‘Everyday music listening’ has grown into a research field in its own right, encompassing perspectives from the humanities (e.g., How do youth use music to establish a robust identity and sense of self?), the exact sciences (e.g., What is the most effective algorithm for making personalised music recommendations like Spotify’s Discover Weekly?), and the social sciences (e.g., To what extent does personality determine musical taste?).

Working in small groups, students in this course will learn how to synthesise heterogenous sources of quantitative data to understand more about their own daily musical experiences and the musical experiences of others. The course takes a breadth-first approach so that (1) students will be exposed to as many areas as possible where they can apply skills they have developed in other courses to music and (2) students with a strong interest in the subject will be prepared to deepen their understanding in courses such as Computational Musicology or Cognitive Musicology. Each group will design, execute, and analyse a small research experiment on everyday music listening, incorporating questionnaires from the music cognition literature and listening histories from streaming services like Spotify and Apple Music, guided and inspired by a serious of lectures and practical sessions on research topics and tools from cognitive and computational musicology.

The first half of the course will focus designing a good research experiment, including practical sessions about tools like the Spotify Developer API and online surveys with Qualtrics. Students will also be exposed to major trends in quantitative musicological research and will be asked to write a short article review on a topic of their choice. This portion of the course will conclude with group presentations of their research plans.

In the second half of the course, as each group is collecting data, the course content will shift its focus toward analysis and visualisation techniques. Over the course the second half, students will build up an online portfolio in place of a research report to document their experiments and results. In addition to working on their own portfolios, students will make weekly peer reviews of work from other groups, so that the best ideas can spread easily across the course. After final group presentations of the research results in the last week of the course, each student will choose a research project about which to write an extended critique, with an emphasis on potential directions for further study.

Coordinator

Ashley Burgoyne

Timetable

All lectures will take place on-campus and we assume you can be physically present during the scheduled hours. You can find the timetable on Datanose.

Registration

Registration is possible for students participating in an Honours programme. The registration period for the Honours courses will be from June 6, 10:00 am to June 10, 11.59 pm. You can register through the online registration form that will appear on Honoursmodules IIS. (registration is NOT through SIS)

Please note: Placement is not guaranteed if you register after June 10, so make sure you register on time. You will hear which course(s) you are registered for before the end of June. 

For questions about registration, please contact us at: honours-iis@uva.nl.