Belison National School
Belison, Antique
ASSESSMENT ON THE EFFECTS OF LISTENING TO MUSIC TO THE COGNITIVE
PERFORMANCE OF SCIENCE, TECHNOLOGY,ENGINEERING, MATHEMATICS
(STEM) STUDENTS
A Research Proposal
Presented To Mr. Albert Morillo
Belison National School
Belison, Antique
By
Calixto Popelo
John Francis Masabio
Zynnette Kaye Ybera
Mario Busayong
Aldrin Subillaga
Fritzel Eljane Mina
Shermaine Chavez
John Mison Ardonia
JULY 2020
Belison National School
Belison, Antique
JULY 2020
Approval Sheet
In Partial Fulfilment
Of the Requirements for the Subject
Practical Research 1
By:
Calixto Popelo
John Francis Masabio
Zynnette Kaye Ybera
Mario Busayong
Aldrin Busayong
Fritzel Eljane Mina
Shermaine Chavez
John Mison Ardonia
Approved:
Mr. Albert Morillo
Noel A. Polaron
Principal IV
Belison National School
Belison, Antique
RESEARCH ABSTRACT
Title: ASSESSMENT ON THE EFFECTS OF LISTENING TO MUSIC TO THE
COGNITIVE PERFORMANCE OF SCIENCE, TECHNOLOGY,ENGINEERING,
MATHEMATICS (STEM) STUDENTS
Authors:
Calixto Popelo
Aldrin Subillaga
John Francis Masabio
Fritzel Eljane Mina
Zynnette Kaye Ybera
Shermaine Chavez
Mario Busayong
John Mison Ardonia
Track: Science, Technology, Engineering and Mathematics
Teacher: Mr. Albert Morillo
School: Belison National School
Address: Magsaysay St. Poblacion, Belison, Antique
Date: July 2020
This descriptive-survey study was concerned with the effects of listening to music to the
cognitive performance of STEM students. 30 students were selected to all senior high in Belison
National School. Data were obtained through researcher-made questionnaires which have been
validated and reliability-tested for utilization in the study. The survey instrument used in this
study was designed to assess the effects of listening to music to the cognitive performance of
STEM students of Belison National School during the Academic Year 2019-2020.
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Table of Contents
Page
Chapter 1: Introduction to the Study ……………………………………………………..
1
Background of the Study ……………………………………………………………….
1
Statement of the Problem ……………………………………………………………
4
Significance of the Study …………………………………………………………….
4
Definition of Terms …………………………………………………………………..
5
Delimitation of the Study …………………………………………………………….
6
Chapter 2: Review of Related Literature ………………………………………………..
7
The Relationship Between Music Aptitude and Music Performance ………………
7
Cognitive Performance after Listening to Music ……………………………………
9
Background Music and Cognitive Abilities ………………………………………….
14
The Relationship Between Music Training and Cognitive Performance …………...
17
Theoretical Framework ………………………………………………………………
19
Conceptual Framework ………………………………………………………………
21
Chapter 3: Method …………………………………………………………………………
23
Purpose of the Study and Research Design …………………………………………
23
Respondents ………………………………………………………………………….
24
Instruments …………………………………………………………………………...
24
Data Collection ……………………………………………………………………….
24
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Table of Contents
Chapter 4: Result and Discussion …………………………………………………………
Page
25
Table 1: Demographic Profile ………………………………………………………..
25
Table 2: Music Listening ……………………………………………………………..
26
Table 3: Studying with Music ………………………………………………………..
26
Table 4: Memory Formation ………………………………………………………...
27
Table 5: Music and Concentration …………………………………………………..
27
Table 6: Cognitive Performance ……………………………………………………..
28
Table 7: Beating Stress and Anxiety ………………………………………………...
28
Table 8: Effects of Music ………………………………………………………….....
29
Table 9: Mode of Studying …………………………………………………………..
30
Table 10: Studying with Music ………………………………………………………
30
Table 11: Music Genre ……………………………………………………………….
31
Chapter 5: Summary, Conclusions, and Recommendations ……………………………
32
Summary ……………………………………………………………………………..
32
Findings ……………………………………………………………………………….
33
Conclusions …………………………………………………………………………...
34
Recommendation …………………………………………………………………….
35
Acknowledgement ……………………………………………………………………
36
References
…………………………………………………………………………37
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Chapter I
Introduction to the Study
Chapter One is divided into five parts: Background of the Study, Statement of the
Problem, Significance of the Study, Definition of Terms, and Delimitation of the Study.
Part One, Background of the Study, gives the overview or the rationale of the research
problem.
Part Two, Statement of the Problem, mentions general and specific problems
Part Three, Significance of the Study, gives the importance of the result of the study to
different persons, organizations, and institutions that directly or indirectly will benefit from it.
Part Four, Definition of Terms, discusses the terms used in the study, which are defined
conceptually and operationally.
Part Five, Delimitation of the Study, cites the coverage and limitation of the study.
Background of the Study
Music is a very significant part of our daily lives; the image of the quietly-focused
student isolating themselves into a personal study zone has led to interest into whether listening
to music actually helps studies or not. Research into the field has proven fairly ambiguous, with
many studies contradicting each other. However this does provide a useful insight for students
who maybe looking into ways to use music to enhance their exam performance.
However, research has shown that performance in tasks involving memory and
concentration was better in a silent environment, though, studying in place often disturbed by
talkers, sneezers, or traffic, few students have access to a silent study space. Subjects tested in
environments with background music were found to get better results than those tested against
background noise. Therefore, taking along an iPod and a set of headphones may come in handy
if you’re looking to avoid being distracted by any ambient sounds. (www.independent.co.uk)
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Music has become much more readily available to the public in the past decades. One
influencing factor was the increasing availability of music: whilst in the past one was in need of
CDs or tapes and an according player, nowadays music can be played digitally on many different
devices such as computers, mobile phones or iPods. Furthermore, the choice of available songs is
almost endless due to music portals. This makes it possible to select suitable songs for different
situations, such as relaxing songs for a cozy evening or activating songs before going out. Due to
these advances in music technology, learning with background music has received more and
more attention over the last decade (e.g., Schwartz et al., 2017). For some situations it seems
intuitive to think that music would help to enhance our experience – but how do music and
learning fit together? At present the effects of background music while learning and the
mechanisms behind this are unclear. On the one side, music seems to have a positive (Mozart
effect; Rauscher et al., 1993) and stimulating effect (arousal-mood-hypothesis; Husain et al.,
2002), which could improve learning. On the other side, background music could lead to an
additional burden on working memory (seductive detail effect; e.g., Rey, 2012), thus hindering
learning. To be able to simultaneously deal with the learning material and the background music,
the learner’s working memory capacity is a crucial factor to consider.
Music listening is one of the most enigmatic of human behaviors. Most common
behaviors have a recognizable utility that can be plausibly traced to the practical motives of
survival and procreation. Moreover, in the array of seemingly odd behaviors, few behaviors
match music for commandeering so much time, energy, and money. Music listening is one of the
most popular leisure activities. Music is a ubiquitous companion to people's everyday lives.
The enthusiasm for music is not a recent development. Recognizably musical activities
appear to have been present in every known culture on earth, with ancient roots extending back
250,000 years or more (see Zatorre and Peretz, 2001). The ubiquity and antiquity of music has
inspired considerable speculation regarding its origin and function.
(www.ncbi.nlm.nih.gov)
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Musical training has recently gained additional interest in education as increasing
neuroscientific research demonstrates its positive effects on brain development. Neuroimaging
revealed plastic changes in the brains of adult musicians but it is still unclear to what extent they
are the product of intensive music training rather than of other factors, such as preexisting
biological markers of musicality. In this review, we synthesize a large body of studies
demonstrating that benefits of musical training extend beyond the skills it directly aims to train
and last well into adulthood. For example, children who undergo musical training have better
verbal memory, second language pronunciation accuracy, reading ability and executive
functions. Learning to play an instrument as a child may even predict academic performance and
IQ in young adulthood. The degree of observed structural and functional adaptation in the brain
correlates with intensity and duration of practice. Importantly, the effects on cognitive
development depend on the timing of musical initiation due to sensitive periods during
development, as well as on several other modulating variables. Notably, we point to motivation,
reward and social context of musical education, which are important yet neglected factors
affecting the long-term benefits of musical training. Further, we introduce the notion of rhythmic
entrainment and suggest that it may represent a mechanism supporting learning and development
of executive functions. It also hones temporal processing and orienting of attention in time that
may underlie enhancements observed in reading and verbal memory. We conclude that musical
training uniquely engenders near and far transfer effects, preparing a foundation for a range of
skills, and thus fostering cognitive development. (www.frontiersin.org)
People intuitively use music to support their thinking at work. Spotify is full of playlists to help
gear your cognitive state towards concentration and improved memory: you might even be using
one while you are reading this very article! In part due to the popularity of this productivity hack,
research on the topic of enhancing cognitive function with music is abundant. However, the
wealth of investigation has focused on what happens to cognitive processing after listening to
music; there is much less investigation of what occurs during music listening. According to
studies,
music
exerts
its
effects
on
cognition
(www.google.com/amp/syncproject.co/blog)
8
through
its
power
on
emotions.
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Statement of the Problem
Generally this study is conducted to Assess the Effectiveness of Listening to Music to the
Cognitive Performance of STEM students of Belison National School (BNS) during the
Academic Year 2019-2020.
Specifically, this sought to answer the following questions:
1. What are the Effects of Listening to Music to the Cognitive Performance of Students?
2. What is/are the perception to the Effects of Listening to Music to the Cognitive
Performance of Students ?
Significance of the Study
This study aimed to assess the effectiveness of Listening to Music to the Cognitive
Performance of STEM students of Belison National School (BNS).
The results of this study will be benefited by the following:
1. Students
The students will recognize the effects of listening to music in relation to their
cognitive performance.
2. Teachers
The teachers will be able to understand the effects of listening to music to the
cognitive performance of students and encourage them to listen to different genres of
music.
3. Administrators
The administrators will support the school in implementing some of the activities
where students can widen their knowledge through listening to music.
4. Parents
Parents would be aware for the importance of listening to music in the learning of
their children.
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5. Future Researchers
Future researchers might use the result of this study in their own research.
Definition of Terms
Assessment
Assessment is the process of gathering and discussing information from multiple and
diverse sources in order to develop a deep understanding of what students know, understand and
can do with their knowledge as a result of their educational experiences.
(https://www.westminster.edu)
In this study, the same definition was applied.
Music
Music is an art concerned with combining vocal or instrumental sounds for beauty of
form or emotional expression, usually according to cultural standards of rhythm, melody, and, in
most western music, harmony. (https://www.britanica.com)
In this study, music refers to music that may improve focus on a task by providing
motivation and improving mood.
Cognitive Performance
Cognitive Performance refers to multiple mental abilities, including learning, thinking,
reasoning, remembering, problem solving, decision making and attention.
(http://www.sciencedirect.com)
In this study, the same definition was applied.
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Delimitation of the Study
This study aimed to Assess the Effects of Listening to Music to the Cognitive
Performance of STEM students.
This study was limited to all Science, Technology, Engineering, Mathematics (STEM)
students.
The correspondents were randomly selected and interviewed as to their perception on the
effects of listening to the music to their cognitive performance
A set of questionnaires was used to determine the effects of Listening to Music to the
Cognitive performance of Science, Technology, Engineering, Mathematics (STEM) students
during the Academic year 2019-2020.
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Chapter II
Review of Related Literature
Chapter Two presents literatures relevant to the cognitive performance of students when
it comes to music. This includes four parts: The Relationship Between Music Aptitude and
Cognitive Performance, Cognitive Performance after Listening to Music, Background Music and
Cognitive Abilities, The Relationship Between Music Training and Cognitive Performance
The Relationship Between Music Aptitude and Cognitive Performance
Music aptitude refers to natural music abilities or the innate potential to succeed as a
musician. One school of thought (e.g., Ericsson, Krampe, & Tesch-Ro¨mer, 1993; Howe,
Davidson, & Sloboda, 1998) contends that innate music talent (i.e., aptitude plus a demonstrated
ability to perform music) does not account for variations in levels of musicality. Rather, expert
levels can be achieved by anyone who starts early enough and works hard enough. In short,
practice makes perfect (cf. Meinz & Hambrick, 2010). The debate about the existence of music
talent or aptitude is beyond the scope of the present chapter. We assume that music aptitude
exists, that it varies among individuals, and that aptitude is something that tests of music aptitude
measure. Although this definition is circular, our principal focus is on whether tests of music
aptitude measure an ability that is independent of or associated with other cognitive abilities.
The issue of music aptitude as an ability distinct from other cognitive abilities is closely
related to concepts of modularity (Fodor, 1983; Peretz, 2009; Peretz & Coltheart, 2003) and
multiple intelligences (Gardner, 1983, 1999). The notion of modularity proposes that (1) the
brain has specialized modules for processing different kinds of information, (2) domain-specific
information (re: language, faces, music, and so on) is processed automatically by the appropriate
module, and (3) each module functions independently of other modules (Fodor, 1983). Gardner
(1983, 1999) posits similarly that intelligence is a multidimensional construct. In the original
formulation of his theory of multiple intelligences, he specified seven distinct intelligences:
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bodily-kinesthetic, interpersonal, intrapersonal, linguistic, logical-mathematical, spatial, and
most importantly, musical intelligence. From either the modularity or multiple intelligences
perspective, music aptitude should be distinct from other abilities.
The typical task on tests of music aptitude involves presenting two short melodies (or two
short rhythms) on each trial. Listeners are asked whether the second melody (or rhythm) is the
same as or different from the first. After several trials, a score is calculated separately for each
test. An aggregate score can also be calculated by averaging across tests.
The origin of music-aptitude testing is often attributed to Seashore (1919, 1960).
Seashore’s test has six subtests, including pitch and rhythm tasks as well as subtests of loudness,
meter, timbre, tonal memory, and an aggregate measure of general music aptitude. In North
America, one of the most well-known measures is Gordon’s (1965) Music Aptitude Profile
(MAP), which has seven subtests. Gordon later simplified his approach, forming three different
tests based on grade level: the Primary Measures of Music Audiation (PMMA, kindergarten to
third grade; Gordon, 1979), the Intermediate Measures of Music Audiation (IMMA, first to sixth
grade; Gordon, 1982), and the Advanced Measures of Music Audiation (AMMA, seventh grade
and higher; Gordon, 1989). Each test has only two subtests (pitch and rhythm). In the United
Kingdom, Wing’s (1962) Musical Aptitude Test has been used frequently, as has Bentley’s
(1966) Measures of Musical Abilities. All of the aptitude tests and their corresponding subtests
tend to be correlated at moderate to high levels (e.g., Gordon, 1969; McLeish, 1968; Vispoel,
1992; Young, 1972, 1973). Unfortunately, there is no test of music aptitude that is considered to
be the “gold standard.” Consequently, the particular test varies from study to study, which
undoubtedly contributes to inconsistent findings. In tests of the validity of aptitude measures,
criterion variables (i.e., those that should be correlated with aptitude) also vary across studies.
Often, construct validity is tested by examining associations between aptitude scores and a
teacher’s or parent’s subjective rating of the participant’s “musicality” (Davies, 1971; Drake,
1954; Harrington, 1969; Tarrell, 1965; Young, 1972, 1976). These correlations are typically
positive but small to moderate in size, which is not surprising because aptitude tests present
participants with short auditory sequences13that are a far cry from actual musical pieces. Music
training is seldom used as a criterion variable precisely because aptitude tests are supposed to
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measure natural music ability independent of training. Nevertheless, when musically trained and
untrained participants are compared, the trained group typically has higher aptitude scores
(Bentley, 1970; Davies, 1971; Drake, 1954; Flohr, 1981; Forgeard, Winner, Norton, & Schlaug,
2008; Gordon, 1969, 1980, 2001; Hassler, 1992; Hassler, Birbaumer, & Feil, 1985; Isaacs &
Trofimovich, 2011; Milovanov, Pietila¨, Tervaniemi, & Esquef, 2010; Milovanov, Tervaniemi,
Takio, & Ha¨ma¨la¨inen, 2007; Posedel, Emery, Souza, & Fountain, 2011; Tsang & Conrad,
2011; Wallentin, Nielsen, Friis-Olivarius, Vuust, & Vuust, 2010).
The major question discussed here is whether music aptitude is related to nonmusical
cognitive abilities. The relevant studies have examined associations between music aptitude and
language skills, mathematical abilities, and general intelligence. Links between music aptitude
and nonmusical abilities are problematic for theorists who posit modularity for music (Peretz,
2009; Peretz & Coltheart, 2003) or that music ability represents an intelligence distinct from
other abilities (Gardner, 1983, 1999).(Retrieved from www.researchgate.net, February 28, 2020)
Cognitive Performance after Listening to Music
Schellenberg and his colleagues (Husain, Thompson, & Schellenberg, 2002; Nantais &
Schellenberg, 1999; Schellenberg & Hallam, 2005; Schellenberg, Nakata, Hunter, & Tamoto,
2007; Thompson, Schellenberg, & Husain, 2001) sought to determine whether the Mozart effect,
when evident, was a consequence of arousal and mood. The basic idea was that any stimulus that
improves how a person feels can in turn improve how they perform on a cognitive task. The
advantage of this hypothesis is that it explains the Mozart effect with two links that are well
established in the psychological literature.
Consider links between music listening and emotional responding. People choose to
listen to music because of the way it makes them feel (e.g., Juslin & Va¨stfja¨ll, 2008; Lonsdale
& North, 2011; Sloboda, 1992). Calming music changes cortisol levels (Flaten, Asli, &
Simonsen, 2006) and blood pressure (Triller, Erzen, Dub, Petrinic-Primozic & Kosnik, 2006),
and listening to music reduces anxiety in medical contexts (Bare & Dundes, 2004; Cooke,
Chaboyer, Schluter, & Hiratos, 2005; Pelletier, 2004; Weeks & Nilsson, 2010). Music listening
also facilitates falling asleep (Field, 1999), and it increases levels of sedation for patients in
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intensive care (Dijkstra, Gamel, van der Bijl, Bots, & Kesecioglu, 2010). Listening to one’s
preferred music can even reduce perceived pain levels after surgery (Ebneshahidi & Mohseni,
2008). Music’s ability to calm the listener is one reason why music therapy often yields positive
effects (Gold, Voracek & Wigram, 2004). Thus, it is clear that music listening can change one’s
emotional state.
There is also an abundance of evidence that feelings influence cognitive performance
(e.g., Cassady, Mohammed, & Mathieu, 2004; Isen & Labroo, 2003, O’Hanlon, 1981). Isen
(2009) illustrated how positive affect enhances cognitive abilities, including decision making,
problem solving, social interaction, and thought processes in general. Positive affect is associated
with increases in dopamine levels, which may improve cognitive flexibility (Ashby, Isen, &
Turken, 1999). Effects of emotional state on cognition are evident even with small increases in
positive affect, such as those that occur when receiving a small gift or watching a comic film.
For example, in a problem-solving task that required participants to15solve Duncker’s (1945)
candle problem, participants who saw a brief comic film just before performed better than
control participants (Isen, Daubman, & Nowicki, 1987). Similarly, participants who were given a
small bag of candy performed better than controls on a test of remote associates (Isen et al.,
1987). Moreover, negative affect (e.g., boredom) impairs cognitive performance (Cassady et al.,
2004; O’Hanlon, 1981). Thus, links between arousal and/or mood and cognitive performance are
also well established.
In the first of a series of studies, Nantais and Schellenberg (1999) had participants
complete one of two sets of PF&C items on two different visits to the laboratory, once after
listening to Mozart (K. 448) for 10 minutes and once after sitting in silence. The order of the
conditions (Mozart then silence or silence then Mozart) and the two sets of PF&C items was
counterbalanced, with an equal number of participants in each of the four cells. PF&C
performance was better after listening to Mozart than after sitting in silence, thus replicating the
Mozart effect. This result was not surprising because the control condition involved sitting in
silence while staring at a computer monitor for 10 minutes, which was unlikely to put
participants in an optimal state of mind for any sort of task. A separate group of participants was
tested identically but the Mozart music was replaced with a piece composed by Schubert from
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the same CD, performed by the same pianists with the same production values. For these
participants, a Schubert effect (i.e., better PF&C performance after listening to Schubert than
sitting in silence) was evident and similar in magnitude to the Mozart effect. Again, adverse
aspects of the control condition virtually guaranteed the outcome. For a third group of
participants, Nantais and Schellenberg (1999) used the same experimental design but they
compared PF&C performance after listening to Mozart or a narrated story written by Stephen
King. The story was chosen because it was an auditory stimulus that changed over time (like the
Mozart piece) and it was likely to be as enjoyable as listening to Mozart for a sample of college
freshmen. Accordingly, the authors predicted that both Mozart and King should enhance
cognitive performance equally, and this prediction was confirmed. After completing the
experiment, participants were asked which listening experience they preferred. Approximately
half preferred the music; the other half preferred the story. When the data were reanalyzed as a
function of preference and condition, performance was better in the preferred than in the
nonpreferred conditions. In other words, there was a Mozart effect for participants who preferred
the music, but a Stephen King effect for participants who preferred the story.
Thompson et al. (2001) used the same basic design. Each participant completed a version
of the PF&C task after listening to music and sitting in silence. The music was the same Mozart
piece used earlier (K. 448) for half of the participants, and Albinoni’s Adagio for the other half.
The Adagio is a classic example of sadsounding music, written in a minor key with a slow
tempo. Measures of arousal and mood were administered before and after the listening
experiences. The hypotheses were that (1) there would be no Albinoni effect because the piece
sounds so somber, (2) a Mozart effect would once again be evident (the first movement is happysounding with a fast tempo and in a major key), and (3) the advantage for Mozart over silence
would be eliminated after controlling for changes in arousal or mood. The results were consistent
with these predictions. Because the Albinoni piece is relatively well known and considered to be
a quintessential piece of sad-sounding music, however, it could have evoked particular
associations with sad events, such that these associations rather than the music were the source of
the null effect.
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Accordingly, Husain et al. (2002) conducted an additional experiment in which they
manipulated the tempo and mode of the same piece (Mozart K. 448) using MIDI. As noted,
happy-sounding music tends to be fast-tempo and in a major key, whereas sad-sounding music
tends to be slow and minor (Hunter & Schellenberg, 2010). Each participant completed the
PF&C task after listening to one version of the Mozart piece: fast/major, slow/major, fast/minor,
or slow/minor. Arousal and mood were measured before and after listening.
PF&C performance was better after the fast and major-key versions. Arousal levels were
improved after hearing the fast versions, whereas moods were improved after hearing the majorkey versions. As predicted, changes in arousal and mood accounted for the bulk of the variance
in PF&C scores.
If effects of music on cognition are determined by music’s emotional impact, then the
type of music that is the most effective in this regard should depend critically on the particular
sample of listeners. In the next study (Schellenberg & Hallam, 2005), more than 8,000 10- and
11-year-olds living in the United Kingdom were recruited from approximately 200 schools to
participate in a study of the Mozart effect, which was coordinated by the British Broadcasting
Corporation (BBC). At each school, students were assigned to one of three rooms at exactly the
same time. In one room, they heard pop music on BBC Radio 1, including a song by the band
Blur. In a second room, they heard a Mozart piece over BBC Radio 3. In the third room, they
listened to Susan Hallam discuss the experiment on BBC Radio 5. After listening to the radio,
they completed two tests of spatial abilities. According to the arousal and mood hypothesis, the
pop songs should be the most likely to put the children in an optimal emotional state for the
cognitive tests. On the simpler of the two spatial tests, no differences among groups emerged. On
the more difficult test, however, performance was indeed best for the children who heard pop
songs. In other words, a Blur effect was evident for 10- and 11-year-olds living in the United
Kingdom.
Taking this approach even further, Schellenberg et al. (2007) tested the creative abilities
of 5-year-old Japanese children. Recall that the arousal and mood hypothesis does not give
special status to music listening. Any experience that changes the participant’s emotional state
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can influence cognitive performance. Moreover, the hypothesis extends beyond spatial abilities
to cognitive performance construed broadly, including creativity, which is considered to be one
aspect of cognition (e.g., Sternberg, 2009). In an initial (baseline) session, children were given a
piece of paper and 18 crayons and asked to draw whatever they liked.
They subsequently made another drawing after a musical experience: listening to Mozart
(K. 448), Albinoni’s Adagio, or children’s playsongs, or singing children’s playsongs. The
hypothesis was that creativity would be enhanced after singing or listening to the18playsongs.
The dependent measures were drawing times and ratings made by adults about each child’s pair
of drawings in terms of creativity, energy, and technical proficiency. In line with predictions,
drawing times increased more from baseline in both playsong groups than in the Mozart and
Albinoni groups. Ratings of creativity, energy, and technical proficiency also increased relative
to baseline for children who heard or sang playsongs, but these ratings decreased for children
who heard Mozart or Albinoni. In short, a playsong effect was evident for Japanese 5-year-olds.
In another experiment that examined whether the Mozart effect extends beyond measures of
spatial ability, college freshmen were tested on measures of processing speed or working
memory after they heard Mozart or Albinoni (Schellenberg et al., 2007). Each student came to
the lab twice, both times completing one test after one listening experience. The order of the tests
and the musical pieces was counterbalanced. Arousal and mood were measured before and after
the music listening. At the first testing session, music listening led to inconsistent changes in
arousal and mood and there were no differences between conditions on either cognitive test. At
the second session, the data were consistent with predictions. Arousal increased after listening to
Mozart but decreased after listening to Albinoni; similarly, mood improved after listening to
Mozart but declined after listening to Albinoni. Although performance on both cognitive tests
was better after listening to Mozart, the comparison was significant only for the test of
processing speed. When these data are considered jointly with those from the British children
(Schellenberg & Hallam, 2005), it appears that effects of emotional state on cognition may
indeed be greater on some tasks (e.g., more difficult tests, tests of visuospatial abilities or
processing speed) than on others (e.g., easier tests, tests of working memory; see also Rauscher
et al., 1995; Steele, Ball, & Runk, 1997). In any event, there is no compelling evidence of a
special link between listening to Mozart (or to any Classical music) and visuospatial (or spatial18
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temporal) abilities. Rather, listening to music is an effective way to improve one’s emotional
state, and how one feels can influence cognitive performance quite generally.
As an aside, very few published studies have examined mathematical performance after
listening to music. Although there was improvement in one study from pretest to posttest on a
measure of mathematical ability, such improvement was similar whether participants listened to
Mozart, Bach, or ocean sounds in the interim (Bridgett & Cuevas, 2000). In another study
(Jausovec & Habe, 2003 ˇ), performance on a mathematical task was slightly (but not
significantly) worse after listening to Mozart than after sitting in silence.(Retrieved from
www.researchgate.net, February 28, 2020)
Background Music and Cognitive Abilities
The question of whether background music is able to enhance cognitive task performance
is of interest to scholars, educators, and stakeholders in business alike. Studies have shown that
background music can have beneficial, detrimental or no effects on cognitive task performance.
Extraversion—and its postulated underlying cause, cortical arousal—is regarded as an important
factor influencing the outcome of such studies. According to Eysenck's theory of personality,
extraverts' cortical arousal at rest is lower compared to that of introverts. Scholars have thus
hypothesized that extraverts should benefit from background music in cognitive tasks, whereas
introverts' performance should decline with music in the background. Reviewing studies that
have considered extraversion as a mediator of the effect of background music on cognitive task
performance, it is demonstrated that there is as much evidence in favor as there is against
Eysenck's theory of personality. Further, revisiting Eysenck's concept of cortical arousal—which
has traditionally been assessed by activity in the EEG alpha band—and reviewing literature on
the link between extraversion and cortical arousal, it is revealed that there is conflicting
evidence. Due to Eysenck's focus on alpha power, scholars have largely neglected higher
frequency bands in the EEG signal as indicators of cortical arousal. Based on recent findings, it
is suggested that beta power might not only be an indicator of alertness and attention but also a
predictor of cognitive task performance. In conclusion, it is proposed that focused music
listening prior to cognitive tasks might be a more efficient way to boost performance than
listening to background music during cognitive tasks.
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There has been a surge in commercial applications promising to improve their users'
concentration and focus by playing specifically designed music in the background. The basic
idea is simple: playing background music activates your brain and leads to better performance in
cognitive tasks. However, this idea comes with several issues. For example, even if music is
specifically designed to set free cognitive resources it is implausible that every person benefits in
the same manner in a cognitive task. A piece of music that has beneficial effects on cognitive
task performance for one individual may well have no effect, or even detrimental effects, for
another. Is searching for background music that enhances cognitive task performance therefore
chasing a red herring? Not necessarily, if—as a first step—we are able to identify and better
understand the neural underpinnings that enhance cognitive task performance in general. As a
second step, we may begin to ask what are the characteristics of the music needed to change an
individual's neural activation in a specific way. Since inter-individual differences play an
important role in this endeavor, the evidence in favor of, and against, Eysenck's theory of
personality will be reviewed before a new perspective is provided.
Although the effects of background music on cognitive task performance have been
studied by psychologists and educators for more than seventy years (Fendrick, 1937), no clear
pattern of results has emerged thus far. On the one hand, background music, in comparison with
silence, has been found to be beneficial for reading comprehension (Kiger, 1989), foreign
vocabulary learning (de Groot, 2006; Kang and Williamson, 2014), spatial and linguistic
processing (Angel et al., 2010), IQ tests (Cockerton et al., 1997), spatial and numerical reasoning
(Miller and Schyb, 1989), visual search tasks (Crust et al., 2004), and students' achievement in a
psychology class (Schreiber, 1988). On the other hand, background music, compared to silence,
has been found to impair cognitive performance, showing detrimental effects for reading
comprehension (Fendrick, 1937; Henderson et al., 1945; Etaugh and Ptasnik, 1982; Furnham and
Bradley, 1997; Avila et al., 2012; Thompson et al., 2012), verbal memory (Iwanaga and Ito,
2002; Woo and Kanachi, 2005; Cassidy and MacDonald, 2007), visual memory (Furnham and
Bradley, 1997), serial recall of digits (Nittono, 1997; Alley and Greene, 2008), Stroop tasks
(Parente, 1976; Cassidy and MacDonald, 2007), writing fluency (Ransdell and Gilroy, 2001),
and logical reasoning and associative learning (Crawford and Strapp, 1994). Yet other
investigations revealed that background music had no significant impact on cognitive task
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performance whatsoever (Henderson et al., 1945; Freeburne and Fleischer, 1952; Furnham and
Allass, 1999; Pool et al., 2003; Alley and Greene, 2008; Schlittmeier and Hellbrück, 2009;
Thompson et al., 2012). A recent meta-analysis on the effects of background music on adults'
cognitive, affective and behavioral responses seems to support the trend toward an overall null
effect (Kämpfe et al., 2011).
Without theory-driven research focused on inter-individual differences, these
contradictory findings are not surprising. To address this issue, many scholars have used
Eysenck's theory of personality (Eysenck, 1967) as a theoretical framework for their studies.
While there are several inter-individual differences that influence the effects of background
music on cognitive task performance—ranging from personality traits to musical taste and age—
one inter-individual difference that has been studied extensively is extraversion.
According to a particular aspect of Eysenck's theory of personality, extraversion can be
described and explained by the underlying cortical arousal. Extraverts are reported to have a
lower level of cortical arousal compared to introverts. Eysenck's theory therefore predicts that
introverts require little or no external stimulation to reach an optimal level of cognitive
performance, whereas extraverts require comparatively more external stimulation. External
stimulation exceeding the optimal threshold should lead to a decline in cognitive performance,
following the Yerkes-Dodson Law (Yerkes and Dodson, 1908). Thus, presented with moderate
to high levels of external stimulation should lead to a decline in introverts', but not extraverts',
cognitive performance.
Using background music as a source of external stimulation—which has been shown to
increase arousal in participants in several studies (Thompson et al., 2001; Jones et al., 2006;
Schellenberg et al., 2007)—researchers have empirically tested Eysenck's theory by investigating
intro-
and
extraverts'
performance
in
different
www.researchgate.net, February 28, 2020)
21
cognitive
tasks.(Retrieved
from
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The Relationship Between Music Training and Cognitive Performance
Associations between music training and general cognitive ability extend beyond
intelligence testing to grades in school. For example, Wetter, Koerner, and Schwaninger (2009)
examined the academic records of third- to sixth-grade Swiss children who either did or did not
take music lessons outside of school. Children with lessons had higher average grades even when
SES was held constant, and the advantage was evident across all school subjects except for
sports. Similarly general associations are evident in samples of students from the US. Fitzpatrick
(2006) examined performance on standardized tests of academic proficiency for more than
15,000 American high-school students, more than 900 of whom were registered in an
instrumental music course. The music and control groups were further subdivided into low- and
normal-SES groups. Fitzpatrick looked at performance in fourth, sixth, and ninth grades, before
the students opted to take a music course in high school. With differences in SES held constant,
the future instrumentalists outperformed the control group in every subject at each grade level.
These results confirm that high-functioning children are more likely than other children to take
music lessons, at least in high school. Other evidence implies that (1) positive associations
between taking music classes in school and performance on standardized tests are more likely
when the instruction is of particularly high quality (Johnson & Memmott, 2006), and (2)
replacing some standard academic classes with instrumental music lessons does not have a
negative impact on average grades in elementary school (Kvet, 1985). Gouzouasis, Guhn, and
Kishor (2007) examined performance on standardized tests of academic achievement among
150,000 Canadian 12th-grade students. The tests provided separate scores for mathematics,
English, and biology. Compared with other students, those who took music classes in 11th grade
had higher scores in mathematics and biology but not in English. Among the music students,
grades in 11th-year music courses were correlated positively with 12th-year standardized cores
for mathematics and biology, and weaker but still evident for English. By contrast, participation
in 11th-grade visual arts courses was not associated with standardized test scores in 12th grade.
These results confirm that high-functioning students are more likely than other students
to take high-school courses in music but not in visual arts, that taking music courses in high
school does not interfere with achievement in core academic subjects, and that students who do
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well in music classes tend to do well in other subjects. Similar findings in Schellenberg’s
(2006b) study revealed that among elementary-school children, as duration of training increased,
so did academic performance whether it was measured with actual grades on report cards or
performance on a standardized test, and even when SES and duration of nonmusical activities
were held constant. Even more provocative was the finding that school performance was
associated positively with duration of training when IQ was controlled. In other words, children
who took music lessons for years on end tended to be particularly good students. Duration of
playing music regularly in childhood also predicted high-school average when SES was
controlled. Finally, there is experimental evidence that 1 year of music training causes small
improvements in academic achievement (Schellenberg, 2004). The association between duration
of music training and general cognitive abilities suggests that professional musicians should be
geniuses. When highly trained individuals or professional musicians are compared with similarly
professional individuals without music training, however, the association often disappears. In
other words, although professional musicians may be above average in intelligence, people who
are highly trained in other disciplines perform at similar levels. For example, when members of a
symphony orchestra or students from university music departments were compared with students
from other disciplines (e.g., psychology, business) with a similar amount of education, the IQ
advantage for the music students vanished (Franklin et al., 2008; Helmbold et al., 2005) or
favored the students from the nonmusic disciplines (Brandler & Rammsayer, 2003). Similarly,
when the comparison involved highly trained versus untrained participants, differences in
intelligence fell short of statistical significance (Sluming et al., 2002) or disappeared altogether
(Bialystok & DePape, 2009; Patston & Tippett, 2011; Schellenberg & Moreno, 2010).
Thus, it appears that music training is associated positively with intelligence when
training is added as an activity on top of regular schooling. One problem with this interpretation
is that many of the null findings involved tests of fluid intelligence (Bialystok & DePape, 2009;
Brandler & Rammsayer, 2003; Franklin et al., 2008; Helmbold et al., 2005; Patston, Hogg, et al.,
2007; Patston & Tippett, 2011; Schellenberg & Moreno, 2010)—such as the Cattell Culture Fair
Test, Raven’s Progressive Matrices, or the Matrices subtest from the Wechsler tests—rather than
more comprehensive measures that include subtests of learned abilities (e.g., vocabulary).
Although the null findings might therefore be interpreted as showing that associations between
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music training and cognitive abilities do not extend to pure measures of fluid intelligence, other
researchers have reported such an association (Dege´, Kubicek, & Schwarzer, 2011; Forgeard,
Winner, et al., 2008; Hille et al., 2011; Portowitz et al., 2009; Thompson et al.,242004; Trimmer
& Cuddy, 2008). In short, the distinction between music training in childhood and whether one is
a “real musician” appears to be an important one, such that associations with general cognitive
ability are much more likely in the former case.(Retrieved from www.researchgate.net, February
28, 2020)
Theoretical Framework
The theoretical framework of this study discusses the effects of listening to music to the
cognitive performance of STEM students. There is a wide range of evidences concerning
associations between music and cognitive abilities. These are the Music Aptitude, Music
Training, Listening to Music and Background Music. Under the Music Aptitude are the concepts
of modularity and multiple intelligences theory. While under the Music Training, Listening to
Music and Background Music are the Music Learning Theory, Mozart effect and Eysenck’s
Theory, respectively. The effects of listening to music to the cognitive performance of STEM
students of Belison National School can be classified into the four evidences they are under.
They can identify their aspects of cognition all related to music with this evidences.
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Figure 1. Theoretical Framework
Music
Participating in Music
Classes
Music Aptitude
Concepts of
Modularity
Melomaniac
Music Training
Multiple
Intelligences
Theory
Listening to
Music
Music
Training
Theory
Mozart Effect
Cognitive Performance of STEM Students
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Background
Music
Eysenck’s
Theory
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Conceptual Framework
The conceptual framework of this study discusses the factors involved in the effects of
listening to music to the cognitive performance of STEM students of Belison National School. In
knowing the effects of listening to music, four factors are most notably interconnected with each
other that lead to enhance performance of students cognitive. These are the Environment,
Learner’s Working Memory Capacity, Personality of the Student and Exposure Effects. The first,
Environment, open environment sometimes is disturbed by talkers of traffics. Therefore, set of
headphones may come in handy if you are looking to avoid being distracted by any ambient
sounds. Learner’s Working Memory Capacity has a crucial influence on learning with seductive
details. The higher the learner’s working memory capacity, the better they learn with background
music. Personality of the students is also a factor because students prefer styles of music are
consistent with their personalities. For instance, people who have a need for creative and
intellectual stimulation prefer unconventional and complex music styles. Exposure Effects, on
the other hand, shape our musical preferences. Repeated exposures can be considered as a form
of classical conditioning that can increase liking of stimuli through a process of conditioning. All
this factors are important, and with each individual, they vary very significantly.
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Figure 2. Conceptual Framework
Listening to Music
Factors
Environment
Personality of the
Students
Exposure Effects
Learner’s Working
Memory Capacity
Cognitive Performance of STEM Students
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CHAPTER III
Method
Chapter 3 includes four parts: Purpose of the Study and Research Design, Respondents,
Instrument, and Data Collection.
Part One, Purpose of the Study and Research Design, presents the reasons on why how
the study was conducted.
Part Two, Respondents, presents the participants in the study and how they were chosen.
Part Three, Instruments, describes the number of items and structure of questions.
Part Four, Data Collection, presents the procedures or steps in gathering the data needed
in this study.
Purpose of the Study
This study aims to Assess the Effects of Listening to Music to the Cognitive Performance
of Science, Technology, Engineering, Mathematics (STEM) Students.
Specifically, this sought to answer the following questions:
1. What are the Effects of Listening to Music to the Cognitive Performance of Students?
2. What is/are the students perceptions on the Effects of Listening to Music to the Cognitive
Performance of Students?
The descriptive analysis of this research was used in this study because the researchers
gave researcher-made questionnaires among the STEM students to answer for the study.
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Respondents
Respondents of this study were the STEM students of Belison National School.
Table 1
Entire Group
Category
F
%
A. Entire Group
30
100
 Males
15
50
 Females
15
50
B. Gender
Instrument
One set of questionnaire was used in gathering the data. These data were then used in
Assessing the Effects of Listening to Music to the Cognitive Performance of STEM students of
Belison National School.
Data Collection
The survey instrument used in this study was designed to Assess the Effects of Listening
to Music to the Cognitive Performance of STEM students of Belison National School.
A personal data sheet requested demographic data in addition to the responses to the survey
questions. The survey instruments were distributed to 30 STEM students.
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Chapter IV
Result and Discussion
This chapter deals with the results and discussion of the gathered data through the distributed
questionnaire. The aim of this research is to Assess the Effectiveness of Listening to Music to the
Cognitive Performance of STEM students of Belison National School (BNS).
Table 1 shows the number and percentage of the 30 male and female respondents of the
G12 STEM class.
Table 1
Demographic Profile
Entire Group
Respondents
30
Male
Female
n
%
n
%
15
50
15
50
As shown in table 1, out of 30 respondent both male and female has the same number and
percentage.
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Table 2 shows the result of the answer to Question No. 1.
Table 2
Music Listening
Question
Always
Often
Sometimes
Rarely
Never
How often do you listen
n
%
n
%
n
%
n
%
n
%
to music?
17
56.67
8
26.67
5
16.67
0
0
0
0
As shown in Table 2, 17 or 56.67% of all the respondents answered always when asked
on how often they listen to music, 8 or 26.67% answered often and 5 or 16.67% answered
sometimes. There are no answers for the rest of responses. This means that majority of the
respondents always listen to music.
Table 3 shows the result of the answer to Question No. 2.
Table 3
Studying with Music
Question
Very
Frequently
Occasionally
Rarely
Never
Frequently
Do you listen to music
n
%
n
%
n
%
n
%
n
%
when you study?
4
13.33
13
43.33
6
20
6
20
1
3.33
As shown in Table 3, 4 out of 30 or 13.33% of the respondents answered very frequently
when asked if they study while listening to music, 13 or 43.33% answered frequently, 6 or 20%
answered occasionally and rarely and 1 or 3.33% answered very rarely which means that STEM
students frequently listen to music while studying.
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Table 4 shows the result of the answer to Question No. 3.
Table 4
Memory Formation
Question
Do you agree that music
SA
A
U
D
SD
n
%
n
%
n
%
n
%
n
%
12
40
17
56.67
0
0
1
3.33
0
0
creates a positive mood
which indirectly boost
memory formation?
As shown in Table 4, 12 or 40% of the respondents strongly agrees that music creates a
positive mood which indirectly boost memory formation, 17 or 56.67% agrees, 1 or 3.33%
disagrees and none is undecided or strongly disagrees. This means that most of the respondents
agrees with the implication of the question.
Table 5 shows the result of the answer to Question No. 4.
Table 5
Music and Concentration
Question
Does listening to music
improve concentration?
SA
A
U
D
SD
n
%
n
%
n
%
n
%
n
%
4
13.33
12
40
11
36.67
3
10
0
0
As shown in Table 5, 4 or 13.33% of the respondents strongly agrees that music improves
concentration. Those who agrees are 12 or 40% , those who are undecided are 11 or 36.67% and
those who disagrees are 3 or 10%, and there is none who strongly disagrees.
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Table 6 shows the result of the answer to Question No. 5.
Table 6
Cognitive Performance
Question
Does listening to music
improve your cognitive
performance?
SA
A
U
D
SD
n
%
n
%
n
%
n
%
n
%
5
16.67
18
60
3
10
4
13.33
0
0
As shown in Table 6, 5 or 16.67% of the respondents strongly agrees that listening to
music improves your cognitive performance, 18 or 60% agrees, those who are undecided are 3 or
10%, 4 or 13.33% disagrees and none of them strongly disagrees.
Table 7 shows the result of the answer to Question No. 6.
Table 7
Beating Stress and Anxiety
Question
Can music satisfy your
inner mind to beat stress
and anxiety?
SA
A
U
D
SD
n
%
n
%
n
%
n
%
n
%
12
40
17
56.67
1
3.33
0
0
0
0
As shown in Table 7, 12 or 40% of the respondents strongly agrees that music can satisfy
inner mind to beat stress and anxiety, those who agrees are 17 or 56.67%, only 1 or 3.33% is
undecided and there is none who disagrees or strongly disagrees. Which means that most of the
respondents agrees to the implication of the question.
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Table 8 shows the result of the answer to Question No. 7.
Table 8
Effects of Music
Question
Do you agree that the
SA
A
U
D
SD
n
%
n
%
n
%
n
%
n
%
7
23.33
18
60
3
10
2
6.67
0
0
effects of listening to
music to the cognitive
performance of STEM
students vary
significantly with each
individual?
As shown in Table 8, 7 or 23.33% of the respondents strongly agrees that the effects of
listening to music to the cognitive performance of STEM students vary significantly with each
individual, 18 or 60% agrees, those who are undecided are 3 or 10%, only 2 or 6.67% disagrees
and none of the respondents strongly disagrees.
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Table 9 shows the result of the answer to Question No. 8.
Table 9
Mode of Studying
Question
Which do you prefer more?
Studying with
Studying
music
without music
Undecided
n
%
n
%
n
%
18
60
7
23.33
5
16.67
As shown in Table 9, 18 or 60% of the respondents prefer studying with music, those
who prefer studying without music are 7 or 23.33% and those who are undecided are 5 or
16.67%. Which means that majority of STEM students prefer studying with music.
Table 10 shows the result of the answer to Question No. 9.
Table 10
Studying with Music
Question
Soothing and
Loud and
relaxing music
rhythmic
Undecided
music
If you like studying with music, which do
n
%
n
%
n
%
you prefer to listen?
18
60
0
0
12
40
As shown in Table 10, 18 or 60% of the respondents prefer soothing and relaxing music,
none of the respondents prefer loud and rhythmic music and those who are undecided are 12 or
40%. Which means that majority of STEM students prefer soothing music.
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Table 11 shows the result of the answer to Question No. 10.
Table 11
Music Genre
Question
Classical
K-pop
Country
Rap
Pop
What genre of music
n
%
n
%
n
%
n
%
n
%
do you listen the most?
3
10
4
13.33
0
0
0
0
11
36.67
Rock
EDM
Techno
Hip-hop
R&B
Jazz
n
%
n
%
n
%
n
%
n
%
n
%
0
0
0
0
2
6.67
3
10
6
20
1
3.33
As shown in Table 11, 3 or 10% of the respondents listen to classical music the most, 4 or
13.33% listen to Kpop music the most, 11 or 36.67% listen to pop music the most, 2 or 6.67%
listen to techno music the most, 3 or 10% listen to hiphop music the most, 6 or 20% listen to
R&B music the most and only 1 or 3.33% listen to jazz music the most. There are no answers for
the rest of the other genres with implication to the question.
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Chapter V
Summary, Conclusions, and Recommendations
This chapter presents the summary of the research work undertaken, the conclusions drawn, and
the recommendation made as an outgrowth of this study entitled, Assessment on the Effects of
Listening to Music to the Cognitive Performance of Science, Technology, Engineering and
Mathematics (STEM) Students of Belison National School.
Summary
This study utilized the descriptive research design through survey with the use of
questionnaires. The respondents of the study was the G11 and G12 STEM students of Belison
National School of the school year 2020-2021. The researchers used questionnaire method to
analyze the results of the study.
More specifically, the researchers sought to answer the following:
1. What are the Effects of Listening to Music to the Cognitive Performance of STEM
students?
2. What is/are the student's perception to the Effects of Listening to Music to the Cognitive
Performance of STEM students?
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Findings
The findings of the study were the following:
1. In Table 2, 17 or 56.66% of all the respondents answered always when asked on how
often they listen to music, 8 or 26.66% answered often and 5 or 16.66% answered
sometimes. There are no answers for the rest of responses. This means that majority of
the respondents always listen to music.
2. In Table 3, 4 out of 30 or 13.33% of the respondents answered very frequently when
asked if they study while listening to music, 13 or 43.33% answered frequently, 6 or 20%
answered occasionally and rarely and 1 or 3.33% answered very rarely which means that
STEM students frequently listen to music while studying.
3. In Table 4, 12 or 40% of the respondents strongly agrees that music creates a positive
mood which indirectly boost memory formation, 17 or 56.66% agrees, 1 or 3.33%
disagrees and none is undecided or strongly disagrees. This means that most of the
respondents agrees with the implication of the question.
4. In Table 5, 4 or 13.33% of the respondents strongly agrees that music improves
concentration. Those who agrees are 12 or 40% , those who are undecided are 11 or
36.66% and those who disagrees are 3 or 10%, and there is none who strongly disagrees.
5. In Table 6, 5 or 16.66% of the respondents strongly agrees that listening to music
improves your cognitive performance, 18 or 60% agrees, those who are undecided are 3
or 10%, 4 or 13.33% disagrees and none of them strongly disagrees.
6. In Table 7, 12 or 40% of the respondents strongly agrees that music can satisfy inner
mind to beat stress and anxiety, those who agrees are 17 or 56.66%, only 1 or 3.33% is
undecided and there is none who disagrees or strongly disagrees. Which means that most
of the respondents agrees to the implication of the question.
7. In Table 8, 7 or 23.33% of the respondents strongly agrees that the effects of listening to
music to the cognitive performance of STEM students vary significantly with each
individual, 18 or 60% agrees, those who are undecided are 3 or 10%, only 2 or 6.66%
disagrees and none of the respondents strongly disagrees.
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8. In Table 9, 18 or 60% of the respondents prefer studying with music, those who prefer
studying without music are 7 or 23.33% and those who are undecided are 5 or 16.66%.
Which means that majority of STEM students prefer studying with music.
9. In Table 10, 18 or 60% of the respondents prefer soothing and relaxing music, none of
the respondents prefer loud and rhythmic music and those who are undecided are 12 or
40%. Which means that majority of STEM students prefer soothing music.
10. In Table 11, 3 or 10% of the respondents listen to classical music the most, 4 or 13.33%
listen to Kpop music the most, 11 or 36.66% listen to pop music the most, 2 or 6.66%
listen to techno music the most, 3 or 10% listen to hiphop music the most, 6 or 20% listen
to R&B music the most and only 1 or 3.33% listen to jazz music the most. There are no
answers for the rest of the other genres with implication to the question.
Conclusion
Music is a very significant part of our daily lives: the image of the quietly-focused student
isolating themselves into a personal study zone has led interest into whether listening to music
actually improves cognitive performance or not. In the STEM students 4 out of 30 or 13.33% of
the respondents answered very frequently when asked if they study while listening to music, 13
or 43.33% answered frequently, 6 or 20% answered occasionally and rarely and 1 or 3.33%
answered very frequently. Through this study, there is assessment in the effects of listening to
music to the cognitive performance of STEM students of Belison National School. In the end,
these preferences will serve as guides to students, and it is up to them to decide whether to listen
to music while studying or not.
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Recommendation
1. The students should recognize the effects of listening to music in relation to their
cognitive performance.
2. The teachers should be able to understand the effects of listening to music to the
cognitive performance of students and encourage them to listen to different genres of
music.
3. The administrators should support the school in implementing some of the activities
where students can widen their knowledge through listening to music.
4. Parents should be aware of the importance of listening to music in the learning of their
children.
5. For future researchers, the results of this study can be a source of reference should they
decide to conduct their research of the same topic.
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ACKNOWLEDGEMENT
The researchers would like to extend their profound and genuine gratitude to the
following persons who have shared their knowledge, assistance, time, resources for the
completion of the study.
To the researcher’s parents.
To Mr. Albert Morillo, for being an understanding adviser for the subject Research
Report and for helping in this study and sharing his time, intelligent advises, suggestions,
recommendations, and keeping us on the right track until the study is finished.
And above all, to God Almighty, who gave the wisdom, strength and perseverance to
complete this study.
The Researchers
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REFERENCES
www.independent.co.uk
www.ncbi.nlm.nih.gov
www.frontiersin.org
www.google.com/amp/syncproject.co/blog
https://www.britanica.com
http://www.sciencedirect.com
www.researchgate.net
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