Social Security Administration Case Study (Knowledge of Plain English Required)

Case Study #4 – Federal Agency Audience and Readability Analysis

For this case study, you will learn about Plain English (or Plain Language) as well as understand the audiences most likely to visit the website of your assigned federal agency.

Deadline

Wednesday, October 24 by 11:59pm.

Class is cancelled on October 22 and 24. Email Boettger if you have any questions about the assignment.

Deliverables and Canvas submission information

· Federal Agency report. Submit your report as a MS-Word file and upload it to Canvas.

Step 1. Watch selected videos from the Writing in Plain English course

Watch selected videos from the “Writing in Plain English” course with Judy Steiner-Williams via Lynda.com. (Access Lynda from either the “Databases” link at library.unt.edu, or by selecting the “Sign in with your organization portal” link on the Lynda.com homepage).

In “1. Writing Clearly” part of the course, watch the “What is plain English?” video as well as the “Government’s impact on plain English” video. Next, watch at least three videos of your choice under “3. Make Writing Clear and Plain” and at least two videos of your choice under “4. Revise for Understanding.” Choose videos that are on unfamiliar topics –learn some stuff!

Step 2. Research your federal agency

Conduct web research on your assigned federal agency (see assignments on last page of this description). In particular, why was the agency created and who is the targeted population that the agency serves? What are the core services this agency provides, and have these services expanded or evolved over time? What’s the current state of the agency (i.e., does it appear to be increasing or decreasing its services? Is its intended population growing or decreasing?)?

Step 3. Analyze the analytics of your agency’s website

Analyze the analytics of your agency’s website via http://analytics.usa.gov. On average, how many users visit this website? What cities and countries most often visit the website? Consider why visitors from a specific city might frequent that agency’s website more often than visitors from other cities (i.e., is there a correlation between particular cities/audiences and the services the agency offers?).

Finally, in addition to the agency’s home page, identify the website’s most popular content page over a 30-day period (Note: some of the top pages are forms or links to external sites. You’re looking for the most popular content page within that particular agency).

Step 4. Analyze the readability of your agency’s homepage and its most popular content page

Your assigned agency’s homepage and its most popular content page will serve as the content sample for this case study. Analyze the collective readability of these pages via the Readability Analyzer from Datayze (https://datayze.com/readability-analyzer.php).

The readability results offer some insights into how effectively the content is serving your agency’s audience. Choose which results you believe are most useful to gaining this understanding. Refer to your notes from the Sept 24 lecture on readability statistics/formulas, such as Flesch-Kincaid and Dall-Chall.

Step 5. Write a report on your findings

Summarize your findings in a one-page report addressed to me.

Provide a brief summary of your assigned agency, including a discussion of its history, services, and targeted audience. In addition, summarize the analytics research you conducted on your agency’s website. How does the web traffic/results reflect what you know about the agency? Provide the Web URL of your agency’s homepage and the ULR of the most popular content page.

Finally, summarize your readability analysis. Report the results that you believe are most interesting or relevant to understanding the overall readability of these webpages. Based on the results, do you believe users will have an easy or difficult time understanding the content? Why or what not?

Federal Agency Assignments

Your federal agency assignment is below (randomly assigned with the =RAND() formula):

Student	Agency
Adkins, Evan	Department of Commerce
Anderson, Christopher	Department of Homeland Security
Avellaneda, Lizbeth	Department of Housing and Urban Development
Carey, Rachel	National Archives and Records Administration
Conner, Givon	Social Security Administration
Foster, James	Department of Defense
Hossain, Muhammad	National Aeronautics and Space Administration (NASA)
Jackson, Brooke	Department of Education
Kleypas, Andrew	Department of Interior
Kronenberger, Jay B	Small Business Administration
Michial, Semmy	Department of Commerce
Nguyen, Jenny	Department of Energy
Parker, James	Department of Veterans Affairs
Plain, Sarah	Department of Transportation
Roncancio, Juliet	Department of Education
Sanderson, Matthew	Department of Agriculture
Schindler, Alex	Department of Treasury
Shortino, Joseph	Department of Health and Human Services
Smith, Destini	Environmental Protection Administration
Staton, Leon	Department of State
Stewart, Michael	Department of Justice
Velderman, Alexander	Department of Justice
Veloz, Ivette	Department of Labor
Wiseman, Sarah	Department of Housing and Urban Development
Wulf, Ethan	General Services Administration