The Effect of Music on the Level of Mental

Concentration and its Temporal Change

Fumiya Mori

, Fatemeh Azadi Naghsh

and Taro Tezuka

Department of Children and Families, City of Takasaki, 370-8501 Takasaki, Japan

Graduate School of Library, Information and Media Studies, University of Tsukuba, 305-0821 Tsukuba, Japan

Faculty of Library, Information and Media Science, University of Tsukuba, 305-0821 Tsukuba, Japan

Keywords:

Concentration, Attention, Music, Temporal Pattern.

Abstract:

Concentration is one of the most important factor in determining the efﬁciency of learning. There has not

been, however, much systematic research on controlling the level of concentration. We therefore examined the

effect of an external factor, namely playing music, on the performance on a task that requires much attention.

We compared three conditions: music that the subject likes, music that the subject is not familiar with, and

silence. The result showed that listening to music that the subject likes do increase the performance level.

Also, we discovered that there exist different temporal patterns in the change of performance. The result also

indicated a relationship between the temporal pattern in concentration and the external factor.

1 INTRODUCTION

The efﬁciency of learning is highly dependent on the

mental state that the person is in. When the person is

highly concentrated, he can understand and memorize

many complicated concepts in a short period of time,

whereas when he is not concentrated, he cannot learn

as effectively.

Although the change in the level of concentration

is in part a spontaneous process, it is nevertheless af-

fected by external factors as well. The effect is ev-

ident when one considers how productive he can be

when the deadline is approaching. Surprisingly, there

has not been much work in changing the environmen-

tal factors to create higher performance in learning.

Various books describing techniques to enhance

concentration have been published, but most of them

are solely based on personal experiences rather than

objective experiments. For example, many students

listen to music while they study at home. They seem

to have learned from their experience that music in-

creases their level of concentration. There has not

been, however, much work on evaluating if music

could be used to control the level of concentration.

In contrast to education, there is an extensive

amount of research in the ﬁeld of sports science,

where all efforts are put to win a competition (Katch

and Katch 1999). Physical and mental quantities of

athletes are measured and analyzed to reach highest

performance. The approach here is more objective

and quantitative. If such approach was successfully

applied to education the effect would be tremendous.

One of the ways to measure the effect of music on

learning is to measure how concentrated the subject

is. In this paper, we describe a system aimed at mea-

suring the level of concentration based on the perfor-

mance of the subject. We compare three conditions,

namely playing music that the subject likes, playing

music that the subject is not familiar with, and silence.

The overall performance of the subject and the tempo-

ral change in the performance level will be compared

and analyzed, to objectively evaluate if music have

positive or negative effect on concentration.

The rest of the paper is organized as follows. In

Section 2 we describe our model of concentration, and

factors that would affect it. Section 3 is on implemen-

tation of our system. It is followed by Section 4 where

we illustrates the design and the result of the experi-

ment. Section 5 is on related work. Finally, Section 6

concludes the paper.

2 MODEL

For a person to learn something new, he/she has to be

attentive to the content of learning. When a certain

amount of contents are to be learned, sustaining at-

Mori F., Naghsh F. and Tezuka T..

The Effect of Music on the Level of Mental Concentration and its Temporal Change.

DOI: 10.5220/0004791100340042

In Proceedings of the 6th International Conference on Computer Supported Education (CSEDU-2014), pages 34-42

ISBN: 978-989-758-020-8

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

tention for a certain amount of time is a requirement.

In this paper, we deﬁne concentration as a sus-

tained high level of attention to the task. In order to

measure it, we therefore employ a task that requires

attention. Figure 1 illustrates the overall construction

of our model. Arrows indicate causal relationships.

Concentration is determined by internal parameters,

which is affected by external factors. By changing

the external factors, we assume it possible to change

the level of concentration (or attention).

Figure 1: External factors and internal parameters.

In this paper, we mainly focus on how music and

time affect the performance level on a task that re-

quires concentration. We discuss the model in more

detail in the following subsections.

2.1 Attention and Learning

In cognitive science, much work has been done to ex-

plain how attention affects different aspects of learn-

ing. The main position is even stated that there is no

learning without attention (Schmidt 1995). A num-

ber of researchers have argued that different types of

learning (e.g., explicit and implicit) depend on atten-

tion (Tomlin and Villa 1994).

Studies have inferred that attentional mechanisms

is essential for all learning even for simple percep-

tual task (Ahissar and Hochstein 2002) and that more

complex learning requires more attention (Schmidt

1995). One established principle of visual attention

is that the harder a task is, the more attentional re-

sources are used to perform the task and the smaller

amount of attention is allocated to peripheral process-

ing because of limited attention capacity (Huang and

Watanabe 2012).

2.2 The Effect of Emotion on Attention

Some researchers have discussed that excitement may

enhance attention and facilitate ﬂexibility. On the

other hand, it has been pointed out that positive mood

may reduce the subject’s performance (Schwarz and

Clore 1983, Schwarz and Clore 1988, Rank and Frese

2008). When a subject experiences positive affective

states, he assumes he is performing sufﬁciently well

thus he withdraws effort. Also, in Cerin et al.’s model

predicts that, in general, an affective proﬁle charac-

terized by mild to moderate intensity levels of threat-

related affects (e.g. fear and apprehension) and af-

fects conducive to or associated with approach behav-

ior and task-focused attention (e.g. interest, excite-

ment and enjoyment) will be perceived as facilitating

performance (Cerin et al. 2000).

We however consider that the balance between ex-

citement and calmness is important. If a person is

overexcited, it often happens that he is distracted by

any small stimuli and cannot concentrate on the task.

On the other hand, if one’s mind is too calm or re-

laxed, he would not feel like doing anything. The

level most appropriate for a task lies somewhere in

between excited and relaxed. We assume that listen-

ing to music that one likes has a modulating effect,

with excitatory and inhibitory factors, helps achieve

the best performance. Some music excites and other

music calms. We assume that people know from ex-

perience which music is best for them to modulate

music to sustain his/her level of attention. We test

this hypothesis through experiments described in this

paper.

2.3 Temporal Change in the Level of

Attention

Time has various effects on cognitive performance

(Grondin 2008). For example, it has been pointed

out that attention is limited in time (Nobre and Coull

2010). Humans cannot sustain a high level of concen-

tration for a long period of time. Learning is no ex-

ception. In practice, it is important to know how the

level of attention changes, how it can be recovered, in

order to make humans more productive.

It is also known that there are various rhythms

in mental processes, from short ones to long ones

(Buzsaki 2006). The level of concentration does not

monotonically decreases either. It may have some

rhythm, or it may rise as the end of the task ap-

proaches. It may follow different patterns other than

rhythms, for example constant decrease in perfor-

mance. By measuring the temporal change in per-

formance, we try to uncover the temporal change of

concentration. In this paper, we try to uncover such

different patterns through experiments.

TheEffectofMusicontheLevelofMentalConcentrationanditsTemporalChange

3 IMPLEMENTATION

We implemented a system aimed at controlling the

level of concentration. In this section, we ﬁrst de-

scribe a way to measure it, then describe the actual

implementation.

3.1 Measurement of Mental

Concentration

Our system measures the level of concentration using

the amount of time required to perform a task that re-

quires attention. It is based on a “conjunction search”

task, where the subject is presented with signs that

have combinations of features, such as shape, color,

and orientation (Bergen and Julesz 1983). Figure 2

shows an example of the image presented to the sub-

ject when using our system.

Figure 2: Conjunction search task.

The subject is presented with 100 signs, aligned

into 10 rows and 10 columns, shown on a computer

screen. Signs are in two types, namely T and L, and

in two colors, blue and orange. The subject is asked

to ﬁnd a sign that is different from the rest in two as-

pects. For example, about half of the signs are blue T,

and about the half are orange L, but there is one ex-

ception, either orange T or blue L. Once the subject

ﬁnds it, he presses a key, and then the next trial starts.

The exceptional sign is presented at different location

each trial.

Usually, it is easy for a subject to ﬁnd an excep-

tional sign when there is only one feature involved

(Duncan and Humphreys 1989). It is an unconscious

process, and the exceptional sign “pops out”. In other

words, the subject notices the exception without pay-

ing much mental effort.

On the other hand, one that is exceptional because

of a combination of features, it requires much more

time to ﬁnd it. Usually, it requires conscious process

for searching it. It means that consciousness is in-

volved in the combinatorial search process. Consider-

ing the usual assumption that consciousness is closely

related to attention, the task requires much attention,

or concentration. By measuring the time required to

ﬁnd the exception, we can quantitatively evaluate the

level of concentration. This type of test is widely used

in psychology to measure the level of attention put by

the subject.

In our system, the subject can click a sign by mov-

ing a pointer using the mouse. If the clicked sing is

not the exceptional one, it is recorded as a mistake. By

a preliminary experiment, we checked that time re-

quired for moving the pointer to the exceptional sign

is negligible compared to time necessary for ﬁnding

the sign.

3.2 Environmental Factors

As a control factor to affect the internal parameters,

we chose to focus on music. Music affects emotion,

making a person feel happy or sad. It is natural to

think that it may affect internal parameters mentioned

above. It has already been pointed out that it im-

proves performance on spatial tasks (Schellenberg et

al. 2007). Our experiments are to see if this is also

true for tasks that involve concentration, and see if

it can be quantitatively and systematically measured

with an aid of a computer program.

In our experiments, we compared 3 conditions

listed below.

1. Silence.

2. Music that the subject likes.

3. Music that the subject is unfamiliar with.

We chose to compare between music that are liked

by the subject and that the subject is unfamiliar with.

We assume that when the subject is listening to the

music that he likes, performing the task becomes

more enjoyable.

We asked the subjects to name a song that he/she

likes, and used it in the experiment. For unfamiliar

music, subjects were provided with music liked by

other subjects, after checking that he/she is actually

unfamiliar with it.

Using music that the subject likes is to determine

the effect of enjoyment on concentration. The goal

of our experiment is to determine whether the effect

comes directly from the music itself, or is strongly

inﬂuenced by the subject’s liking to it.

CSEDU2014-6thInternationalConferenceonComputerSupportedEducation

3.3 Software

For implementing our system, we used PsychToolbox

(Brainard 1997, Kleiner, Brainard and Pelli 2007),

which is a set of functions run on Matlab, aimed at

vision research. PsychToolbox contains various func-

tions that could be used for creating psychological

tests. For implementation, we used Octave, a Matlab

compatible software.

4 EXPERIMENTS

We performed experiments on 12 subjects. All of

them were undergraduateand graduate students, rang-

ing from a freshman to 1st year in master’s course.

Using our system, we measured the number of tri-

als each subject could perform during a set amount

of time (15 minutes), under different conditions. Sub-

jects were asked to perform trials as many times as

possible. In other words, they were asked to ﬁnd ex-

ceptional signs as fast as possible.

The types of music that were played were mostly

pop music, with lyrics. There were up-tempo ones

and slow-tempo ones, depending on the preference of

each subject. When we could, we chose unfamiliar

music from those that were liked by other subjects.

This was to avoid the effect that comes from the types

of music, for example the positive effect on concen-

tration that may arise from listening to up-tempo mu-

sic.

4.1 Comparison among Subjects

The numbers of trials that the subjects could perform

under three conditions mentioned in the previous sec-

tion is indicated in Table 1. The three conditions were

silence, playing music that the subject likes, and play-

ing music that the subject is unfamiliar with.

It shows scores for each condition, which are the

numbers of trials that the subject succeeded within the

time limit of 15 minutes. If the subject could complete

each trial in a shorter time, he gets a higher score.

To avoid the effect from the subject getting used

to the task and performing better in the latter part of

the experiment, we arranged the conditions in differ-

ent orders. The order of conditions the experiment

was carried out for each subject is indicated by the

second column of Table 1, using order IDs. The order

is explained using Table 2.

The result shows that the average score were high-

est when the subject was listening to the music that

he likes. The second highest was when he listened to

the music that he is unfamiliar with, and the lowest

Table 1: Scores of subjects under different conditions.

Subject Order Silence Like Unfam.

A I 98 89 113

B I 86 84 84

C II 119 119 96

D II 54 61 69

E III 71 72 62

F III 106 132 109

G IV 88 96 93

H IV 109 105 105

I V 116 131 138

J V 115 110 112

K VI 54 51 43

L VI 40 56 53

Total 1056 1106 1077

Avg 88 92.17 89.75

Table 2: Order of testing.

Order Silence Like Unfam.

I 1st 2nd 3rd

II 3rd 2nd 1st

III 2nd 3rd 1st

IV 2nd 1st 3rd

V 1st 3rd 2nd

IV 3rd 1st 2nd

was for the silence condition. It indicates that perfor-

mance can be improved using music.

Table 3 shows the number of mistakes made by the

subjects when carrying out the test. It shows that the

number of mistakes was least when the subject was

listening to the music he likes. Figure 3 illustrates the

same information as a graph.

Table 3: The number of mistakes made by subjects.

Subject Silence Like Unfam. Total

A 0 1 1 2

B 1 0 0 1

C 0 0 0 0

D 2 0 2 4

E 0 2 2 4

F 0 0 0 0

G 0 0 0 0

H 1 0 0 1

I 0 0 0 0

J 3 1 1 5

K 0 1 1 2

L 2 0 0 2

Total 9 5 7 21

TheEffectofMusicontheLevelofMentalConcentrationanditsTemporalChange

Figure 3: The number of mistakes made by subjects.

4.2 Temporal Change in Performance

In the experiment, each subject was asked to perform

the task for 15 minutes, for each condition. After per-

forming a task under one condition, the subject takes

5 minutes break.

Since the task is rather simple, so it is assumed

that the subjects get tired with the task, or bored,

which would lower the performance. Unless a high

level of concentration is maintained, the performance

level of the subject is unlikely to be constant.

Figure 4-9 shows one example of the change in

the performance level as a subject did a sequence of

trials. The x-axis indicates the trial ID and the y-axis

indicates the time it took for the subject to complete

that trial, i.e. to ﬁnd the exceptional sign and click it.

The sequence of the times taken for ﬁnishing tri-

als was considered as a function of sample points in

time. We applied second order polynomial ﬁtting to

this function. The polynomials are also shown in the

ﬁgures. They show the gradual changes of the perfor-

mance levels.

Based on an observation, we grouped the result

into three types. Type 1 is the case when the perfor-

mance level does not change much. In this case, the

polynomial is nearly constant. Type 2 is that the per-

formance worsens as the time passes. In this case,

the polynomial is a nearly linear increasing function.

Type 3 is when the performance is best near the be-

ginning and near the end, and worse in the middle.

In this case, the polynomial is a convex function with

its maximum in the middle part of the trial sequence.

This is summarized in Table 4. In the table, a

is the

coefﬁcient of the quadratic term and a

is the coefﬁ-

cient for the linear term, for the second order polyno-

mial ﬁtting. Note that the performance is better when

the y-value is lower.

The frequent appearance of Type 3 (high in the

middle) was interesting, possibly indicating the rise in

the performance level when the deadline is approach-

ing.

In general, the overall performance level (the

score the subject obtained) was highest for Type 1 and

lowest for Type 3. Also, Type 1 was most frequent

when the subject was listening to the music that he

liked. On the other hand, Type 3 was most frequent

when the subject was in the silence condition.

The result indicates that listening to preferred mu-

sic condition raises the overall performance because

it reduces occasions where the subject cannot ﬁnd the

exceptional sign and takes unusually longer time to

ﬁnish the trial.

Table 4: Types in the temporal change of performance.

Type Polynomial ﬁtting a

Type 1 Roughly constant a

≈ 0 a

≈ 0

Type 2 Increasing a

≈ 0 a

> 0

Type 3 High middle, low ends a

> 0

Figure 4: Temporal change under the silence condition

(Subject C, Type 2).

Figure 5: Temporal change under the liking music condition

(Subject C, Type 1).

The regression curve may seem to be dependent

on large values that intermittently occurs. However,

since one of the aims of our experiment was to see the

lack of attention, the fact that the subject took a long

time to ﬁnd the exceptional sign does carry informa-

tion. We did not consider them as outliers.

CSEDU2014-6thInternationalConferenceonComputerSupportedEducation

Figure 6: Temporal change under the unfamiliar music con-

dition (Subject C, Type 2).

Figure 7: Temporal change under the silence condition

(Subject F, Type 3).

4.3 Discussion

Our result that music affects the level of concentra-

tion have various application in the daily practicality

of learning. When doing self-study, selecting appro-

priate music would help raise the performance. Even

in a classroom, when it is not a lecture-style class but

is a practice-style, it might help students by allowing

them to listen to music while solving problems.

Teachers may even advice students to try out dif-

ferent types of music while studying, since our result

Figure 8: Temporal change under the liking music condition

(Subject F, Type 1).

Figure 9: Temporal change under the unfamiliar music con-

dition (Subject F, Type 3).

indicates that familiarity to music may affect the tem-

poral change in the level of concentration.

Also, the method proposed in this paper to mea-

sure the level of concentration may be used for other

purposes too, for example to know how long a subject

can stay concentrated in learning.

5 RELATED WORK

In this section, we discuss related work from different

aspects.

5.1 Factors That May Affect Mental

Concentration

Onyper et al. tested a group of subject to solve puzzles

or memorize items, while chewing gum (Onyper et al.

2011). They were compared with another group that

did not chew gum during the test. The result indicated

that chewing gum has positive effect on the subjects’

performance. They state that chewing gum may wake

you up and increase the level of concentration.

Nittono et al. found out that when the subject

is presented with a cute (“kawaii”, in recent termi-

nology) picture preceding a task, his performance in-

creased (Nittono et al. 2012). Although they hypoth-

esized that a cute picture makes the subject focus on

the details of it and increase his performance, it could

also be resulting from the increased level of concen-

tration due to excitement or enjoyment.

Our work is different from existing work in that

it focused on music among many possible factors. It

is also different in that it intended to capture the tem-

poral change in the level of concentration in a short

time span, i.e. in the order of seconds, which is much

shorter than usually considered.

TheEffectofMusicontheLevelofMentalConcentrationanditsTemporalChange

5.2 Cognitive Performance While

Listening to Music

Rauscher et al. reported the superior spatial abilities

for participants who listened to a recording of music

composed by Mozart compared to those who sat in si-

lence or listened to relaxation instructions (Rauscher,

Shaw and Ky 1993). Because the performance was

better on the spatial tasks after listening to Mozart,

this result became known as the Mozart effect (Schel-

lenberg 2005). Reviewing studies that examined ef-

fects of listening to music on cognitive performance

can be divided to two general group: performance af-

ter listening to music and performance while listen-

ing to music or background music. Despite the dif-

ference, it is pointed out that music inﬂuences a wide

range of behaviors including cognitive performance

(Schellenberg 2012). In these studies, however, it

was not checked whether the subjects actually liked

Mozart. In comparison, we made a distinction be-

tween music liked by the subject and the one that the

subject is not familiar with. Our result showed that

while music itself raises concentration, the one that is

liked works even better.

Shih et al. compared how music with, and with-

out, lyrics affects human attention (Shih, Huang and

Chiang 2012). Background music with, and with-

out lyrics, was tested for effects on listener concen-

tration in attention testing using a RCT (randomized

controlled trial) study. The ﬁndings revealed that, if

background music is played in the work environment,

music without lyrics is preferable because songs with

lyrics are likely to have signiﬁcant negative effects on

the concentration and attention of worker.

Patston and Tippett examined the overlap be-

tween music and language processing in the brain and

whether these processes are functionally independent

in expert musicians (Patston and Tippett 2011). A lan-

guage comprehension task and a visuospatial search

task were performed under three conditions: music-

correct, music-incorrect, and silence for expert musi-

cians and non-musicians. The performance of musi-

cians was negatively affected by the presence of back-

ground music compared to silence when performing a

language comprehension task. In contrast, the perfor-

mance of non-musicianswas not affectedon either the

language task by the presence of music played either

correctly or incorrectly.

Cassidy and MacDonald studied the effects of HA

(music with high arousal potential and negative af-

fect), LA (music with low arousal potential and pos-

itive affect), and everyday noise, on the cognitive

task performance of introverts and extraverts (Cas-

sidy and MacDonald 2007). Performance was de-

creased across all cognitive tasks in the presence of

background sound compared to silence. HA and LA

music produced differential distraction effects, with

performance of all tasks being poorer in the presence

of HA compared to LA and silence, in the presence of

noise than silence across all tasks, and in the presence

of noise than LA in three of the four tasks.

Furnham and Strbac examined whether back-

ground noise would be as distracting as music (Furn-

ham and Strbac 2002). In the presence of silence,

background garage music and ofﬁce noise, subjects

with introvert and extravert personalities carried out a

reading comprehension task, a prose recall task and a

mental arithmetic task. Results found a signiﬁcant in-

teraction between personality and background sound

on comprehension task only, although a trend for this

effect was clearly present on the other two tasks. Par-

ticipants performed best in silence, background mu-

sic was second best for performance, and background

noise was lowest results.

The existing work mainly focused on making

comparison among music, silence and noise, whereas

in our work music liked by the subject is compared

with unfamiliar one. In this sense, it is more related

to the emotion of the subject. Also, the existing work

has not discussed much on how listening to music

may affect the temporal change in the level of con-

centration. We designed and carried out experiments

to check this effect.

5.3 Music for Enhancing Learning

Researchers from psychology as well as sociology

have attempted to explain the importance of mu-

sic for intellectual development by focusing on a

variety of cognitive ability. Singer (Singer 2008)

and Barker (Barker 2008) reported that music in-

creased the chance students remembered what they

had learned, by assisting the recall of information.

Binkiewicz discussed the idea that songs are pow-

erful pedagogical tools that enliven a classroom and

enhance student learning in an enjoyable manner

(Binkiewicz 2006).

When music is utilized learning, positive results

occurred in achievement. Music showed positive im-

pacts on achievement as Southgate and Roscigno as-

sessed three patterns of music participation: in school,

outside of school, and parental involvement in the

form of concert attendance and possible effects on

math and reading performance for both elementary

and high school students (Southgate and Roscigno

2009). Their study captured the signiﬁcant inﬂu-

ence of music involvement for both math and reading

achievement.

CSEDU2014-6thInternationalConferenceonComputerSupportedEducation

Paquette and Rieg described the beneﬁts of in-

corporating musical experiences into daily instruc-

tion and argued that integrating experiences with mu-

sic in the childhood classroom supports English lan-

guage learners’ literacy development (Paquette and

Rieg 2008). Sims examined the effects of high versus

low teacher affect and active versus passive student

activities during music listening on preschool chil-

dren’s attention (Sims 1986). Data obtained through

observation indicated that children were most atten-

tive during music listening activities when the teacher

exhibited high magnitude nonverbal affect, and when

they were given a hand-movement activity in which

to participate.

Our paper focused on the effect of music on the

level of concentration, which is related to perfor-

mance in general, rather than speciﬁc tasks in learn-

ing. By focusing on a simple task rather than com-

plicated ones, we believe that we could quantify more

fundamental parameter that affect the level of perfor-

mance.

6 CONCLUSION

In order to increase the concentration level and raise

the performance in learning, we implemented a sys-

tem for measuring it, and examined the effect of an

external factor, namely playing music that the subject

likes. The result showed that playing music does have

positive effects on the level of concentration, which

would contribute to the performance level.

In future work, we would like to carry out exper-

iments using more subjects, to make our result more

statistically reliable. We would also like to look at

the temporal patterns of concentration in more detail.

We would like to see if there is actually rhythms for

concentration, as mentioned by Buzsaki for different

mental processes (Buzsaki 2006). We would like to

explore this, for example using frequency analysis.

We also plan to carry out more controlled testing, us-

ing a larger number of subjects, to validate our hy-

pothesis.

We also plan to explore modulation of the excite-

ment level using music, and see if the concentration

can be improved. When the subject is too relaxed,

we make him listen to excitatory music, and while

the subject is overexcited, we make him listen to in-

hibitory music. We would like to see if the concen-

tration level can effectively controlled that way. We

expect the result to provide a fundamental basis for

creating the environment most suited for learning.

ACKNOWLEDGEMENTS

This work was supported in part by JSPS KAKENHI

Grant Numbers 21700121, 25280110, and 25540159.

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