The Impact of Listening to Music on Cognitive Performance

By Arielle S. Dolegui
2013, Vol. 5 No. 09 | pg. 2/2 |

Results

This study was conducted in a repeated-measured design; therefore, a paired sample t-test was used for the analysis. An alpha level of .05 was used for the analysis. The independent variable was the type of music played at two different levels of intensity: high intensity and low intensity. The dependent variable was the performance score, which was measured in terms of accurate answers obtained in each of the tests. The tests were not graded for completion but for accuracy only.

In agreement with the first hypothesis, performance scores were significantly higher in silence (M= 12.94) than in all four music conditions, intensity levels, and types of music combined (M= 11.99), t(31)= 2.21, p <.05. The second hypothesis was also supported in the study; participants obtained significantly higher test scores at low intensity (M= 25.63) than at high intensity of both types of music (M= 22.34), t(31)= 4.75, p <.001. Performance scores were also significantly higher in silence (M= 12.94) than in loud music at high intensity (M= 10.78), t(31) = -2.90, p< .05.

However, there was also no significant difference in test scores between participants in the soft music conditions (M= 23.75) and performance in the loud music conditions (M= 24.22), t(31)= -0.56, p= 0.582.

Discussion

The present study sought to demonstrate the impact of different genres of music played at different volume levels on cognitive performance. In accordance with the first hypothesis, participants performed better in silence than they did in any music conditions. The findings were also in agreement with the second hypothesis. They demonstrated that the performance was significantly worse in the presence of loud music at high intensity. Contrary to the third hypothesis, however, there was no significant difference between the type of music that was played and performance scores. The scores were not significantly higher in the soft music versus the loud music condition. Interestingly, there was no difference when the scores from the soft music at high intensity were compared to scores from the loud music at high intensity.

These results seem to parallel those of Smith and Morris (1977). In their study, they also found that participants performed better on a cognitive processing test while listening to no music than they did while listening to either stimulating or sedative music. They determined that performance is impaired with music and optimized with no music. However, their study revealed that participants performed significantly better while listening to sedative music than they did while listening to stimulating music, whereas the current experiment found no significant difference in test scores between the loud music and soft music conditions.

The third hypothesis suggested that performance would be better in the soft music condition when compared to the loud music condition because it was believed that classical music would provide a positive, soothing, and comfortable environment for the participants due to its relaxing tone that will facilitate information processing. However, that hypothesis was not supported by the results; it is important to note that the overall performance was significantly lower in the loud music at high intensity. Based on these results, the presence of lyrics and the consistent use of louder instruments, such as drums, bass and, electric guitar to the heavy metal rock music can be seen as reasons for its distracting effects.

Interestingly, while the findings of this study revealed that it is the intensity of the music rather than the type of music that matters the most when it comes to cognitive performance, it is still noteworthy to point out that scores were significantly higher when participants completed the tests in the silence condition. Through this process, it can be implied that it is easier to process information in the presence of a minimal level of distraction. It can be implied that students should not listen to any music or allow any auditory disturbance while studying to obtain maximum performance level. Students should strive to study and learn in an environment such as the library or a private study room that is as quiet as possible, especially when the material requires higher cognitive processing.

The sample size was the major limitation of this study. Although two of the predictions were supported with this sample, large samples could have provided more reliable significances that could be generalized to the college student population. Due to the limited availability of participants, this study was conducted in a repeated-measured design, which could also be a limiting factor. The sequence in which the tests were given was not randomized throughout the experiment; as such, learning effects could account for the improvement in later tests as the study progressed. Future research should strive to change the sequence in which the tests are administered to guarantee that the results obtained are those of the treatment effects and to eliminate or reduce possible learning effects.

The design of the room could also be another limitation to this experiment. Where participants were seated in the room could have had an effect on how the music was heard. Hence, for participants sitting closer to the speakers, the music was louder than those who were sitting on the other side of the room. This variance in volume level may have either positively or negatively affected the results. Although, some of the results from this study showed that the arithmetic problems were a sufficient tool to assess cognitive performance; however, they may have been too simple for students on the collegiate level to perform. Besides, there were no mathematical base level assessments conducted prior to the study. Participants with stronger skills could have had a biased advantage, whereas those with lower mathematical skills would have had a biased disadvantage. Future research should plan to design more complex cognitive processing tests, such as memory tests or reading comprehension questions from standardized tests like the GRE or the SAT. This could provide a more accurate depiction of the participants’ cognitive processing abilities.

Results from the current study demonstrated how important it is to consider the effects of distracting music on cognitive performance. It was shown that the volume plays a crucial role and could be more important than the type of music played. However, data from this study has demonstrated that silence seems to be the best environment to maximize performance when engaging in cognitive activity. Classical music was not shown to enhance performance contrary to the study’s expectations. Hence, the direct benefits of listening to music on cognitive processing could be more of a fantasy than a reality.


References

Beeson, Sean. (2004). Morning Light. On Ivory Dreams [CD]. United States: Serenity Studio LLC.

Cockerton, T., Moore, S., & Norman, D. (1997). Cognitive test performance and background music. Perceptual and Motor Skills, 85(3, Pt 2), 1435-1438.

Demon Hunter. (2004). Not ready to die. On Summer of Darkness [CD]. Nashville, United States: Solid State.

Dobbs, S., Furnham, A., & McClelland, A. (2011).The effect of background music and noise on the cognitive test performance of introverts and extraverts. Applied Cognitive Psychology, 25(2), 307–313.

Furnham, A., & Bradley, A. (1997). Music while you work: The differential distraction of background music on the cognitive test performance of introverts and extraverts. Applied Cognitive Psychology, 11(5), 445-455.

Hallman, S., Price, J., & Katsarou, G. (2002). The effects of background music on primary school's pupils' task performance. Educational Studies, 28(2), 111-122.

Pool, M. M. (2002). Distraction effects of background on homework performance. Noise and Vibration Worldwide, 33(1), 24-28.

Smith, C.A., & Morris, L. W. (1977). Differential effects of stimulative and sedative music anxiety, concentration, and performance. Psychological Reports, 41, 1047-1053.


Appendix

TEST 1- SM- LO

1. 9+9 =

2. 11-8 =

3. 21÷7 =

4. 12 x 3 =

5. 8+13 =

6. 81÷9 =

7. 35-7 =

8. 4 x 7=

9. 64÷8 =

10. 27+9 =

11. 10-2 =

12. 9 x 6 =

13. 18 ÷6 =

14. 6+9 =

15. 7 x 8 =

16. 32-6 =

17. 48 ÷8 =

18. 5 x 7 =

19. 8 + 6 =

20. 22-8 =

TEST 2 – LM- LO

1. 8+9 =

2. 13-8 =

3. 21÷3 =

4. 12 x 3 =

5. 8+14 =

6. 35÷5 =

7. 25-7 =

8. 4 x 6=

9. 24÷8 =

10. 17+7 =

11. 13-5 =

12. 9 x 4 =

13. 18 ÷3 =

14. 16+7 =

15. 31-6 =

16. 7 x 7 =

17. 36 ÷6 =

18. 8 x 7 =

19. 9 + 8 =

20. 21-6 =

TEST 3-SIL

1. 6+7 =

2. 12-7 =

3. 24÷4 =

4. 11 x 5 =

5. 7+15 =

6. 35÷5 =

7. 26-9 =

8. 8x7 =

9. 34÷2 =

10. 18+7 =

11. 14-5 =

12. 7 x6 =

13. 18 ÷3 =

14. 26+9 =

15. 21-6 =

16. 4 x 9 =

17. 49 ÷7 =

18. 7 x 3 =

19. 6 + 9 =

20. 19-8 =

TEST 4- SM-HI

1. 5+6=

2. 11-7 =

3. 26÷2 =

4. 9 x 5 =

5. 6+17 =

6. 40÷5 =

7. 27-9 =

8. 6 x 9 =

9. 54÷2 =

10. 19+9 =

11. 16 -9 =

12. 8x6 =

13. 32 ÷4 =

14. 25+9 =

15. 31-6 =

16. 7 x 9 =

17. 49 ÷7 =

18. 8 x 9 =

19. 19 + 7 =

20. 38-9 =

TEST 5– LM-HI

1. 7+9 =

2. 41-7 =

3. 36÷2 =

4. 9 x 3 =

5. 5+19 =

6. 20÷5 =

7. 28-9 =

8. 9 x 9 =

9. 48÷4 =

10. 18+8=

11. 17 -9 =

12. 8x7 =

13. 32 ÷8 =

14. 15+9 =

15. 31-4 =

16. 7 x 5 =

17. 28÷7 =

18. 9 x 4 =

19. 29 + 8 =

20. 36-9 =

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