Syllabus

COURSE DESCRIPTION

This senior-level hands-on course will introduce students to all phases of data journalism, including: finding and evaluating data sources, analyzing and organizing data, reporting with numbers, and visualizing data. Moreover, students will learn skills in spreadsheet and database operation, data analysis software and data visualization.

Class meetings feature a combination of lecture, exercises, class discussion, and reporting skills workshops.

LEARNING GOALS

  1. Identify patterns in data that help uncover news trends
  2. Learning effective ways to harvest and make sense of the data
  3. Conceptualize clear and concise ways to illustrate trends in news
  4. Create interactive graphics using both custom tools and web-based services
  5. Evaluate effectiveness of data-based storytelling projects, both of their own creation and across the industry.

READINGS

Brant Houston (2015). Computer-Assisted Reporting. Rutledge.

Jonathan Gray, Liliana Bounegru, and Lucy Chambers (eds.). The Data Journalism Handbook. (FREE) http://datajournalismhandbook.org/1.0/en/

Cuillier, D. & Davis, Ch. (2011). The Art of Access. CQ PRES (PDF)

Doing Journalism with Data” online course subscription (FREE)

 ADDITIONAL RESOURCES

UH technology training: University of Houston offers free instructor-led technology courses to current UH students, staff and faculty. Classes are offered year-round and are held in room 106-P on the first floor of MD Anderson Library. Registration is required and space is limited. Of particular interest to this course are the training on Excel 2013 to be offered this month from January 23-26. Visit the training calendar for additional information and to register. You can also download a PDF version (281 kb) of this month’s calendar.

Join Investigative Reporters & Editors for the $25 annual student fee for access to their exclusive tip sheets for data journalism; exclusive data sets; examples of data journalism projects; jobs boards; and list serves full of helpful people and resources.

Bookmark and visit regularly data journalism-oriented websites, including Data Driven Journalism, 538, ProRepublica, The Guardian, The Upshot, etc.

COURSE REQUIREMENTS

Short Assignments. Students complete in-class and homework assignments that help them strengthen skills in quantitative reasoning, data analysis, data visualization and topics of law and ethics. All assignments are reviewed in groups and as a class to help broaden the class perspectives on evaluating data and using it for journalism.

Spreadsheet Assignments (2). Students learn first-hand how to gather and manually input data into spreadsheets for analysis and reporting during an in-class exercise. Attendance and participation required.

Project Blog Posts (4). In progress toward completion of the final reporting project, students make project-related blog posts on their topic and reporting. Students will locate data of social significance, clean and present it in an Excel spreadsheet, identify possible newsworthy aspects to the data set, generate a list of possible sources and outline a reporting plan for producing a multimedia journalism project. The final project post serves as a rough draft of the final project and receives heavy markup for further reporting and editing.

Data Visualization (2): Students combine data visualization skills with original newsgathering to create two blog posts that demonstrate their mastery of the reporting and storytelling techniques covered in the third half of the course.

Final Reporting Project. The culminating project of the semester is a reflective and collaborative approach to data analysis and data journalism that asks students to produce focused, in-depth journalism using shoe leather and data reporting to focus on a specific issue using Houston as the classroom. Student contributions may come in a variety of forms, including but not limited to: interviewing sources; acquiring records; writing and editing text; contributing, editing and analyzing spreadsheets and data; photography and other audiovisual reporting; constructing multimedia reporting elements; mapping; and data visualization.

Students will be expected to produce high quality journalism commensurate with their experience level with extra assigned components. Projects are presented in class at the end of semester and should be accompanied by documentation of submission for publication in student media or via freelance work.

CLASS POLICIES

Work Expectations: This course is intensive. You will often be working on several projects and/or homework assignments at the same time plus keeping up with readings for classes. You will need to begin your projects in advance and not start working on them the night before they are due. If you are struggling with the material or the workload, I expect you to come see me during office hours to discuss it. You are responsible for the work but I am responsible for helping you, guiding you and making sure you are not overwhelmed. But I cannot offer help if you don’t tell me you need help.

Attendance expectations: As juniors and seniors in a 4000-level course, you are expected to attend every class and to participate in class discussion. Treat the class like a job. If you know you will be late, or if you need to leave class early, or if you will have to miss class for any reason (excused or unexcused), contact me ahead of time. E-mail is the preferred means of notification, followed by leaving a phone message on my office phone. If you fail to come to class, it will affect your grade.

Late work: Assignments may be turned in for a grade but will fall under the late paper policy unless turned in before class time or turned in late with prior permission of instructor. Any assignment turned in later than the deadline will be lowered one letter grade for each day it is late. An assignment that is more than THREE days late without prior arrangement with the instructor will not be graded, and the student will receive a zero on the assignment.

Behavioral expectations: Arrive to class on time and ready to participate.

  • Turn your cell phones to silent/vibrate.
  • Respect others; don’t speak when someone else is
  • Listen closely and disagree calmly with others’ opi
  • Do not text message, check personal e-mail, instant message, surf the Web or study for other classes during class You may be asked to leave the class if you are inattentive and/or using the computer for activities not related to class assignments.

During the course we will discuss controversial topics on which student opinion may be both passionate and divided. I expect and desire debate. However, I expect you to agree/disagree calmly and to respect others’ opinions even when they do not share your point of view. Attack illogical statements and factual inaccuracies, not personalities or individual beliefs. Anyone who shouts, engages in personal insults or relies on religious, racial, ethnic, sexual, age or gender bias in place of real arguments will be asked to leave the class.

ACADEMIC HONESTY

Academic dishonesty is a completely unacceptable mode of conduct and will not be tolerated in any form at the University of Houston. All UH students, regardless of their chosen discipline, are expected to contribute to an atmosphere of the highest possible ethical standards. Maintaining such an atmosphere requires that any instances of academic dishonesty be recognized and addressed. The UH Academic Honesty Policy is designed to handle those instances with fairness to all parties involved: the students, the instructors, and the University itself. All people involved in academic dishonesty will be disciplined in accordance with University regulations and procedures. Discipline may include suspension or expulsion from the University. All students and faculty of the University of Houston are responsible for being familiar with this policy.

 To review the full policy, go to: http://www.uh.edu/academics/catalog/policies/academ-reg/academic-honesty/

HELP & RESOURCES

  1. Come see me.One of the keys to student success is regular contact with faculty. You are encouraged make an appointment to meet during my office hours. Many questions and issues can be easily resolved this way.
  2. Use online resources. Your first to-go online place is the Blackboard site for this course. There you will find most of our readings, study guides, exam questions, online discussions, etc. Google Scholar is another great resource to find materials. UH libraries provide online access to most academic journals and some books.
  3.  Get to know the reference desk. Our library staff is eager to help guide your research and to orient you to our library’s paper and online resources.
  4. Use the Writing Center. UH Writing Center is a free resource that offers one-on-one consultations for any stage of the writing process. For more info see http://www.uh.edu/writecen/
  5. Use the Learning Support Services. They provide tutorial for certain courses, learning assessment, and offer seminars and workshops on learning strategies. For more info see http://www.las.uh.edu/lss/
  6. Use the Student Information and Assistance Center. Provides information on a variety of campus-related services, is located in University Center UC—Building 565 (Room 125) and can be reached by phone: (713) 743-5060.

TENTATIVE SCHEDULE

The following is a tentative outline of lecture topics, readings and assignment due dates. Based on student interest and progress through the course, the assigned readings and topics may change. Due dates are unlikely to change.

Part One: Getting the Data

Week/

Date

Class agenda Reading Assignments/deadlines
W 1

Jan 18

Into to Data Journalism Gray, Bounegru, and Chambers: “Introduction”

Columbia Journalism Review – Serious Fun with Numbers.

Interest Survey in class
Skills Covered: Defining and recognizing data-driven journalism and its role in society
W 2

Jan 23-25

Open Source data Houston: Chapter 2: ”Online Resources” Homework assignment:

Sign in for Group Project

Skills Covered: Mining the Internet for Big and Small Data
W 3

Jan 30-Feb 1

The web as a data source Gray, Bounegru, and Chambers: “Getting Data”

Watch Video: Google Search for Journalists

Project Blog Post 1: create project blog and present a rationale for the project topic
Skills Covered: Whether you’re looking at an email address, website, image, or Wikipedia article, we will discuss the tools that will tell you more about their backgrounds.
W 4

Feb 6-8

Getting data from the web Houston: Chapter 9: ”Fact-checking the database: How to find and clean dirty data”

Gray, Bounegru, and Chambers: “Understanding data”

Doing Journalism with Data online course: Module 2.3: “Introduction to Scraping” (14min) and Module 4: “Dealing with messy data”

Project Blog Post 2: locate data for your project
Skills Covered: Data scraping (Tabula); Cleaning data
W 5

Feb 13-15

Data Laws and sources Cuillier & Davis: Ch 3: “Become and Access Law Expert” & Ch 5: “Strategies for Effective Requests” (Blackboard)

Doing Journalism with Data online course: “Data Laws & Sources” (18min)

 
Skills Covered: Acquiring public records and data; filing successful FOI requests.

Part Two: Understanding the Data

 

W 6

Feb 20-22

Data journalism basics Watch: Stanford’s 54-minute video on data journalism’s rise Homework assignment: Submit a FOI request
Skills Covered: Finding the Story in Your Data
 

W 7

Feb 27- Mar 1

Data journalism basics Houston: Chapter 3: ”Spreadsheets, part 1: Basic Math for Journalists”

Doing Journalism with Data online course: Module 3.1: Newsroom math and statistics (15.46min) and Module 3.2: Sorting ad filtering data in Excel (15:57 min)

Spreadsheet Assignment 1(class activity)

 

Skills Covered: Data analysis skills for journalists; sort/filter & other spreadsheet basics
W 8

Mar 6-8

Spreadsheet Analysis Techniques Houston: Chapter 3: ”Spreadsheets, part 2: More math that Matters”

Doing Journalism with Data online course: Module 3.3: “Making new variables with functions” (18:14min) and Module 3.4: “Summarizing data with pivot tables” (16:19min)

Project Blog Post 3: Clean and present your data in a spreadsheet
Skills Covered: Advanced spreadsheet functions like pivot tables
W9

March

13-18

Enjoy your Spring Break
W  10

Mar 20-22

 

Understanding Pools Poynter Free Course: “Understanding and Interpreting Pools” (registration required) Spreadsheet Assignment 2 (homework activity)
We examine the practices of polling as a way to understand various scenarios of statistical bias and error.

·       Statistical significance

·       Poll reliability

·       Forecasting

Part three: Visualizing and Displaying data

 

 

W 11

Mar 27-29

 

Data Visualization:

Infographics and Charts

Gray, Bounegru, and Chambers: “Delivering Data”

Doing Journalism with Data online course: Module 5.1: “The main principles of datavisualization” (15:45min)

 
Skills Covered: Infographics resources
W 12

April 3-5

 

Data Visualization: Mapping Doing Journalism with Data online course: Module 5.2: “Choosing the best graphic forms” (26:28min)

“Mapping data and visualizing geospatial information: A quick introduction for journalists”

Data Visualization Assignment 1
Skills Covered: Using mapping software
 

W 13

Apr 10-12

Data Visualization: Tableau Watch: Tableau public tutorials

8 examples of data visualization and digital storytelling (Blackboard)

Data Visualization Assignment 2
Skills Covered: Interactive data visualization with Tableau software
 

W 14

Apr 17-19

Law & Ethics of Data Journalism Cuillier & Davis: Ch 9: “Writing the FOI story and FOI ethics” (Blackboard)

TBA

Project Blog Post 4: identify newsworthy aspects of the data and outline a reporting plan
Skills Covered: De-identifying data and basics of intellectual property and access law.
W 15

Apr 24-26

Final Project Presentations
Finals Week

May 2-6

TBA