Short Description:
This assignment was created for a credit bearing course for first year students. It's designed to help students take what they've learned about algorithmic bias from the course lectures and readings and apply it to their own search practices. They also critically analyze search results for advertisements and compare DuckDuckGo to Google. [You could also look at this assignment as an adaptation of Jacob Berg's wonderful, "Googling Google," assignment at https://www.projectcora.org/assignment/googling-google-search-engines-ma... ]
Learning Outcomes:
Students will be able to: -identify advertisements within a list of search results -discuss the role advertising plays in how search results are ordered -describe how search results are impacted by human biases in their ranking algorithms
Course Context (e.g. how it was implemented or integrated):
This assignment occurred early in the semester as we discussed algorithms, bias, and filter bubbles. Students were asked to draw on class discussions and lectures on page rank, the history of search engines, and filter bubbles. Other assigned material going into this assignment the IRL podcast episode "Social Bubble Bath" and Eli Pariser's TED talk on filter bubbles. Students commented that they enjoyed this assignment, weren't aware that Google was an advertising company, and were unfamiliar with DuckDuckGo. The course itself was designed and taught by me (a librarian) as part of our first year seminar program.
Potential Pitfalls and Teaching Tips:
Be careful with the choose your own image search --- several students picked topics such as our institution name or vague concepts like "music" which didn't as clearly illustrate the course concepts. In the future I would remove the choose your own option for the image component. This assignment was designed with first year students in mind.
