Lecturer and Teacher-Special Programs Pool - Journalism - Graduate School of Journalism


J212 Advanced Audio - 33% time appointment (3 teaching hrs/week)

This class has students produce narrative, long-form audio stories. Students will learn the fundamentals of creative audio including finding, mapping, and planning narrative audio stories; understanding the pitch process for either radio or podcasts industries; audio interview skills; and script writing for the ear. This class will leave students with a strong foundation for entering the emerging field of creative audio industries for radio or podcast.

J222 Interactive Narratives - 33% time appointment (3 teaching hrs/wk)

This course explores new and experimental story formats for news, which can include longform scrollytelling, non-linear narratives, vertical video, motion graphics, animation, live blogs, timelines, bot and chat apps, interactive data visualizations, virtual reality or augmented reality, and innumerable other approaches to storytelling in the digital age.

The course will ideally involve the use of one or more of the following technologies: Adobe Premiere, After Effects, HTML/CSS/JavaScript, virtual reality (and the respective software to create these experiences), 360 video cameras and software, or other technologies that the candidate may demonstrate for students. The instructor will have agency to choose which forms to explore, and can bring in guest speakers in the field to speak on some of these approaches. Candidates will have access to an existing syllabus to use as a guideline.

J298 Data Journalism - 33% time appointment (3 teaching hrs/wk)

This course focuses on the basics of Data Journalism as a branch of investigative reporting. The candidate will be asked to focus emphatically on accountability reporting through data-driven journalism, and to be proficient in teaching students how to mine datasets for stories that are compelling, authoritative, and ground-breaking. The course may provide students with technical expertise some of the following: Basic statistics; open source (OSINT) investigation techniques; data cleaning/analysis; web scraping; and software such as R Studio, Python, SQL, spreadsheets, OpenRefine, Machine Learning, GIS, or SPSS/PSPP. In addition, the course should focus on the fundamental principles of data analysis and visual presentation, and how to acquire, process and