Science University Research Symposium (SURS)

Publication Date

Fall 11-24-2025

College

College of Sciences & Mathematics

Department

Psychological Science, Department of

SURS Faculty Advisor

Dr. Michael Oliver

Presentation Type

Metadata Only

Abstract

Selective attention refers to the brain’s ability to focus on relevant information while filtering out distractions. Research suggests that language cues and semantic context can shape how attention is directed, indicating that cognitive control is context-dependent (Reisman, 1964). Environmental factors such as background noise can also disrupt attention, leading to reduced accuracy on cognitive tasks (Pearson & Lane, 1984). In the present study, we examined music as both a linguistic and environmental variable influencing selective attention. Previous findings indicate that lyrical music can serve as a significant distractor, impairing attentional performance in both music and non-music majors (Darrow et al., 2006). Building on this concept, our study investigates how the presence or absence of music affects performance on cognitive tasks. We hypothesize that selective attention will be stronger in silence and weaker when participants are exposed to lyrical music. Specifically, we predict that participants will solve math problems more quickly and accurately in a silent environment compared to one with familiar lyrical music. Using a within-subjects design, participants completed two equivalent sets of math problems: one in silence and one with lyrical music playing. Completion time and accuracy were recorded as measures of attentional performance, and differences between conditions were analyzed using paired-sample t-tests. This research extends the work of Paéz-Maldonado et al. (2020) and Ahmad and Sultana (2021) by isolating auditory stimulation as an environmental factor affecting selective attention and academic performance. Understanding how music influences cognitive control can inform recommendations for study environments and strategies to enhance learning efficiency in higher education settings.

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