Performance Implications Of Working With Music In The Background
Location
SU 219
Department
Computer Science
Abstract
Human-Computer Interaction is concerned with designing computer technology to best serve the needs of its human users. This includes studying how users actually utilize technology in both intended and unintended ways while studying the performance implications. When users attempt to use multiple technologies at once, they are potentially acting outside of the assumptions made by the designers. These “edge cases” are important to study if we are to minimize the negative effects of such actions. Multitasking is a subfield of Human-Computer Interaction that addresses people performing multiple tasks on one or more devices. While there is a significant body of work on interleaved multitasking, where people start a task, switch to a different task, and then continue the original task, few studies have examined parallel multitasking, where two or more tasks are happening at the same time, on a single device. Listening to music while working on a computer or mobile-based task falls into this latter category. Music is more prevalent in our society at this point than at any other point in history. People now have the ability to stream music from their mobile devices while performing any task. Gathering a deeper understanding of how music affects performance on different tasks will help further our understanding of parallel multitasking. In order to examine how music impacts performance we created an Android app where participants perform five different types of cognitive tasks on a mobile device: mental arithmetic, memory, reading comprehension, concentration, and spatial abilities. Participants will be divided into three conditions: music with lyrics, music without lyrics (instrumental music) and no music. Participants will be recruited using Amazon Mechanical Turk, a web-based labor market where “requesters” can post paid tasks which are completed by “workers.” There have been several scientific studies which have evaluated the platform as a source of data comparable to “convenience samples” and undergraduate studies. The platform is extremely robust, reliable and trustworthy with the additional benefit of allowing researchers to quickly recruit a sizeable number of participants at a fraction of the cost of traditional studies. According to previous literature, reading comprehension and memory tasks appear to be more susceptible to interference caused by listening to music. When music is played in the background, the brain has to use some of its finite resources in order to process the music being heard, even if it is not being actively listened to. We hypothesize that participants listening to music, particularly music with lyrics, will have lower performance in each of our five tasks when compared with the other conditions, especially for the memory and reading comprehension tasks. We plan to report on the results of this study. The overall goal of our study is to examine a difficult to observe topic within multitasking by approaching it from a new angle. This brings together literature from Human-Computer Interaction, Music, and Psychology in order to find ways in which we can better harness music to work with users and minimize interruptions.
Performance Implications Of Working With Music In The Background
SU 219
Human-Computer Interaction is concerned with designing computer technology to best serve the needs of its human users. This includes studying how users actually utilize technology in both intended and unintended ways while studying the performance implications. When users attempt to use multiple technologies at once, they are potentially acting outside of the assumptions made by the designers. These “edge cases” are important to study if we are to minimize the negative effects of such actions. Multitasking is a subfield of Human-Computer Interaction that addresses people performing multiple tasks on one or more devices. While there is a significant body of work on interleaved multitasking, where people start a task, switch to a different task, and then continue the original task, few studies have examined parallel multitasking, where two or more tasks are happening at the same time, on a single device. Listening to music while working on a computer or mobile-based task falls into this latter category. Music is more prevalent in our society at this point than at any other point in history. People now have the ability to stream music from their mobile devices while performing any task. Gathering a deeper understanding of how music affects performance on different tasks will help further our understanding of parallel multitasking. In order to examine how music impacts performance we created an Android app where participants perform five different types of cognitive tasks on a mobile device: mental arithmetic, memory, reading comprehension, concentration, and spatial abilities. Participants will be divided into three conditions: music with lyrics, music without lyrics (instrumental music) and no music. Participants will be recruited using Amazon Mechanical Turk, a web-based labor market where “requesters” can post paid tasks which are completed by “workers.” There have been several scientific studies which have evaluated the platform as a source of data comparable to “convenience samples” and undergraduate studies. The platform is extremely robust, reliable and trustworthy with the additional benefit of allowing researchers to quickly recruit a sizeable number of participants at a fraction of the cost of traditional studies. According to previous literature, reading comprehension and memory tasks appear to be more susceptible to interference caused by listening to music. When music is played in the background, the brain has to use some of its finite resources in order to process the music being heard, even if it is not being actively listened to. We hypothesize that participants listening to music, particularly music with lyrics, will have lower performance in each of our five tasks when compared with the other conditions, especially for the memory and reading comprehension tasks. We plan to report on the results of this study. The overall goal of our study is to examine a difficult to observe topic within multitasking by approaching it from a new angle. This brings together literature from Human-Computer Interaction, Music, and Psychology in order to find ways in which we can better harness music to work with users and minimize interruptions.
Comments
Rachel Adler is the faculty sponsor of this project.