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The effects of music familiarity and music as a working memory load on arithmetic task performance

Researcher Sook-Fern Mok

Supervisors Dr Natalie Jackson & Dr Bethanie Gouldthorp

Date: 10th May, 2010

Our study aims to investigate the effects of familiar music as a load on working memory (containing three components, the Central Executive, Phonological Loop and Visuospatial Sketch Pad. It is used in most cognitive activities a person is engaged in and the term is used to refer to the resource that the brain utilizes to organize these activities) in an adult sample.

According to the Australian Bureau of Statistics in 2008, Australians are increasingly integrating music as part of their lives, be it listening to music whilst involved in another activity eg. doing homework, or having music at workplaces. It is hypothesized that a working memory load should be most distracting during calculation because the individual uses working memory during calculation and distractions make it more difficult to perform the calculation. Music creates cognitive load and this leaves less in terms of cognitive resources available for performing arithmetic.

Most research into effects of music on cognitive performance has more commonly been undertaken with reading comprehension and more needs to be done with mental arithmetic to determine its function in relation to enhancing or inhibiting mental arithmetic performance. It has been found that high-skill participants use less cognitive resources during calculation and hence music is less distracting to them as compared to low-skill participants (Imbo & Vandierendonck, 2007). This is the rationale behind the ACER Clerical Test which you took after the computer task. Familiarity has been rarely examined as a proper variable but it has been found that familiar noises evoke habituation effects (a process by which a person’s response decreases following repeated exposure to the same stimuli), which meant that unfamiliar music is potentially more distracting (Culbert & Posner, 1960).

Our hypotheses for the experiment thus are that unfamiliar music would be more detrimental to arithmetic performance than familiar music. Our next hypothesis is that music would be more detrimental to arithmetic performance than silence. We also predict that high-skill participants would find the music conditions less distracting than low-skill participants.

Participants took a pre-test questionnaire that collected demographical questions such as age and gender. Questions such as the frequency of studying mathematics with music, arithmetic anxiety and prior music training were asked. Next, the participants underwent a computer arithmetic production task where they had to answer an arithmetic problem by saying the answer out loud (i.e., production task) with music playing through headphones in four out of the five conditions they went through. After the computer task, a post-test questionnaire enquiring into how distracting the music was and music familiarity was given. To measure arithmetic ability, they took the arithmetic section of the ACER Short Clerical Test after that.

The first two hypotheses were not supported whilst the third was supported only partially. Whilst we found increased accuracy (measured by no. of correct responses), reaction times (RTs) in general were also higher in the music conditions and there was no significant difference between familiar and unfamiliar music. We attributed this to two factors – that the four second interval in the task was too short, thereby leading to many participants answering the problem late and also because of the interval, participants’ anxiety levels increased. With increased anxiety levels, there are less cognitive resources available to process the arithmetic problem, leading to an increased RT. Another explanation to the lack of significance could be that the participant is concentrating hard on answering the question and thus, music familiarity does not matter. A filtering effect posited by Salamé and Baddeley (1989) stated that humans could have a auditory filter and auditory inputs are filtered out by importance. Since the individual is trying to answer the problem, the music (auditory) input is filtered out as being less important.

There were no significant differences in performance between music and silence, which contradicts previous research. This was due to the fact that the testing lab was not completely soundproof and external noises could be processed by the individual thereby affecting performance. Noise has been found to be more detrimental to performance than music (Banbury & Berry, 1998). Another reason would be that production tasks have not been generally used when investigating music and arithmetic, as previous studies have used written arithmetic tasks as a measure.

A positive correlation was found between anxiety and ability. This was expected, as high ability participants have higher mastery of arithmetic concepts, they feel more confident with arithmetic and tend to do well. Low ability participants on the other hand, have inadequate mastery of arithmetic and thus do not do well. They tend to adopt an avoidant approach towards arithmetic thus not gaining enough practice to gain mastery. Anxiety and RT was also positively correlated only in music. With high anxiety, the individual uses more cognitive resources worrying and thus performance is detrimental. Music further taxes cognitive resources, thus the effect was only observed in music.

Our study has provided support for the cognitive load theory relating to arithmetic. Mental arithmetic is a complex cognitive process and does occupy a reasonable amount of load in the cognitive capacity and factors influencing its fluency are the individual differences which compete to enhance or inhibit mental arithmetic performance.

Our findings are applicable to workplaces, institutions or even individuals. We found increased accuracy but slower RTs in mental arithmetic, meaning that the task was probably more difficult when music was played, leading participants to take longer to achieve a correct response i.e., the speed-accuracy trade off mentioned earlier. This is strong evidence that music was affecting arithmetic processing negatively, especially for participants with low arithmetic ability.

In conclusion, this study revealed that music does enhance mental arithmetic performance in terms of accuracy, not RTs. Correlations between anxiety, ability, accuracy and RT yielded further evidence for the cognitive load theory (Dove, 2009). Higher RTs also meant that music was playing a negative role in inhibiting performance rather than enhancing it, especially if an individual is not sufficiently skilled. The familiarity variable was an exploratory variable but could have been better generated for data analysis and the testing room not being fully soundproof created a confound of noise in the silent condition. In order to reap potential benefits for an individual, individual differences such as anxiety and ability have to be considered. Music should not be used in situations where speed is required as accuracy will be compromised.