Academic Technology can help you with your courses in ways you may not have realized. Beyond supporting Moodle and Zoom and helping you to redesign a course, academic technologists also provide deep support in, for instance, video production and all-things data. Let’s look at Barbara Allen’s Media and Electoral Politics courses (a collection of related classes over the past 20 years). Dr. Allen engages with students to grow their media and political savvy. The students analyze and create political ads, and create robust research designs to study responses to various aspects of political advertising and news reporting about politics.
Academic technologists have been there nearly every step of the way.
Part of the courses this past fall included an in-depth study of the effect of the gender of the narrator of political ads. Dr. Allen needed both multiple original political ads created prior to the course start date, and she wanted to teach students to produce their own ads. For this work, Dr. Allen worked with Dann Hurlbert, Media & Design Specialist. Dann and Barbara scripted, recorded voice-overs for, and produced four political ads. Identical ads were narrated by both male and female speakers, giving students a distinct data point to survey and analyze.
Dann and his students also worked with Barbara to create a course trailer video that Dr. Allen can use to advertise the course itself.
Dr. Allen also needed a complex survey instrument to get a robust response to the ads created before the term started. This survey/research instrument included numerous baseline questions about each student’s political outlook and opinions, their impressions about each of the four political ads, and a follow up survey to see what “stuck” from the ad-treatments.
Paula Lackie, Academic Technologist for Data, worked with Dr. Allen on creating this longitudinal study in Qualtrics, designing the process so that everyone who took the survey had a consistent lag-time between each survey phase for each respondent.
The buffer time between the surveys was a necessary component of the research design, but there wasn’t much time to get the survey series distributed. The survey design itself was rather complex. The resulting data needed additional work before the students could begin any analysis; the 3 phases of the study needed to be linked longitudinally and a specific subset of the variables pulled, anonymized, and made ready for students in the classes. This data-cleaning and processing work was ably managed by Juntao Zhong ‘23, a member of the DataSquad. In addition, the DataSquad converted the data into Tableau format, trained the classes in Tableau use, and supported them through the Quantitative Resource Center.