Technological and Quantitative Literacy
   

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BGS 290 -- Section 24 (Robin Campus)

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Community Research Project -- Overview and Workshop Session I

This project is a hands-on, data-centered activity that draws on a wide range of academic skills: research, critical analysis, technological and quantitative literacy, and writing.  Focusing on a Chicago-area community of your choice -- either a city neighborhood or an outlying suburban town/city -- you will gather qualitative and quantitative data from several key sources (see below), construct tables and graphs based on those data, and analyze this information in a 4-6pp essay or equivalent PowerPoint presentation.  Class projects will be posted on our 290 Bb site to create an archive of city and suburban profiles for this semester.

The goals of the assignment are to learn practical techniques for retrieving, manipulating, presenting, and critiquing statistical information; to understand the relationship between qualitative and quantitative data in the context of a particular research problem; to merge your developing technological and quantitative literacy in a practical, hands-on way; and to deepen your understanding of the history, socioeconomics, and demographics of a specific Chicago-area community.  Taken as a whole, our profiles of specific communities will offer a complex and revealing view over time of population, race, housing, income, education, and other factors in a wide range of Chicago neighborhoods and surrounding communities.

Key resources include:

Workshop Session I

Bring 2 floppy disks, Local Community Fact Book handouts, stats news article from week 9, and your community profile from the Encyclopedia of Chicago.

  1. Identify census tracts from 1990 within your community from Local Comm Fact Book tables in your handout.
  2. Locate your neighborhood/town in Social Explorer's mapping tool by zooming in on your area or using the Find function to locate a town or street address.
  3. Choose a zoom-level view of your designated town/neighborhood to see as much detail as possible within the total community area.  You might need to futz with this a bit to find a good view.
  4. Choose a mapping variable (e.g., population density, race, income, etc.) to view.  The map you choose will not affect the statistical report you generate in step 5, but the map you designate will show up along with the report.  
  5. Create a statistical report (choose "comprehensive report") on the area by selecting the appropriate census tracts determined in Step 1 above.
  6. Go back to your statistical report you generated in step 5 in Internet Explorer, and Print a copy of your statistical report and map image.
  7. Save your Excel and/or Word files to your floppy disks
    1. Type a few notes before or after your map and legend images in Excel or Word, linking it to the information in the stats report table you generated, for future reference. 
    2. Print a copy of this file(s).
    3. Open up a separate window in Explorer and get into our 290 Bb site.  Add your Excel and/or Word file to your Dropbox, located under Bb Tools.
  8. Return to your community in Social Explorer and choose a different variable to map; repeat Step 5, choosing "summary report"; then repeat Steps 6 and 7 for your new maps/legends (using the same Excel or Word document).  You can play around at this point by experimenting with different kinds of data maps, perhaps generating 3-4 total.

After Session I

Look through your data sets -- your qualitative community histories; your statistical info from 1980, 1990, and 2000; and your thematic maps -- and identify key places for closer analysis.  What parts of the data particularly interest you?  Which of the statistical variables relate to some of the key sociohistorical issues cited in your narrative profiles?  Do you see differences in the way the community is depicted in the 1990 and 2003 narrative accounts?  If so, which parts of the quant data are relevant to these differences?

For Workshop Session II

Bring all materials from session I as well as notes and ideas from the past week's preliminary analysis of data.

 

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Last Updated:  26 November 2005