Quiz 1 – Take Home – Due Wed., Feb. 7

Due Wednesday, Wed. Feb. 7 before class starts. Post it to the comments section of this post. Worth 15 quiz points. No late work accepted.

1. Pick a topic or subject you are interested in and you might like to work on later in the semester (i.e., education, politics, sports, environment, immigration, entertainment.) Narrow it down or focus it (i.e., environment in New Jersey or professional Rugby or immigration in South Jersey).

2. Using the “Where do journalists find data?” and smarter searching lectures, identify a range of possible sources of data for your topic. You are looking for places that collect and publish data. Don’t worry about what the data is at this point; just cast a wide net for sources.

3. Make a list of 10 sources with links to each. Each source and link is worth 1 point each. Make sure you have at least 5 different kinds of sources in your list (i.e., government, academic, non-profit, etc). 1 point for each kind of source. (Note: Federal, state and local government can each count as their own kind of source.)

4. Post your list in the comment section for this post. Include your first name, the source of the data, the kind of source (remember you need at least 5 different ones) and a link to the data.

For example, see my sample list of sources of data related to Rowan University in the comments below.

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Week 2 – Mon., Jan. 22 and Wed., Jan. 24

In Class:
Discussion: Your data journalism examples
Inverted pyramid of data journalism
Lecture: 10 common sources of data
Tools and Tips for Smarter Searching

Assignments:
-Read DJH – Five Minute Field Guide
-Complete Advanced Search tutorial (Google News Labs, 7 min.)
Complete the NJ Data Scavenger Hunt – Due Monday, Jan 29

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What is Data Journalism? Takeaways from your examples and discussion



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NJ Data Scavenger Hunt – Spring 2018

Tools to Use:

Instructions:

  1. Answer each questions on the NJ Scavenger Hunt handout.
  2. For each question, find the most recent information you can. (Note: Some may be a few years old.)
  3. Make a brief note of where or how you found the information.
  4. If you are unsure of your answer or want to verify it, try finding a second source.

Bring your NJ Data Scavenger Hunt answers to class on Monday, Jan. 29.

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Week 1 – Wed., Jan 17

In Class:
–Introductions
Course overview
–Download a pdf of the full syllabus here if you wish
Lecture: What is Data Journalism?

Assignments:
-Make sure you are clear on the assignmentsclassroom policiesreading resources, and schedule for the semester.
-Read DJH – What Is Data Journalism?
-Read DJH – Why Journalists Should Use Data
-Read DJH – Why is Data Journalism Important?
-For Monday, Jan. 22, explore and bring an example of data journalism to discuss. Follow these instructions.

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Your Data Journalism Examples

For Monday’s class (Jan 22), I’m asking everyone to explore three news sites:

Come prepared to discuss the following:

1.) Describe each site and what makes it unique? Who publishes it? What is its focus and audience? What kind of content do they produce?

2.) Pick a specific article, infographic or post from one of these sites that you particularly like.

Copy and paste a link to the specific data journalism in the comment field below under Leave a Reply. Please enter your First Name (no last name or other info needed) and copy the link.

Come to class ready to briefly answer the following questions. No need to write this, just think about it.

  • What is the story or information?
  • What is the source of the data? Where did it come from?
  • How did they present it or visualize it?
  • What did you like about it? Why did it stand out to you?
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Welcome to Data Journalism – Spring 2018

Data Journalism – 24286 – JRN 02363 – 1
Monday and Wednesday 11:00 a.m. – 12:15 p.m.
301 High Street Room 215

Explore the assignments, classroom policies, reading resources, and schedule for the semester.

Download a pdf of the full syllabus here.

COURSE DESCRIPTION:
This course is an introduction to the collection, analysis, and presentation of data by journalists for the purpose of engaging and informing the public.

COURSE OBJECTIVES:
In this course, students will:

  • Explore key data journalism concepts and skills.
  • Gain insight into how data journalism is practiced in newsrooms.
  • Learn how to obtain data sets through newswires, strategic searching, FOIA and scraping.
  • Review newsroom math and statistics.
  • Learn techniques for sorting, filtering and cleaning data sets.
  • Think critically about the limitations of datasets and learn to evaluate the strengths and weaknesses of data.
  • Pitch and write news stories using data and statistics.
  • Create basic infographics and visualizations.

TEACHING METHODS:
The course is comprised of brief lectures, readings, in-class assignments, quizzes, a group project and a substantial final project. I will conduct the course as a group facilitator and editor. Students will learn much of the content through practical, hands-on work. The course is dependent on students’ attendance, participation, curiosity, work ethic and teamwork.

ACCOMMODATION POLICY:
Your academic success is important. If you have a documented disability that may have an impact upon your work in this class, please contact me at the beginning of the semester. Students must provide documentation of their disability to the Academic Success Center in order to receive official University services and accommodations. The Academic Success Center can be reached at 856-256-4234. The Center is located on the 3rd floor of Savitz Hall. The staff is available to answer questions regarding accommodations or assist you in your pursuit of accommodations.

OFFICE HOURS:
I welcome conversations with students outside of class. My regular office hours at 6 High Street are Monday to Thursday from 12:30-2pm. I may also be available other times as well. If you would like to make an appointment, email me.

I regularly email students between classes with updates on assignments, grades, and responses to your work. Please check your rowan.edu email throughout the week.

COMPUTER LAB ETIQUETTE:
We will often use the computers for in-class assignments. When we do use them, please refrain from unrelated multi-tasking that may distract you, your classmates and me. Please silence your mobile device before class begins and give your full attention to the course work. I will do the same.

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