis and Big Data

Supported Program Outcomes:

  • SPO1: Construct and evaluate economic models, their assumptions, and their conclusions.
  • SPO2: Acquire diverse skills and strategies in mathematical reasoning/statistical and computational techniques/deductive logic/problem-solving.
  • SPO3: Use mathematics/computational/statistical techniques to analyze real-world situations and policies.

Course Objectives:

  • CO1:Acquire knowledge and interest in approaches to economic analysis that leverage large collections of [geospatially detailed] data
  • CO2: Draw connections between the most innovative products and services on the market today and the big data behind them
  • CO3:Understand how GIS technology can aid critical evaluation of economic outcomes and policies
  • CO4: Develop competence in compiling, combining, manipulating, and evaluating large [geospatial] datasets
  • CO5:Obtain project management experience by working collaboratively with peers to complete a diverse set of highly specialized programming and analysis tasks
  • CO6:Value economic models, their assumptions, and conclusions. Students will also relate theoretical models to real-world data sources to support or invalidate their conclusions through empirical testing
  • CO7: Engage with communities of professionals and other resources that can help further their big data wrangling skills long after completing ECON690

Course Units:

  • CU1: Introduction to Geospatial Information Systems (Practice)
  • CU2: Using GIS to conduct economic analysis (Place)
  • CU3: Basic programming tools for unlocking Big Data’s insights (Programming)
  • CU4: Big Data Rent: How profit maximizers leverage information (Prices)
  • CU5: Leveraging Big Data to measure preferences and predict trends (Prediction)
  • CU6: Evaluating, Visualizing, and Presenting Big Data Effectively (Presentations & Pratfalls)

Unit Being Redesigned:

Unit Objectives:

  • UO1: Understand how economists are utilizing GIS data to more accurately describe human interactions
  • UO2: Appreciate how spatial detail can enhance traditional economics analysis
  • UO3: Classify geospatial tools, identify their effective uses, and outline how each tool can be used to generate new data
  • UO4: Deconstruct the price of a composite good into the value attributable to each of its constituent parts
  • UO5: Summarize how GIS applications enhance economic efficiency by matching trading partners in space
  • UO6: Conduct basic spatial operations to generate new variables
Activity Map
Pre-Class Activities In-Class Activities Post-Class Activities
  • Watch GUS Revolution and Big Data Video
  • Read Ch. 3 and 4 Prep for Lecture 2
  • Read Ch. 1 and 2 Prep for Lecture 3
  • Read "Equal Earth" article Prep for Lecture 6
  • Student Feedback
  • Read John Snow's Article for Lecture 8
  • Read GIS Search and Rescue articles for Lecture 9
  • Minute Essay Lecture 1
  • Discussion on Lecture 1
  • Software Install Lecture 2
  • Map Projections Lecture 3
  • Displaying Geospatial Data Lecture 4
  • Creating Geospatial Data Lecture 5
  • Group Project for Lecture 6
  • Guest Lecture 7
  • Project Proposal Lecture 8
  • Discussion on Lecture 8
  • Hotspot Analysis Lecture 9
  • Search Activity for Lecture 9
  • Essay Assignment on Lecture 4
  • Getting Started Quiz on Lecture 5
  • Problem Sets from Lecture 6
  • Problem Sets from Lecture 8
  • Predictive Pool from Lecture 9

Keywordsblended course map, campus, exampleDoc ID121103
OwnerTimmo D.GroupInstructional Resources
Created2022-09-06 12:46:19Updated2023-12-27 10:45:50
SitesCenter for Teaching, Learning & Mentoring
Feedback  0   0