Classroom Research Project/ Paper C&I... · 2015. 4. 15. · Running Head: PREFERENTIAL MUSIC AND...

Running Head: PREFERENTIAL MUSIC AND READING COMPREHENSION 1

Assignment

LIT 530 – Seminar in Reading Research

Classroom Research Project/ Paper The final paper for the course consists of a classroom

research project on a topic of your own personal and professional interest (20-25 pages; 20

scholarly citations). The traditional way to do research and “write it up” is as follows: introduce

your topic, its significance to the field, frame your own problem or question(s) in relation to the

topic, discuss related literature and describe your methodology and discuss the outcomes and

implications of your project. We will take time to acknowledge, critique and challenge this very

linear process of research. You will be writing this paper in stages throughout course and

receiving much feedback and support from myself and from your peers.

The Effects of Preferential Music Listening on Adolescent Reading Comprehension

Travis O. Knight

SUNY Oswego

PREFERENTIAL MUSIC AND READING COMPREHENSION 2

Abstract

This purpose of this study was to examine the effect personal electronic use may have on

teenaged readers’ comprehension of level-appropriate texts. At play are two major research

questions: whether the effect of personal electronic use for music listening during reading is

positive or negative, and whether or not their use is more pronounced in students with lower

skills. An experiment involving four participants from two school districts in Central and

Western New York State was conducted, wherein the participants completed a battery of

readings from the Qualitative Reading Inventory 5 (Leslie & Caldwell, 2010) with and without

the use of their preferred personal music player and music selection.The results of the study

showed that adolescent reading comprehension is strongly and negatively impacted by the

presence of preferential music.

Keywords: preferential music, reading comprehension, adolescent, attention


The Effects of Preferential Music Listening on Adolescent Reading Comprehension

As a young teacher, I’ve never worked in a classroom where the emission of robotic

noises from my students’ pants or backpacks was unusual. Interruptions caused by the odd

tweets, chimes, and discordant fragments of popular songs that make up their ringtones are an

every-day part of the substitute teaching routine. So too is the automatic response: “Whoever’s

phone that is, silence it now, please and thank you.”

The ranks of students, teenaged and younger, who own and bring their cell phones to

school has been swelling since their acceptance into mainstream culture. What was once a

strange exception--a student with a phone--has become a de facto norm. In fact, recent research

suggest that upwards of 78% of American children between ages 12 and 17 own their own cell

phone (Madden et al., 2013, p. 2). Of those children, nearly half own smartphones, most of

which are capable of playing and recording sound, video, and accessing the Internet. With so

many teens touting electronic devices for personal use, it’s not a surprise that they have made

their way into classrooms en masse, bidden or otherwise.

Generally, student cell phones do not intrude too often on classroom proceedings, but

their presence is felt nonetheless. A lingering, constant distraction, drawing students gazes

towards the device clutched defensively at their bellybutton, rather than on instruction or

demonstration. Students with phones are often prone to navel-staring, playing with phone cases,

or trying to sneak an earbud in when they think I’m not watching. Anecdotally, these behaviors

appear more often in the high schools I serve than in the middle schools, but there is a certain

ubiquity to the behavioral patterns and reaction that should be noted.

Correspondingly, the number of students requesting to actually use their phone in class,

often as a music player, seems to be increasing. Students may desire to fill the quiet of a


classroom as they work, or else to drown out the coughs, desk squeaks, and pencil-scratching

with something more to their liking. And they listen to their music whenever they like at home;

why shouldn’t they have access to their music library in school, too? However, despite their

passionate argument for free access to their technology, the district I work for expressly forbids

electronics use and requires that all devices and/or phones to be turned off and stored in student

lockers before first bell. Teachers are tasked with confiscating phones, which are to be turned

over only to a parent, who must appear in person to retrieve the device. Yet, it is still ordinary to

see students with their earbud-style headphones plugged in as they pass from class to class, or

during independent work.

I want to do right by the students and teachers I serve, so when asked whether or not they

can listen to their music players, I hesitate. I am concerned, initially, that students will be

distracted by their music, but at the same time, if music encourages them to work and study,

perhaps, in the interest of learning, I ought to allow them to use their devices. But even if they

are in fact doing more work, should the actual learning be deleteriously affected by the music,

then perhaps to allow it is a poor policy after all.

These are the thoughts that tug and war whenever permission to “plug in and tune out” is

requested by a student. Typically I am forced to make a gut decision, making a feeble attempt to

judge the assignment against their demonstrated skill, weighing the class chemistry against their

attentiveness, known classroom policies, and a dozen other invisible variables. And I never feel

that I’ve made the right decision.

It is this experience which informs the motivation of this study, which poses as its central

question, “What effect, if any, does listening to preferential music have on reading

comprehension among adolescents?” After plying the existing research, I proceeded to design


and perform a quantitative experiment based on the models I found in the literature, and to

collect comparative, qualitative data about student reading comprehension levels with and

without music. However, the limited size of the student body required me to reach further for

data than I otherwise might have. With just four students, I must also work inductively, looking

for minute patterns to infer generalities from, just as I had worked deductively to arrive at a point

of experimentation. To that end, I also conducted interviews with subjects at various points in the

process to build out my data and enable deeper contextual analysis.

To speak broadly, I found that in general, the presence of music strongly impacted

reading rates and comprehension. However, as I present in my later discussion, the data is not

entirely consistent on either front, and my analysis seeks to combine my statistics with the

research on personality types, as well as with my knowledge of the subjects for a full-bodied

study.

Literature Review

The core question of the this study is to ascertain what, if any, effect preferential music

listening has on teenagers’ reading comprehension. Being a young teacher and a new researcher,

I wasn’t sure where to begin, or how to build my own experimental model. To guide my research

process, I broke down my focus question into smaller, more manageable research questions.

They are as follows:

i. What models of attention exist and are in use by psychology today? If there is a

prevailing model, what does it predict happens within readers’ brains as they decode a

text, and/or how does it account for distraction?


ii. What similar experimental studies exist, and what design/data analysis problems did they

run in to? Which of these can I incorporate or draw from for the present study?

iii. Within the extant studies on the effects of music on attention and reading comprehension,

can personality types account for some of the outlier data observed?

The information and data I gathered from these three focus questions inform my experimental

model, the subsequent data analysis, and more generally, my interactions with subject students.

A discussion of the research I found follows.

A. The Study of Attention and Its Limits

Although close study of attention dates back to at least the middle of the twentieth

century, the predominantly accepted model among attention researchers today is the limited

capacity model. This model of attention suggests that there is a finite capacity to the attentive

resources a person can use to process cognitive tasks (Kahneman, 1973; Tze, 2010). Essentially,

the more attention is dispersed or depleted, the lower their general performance. This is true for

children as well as adults; no one has an unlimited attention span. Kahneman’s theory suggests

that the more complex or demanding an activity one is asked to complete, the less mental energy

there is available for expense on new tasks or items.

There is ample experiential evidence to support the limited capacity model, but

increasingly there is neurological evidence that suggests that the brain’s posterior parietal cortex

may be largely responsible for the distribution and maintenance of attention. While studying the

similarities between visual and spatial short-term memory, Magin et al. (2009) found that the

more complex or demanding a task, the more susceptible subjects were to interference and decay

of performance, upholding the claims of the limited capacity theory of attention (p. 1796). They


observed these effects directly by using an fMRI machine to record subjects brain waves during

the a variety of cognitive tasks that included directed-attention and self-modulation. During more

challenging tasks, interference in attention could be observed as decays in performance: the more

demanding, the more deleterious the effect.

According to Tze (2010), there are two fundamental types of interference that can cause

an individual to fail at a task: capacity interference, and structural interference (p. 38). Capacity

interference occurs when an individual does not have a sufficient attention span to meet the

needs of two cognitive tasks. Structural interference, on the other hand, occurs when two

concurrent mental activities exceed the available attention resources. Though often unaware of it,

humans possess a number of strategies that free up those attentive resources when reading, or

performing memory-based tasks to prevent structural and capacity interference from

overwhelming their day to day lives.

One such strategy is what Rawson and Middleton (2009) call the “the automatization of

low-level tasks” (p. 368). They examine the switch from algorithmic, direct-attention processing

of text to a more automatic process that may help explain the growth of young readers from

letter-by-letter processing of text to memory-based processes, which automate much of the

immediate interfacing with a text. Working with Kahneman’s assumption that our attention

capacities are limited, Rawson and Middleton conclude that it is imperative that retrieval of

textual information (like word-form recognition) be automated and moved into subconscious

territory to enable high-level comprehension of infrequent and complex words. When retrieval is

slowed, either by a weakness with short term memory, or because of interference with the visual

short term memory [VSTM], the reading process becomes ‘more conscious,’ and comprehension

is predictably decayed as more resources are expended on decoding the text.


Supporting Kahneman’s model of limited attention capacity, Mitchell and Cusack (2007)

reason that the ability to mete out attention can be self-directed (p. 1788). That is to say, the

automaticity of text-parsing can be modulated according to the needs or desires of the reader.

They reason that if attention itself is a flexible resource, readers ought to be able to ‘tune’ their

attention to be either highly focused, or widely distributed (pp. 1788-1789). While Mitchell and

Cusack conclude that attention is certainly more flexible and capable of being consciously meted

out, they caution that “Given the highly limited capacity of VSTM and of visuospatial attention,

the ability to manage these resources flexibly is crucial” (p. 1797). The implied follow-up is

obvious: exactly how capable are we of managing our attention resources?

It doesn’t look promising. For example, Choi (2008) found that “most children did not

show the ability to allocate attention preferentially to primary tasks” (p. 1042). Her study focused

on measuring children’s ability to modulate their attention in a variety of settings, alongside

several noise-based stimuli. Indeed, despite the direction to ignore sound-stimuli, the subjects in

her study appeared unable to do so. She reports that “Speech processing appeared to receive

preferential allocation regardless of priority instructions,” suggesting that we may be wired with

a bias towards information presented aurally. Though Choi’s results don’t support the efficacy of

self-direction with regards to attention management, they do support the limited capacity

model’s chief claim: humans only have so much attentive energy to deploy, and if some is being

unwittingly sapped to process phonological information, that leaves a reduced pool for other

work. This “reduced pool” effect has been observed and confirmed by a number of other studies,

which suggest that the brain becomes increasingly vulnerable to overstimulation as the demands

of a task become more strenuous (Bergen, 2005; Rey-Mermet & Meier, 2012).


Ideally, teachers ought to be assigning work within students’ zones of proximal

development [ZOPI], where they are challenged and attentive resources need to be most focused

on the task at hand. The research leads me to anticipate that music will almost always interfere

with reading comprehension, and slows or even halts the acquisition of new information,

particularly in children, whom the Choi suggests are universally less-flexible in their ability to

overcome the phonological intake bias.

B. Studies into Distraction and Reading Comprehension

Over the past ten years, there have been several interesting studies into the effects of

music on students and reading comprehension. Largely, these studies have similar aims to my

own, though they don’t focus on the effects of personal electronic use specifically. To anticipate,

researchers found by and large that music, in any form, almost always results in a neutral and/or

negative net effect on reading comprehension, with a few interesting caveats pertaining to

student strength and preference.

The first study I came across that aligned with my study’s objectives was Anderson and

Fuller’s (2010) study, “The Effect of Music on Reading Comprehension in Junior High School

Students.” Anderson and Fuller studied 334 7th and 8th grade students, with a 51-48 percent split

between male and female (p. 181). They administered the Gates-McGinitie Reading Test, fourth

edition, followed by a brief comprehension test, and a second section during which music was

played (p. 182). For this study, the Billboard Magazine’s Top 100 Hits were used, and speaking

broadly, students reported positive responses to the music. Across all groups, Anderson and

Fuller report that “the musical environment score was lower than the non-music environment

score,” with such significance that more than 75% of students tested did more poorly with music


playing than they did without (p. 183). Interestingly, Anderson and Fuller report a greater decline

in scores among females than males, leading them to conclude that a sensitivity difference may

exist between the genders.

In their conclusions, Anderson and Fuller raise the point that students who prefer to study

with music may be “so accustomed to studying with music that it does not occur to them that

they might comprehend better without the background distraction” (p. 184). They draw a final

conclusion that lyrical music and written text are competing stimuli, which echoes earlier

findings regarding the bias of phonologically-received information over visually-presented

information and the difficulties children have in navigating that bias (Choi, 2008, p. 1042). For

the small group of outliers, it is possible that alternative or unrealized compensating methods

have arisen that allow certain students to perform equally well with and without music, though

Anderson and Fuller come short of suggesting what those methods might be.

Similar conclusions were drawn by Roger Johansson (2011) in his examination of eye

movement during reading while listening to preferential music. Johansson and his research team

tasked 24 non-disabled university students with reading texts and then performing standard

comprehension measures in four different scenarios: silently, listening to recordings of cafe

background noise, listening to classical music, and listening to their preferred music via a stereo

(p. 339). While students read, their eye movements were recorded and examined with high-speed

cameras and computer equipment that allowed the team to analyze readers’ regressions,

saccades, and fixations in all four reading scenarios.

Johansson was surprised to find that there were no major changes in eye movement in

any of the four reading scenarios, in any of the readers (p. 349). While they expected there to be

a difference between first-and second-pass reading of the texts, with longer fixations on words


listening to non-preferred music, no such effect was observed. Nevertheless, Johansson reports

that the most notable finding from the scores was that “compared to reading in silence,

participants performed significantly worse when reading to the non-preferred music” (p. 348).

Similarly, there was no meaningful difference between reading in silence and reading with café

chatter or preferred music. By and large, the effect of music is either significantly negative, or

neutral, as reported by both the Anderson and Fuller and the Johansson studies.

The findings of all of these studies come to a head in W.F. Thompson’s (2010) frank

study, “Fast and loud background music disrupts student reading comprehension.” Bluntly,

Thompson reports that “music is most likely to disrupt reading comprehension when the music is

fast and loud” (p. 705). This is in line with Anderson & Fuller and Johansson's findings about the

effects of music on most readers. Given the nature of most popular music, it is not an

unreasonable expectation that that the music many children may choose would be both fast and

loud. Further, preference for quiet, slower music may help explain some of the aberrations

observed by Anderson and Fuller, in which some students performed consistently better on

standard reading measures when exposed to music.

Thompson’s study also falls in line with Kahneman’s limited capacity model of attention,

in that Choi tells us the brain is phonologically wired to bias its deployment of attentive

resources to process aural information over visual information. If students are performing

significantly worse while exposed to fast-paced, loud, and lyrical music, it is probably that the

presence of that music is causing a capacity interference. If that’s the case, and in light of the

studies I have gathered and presented, it bears without further parade that giving students

permission to listen to music--particularly loud, fast-paced music--is poor practice.


C. Role of Student Personality in Susceptibility to Distraction

During the course of my research, I began to wonder whether or not personality type

might play a role in susceptibility to disruption during reading. Surely, I thought, different types

of learners would be more or less influenced by the presence of music. Or, perhaps Gardner’s

(1983) theory of multiple intelligences might be able to predict who would and would not be

disrupted by music. This line of reasoning formed the basis for my third guiding question, and I

was able to locate a few studies that spoke specifically to this idea.

Madeline Doyle and Adrian Furnham’s study, “The distracting effects of music on the

cognitive test performance of creative and non-creative individuals” (2011) was a likely

candidate. Leading into their study, Doyle and Furnham examine the evidence that extroverts

and introverts might be affected by music differently. Earlier studies into personality differences

demonstrated that “introverts were more negatively, and extroverts more positively, affected by

the introduction of music into their work environment” (p. 2). They reason that introverts are

overwhelmed and overstimulated by the music, is that appeared to be unable to effectively

translate short-term visual stimuli to long-term memory compared to extroverted peers.

However, Doyle and Furnham wished to specify further than the introvert and extrovert

categories, opting to further the research by measuring the same effects on creative and non-

creative individuals.

However, after classifying a sample population of “creative and non-creative”

adolescents by testing them on three personality-based different measures, no evidence was

found to support the hypothesis that music might disrupt either the creative or non-creative group

any more than the other (p. 5). Although Doyle and Furnham noted that creative individuals

tended to be extroverted, and to listen to music, there wasn’t any meaningful difference between


creative/extrovert versus creative/introvert, and their non-creative counterparts. On this basis, the

hypothesis that creativity is more affected by music was rejected.

Adrian Furnham is also the author of several other studies into the intersection of

personality type and distractibility. I chose to follow up his work and identified a second work

that was directly relevant to the current study. His paper, “Musical distracters [sic]” (2007)

studied over a hundred children aged 11 and 12 to examine and identify what, if any, observable

correlations there were between introverts, extroverts, and neurotic personality types. I chose to

refer to his earlier study to make more sense of Doyle’s findings regarding the lack of correlation

between creative and non-creative individuals and musical distractibility. During my review of

his paper, I was surprised to find that the actual difference between extrovert and introvert

performance is not particularly significant, except in the presence of negatively and positively

affective music (p. 416).

To clarify, Furnham identifies that extroverts are more likely to perform comparatively

better in the presence of negatively or ambiguously affective (that is, non-preferential or

unfamiliar) music than are introverts, who are more likely to be more disrupted by positively

affective (or preferential/familiar) music. These findings “diametrically oppose” Furnham’s

original hypothesis that introverts, in general, would be consistently negatively affected by

music, while extroverts would be positively, or neutrally affected (p. 416). It suggests that not

only does personality predict the effect music will have on a student, but so does the type of

music. To a degree, these findings suggest that extroverts may be more capable of ‘tuning out’

music they don’t like or that may distract them, perhaps as side-effect of heightened sociality.

These studies (Doyle & Furnham, 2011; Furnham, 2007) do suggest that while there is a

minor difference between the effects music has on extroverts and introverts, creativity is


probably not among the traits that determines the degree to which music distracts an individual.

Their research does, however, support the previously discussed finding that students who study

with music tend to perform better with it, while those inclined to silence perform better without

music.

Methodology

In order to construct my study, I synthesized a model from those quantitative models I

found among the literature pertaining to attention and distraction testing (Anderson & Fuller,

2010; Johansson, 2011; Tze, 2008). Because of limitations on my sample population, I also

collected a number of quantitative data in the form of informal introductory interviews to aid in

making sense of my data. The compositing of quantitative and qualitative data help deepen my

study’s discussion and conclusions, as the nature of working with diverse and unique students

requires consideration of individuality over mere performance. Additionally, as discussed earlier,

it has been demonstrated that in some cases, individual preference and experiential history with

reading along to music may account for and help contextualize unexpected or outlying data.

With that in mind, I have included a breakdown of the participants and methodology that

governed my study.

A. Participants

For the purposes of this study, four adolescent, high-school level students participated in

standard reading assessments in controlled simulations of the classroom environment. To

anticipate, they completed several formal and informal interviews, and a series of standardized

reading assessments with and without music. However, when prompted, none of my students


elected to choose their own pseudonyms. Instead, I have chosen to refer to them by their first

initial. I have known all of these for many years. I have done my best to allow personal feeling to

color the following descriptions of the students, included for qualitative analysis. For reference,

the transcriptions of introductory interviews with students are included as Appendix D, attached

to this document.

Student D: Aged 16. Grade 11. White. Low-middle SES. Resident of East Syracuse, NY.

Student D, who achieves median grades at his public high school in the suburbs of Syracuse, is a

young man whom I have known for upwards of four years. He is a middle-achieving student,

regularly earning low-B and C marks in his high school classes. He expresses interest in pursuing

a career in the sciences. D lost both his parents at a young age, and suffers from depressive

disorders and emotional instability at times. Currently, he lives with his aunt and cousin. When

spoken directly to, he often becomes furtive. During the introductory interview, D told me that

he often listens to music at school, but not at home. When I followed that up, he explained, “I

guess it makes it more pleasant… I mean, I guess class is boring and quiet and music helps.”

Though he doesn’t specify in the interview why he chooses not to listen to music at home, D did

suggest that math might be a subject he would definitely prefer to study sans music. Per his test

results, D would appear to be a student whose reading comprehension is strongly disrupted by

the presence of music during reading.

Student L: Aged 15. Grade 10. Male. White. Low-SES. Resident of Buffalo, NY.

Student L and I have known each other since he was a baby. He is a top-mark achieving young

man, enrolled in a public high school in the suburbs of Buffalo, NY. Proficient in athletics and

academics alike, L proudly wears his hockey team letterman jacket with Science Olympiad and

Honor’s Society patches sewn on either arm. L lives in a distinctly low-SES home that has been


below the poverty line since he was an infant, due to a family business collapse. Despite this, L

is set on attending the local state college, the University of Buffalo, though he isn’t sure if he

wants to pursue music, or STEM. L lives in a house with his father, stepmother, and step-brother.

Despite the high noise threshold, L does not listen to music when he studied, but says that he

only reads while he studies “Because it makes it less boring.” I noted during our sessions that L

is a slower reader, not because of recognition errors, but because of how often he returns to

earlier sections of a text to re-read. When I asked him about this, he said, “I re-read the sections I

think will be important so I can remember them,” implying that L is reading with the task in

mind. This led to what seemed like inflated reading scores during testing, but paired with high

comprehension scores. Though the quality of answers was not measured statistically in this

exam, anecdotally L’s answers were much more comprehensive than other students’.

Student N: Aged 15. Grade 9. Male. White. Middle SES. Resident of Chittenango, NY.

Student N is a middle-achieving student with middle-grade scores. He attends a public high

school in the suburbs of Syracuse. Due to reading difficulties at a young age, as well as maturity

concerns, N was held back a year in elementary school to allow him to be more prepared for the

increasing rigor of higher grade levels, which seems to have worked. I have known N for over

five years. N is an active community member, engaging in Church and town functions with his

family. N lives with his father and mother, and his occasionally-visiting half-sisters. Both of his

parents work, and they occupy the middle-SES. When asked if he listens to music while he reads

or studies, N told me, “I don’t listen to music…. My mom won’t let me. I study in the dining

hall.” Given N’s history of struggles with academic work, and particularly reading in general,

that answer wasn’t particularly surprising. His father is dyslexic, and though N isn’t officially

diagnosed, both of his parents suspect that he might fall somewhere on that spectrum. Given the


results of his testing, N’s reading comprehension was demonstrably disrupted by the music he

chose to listen to.

Student T: Aged 17. Grade 11. Female. White. Middle-Low SES. Resident of East

Syracuse, NY. Student T is a struggling student who attends a public high school in the suburbs

of Syracuse, NY. She has a history of difficulties in school, including both emotional and

academic troubles. Student T struggles with debilitating anxiety, which is particularly

pronounced when she feels defeated by a challenging task. For this reason, she was held back a

year, and has regularly attended summer school and tutoring programs to help shore up her skills

in reading, math, and personal management. Student T has diagnosed deficits with short term

memory, and is serviced by an IEP in school to assist her in daily learning activities. Outside of

school, she participates in extracurricular sports, babysits, and is interested in pursuing a career

similar to her mother’s, as an x-ray technician. Student T lives with her mother and her cousin in

a middle-low SES home during the weeks, and with her father and stepmother on the weekends.

When asked if she listens to music when she reads or studies, T told me that, “sometimes I do

with the shuffle [her iPod device], but not usually.” She went on to explain that she felt classical

music might help her remember more information, and that she’s gotten into Chopin and Mozart,

using her father’s catalogue as a guide. Given the results of our testing, T is a student whose

comprehension is markedly affected by the presence of music while reading.

B. Testing Procedures

Testing on the four participants was carried out during several weekends across the

months of October and November in 2014. Testing dates were deliberately spread out to prevent

student burnout during the testing batteries. Each student was assessed alone, independently of


one another. The aggregate process was designed to assess their study preferences, word attack

skill, appropriate reading comprehension level, and at the end, their reflections on the process,

allowing me to analyze the qualitative data collected in interview and observation against the

statistical data collected through the administration of the Qualitative Reading Inventory 5.

The first part of the actual data-collection process was a ten-question survey administered

in person during the first session with each student, in which the subjects were asked a series of

questions about their reading and study habits, their music-listening habits, and their perceptions

of the efficacy of their study habits (see Appendix A for the Pre-Testing Survey questions).

Student answers were recorded as we spoke, and ample time was set aside to give students the

chance to explore both my subject and to think reflectively on their own habits through reactive

questioning.

On a weekend following the interview, students were invited to complete the QRI 5’s

word identification task. This portion consists of the students reading from the age-appropriate

word lists. I recorded their Total Automatic and Total Identified scores, and used these to

identify probable reading levels. In all cases except one, the word identification task led to an

appropriate appraisal of reading level, though this was not discovered until after the first testing

session.

I met again with them all in late October to administer the non-music reading portion of

the comprehension tasks (scores listed as SR in the data table, attached as Appendix A). This

consisted of two readings and their related comprehension measure. The texts were selected from

the QRI 5’s grade-appropriate texts. In all cases, students were tasked with one narrative-based

text and one expository-based text. Before they began each reading, I performed a series of pre-

reading comprehension and predictive questions to establish their familiarity with the subject at


hand. Then, as they read, I recorded their times, which are noted in Appendix B. After each

reading, students completed a series of ten-question comprehension question tasks. In all cases,

students tested into either the ‘instructional’ (target) level, or the ‘independent’ level, with the

exception of Student T.

During both of her non-music readings, Student T immediately tested into the

‘frustration’ level. Ideally, her decoding score should have predicted her ‘instructional’ scoring

level, which represents the Zone of Proximal Improvement in the QRI-5’s exam terminology.

This is where students are being appropriately challenged, but are not incapable of performing

the required task with minimal teacher support. As my study sought to simulate the classroom

environment where students would be allowed to listen to music during independent work time,

and where, theoretically, students are working within their ZoPI’s. However, the High School

level texts were not within Student T’s ZoPI. They were demonstrably too difficult for her to

decipher.

Accordingly, once I noticed the discrepancy, I adjusted her exam in order to prevent the

inflation of my data measuring the/any correlation between music and comprehension. One

possible take-away from this hitch may be that that engaging a too-challenging text may lead to

pronounced vulnerability to external disruption. However, I was unable to test this hypothesis,

because Student T’s anxiety became such that we had to take a break. I was not able to further

test her that day. We met again the next afternoon to complete the first portion.

On a subsequent weekend, each student was administered a similar series of reading

comprehension tasks, one narrative and one expository, set at the appropriate reading level for

each student. For this second battery, they were instructed to read while listening to music of

their choosing via a personal electronic device, such as a phone or an mp3 player, and with their


headphones in their ears. Selection of music and volume level was left up to the student, as the

study is intending to simulate the classroom environment, in which a student would self-select

anyhow. What they listened to was recorded after the testing was administered.

As with the first battery, students completed a pre-reading comprehension measure before

they read, and a ten-question comprehension measure afterwards. Their reading times were

recorded and are noted in Appendix B.

For each reading, both raw and composite (with look-backs) scores were recorded.

Students were also encouraged to predict the effect the music had on their listening

during the reading sessions, and to identify the music they listened to. That data is recorded in

Appendix D.

C. Post-Testing Data Analysis

Due to the nature of my study—that is, a quantitative study with a limited subject pool—I

desired to draw out as much data as possible from that which I collected. During my planning

phase, I felt it necessary to incorporate some qualitative research elements into my experimental

framework. These included the introductory interviews and observations taken during testing.

Since I know each of the individuals in my study personally, I was also able to bring to my

analysis that personal knowledge of who the individual is, and how they behave. By treating

each exposure I had to my subjects as a data-rich experience, I was essentially incorporating into

the present study aspects of conceptual grounded theory (Glaser, 2009; Evans, 2013).

On the quantitative side of my data analysis, I reviewed the individual QRI 5 student

profile sheets that I kept for each student. These serve as an index for raw and composite scores,

reading times, textual familiarity, and several other factors pertinent to assessing reading

comprehension and reading growth progress. These items sheets were synthesized into a matrix


that allowed me to compare and average scores and reading times, as well as to ensure the

appropriateness of each student’s leveled reading tasks. The matrix served as the foundational

artifact for analysis, since it allowed me to cross-reference the data for all participants of the

study.

Subject scores were then referenced against the data collecting before, during, and after

the testing as I sought to identify correlations and patterns within the data. Since the study has

few participants, the qualitative data strongly informed my interpretation of the data.

Results of the Study

The focus of this study was to inquire what, if any, effect preferential music had on

adolescent reading comprehension, and to judge therefore whether or not it was appropriate to

allow students to listen to music during independent work in the classroom. A wide selection of

research exists on the topic, and helped inform the structure of this study. After interviewing and

experimenting with subjects, student assessment data was compiled into a matrix that compared

student scoring on comprehension measures, as well as average reading time1. These data were

analyzed for statistical trends before being examined alongside qualitative data on each of the

students for a rounded analysis.

Student reading time averages was the first place I focused my attention to see whether or

not they were affected by music. Using the without-music reading time average as a base, with-

music averages were compared and found a mixed bag of results that did not seem to fall in line

with the predictions of existing research about the overtly disruptive nature of music. At a global

1 Because each text had a different total length, the QRI 5’s reading-time formula was employed, rather than a raw

comparison of scores. This formula “(word count * 60) / ___ seconds” informed my analysis. Scores within the

formula predicted number of words read per minute, overall, and allowed me to measure readers at different skill

levels and across disparate texts. The results are included in Appendix C.


level, words read per minute [WPM] actually increased with exposure to music: the average

WPM in silence was 185.5, whereas with music, the WPM grew to 203.3, resulting in a speed

increase of approximately 8%. That was an unexpected result, as most of the research that

informed this study predicted major disruption by music that would be observable from external

behaviors like reading speed and comprehension measure achievement.

On a student by student basis, however, the WPM issue is less clear. Several trends were

observed among the various types of texts, and scenarios that lend credence to the Furnham

hypothesis that introverts are more affected by music than extroverts. When the narrative-reading

WPM scores were examined, the data suggest that students tended to read slower with music on,

in all but one case (Student L). Students D, N, and T saw significant decreases of about 40 WPM

when exposed to music, whereas L increased his reading speed by 9 WPM. Note that L reports

never reading with music on. Assuming this is true, one mitigating factor might be his

extroversion and sociability.

For the other three participants, the loss in pace may reflect the necessary expense of

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Fig. 1. Narrative Pace: Silent vs. With Music

Silent Reading Reading with Music


more attentive resources on navigating the more structurally and linguistically-complex fiction

text, as opposed to the linear, logically arranged expository texts, as arranged in Figure 1. Note

that the slowdowns (excepting L’s score) are all closely in line with one another.

With expository texts, generally students read more quickly when exposed to music. A

range of reading rate increases were observed; Student D was the least-affected, with an increase

of only 30 WPM, while students N and T both increased by about 55 WPM; Student L increased

by nearly100 WPM, effectively doubling his pace compared against the initial (silent-reading)

expository text, as observed in Figure 2.

It appears that, if music has any effect on a student, the effect is profound, which is in

line with what previous studies found. Indeed, though preferential music appears to be almost

always damaging to reading comprehension, and in some circumstances to reading rate, the

research suggests that the best predictor of whether or not music will have a severe or minimal

effect on reading is the student’s personal experience studying or reading along to music. Those

most stronlgy affected by the presence of music—that is, those whose reading rate are the most

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Fig. 2. Expository Pace: Silent vs. With Music



impacted are the two who don’t study with music; students N and T. On the other hand, students

D and L both do study with music, and show the most gains in WPM while reading an expositive

text, suggesting that, at least on a surface-level, their reading rates were not actually impeded by

the music at all, likely because both students have become immured to studying with music.

Comprehension, however, is another matter. Here the numbers begin to tell a different

story. Previous researchers have observed a definitive trend between the presence of music and a

decay of performance on comprehension measures (Anderson, 2010; Bergen, 2005; Choi, 2008;

Doyle & Furnham, 2011; Furnham, 2007; Johansson, 2012; Rawson, 2009; Thompson, 2012;

Tze, 2010). This study upholds that body of research: in all but one instance, students performed

worse on both the narrative and expository comprehension measures than they did without music

at all. These data are visualized in Figures 3 and 4 (following page).

Speaking generally, students achieved between 80% and 90% on the initial (without

music) comprehension measures in both narrative and expository categories, meaning that they

are being tested at the appropriate level with the QRI 5 based on their word identification scores.

However, on same-level texts in the presence of music, comprehension measures dropped down

to the 60-70% range. That accounts for a range of comprehension loss of up to 30%—a

significant difference that contrasts against the apparent gains in average WPM while reading

expository texts, and seems more in line with the longer average reading times for narrative

texts. However, there does not appear to be a significant disruption difference between the

narrative and expository text types; they’re equally displaced by the music.

At the present time, not enough information was available to explode the data further, but

future analyses might search for trends in how well students perform on implicit and explicit

question types. Basic observational data suggests that explicit comprehension questions, that is,


the questions whose answers were directly represented in the texts, were more difficult for

students in the presence of music, but not enough data was collected to come to any solid

conclusions.


Discussion and Conclusion

Kahneman’s limited capacity theory of attention posits that when humans are

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Fig. 4. Narrative Comprehension: Silent vs.

With Music


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Fig. 3. Expository Comprehension: Silent vs. With Music



overstimulated, their attentive resources deplete quickly, and the quality of a performance can be

observed to decay correspondingly. Broadly speaking, the results of this study uphold the limited

capacity theory of intelligence, as well as the results of other researchers in this field. Based on

both the increase in narrative reading time and the general decrease in reading comprehension

scores in the with-music reading section of the student examinations, it is reasonable to conclude

that students splitting their attention between reading/studying and preferential music are unable

to effectively control their cognitive coordination, leading to what Tze (2008) called a “capacity

interference.” Whether or not they’re reading faster or slower along with music, the mere

presence of music is disruptive to their comprehension.

The core research question of this study asked whether or not it is good practice to allow

students to listen to their music (via smart phones or other electronics) while they complete

independent work in the classroom. Pursuant to my findings, I cannot condone allowing music—

especially preferential music, listened via headphones—during study time, as it is fundamentally

disruptive to comprehension. On top of the disruptive effects of music, headphones erect an extra

barrier between student and classroom/teacher that may exaggerate the effect further.

Additionally, it appears that in some cases music inflates the time it takes to complete a

text (especially narrative-based) reading. That extra time taken does not lend itself to greater

achievement on reading measures, which suggests that although students spend more time “in”

the text, they may not be attending directly to its contents, and therefore aren’t gleaning any

more from it than they would be without the music in the first place.

Thompson’s (2012) previous finding that fast and loud music is incredibly disruptive is

accepted by this study. In the cases of students N and D, who chose to listen to loud, lyric-filled

music during their readings, significant losses of comprehension were observed. Even in the case


of Student T and L, however, who chose quieter and slower-tempo music, reading

comprehension was still affected. Additionally, after review of subject personality types and

performance on the reading measures, both with and without music, I found little evidence to

support Doyle and Furnham’s (2011) proposition that extroverts are less affected by the presence

of music. Some trends in that direction are present—namely in the WPM scores—but within the

admittedly limited constraints of this study, personality differences do not appear to be a

particularly large contributing factor to the effect of music on adolescent reading comprehension.

All students appear to be affected in similar ways by their preferred music choices: namely,

negatively.

Suggestions for Future Study

The constraints on this study left me with several questions for further study. Primarily,

the difference in reading times between narrative and expository, with music playing, warrants

investigation. What, if any, reason is there that narrative reading time would increase when the

reader is exposed to music, while in the same situation expository text decreases? Could it be

some bias due to the structure of the narrative that requires closer attention to the language,

which in turn makes the reader more vulnerable to a capacity interference?

Second, the reading examination, which used the Qualitative Reading Inventory 5 as its

basis, only sheds light on the effect of music and reading comprehension in a traditional

narrative, as one would find in an ELA classroom, and a history-focused non-fiction text. What

effects, if any, would be observed within different domains of reading? The Common Core State

Standards require instructors to teach content area literacy more explicitly, and encourage an


increase in content area reading. Would preferential music have a measurable differential effect

on math or science-centric reading or studying?

Third, this study did not address writing as an area of inquiry. It remains open to measure

the effects of preferential music on student writing skills. During the introductory interviews,

few of my subjects espoused interest in listening to music when writing (or indeed, at having an

interest in writing at all).

Music and its effects on reading comprehension is an area still wide-open for exploration

and investigation. As electronics become increasingly commonplace in the American classroom,

and ever more integral to our students’ sense of identity, we must be vigilant in examining the

effects technology has on our teaching, and their learning. In the case of listening to music in the

classroom, based on the findings of this and other relevant studies, it is probably unwise to allow

the use of music players and other personal electronics in the classroom.


References

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High School Students. School Psychology Quarterly. doi:10.1037/a0021213

Bergen, L. (2005). How Attention Partitions Itself During Simultaneous Message Presentations.

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Choi, S., Lotto, A., Lewis, D., Hoover, B., & Stelmachowicz, P. (2008). Attentional Modulation

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Doyle, M., & Furnham, A. (2011). The distracting effects of music on the cognitive test

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http://groundedtheoryreview.com/2013/06/22/a-novice-researchers-first-walk-through-

the-maze-of-grounded-theory-rationalization-for-classical-grounded-theory/

Furnham, A., & Stephenson, R. (2007). Musical distracters, personality type and cognitive

performance in school children. Psychology of Music. doi:10.1177/0305735607072653

Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. New York: Basic

Books.

Glaser, B. (2007). All is Data. The Grounded Theory Review, 6(2), 1-22.

Glaser, B. (2009). The Novice GT Researcher. The Grounded Theory Review, 8(2), 1-22.


Johannson, R., Holmqvist, K., Mossberg, F., & Lindgren, M. (2012). Eye movements and

reading comprehension while listening to preferred and non-preferred study music.

Psychology of Music, 40(3), 339-356. doi:10.1177/0305735610387777

Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ: Prentice-Hall.

Kendall, J. (1999). Axial Coding and the Grounded Theory Controversy. Western Journal of

Nursing Research. doi:10.1177/019394599902100603

Leslie, L., & Caldwell, J. A. (2011). Qualitative reading inventory: 5. Boston, MA:

Pearson/Allyn & Bacon.

Madden, M., Lenhart, A., Duggan, M., Cortesi, S., & Gasser, U. (2013). Teens and Technology

2013. Retrieved from Pew Research Center website:

http://www.pewinternet.org/files/old-

media/Files/Reports/2013/PIP_TeensandTechnology2013.pdf

Mitchell, D. J., & Cusack, R. (2007). Flexible, Capacity-Limited Activity of Posterior Parietal

Cortex in Perceptual as well as Visual Short-Term Memory Tasks. Cerebral Cortex.

doi:10.1093/cercor/bhm205

Rawson, K. A., & Middleton, E. L. (2009). Memory-Based Processing as a Mechanism of

Automaticity in Text Comprehension. Journal of Experimental Psychology-learning

Memory and Cognition. doi:10.1037/a0014733

Rey-Mermet, A., & Meier, B. (2012). The Bivalency Effect: Evidence for Flexible Adjustment

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Performance. doi:10.1037/a0026024


Thompson, W. F., Schellenberg, E. G., & Letnic, A. K. (2012). Fast and loud background music

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Tze, P., & Chou, M. (2010). Attention drainage effect: How background music effects

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APPENDIX A - Reading Comprehension Score Matrix2

Student T N L D AVG

6th MS HS 6th MS HS 6th MS HS 6th MS HS

ID Auto 100 85 65 95 65 60 100 100 100 100 90 95

ID Total 100 90 75 100 85 65 100 100 100 100 100 100

SR #1

TYPE NR NR NR NR

COMP 90% 70% 80%

SR #2

TYPE EX EX EX EX

COMP 90% 80% N 85%

SR #3

TYPE NR NR NR NR

COMP 80% 80% 80%

SR #4

TYPE EX EX EX EX

COMP 90% 90% 90%

MR #1

TYPE NR NR NR NR

COMP 80% 80% 0.8

MR #2

TYPE EX EX EX

COMP 70% 60% 0.65

MR #3

TYPE NR NR NR NR

COMP 70% 50% 60%

MR #4

TYPE EX EX EX EX

COMP 60% 70% 65%

2 This matrix combines the various scores students achieved on the QRI 5’s comprehension measures that follow

each reading. Individual scores on each comprehension measure (without lookbacks) is recorded, and those scores

are used to average achievement on the far right. Not every student read each text. Students are grouped for ease of

reading and analyzing the spread-out data.


Key:

ID - Word Attack AVG - Average SR - Silent Reading COMP - Comprehension

MR - Music Reading EX - Expository NR - Narrative


APPENDIX B - Reading Rates and Averages Matrix3

Middle School Texts RS WC D L N T AVG NM AVG

WM AVG

Biddy Mason NM 745 258.3 171.9 215.1 185.4 203.2

Malcolm X WM 786 219.3 138.5 179.4

Immigration 1 NM 423 173.8 104 138.9

Immigration 2 WM 417 231.6 156.3 194

High School Texts

Ashes 1 NM 707 296.6 140 218.3

Ashes 2 WM 1224 260.4 149.9 205.1

WWI 1 NM 607 238 101.1 169.6

WWI 2 WM 536 268 201 234.5

Key:

RS - Reading Status NM - No Music WM - With Music WC - Word Count

NM AVG - No Music Average (net) WM AVG - With Music Average (net)

3 This matrix records the reading time data I recorded during reading sessions. During each reading, student times

were recorded. I later plugged them into the QRI 5’s reading rate formula to find student’s reading rates for each text

reading. Reading Rates were then recorded as averages (comparing net WITH MUSIC and net SILENT reading rate

averages.


APPENDIX C - Student Interviews

Interview # 1 - Student T

Me: Do you listen to music when you read or study?

T: No. Sometimes my classes play music, but not at home. Well, sometimes I guess.

Me: Interesting. And when you do listen to music, is it with or without headphones?

T: With. I would rather listen without, but I only have a [iPod] shuffle, so I have to use

headphones.

Me: I see. And what kinds of bands do you like to listen to?

T: Fall Out Boy, Paramour. Pretty much the same as D [laughs, D yells at her from the other

room to stop copying him].

Me: So, you said your classes listen to music in school. Can you tell me more about that?

T: Some of my teachers play music on the radio [stereo?]. They think it helps us concentrate

during quizzes and tests and whatever.

Me: What do you think? Do you think it helps?

T: Not really. I mean, it’s usually so quiet I can barely hear it, and sometimes kids sing along and

distract me. So not really.

Me: Okay, fair points. Why don’t you listen to music at home when you’re studying?

T: Well, I do sometimes with the Shuffle, but not usually. And I think the cords might get in the

way, like when I’m using big textbooks.

Me: Do you think it would help you retain more information?

T: Maybe. It depends on the music. Classical might help me more, maybe. I don’t know.

Mother-in-law: Her father got her into classical.

T: Oh, yeah. He listens to it all the time and now I am too. Chopin and Mozart and—a lot of

Chopin. Four Seasons.

Me: Are there any subjects you think you wouldn’t want to listen to music with, while you

study?

T: No, probably not. It might help with all subjects. Maybe not science. And definitely not when

I’m studying for a test, maybe like, when I do notes. But not science.


Me: Are you sure you don’t listen to music when you study? [I felt like I was getting conflicting

answers.

T: Nope! My resource teacher told me it’s a bad idea. I used to. Not anymore.

Mother-in-law: She really doesn’t. She does her homework with us in the den.

Me: Alright. Well, do you write with music? Like for school work, or stories you might write for

fun outside of school?

T: I don’t have to write a lot for school. They don’t assign stories very often. Sometimes poems.

But no, I like it quiet so I can focus on what I’m doing.

Interview # 2 - Student D


D: Yes, in school, but not at home.

Me: Ok, interesting. When you do listen to music, is it with or without headphones?

D: Uh [hesitation, looks at my mother-in-law] I guess with. iPod earbuds.

Me: Ah. And what bands do you like? What sorts of music?

D: I like alternative rock. Alt-rock. Bands like, I guess, Fall Out Boy and Paramour and that sort.

Me: And you said you listen to music in school, but not outside. Why might you listen to music

in school?

D: I guess it makes it more pleasant.

Me: What do you mean by that?

D: [Looks at my mother-in-law again; I sense he might be nervous talking in front of her, but

there wasn’t anywhere for her to go, really] I mean, I guess class is boring and quiet and music

helps.

Me: And why might you listen to music at home?

D: Laziness really, like at home every once in a while I listen to it.

Mother-in-law: He used to watch TV when he did his homework [D rolls his eyes]


D: Yeah, that’s true. I stopped because I couldn’t get my work done. I don’t do that anymore.

Me: Good strategy. Do you think, when you listen to music, that it helps you in school?

D: Yeah, I think it does.

Me: Do you think you remember more with or without music playing when you read and study?

D: I think you remember more.

Me: Are there any subjects you wouldn’t listen to music while you studied for?

D: Math [he answered immediately]. That’s about it.

Me: Okay, last question. Do you write with music?

D: Write? Like for school?

Me: Well, do you consider yourself a writer? Like, do you write stories, or poems, or songs even

when a teacher doesn’t assign them?

D: Oh, no. But I listen to music when I write for school, yeah. Pretty much the same bands.

Interview #3 - Student N


N: I don’t really read unless my mom makes me. But no I don’t listen to music. Sometimes when

I’m on the computer, and reading news or my forums. When I play Minecraft I listen to music.


N: Usually Pink Floyd of Led Zeppelin. I like some dubstep too.

Me: Do your classes listen to music in school? Do your teachers let you play music?

N: Yeah, a lot of them do. If they don’t have a stereo they let us listen to music on our phones or

whatever. Some of them don’t like it but they don’t stop us if it’s just worksheet stuff.

Me: What do you think? Do you think it helps?

N: Yeah, like, it relaxes me so that I can get through the words. Mrs. G tells me it’s not good, but

everything she says is personal opinion. [At this point, N lapses into a tirade about his teacher

and his argument with her over “Cask of Amontillado.”]


Me: Okay, let’s bring it back around. Do you listen to music when you’re studying?

N: I don’t study! [N forces laughter, then picks up and plays with his phone for a few seconds].

Uh, no. I guess I don’t. Mom won’t let me. I study in the dining room.

Me: Do you think it would help you retain more information?

N: Listening to Music? Uh. Maybe. It’s relaxing. I learn more when I’m relaxed I think.

Me: Do you feel there are any subjects that, if you were listening to music, might be too difficult

to study for?

N: I don’t think so. I mean, maybe with like, science, doing the equations and you forget to put

one in, but no, not really.



N: We don’t write very much in school. So no.

Interview #4 - Student L


L: I listen to music when I study, but not when I read.


L: All types, except metal. Like, I like Pink Floyd, and Pitbull, and Grateful Dead, and John

Williams, and Kid Cuddy. Like, everything. Except metal.

Me: Do your classes listen to music in school? Do your teachers let you play music?

L: Only in chemistry, when we’re working in the lab. Otherwise, none of hte other teachers let us

work with music in school.

Me: What do you think? Does it help in chemistry?

L: It helps drown out everybody else in chemistry. I only listen during work time, though.

Sometimes I listen in ELA when we do reading, but not often.

Me: Do you listen to music when you’re studying at home?

L: Yeah, because it makes it less boring. Like, it’s quiet and you want to fill it with noise, you

know?


Me: Do you think music would help you retain more information?

L: Listening to Music? Yeah, I’m used to it. And during chemistry class, we’re allowed to, but in

math we’re not. On chem tests I can remember more because I can remember the music I was

listening to, but on math, I can’t, and I don’t do as well.

Me: Do you feel there are any subjects that, if you were listening to music, might be too difficult

to study for?

L: Nope, I don’t think so.



L: No. Especially not when I write stories. It’s too distracting. Silence is a bit more boring but

when I write with music I don’t get anything done at all.


APPENDIX D - Student Music Choices

Student T chose to listen to her “Pandora” App on her smartphone. When I asked which

station she chose, T told me that she had chosen to listen to the Classical Music / Strings station.

• Music Effect Prediction: “The music made it harder, and it took me longer to read. I think

it won’t help.”

Student D chose to listen to an album on his smartphone. When I asked what he had chosen,

he told me “Fallout Boy’s new album.” It was loud enough that I could clearly hear the lyrics,

even when I was sitting across the room.

• Music Effect Prediction: “It got in the way of the Vietnam story, made me have to re-read

all of the dialogue.”

Student N chose to listen to Pink Floyd’s Dark Side of the Moon album on his smartphone.

During the intro to the song “Time,” particularly when it came on (I could, again, hear it from

where I was sitting across the room), N because visibly distressed because of the sudden volume

of the music. He removed a headphone and seemed to compromise for that, but did not ask me

whether he could pause, nor did he even move to adjust the volume.

• Music Effect Prediction: “I don’t know, it’s what I do in school sometimes, so probably

nothing.”

Student L chose to listen to Pink Floyd’s The Wall album on his smartphone. L’s volume was

very quiet.

• Music Effect Prediction: “I don’t think it did anything different to me. I mean, it’s Pink

Floyd. We listen to it all the time. I’m used to it.”

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