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Teaching Computer-Assisted Reporting
2015
Brant Houston
University of Illinois
brant.houston@gmail.com
houstonb@illinois.edu
Concepts
• Columns and rows
• Just counting
• Bad data, accuracy checks and data cleaning
• Importance of visualization
• Keeping it simple
Data Skills
• Principles of searching: From Boolean logic
to file type
• Spreadsheets
• Database managers
• Charts and maps
Data Skills
• Building a database
• Cleaning data – start with replace and find and
then update
• Social network analysis
• Statistics
• Scraping as entry to coding
Other reporting skills
• Requesting data including freedom of
information
• Researching the dataset – reading files about
it, reading tip sheets, seeing how it has been
used by journalists and others
• How to do interviews about the data with
those who create it and maintain it
Other reporting skills
• How to do interviews with researchers and
officials to test credibility of the data
• Using observation to augment and test data
analysis – getting out into the field
• How to identify basic stories – change over
time, comparisons, outliers, clusters
Teaching Skills
• Know your class – survey and test hands-on
skills before teaching
• Difference between professional students and
college students
• Show good examples including ones that can
be achieved by students in short time
• Keep it simple - start small – two columns and
five rows
Teaching Skills
• Know your class – survey and test hands-on
skills before teaching
• Show good examples including ones that can
be achieved by students in short time
• Keep it simple - start small – two columns and
five rows
• Go slow – If you think you are going slow, go
slower
Teaching Skills
• Remember that learning software involves
three parts: Small motor coordination, seeing
new windows and icons, and the concepts
• Use relevant data but also use for relevant
stories
Syllabi
• IJEC.org
• IRE.org

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Teaching computer assisted reporting in 2015, Brant Houston #gijc15

  • 1. Teaching Computer-Assisted Reporting 2015 Brant Houston University of Illinois brant.houston@gmail.com houstonb@illinois.edu
  • 2. Concepts • Columns and rows • Just counting • Bad data, accuracy checks and data cleaning • Importance of visualization • Keeping it simple
  • 3. Data Skills • Principles of searching: From Boolean logic to file type • Spreadsheets • Database managers • Charts and maps
  • 4. Data Skills • Building a database • Cleaning data – start with replace and find and then update • Social network analysis • Statistics • Scraping as entry to coding
  • 5. Other reporting skills • Requesting data including freedom of information • Researching the dataset – reading files about it, reading tip sheets, seeing how it has been used by journalists and others • How to do interviews about the data with those who create it and maintain it
  • 6. Other reporting skills • How to do interviews with researchers and officials to test credibility of the data • Using observation to augment and test data analysis – getting out into the field • How to identify basic stories – change over time, comparisons, outliers, clusters
  • 7. Teaching Skills • Know your class – survey and test hands-on skills before teaching • Difference between professional students and college students • Show good examples including ones that can be achieved by students in short time • Keep it simple - start small – two columns and five rows
  • 8. Teaching Skills • Know your class – survey and test hands-on skills before teaching • Show good examples including ones that can be achieved by students in short time • Keep it simple - start small – two columns and five rows • Go slow – If you think you are going slow, go slower
  • 9. Teaching Skills • Remember that learning software involves three parts: Small motor coordination, seeing new windows and icons, and the concepts • Use relevant data but also use for relevant stories