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Running Head: DIGITAL TEXTS 1
Digital Textbooks: The Effects of Input Modality and
Distraction on Student Learning at a Hispanic Serving Institution
Alyssa Denning and Brant Pewonka
Phoenix College
Daniel Grunspan
Arizona State University, Tempe Campus
Amy J. Marin
Phoenix College
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Abstract
We exposed college students at a Hispanic Serving Institution (HSI) to a passage from a digital
psychology textbook in which input modality (reading or listening) and level of distraction were
varied (N = 269; for 126 the first language spoken in the home was English and for 143 it was
not). Students either read the passage, listened to the passage, read and listened simultaneously,
listened while doodling (low distraction), listened while simulating a car ride (moderate
distraction), or listened while preparing a meal (high distraction). We tested recall through the
use of a multiple-choice test. Student retention differed based on input modality. Specifically,
conditions that removed text and replaced it with audio hindered performance. For example,
higher recall scores are shown for students in the conditions that involved reading the text, as
compared to the students in conditions that involved only listening (β = -2,483, p < 0.001).
Performance worsened as we added distractors. Finally, the results suggest that a students’
background with English is important for their retention of textbook information that is presented
in English. Specifically, it appears that having text is more important to students less proficient
in English than it is to more proficient English speakers. Our results suggest that reading digital
texts leads to better recall than simply listening to them, but distraction and early language
experience may be important factors to consider when determining recommendations for digital
textbook use.
Keywords: digital textbooks, distraction, Hispanic serving Institution, HSI, multitasking,
input modality
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Digital Textbooks: The Effects of Input Modality
and Distraction on Student Learning at a Hispanic Serving Institution
The availability of electronic versions of college textbooks is expanding rapidly and these
options are beginning to replace traditional textbooks (Young, 2013). One result of content
digitization is that students have new ways of accessing course material, such as listening to the
text using built-in audio features or e-book reader software (Joseph, 2015). A case in point, a
large community college in the southwest requires a digital-only textbook for their introductory
psychology courses. Regardless of individual preference, all students take in information in a
digital format either by reading from a computer screen, laptop, tablet, or cell phone, or by
selecting the built in audio feature button and listening to the text. End of semester survey data
collected from two thirds of those courses (N = 301) indicated that 71% of students report using
the audio feature at least once during the semester and 28% report listening to the text on either
their phone, tablet, laptop, or desktop as their primary method for taking in textbook information.
According to this survey, one reason that students gave for choosing to listen to their text,
as opposed to reading it, is their belief that they can successfully complete textbook assignments
while engaging in other daily tasks such as riding the bus, folding laundry, or cooking dinner.
The present study sought to examine the impact of various input modalities, that is different
perceptual channels (e.g. audio, text) commonly adopted by students using digital textbooks. Do
students have better memory and understanding for information they read, hear, or read and hear
together? And if students listen to their digital text, does it matter what they do while listening?
Answers to these questions have important implications for college students in terms of
recommended best practices for how to best interact with digital course materials.
Input Modalities
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One of the main goals of the present study was to compare the effectiveness of various
input modalities, specifically print and audio. Previous work on input modalities has gone in one
of two general directions. Some studies have compared digital textbooks with print presentations
of the same material. Several studies have shown that student learning outcomes such as
comprehension, recall, and grades are comparable between students assigned to electronic vs.
traditional print books (Johnson, 2013; Rockinson-Szapkiw, Courduff, & Bennett, 2013;
Roberts, 2017; Taylor, 2011). These findings may hold regardless of whether the electronic
material is presented on desktop computers, laptops, tablets, or other mobile devices (Lin, 2016).
Even comparing print and digital reading under active learning conditions that require the reader
to edit, recognize errors, and improve the quality of a passage, yield no significant differences in
student performance (Eden & Eshet-Alkalai, 2013). Others researchers have shown evidence
that learning may be hampered by electronic formats. Students take a lot longer to read ebooks
and are more likely to multitask than when reading traditional textbooks (Daniel & Woody,
2013). In addition, if students use an electronic version of an open educational resource (OER)
text they do not perform as well on exams as do students assigned to traditional textbooks in
either hard copy or electronic formats (Gurung, 2017).
The second line of research involves comparisons between listening and reading
modalities more broadly. This work yields inconsistent findings. Some studies indicate no
differences in comprehension of content between participants who have listened to or read the
same material (e.g. Moyer, 2011; Rogowsky, Calhoun, & Tallal, 2015). For example, in the
study by Rogowsky and colleagues, adults exposed to a chapter of a nonfiction book recalled the
same amount of information regardless of whether they listened to an audiobook, read from a
tablet, or did both simultaneously. In another study, there were no differences in children’s recall
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of news stories between print and audio versions (Molen & Voort, 2000). In contrast, other
researchers have reported a distinct advantage for reading print over listening (Dubois et al.,
2013). In a study by Daniel and Woody (2010), participants who listened to a podcast of an
article scored lower on a later quiz, than those who had read the same article. Similarly, college
students exposed to a TV science program recalled more details if they had read the transcript,
than if they had listened or watched the program (Furnham, Gunter, & Green, 1990). Thus far,
the literature comparing print and audio input modalities has not included the study of digital
textbooks in higher education. This is, in part, because the availability of audio features in digital
textbooks is new. While electronic textbooks have been around for several decades, early
versions of these books were static and did not include the type of multi-media interactive
content that is published today. The present study sought to fill this gap in the literature by
comparing print vs. audio modalities in the context of college digital textbooks.
Distraction
Students take in textbook information in a variety of settings, alone or with others, noisy
or quiet environments, and often with repeated task interruptions. Sometimes students are
distracted by external factors as they read. For example, listening to music or to a radio newscast
while reading text, has been found to be detrimental to reading comprehension (Hackshaw, 2001;
Hinrichs, 2014; Perham & Currie, 2014). Mobile phone distractions such as instant messaging
and texting can also interfere with reading efficiency (Chen & Yan, 2016). In general, although
students may enjoy the experience of engaging in more than one media activity at a time, media
multitasking has a negative effect on student performance (Van Norman, 2014). Internal
distractions, such as mind wandering, can also have a significant negative effect on reading
comprehension (McVay & Kane, 2012; Pachai et al., 2016). Mind wandering is especially
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frequent and destructive to comprehension when reading dry or difficult material, as is the case
with college textbooks (Feng, D’Mello & Graesser, 2013).
The negative impact of distraction is not limited to reading, but can also detract from
listening (Wammes et al., 2016). Listening to a textbook leaves the listener vulnerable to internal
distractions such as mind wandering, especially since the listener does not have to focus on
visual information. Sousa and colleagues (2013) measured mind wandering through a series of
self-reported thought probes and found that listening to a passage was associated with more mind
wandering and memory hindrance compared to participants who were asked to just read a
passage.
In addition to unintentional mind wandering, students who listen to their textbook may
purposefully engage in secondary tasks such as completing household chores, or may listen
while riding in or driving a vehicle. It is generally agreed that “multi-tasking” or other types of
cognitive distractions are detrimental to comprehension as they reduce the amount of working
memory available. According to the working memory model, our ability to form long term
memories relies on the processing and rehearsal of both auditory and visual information overseen
by a central executive responsible for the temporary management of information (Baddeley &
Hitch, 1974; Baddeley, 2003). Humans have a limited working memory capacity, such that too
much incoming information at one time, or any factors that distract a person from paying
attention, increases cognitive load. A higher cognitive load makes it more difficult to rehearse
and pay attention to information and makes learning less effective (Sweller, 1988).
When students attempt to perform two or more attention-demanding tasks at once they
must switch rapidly back and forth between tasks. This is mentally taxing and is associated with
cognitive costs. We would predict, therefore, that if students listen to their digital textbook while
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trying to complete other tasks, such as making dinner or commuting to school, student
comprehension of the text material will suffer.
Although most research highlights the detriments to performance when engaging in
secondary tasks, a few research studies report benefits to engaging in secondary tasks (e.g.
Roche et al., 2007). However, the type of secondary task appears to play a role in whether or not
it distracts from the primary task. For example, Andrade (2010) found a positive effect for
structured “doodling.” In his study, participants remembered more details of a recorded phone
message if they were asked to doodle (shade in printed shapes) while listening. Similar results
were later found in a study where participants doodled while listening to a boring story and then
completed a memory retrieval task (Singh & Kashyap, 2015). Researchers have noted, however,
that the type of doodling is critical to performance. In a study comparing recall after participants
listened to a fictional dialogue between two people, found that participants engaging in
structured doodling during the auditory playback performed significantly better than those
participants engaging in an unstructured doodling task (Boggs, Cohen, & Marchand, 2017). The
authors concluded that unstructured doodling requires a greater cognitive load. This occurs
because the doodler must decide what to doodle and is more likely to produce mental images and
engage in thoughts related to the image, as opposed to the structured doodler who has only a
small task requiring minimal attention.
A continual small load task, like structured doodling, may reduce the likelihood of
daydreaming. If one’s primary task is dull and susceptible to daydreaming, then a small load task
may actually be helpful. One of the goals of the present study was to examine several types of
secondary tasks of varying cognitive loads considered to be typical types of tasks students report
engaging in while listening to their textbook.
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Understudied Student Populations
The majority of psychology research participants have, and continue to be, white students
attending Universities (Henrich et al., 2010; Yancey et al., 2006). A lack of diversity in research
samples has been a criticism of psychological research (Sugden & Moulson, 2015). Despite
mandates by the National Institutes of Health requiring funded research to include a sizable
number of ethnic minorities, the proportion of minority participants in research samples remains
low (Chen et al., 2014). More recently, Scholarship of Teaching and Learning (SoTL) experts
have encouraged researchers to include demographic and cultural measures in their work
(McKinney, Atkinson, & Flockhart, 2017). Science educators are calling for an increase in the
number of educational research studies focusing on community college populations (Schinske et
al., 2017). This latter point is particularly important because there are strikingly few science
education research studies currently using community college samples despite the fact that nearly
half of all undergraduates attend community colleges and the majority of ethnic minority student
in higher education are enrolled in community colleges (American Association of Community
Colleges, 2016).
The present study was conducted at a Hispanic-serving institution (HSI), allowing us to
examine an intersection of two understudied research populations – Hispanics and community
college students. A federal designation of HSI is given if at least 25% of the full-time
undergraduate enrollment is made up of Hispanic students. These schools are fewer than 10% of
the total number of colleges and Universities in the U.S., but they enroll more than two-thirds of
all Hispanic undergraduates (HACU, 2017). The present study was conducted at a community
college in which more than half the enrolled students identify as Hispanic. Rather than viewing
ethnicity as a variable of noise, the authors assert that the inclusion of ethnicity as a central
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element of the present research allows for a deeper understanding of the phenomenon being
studied, which in this case, was the use of digital textbooks across a diverse population of
students.
Students at Hispanic-serving institutions have reported a variety of challenges to college
success and this includes issues related to campus climate, cultural factors, mentoring, and
language barriers (Arbelo-Marrero & Milacci, 2016; Medina & Posadas, 2012; Rood, 2009). Of
particular interest in the present study is the variable of language, as many Hispanic students are
reading academic textbooks in a language other than their native language. The mismatch
between ones first home language (L1) and the language of the required course materials may
have an impact on whether reading or listening to a textbook is preferable for learning.
There are distinct differences in how acoustic and printed information are processed and
these differences may be further influenced by language experiences. Although both modalities
involve decoding and comprehension, when reading print, the reader can use strategies such as
skimming to help get a sense of the big picture (Lund, 1991). With listening, there is less control
over the pace of the incoming information, thus there is no way to skim and the listener is at the
mercy of accents. For those learning English as a second language, there are a variety of
cognitive restraints during listening, including problems with word recognition, attentional
failure during processing, inefficient parsing, and failure to use mental representations (Goh,
2000). Non-native English speakers also direct proportionately more attention to the sounds of
the words and less attention to the meaning of the words when listening to information compared
to native speakers (Conrad, 1985). In addition, if a student takes in information by auditory
means, but is quizzed on that information in writing, the student has to switch modalities.
Switching modalities for non-native speakers may be more difficult than for native English
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speakers. We might predict, therefore, that students whose L1 is not English would have a
disproportionately larger disadvantage when it comes to listening to the textbook over reading
the textbook.
Study Goals
The purpose of this study was to explore the effectiveness of the different ways that
students take in textbook information (i.e. by listening or by reading) using an actual college
textbook and mimicking environmental conditions of typical use in a diverse community college
population. Based on prior research, we hypothesized that reading would be superior to listening.
In addition, students who use the audio feature of digital books often do so in the context of
engaging in other activities, so we investigated the role of distraction by asking students to either
doodle, sit through a simulated ride in a car, or prepare a meal while listening to their textbook.
We hypothesized that secondary tasks requiring greater cognitive load would negatively impact
performance. Because the study was conducted at an HSI, we also examined whether one’s L1
was an important moderator of the effects of input modality. We hypothesized that students
whose L1 was not English, would have even greater difficulty in recalling information that they
took in through listening than through reading.
Method
An Institutional Review Board reviewed and approved the current study to ensure
that study participants were treated ethically and were adequately protected.
Participants
Two-hundred and sixty-nine undergraduate students (121 males and 148 females)
completed the experiment. The participants were recruited from 8 first year psychology courses
at a large southwestern community college and received extra credit from their instructor for
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their participation. Participants ranged from 17 - 60 years of age (M = 21.77, SD = 6.11). This
community college is designated as an HSI (Hispanic Serving Institution) with 59% of the
participants identifying as Hispanic (N = 158), while 19% identified as White/Caucasian (N =
49), 11% as Black or African-American (N = 30), and the remaining 10% as either Native
American (N = 5), Asian/Pacific Islander (N = 9) or other (N = 17). Fifty-three percent of
participants reported that English was not the first language spoken in their home (N = 143).
Regarding educational experience and background, 96% of the participants reported less than 2
years of college, and 64% identified as first-generation students.
Materials
The Passage. All the participants were exposed to the same 700-word passage from the
digital introductory psychology text, Psychology (Marin & Hock, 2016), presented on REVEL
(an educational technology platform that allows for an immersive multimedia experience). The
passage covered educational content on four basic problem solving strategies – algorithms,
heuristics, incubation, and insight. For the conditions utilizing the REVEL audio feature, a male
voice spoke slowly and clearly, reading the 4 minutes and 32 second passage word for word.
This passage was a module not used by instructors at the present institution.
The Assessment Instrument. A 10 item multiple choice instrument was used to assess
student learning following participants’ exposure to the passage. Six of the items measured basic
comprehension of the problem-solving strategies covered in the passage. For example: “What
systematic problem-solving method guarantees a solution, provided that one exists?” (a – a
heuristic, b – an algorithm, c – a script, d – a mental set). Two of the items asked students to
apply what they’d learned. For example: “Talia is looking for her cat by methodically searching
each room, and then closing the door to that room after she leaves. She is using what type of
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problem solving strategy?” (a – a heuristic, b – an attribution, c – an algorithm, d – a hunch).
Two of the items required direct recall of specific information contained only in this passage.
Even if a student had prior knowledge of problem-solving strategies, they would not be able to
answer these questions without hearing this specific passage. For example: “In the passage, you
learned about a research study conducted with college students. What type of task did they use
with the students? (a – monopoly, b – a gambling game, c – a bowling game, d – a video game).
Procedures
Participants completed the experimental task in groups of 10 – 15 in a small classroom
setting. At the start of each experimental session, students completed a consent form and a
demographic profile. Participants were assigned a number based on their seat in the test room
and were asked to include this number on all testing materials, thereby avoiding the use of any
personally identifying information. All participants were given the same overview of the study:
Instructors are always looking for the best ways to help students take in and remember
information. The goal of this study is to explore a variety of study techniques and their
effect on learning. During the study, you may be asked to read, watch, or listen to some
information typical to that found in an introductory psychology textbook. You may also
be asked questions about what you’ve learned.
Participants were randomly assigned to one of the following six conditions:
Listening only. Participants listened to the audio passage.
Reading only. Participants were given 5 minutes to silently read the passage. They were
instructed to read at a typical pace and not rush through the material.
Listening while reading. Participants listened to the audio passage while simultaneously
reading along with the material.
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Listening while doodling. Participants listened to the audio passage while
simultaneously engaging in a structured doodling task similar to those used in prior research (see
Andrade, 2010; Boggs, Cohen, & Marchand, 2017; Singh & Kashyap, 2015). Participants were
given a sheet of paper with squares and instructed to shade in every other square. They were also
informed that their doodling skills would not be judged or evaluated and were told to doodle at a
natural pace.
Listening while simulating a car ride. Participants listened to the audio passage while
simultaneously watching a video on a classroom screen intended to simulate the experience of
riding in a car. The video was filmed along a local freeway with moderate levels of traffic in
daylight hours and was intended to mimic the driving conditions students might experience on
their way to the college. It was filmed from the passenger seat and oriented to capture the
forward view of the road out the front windshield. An experimenter instructed participants to
maintain their focus on the screen for the full 5 minutes while the audio passage played.
Listening while preparing food. Participants listened to the passage while
simultaneously setting a table and making a peanut butter and jelly sandwich. Participants were
given the rationale that most students who listen to their textbook are likely to engage in other
routine daily activities. The room was set up to provide each participant with their own table and
chairs. Participants were instructed to visit various stations that had been set up on the outside
edge of the room (paper plates, cups, forks, knives, napkins, bread, peanut butter, and jelly) and
were told to collect the items needed to prepare a place setting and make a sandwich. Participants
were informed that this was not a competitive activity and were instructed to complete the task at
a typical pace.
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After participants were exposed to the passage, they were given 8 miutes to answer the
assessment questions.
Results
To examine the impact of different input modalities on student information retention, we
performed a hierarchical regression analysis. The first model included only the input modality
with the Reading condition set as a reference and dummy variables for the other five conditions.
The second model included input modality and a dichotomous L1 status variable, with English
set as the reference. The final model included input modality, L1 status, and an interaction
between the dummy variables for input modality and L1 status. Partial F tests were used to
assess which of the nested models best fit the data.
A visualization of the residuals for each model showed a strong ceiling effect in
assessment scores. Ceiling effects occur when many respondents achieve the highest score
possible. In this case, many respondents answered all ten of the assessment questions correctly.
This can influence regression results, because the dependent variable lacks variation between
participants who scored a ten on the assessment. We determined whether the ceiling effect biased
our regression results by fitting censored regression models (Supplemental table 1) that model an
uncensored latent outcome in place of the censored outcomes (Henningsen, 2011). The results of
the censored regression indicated that our linear regression models were not strongly biased.
The mean score for all students on the test was relatively high (M= 6.80, SD = 2.71), with
visible differences across conditions and by L1 status (Figure 1). The number of participants in
each condition by L1 status is available in Supplemental table 2. A regression model with input
modality as the only independent variable explained 27.6% of the variance in post-test scores,
F(5, 263) = 20.07, p < 0.001, with students in the ‘Reading’ condition scoring higher on the post-
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test than students in all other input modality conditions other than Reading and Listening
condition, where there was no significant difference (Table 1). Adding student L1 status in the
second model increased the amount of variance explained to 30.2% F(6, 262) = 18.9, p < 0.001.
A partial F test between the first and second model indicates the second model significantly
reduces the residual sum of squares compared to the first model F(1, 262) = 9.72, p = 0.002,
indicating that L1 status has a significant effect on assessment scores. Students who come from
homes where English was not the primary language scored significantly lower on average than
those from homes where English was the primary language (β = -0.875, p = 0.002), controlling
for condition. The coefficients for input modalities were very similar to those indicated in the
first regression. Controlling for student L1 status, students in the Listening condition (β = -2.385,
p < 0.001), Listening while doodling condition (β = -1.559, p = 0.001), Listening in a simulated
car ride condition (β = -2.091, p < 0.001), and Listening while preparing food condition (β = -
4.197, p < 0.001) all scored significantly lower on the assessment compared to students in the
Reading condition. Students in the reading while listening condition did not significantly differ
on their assessment score from those in the Reading condition (β = 0.041, p = 0.937).
Adding an interaction between L1 and input modality in the third model increased the
amount of variance explained to 32.5% F(11, 257) = 11.28, p < 0.001. However, a partial F test
between these models indicates that the added interaction does not significantly reduce the
residual sum of squares F(5, 257) = 1.79, p = 0.116, indicating no improvement in model fit
with the added interaction. Thus, while input modality and the L1 status of the student are
significant predictors for performance on assessment, our data do not support that the
relationship between condition and assessment scores depends on the L1 status of the student.
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Figure 1: Mean comprehension scores and standard errors by students by input modality
condition and first home language. Scores were lower in distracted listening conditions and
among students whose first home language was not English.
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Table 1
Regression coefficients, standard errors, and p-values for three alternative models predicting
student test scores.
Summary of Hierarchical Regression Analysis Predicting Test Scores (N = 269)
Model 1
Model 2
Model 3
Variable
β
SE
p
β
SE
p
β
SE
p
Constant
8.585
0.363
<0.001
9.090
0.554
<0.001
8.333
1.130
<0.001
Condition
(Ref =
Reading)
Listening (6)
-
2.483
0.492
<0.001
-
2.385
0.484
<0.001
0.797
1.530
0.603
Reading
while
listening (5)
0.063
0.527
0.095
0.041
0.519
0.937
1.389
1.627
0.394
Listening
while
doodling (2)
-
1.548
0.482
0.001
-
1.559
0.474
0.001
1.148
1.493
0.442
Listening in
‘car’ (4)
-
2.194
0.499
<0.001
-
2.091
0.492
<0.001
-2.193
1.633
0.180
Listening
while
preparing
food (3)
-
4.228
0.510
<0.001
-
4.197
0.502
<0.001
-2.754
1.608
0.088
L1 (Ref =
English)
Other
-
0.875
0.281
0.002
0.166
0.709
0.814
Listening X
Other
-2.172
0.961
0.025
Reading while
listening X
Other
-0.889
1.030
0.389
Listening
while doodling
X Other
-1.796
0.941
0.057
Reading in
‘car’ X Other
-0.013
0.992
0.990
Listening
while
preparing food
X Other
-0.956
0.999
0.340
F
20.07***
8.479**
11.28***
R2
0.276
0.302
0.326
AIC
1225.19
1217.39
1218.19
Note. *p < 0.05. **p < 0.01. ***p<0.001.
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Discussion
The method by which textbook content is delivered is important to student retention of
information. Specifically, conditions that remove text and replace it with audio hinder
performance on a short assessment. This information is important for students to have, as many
may forgo print in favor of audio out of convenience, not knowing the costs associated with that
choice. If students do choose to listen to their text, our findings suggest that it should only be
done in conjunction with reading the print. This recommendation is consistent with previous
work that highlights the benefits of combining listening with reading (Gray, Davis, & Liu, 2011).
For example, synchronizing e-books and audio books for elementary students has been shown to
increase their reading motivation, reading stamina, and vocabulary development (Larson, 2015).
Performance also appears to decline as distractors are added. It’s safe to conclude that
distracted listening does not benefit anyone. All students should be encouraged to avoid
distraction while listening to digital texts, although convincing them to alter their study practices
may prove difficult. The desire to multitask is a powerful phenomenon, despite its negative
impact on productivity and learning. Terry and colleagues (2016) implemented an awareness-
based intervention in an educational setting with the hopes of encouraging attitudinal,
metacognitive, and behavioral shifts in students who engage in media multitasking (e.g. using
their electronics while reading their textbook). Unfortunately, greater awareness was ineffective
in shifting attitudes or changing actual behaviors. This may be because students reported their
media multitasking was largely due to feelings of dependence on, and anxiety at being without
their device, rather than a desire to multitask in order to get more accomplished. This is one
example of many illustrating that the motivation to multitask has social and emotional rewards
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and students are willing to sacrifice learning for these gains (Becker et al., 2013; Rosen et al.,
2013).
Conducting the research at a Hispanic Serving Institution allowed us to examine the role
of language as a variable. We found that Students’ background with English is important for
their retention of textbook information that is presented in English. Specifically, students whose
first language was English performed better, on average, than students who reported that their
first language was not English. While this is not surprising, it is important to consider for
pedagogical purposes. English language learners may need additional supports when it comes to
mastering textbook material. This finding is also important for research purposes in the
scholarship of teaching and learning– as the language background of a student is likely to be an
important variable to measure and consider in future work.
The interaction between input modality and L1 status did not significantly improve our
model fit at alpha=0.05. However, our results do suggest that there may be an important
relationship between L1 status and input modality. Specifically, it appears that having text may
be more important to students less proficient in English than it is to more proficient English
speakers. It is noteworthy that Test scores for L1-not English students were, on average, much
higher in the two conditions where text was available compared to all of the listening conditions,
even the two least distracting listening conditions (concentrated listening, and listening while
doodling). The size of the dropoff for these two conditions was not as large for L1-English
students. Our study was not designed to test this specific hypothesis (that of text vs. non-text),
but we feel that our results warrant a deeper investigation into whether there is a real effect that
our study lacked the power to investigate.
Limitations and Future Directions
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The current study sought to understand the effect of input modality on student retention
in a population of students at a large Hispanic serving community college. While the main
question of interest centered on the influence of input modality, the unique student population
required taking students’ home language into account to better model the data. However, this
came at the cost of reducing statistical power; once L1 status was considered, the number of
students in each condition (L1 status by input modality) ranged from 18 to 29. The small sample
size that emerges once the data are divided by condition and L1 status suggests that further work
testing the impacts of input modality on students of different linguistic backgrounds is warranted
to increase resolution and confidence on the findings presented here.
Although the present study involved students reading an actual textbook in a classroom
setting, there were many aspects of real life studying that could not be mimicked in a controlled
experiment. The present study was limited to the measurement of three specific forms of
distraction -- doodling, a simulated ride in a car, and preparing a meal. However, we did not
include multimedia forms of distraction which have been strongly linked to college student
behavior and performance (Bowman, Waite, & Levine, 2015). Multimedia use in which students
interact with smart devices while trying to attune to other media at the same time, is a common
form of multitasking. Some studies show that media multitasking occurs in over 70% of student
study sessions (Judd, 2013). Socially focused forms of distraction, such as using Twitter and
Facebook, are the most pervasive type of all multitasking behaviors for college students (Junco,
2013).
In addition, the present study measured only a single distraction for each participant. In
actual everyday use, it is unlikely that a student is distracted by only one secondary task while
taking in textbook information. Previous research suggests that the majority of students engage
DIGITAL TEXTS 21
in multiple distracting behaviors. In one study, students were observed for 3 hours while they
studied and completed homework (Calderwood, Ackerman, & Conklin, 2014). Engaging in
multiple distractions was found to be the norm, as the majority of students shifted between a
variety of behaviors including checking backpacks, using cell phones, watching videos, checking
computer e-mail, and leaving the room to use the bathroom or vending machine. In another
study, students preparing for an exam multitasked with an average of five different unrelated
digital medias (e.g. checking e-mails, searching the internet, using Facebook, etc.) during a study
session (Patterson, 2017). Future research targeting naturalistic study environments that allow
students to engage in multiple types of multi-tasking simultaneously would better match how
students interact with their course materials.
Along these lines, the design of the present study did not allow us to consider the variety
of individual differences in student personality and preferences for input modalities and
distraction when using with their textbook. There is prior research to suggest that personality
type can play a role in one’s ability to handle distraction in study situations (Ylias & Heaven,
2003). For example, creative individuals are less distracted by listening to music while studying
(Doyle & Furnham, 2012) and students high in sensation seeking are more likely to multitask
than students who score lower on this dimension (Chang, 2013). Experience may be important as
well, as first year college students tend to multitask significantly more than upper class students
(Delello, Reichard, & Mokhtari, 2016). Perhaps we would not have found the impairments in
performance to the extent that we did, if students had been allowed to choose their preferred
method of delivery as well as the nature and types of distractions.
The location of the present study at an HSI meant that nearly all the students whose L1
was not English had an L1 of Spanish. It is unclear whether the findings would be similar for
DIGITAL TEXTS 22
participants from different linguistic and cultural backgrounds. Our population is not a perfect
representation of the larger student population in higher education. International students make
up 44% of the total graduate student population in the U.S. (NCELA, 2017), and the first
language for the majority of these students is not Spanish, but Chinese. Future research, in
general, could benefit from closer examination of the unique contributions that cultural and
linguistic factors have on the digital textbook experience for college students in other contexts.
Finally, the measurement tool used in the present study was a short multiple choice
recognition task. In many educational settings, students are asked to complete assignments or
take tests that involve free recall. There is research to suggest that distraction has a different
impact on recognition vs. recall performance (Singh & Kashyap, 2015). In addition, in several
of our experimental conditions the test scores were very high, resulting is somewhat of a ceiling
effect. More extensive comprehension tests that are both longer and involve both recall and
recognition may be better ways to capture student learning. Future research capturing recall over
a longer time frame would also better mimic actual study conditions for college students, who
are often asked to recall information taken in days or weeks prior.
Conclusions
The results of this study indicate that the way a student takes in digital textbook
information, and what they do while they are taking in that information plays a role in recall.
However, specific recommendations for how students should engage with their digital text may
depend on the student’s prior language experiences. Textbook modality was particularly
important for students from homes where English was not the first language spoken. These
learners should prioritize reading their text over listening. Distraction when listening to the text
is important for all students to avoid, particularly if the secondary task requires a high level of
DIGITAL TEXTS 23
cognitive load. Few studies of digital textbook use in higher education have considered student
background as it pertains to language. More research with populations whose demographics are
representative of the larger U.S. population is needed as the number of English language learners
in the U.S. is increasing rapidly. It is estimated that by 2025, 1 in 4 students in the U.S. will be
an English language learner (NCELA, 2017). To best serve this diverse population of students,
we must first recognize the unique challenges students face and tailor pedagogical practices
based on empirical evidence.
DIGITAL TEXTS 24
References
Andrade, J. (2010). What does doodling do? Applied Cognitive Psychology, 24(1), 100-106.
American Association of Community Colleges (2016). Fast Facts.
www.aacc.nche.edu/AboutCC/Documents/AACCFactSheetsR2.pdf (accessed 2 July
2017).
Arbelo-Marrero, F., & Milacci, F. (2016). A phenomenological investigation of the academic
persistence of undergraduate hispanic nontraditional students at hispanic serving
institutions. Journal of Hispanic Higher Education, 15(1), 22-40.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1177/1538192715584192
Baddeley, A. (2003). Working memory: looking back and looking forward. Nature Reviews.
Neuroscience, 4(10), 829.
Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of learning and motivation,
8, 47-89.
Becker, M. W., Alzahabi, R., & Hopwood, C. J. (2013). Media multitasking is associated with
symptoms of depression and social anxiety. Cyberpsychology, Behavior, and Social
Networking, 16(2), 132-135.
Blackburn, A. M. (2013). A study of the relationship between code switching and the bilingual
advantage: Evidence that language use modulates neural indices of language processing
and cognitive control (Doctoral Dissertation). Retrieved from Dissertation Abstracts
International (DAI-B 75/04(E)).
Boggs, J. B., Cohen, J. L., & Marchand, G. C. (2017). The effects of doodling on recall ability.
Psychological Thought, 10(1), 206-216. doi:10.5964/psyct.v10i1.217
DIGITAL TEXTS 25
Bowman, L. L., Waite, B. M., & Levine, L. E. (2015). Implications for College Students. The
Wiley Handbook of Psychology, Technology and Society, 388.
Calderwood, C., Ackerman, P. L., & Conklin, E. M. (2014). What else do college students “do”
while studying? An investigation of multitasking. Computers & Education, 75, 19-29.
Chang, T. (2013). Predictors of multitasking behavior and the impact of multitasking on learning
(Order No. AAI3543864). Available from PsycINFO. (1442390681; 2013-99170-556).
Retrieved from
http://login.ezproxy1.lib.asu.edu/login?url=http://search.proquest.com.ezproxy1.lib.asu.e
du/docview/1442390681?accountid=4485
Chen, Q., & Yan, Z. (2016). Does multitasking with mobile phones affect learning? A review.
Computers in Human Behavior, 54, 34-42.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1016/j.chb.2015.07.047
Chen, M. S., Lara, P. N., Dang, J. H., Paterniti, D. A., & Kelly, K. (2014). Twenty years post
‐NIH Revitalization Act: Enhancing minority participation in clinical trials (EMPaCT):
Laying the groundwork for improving minority clinical trial accrual. Cancer, 120(S7),
1091-1096.
Conrad, L. (1985). Semantic versus syntactic cues in listening comprehension. Studies in Second
Language Acquisition, 7(01), 59-69.
Daniel, D. B., & Woody, W. D. (2010). They hear, but do not listen: Retention for podcasted
material in a classroom context. Teaching of Psychology, 37, 199-203.
doi:10.1080/00986283.2010.488542
Daniel, D. B., & Woody, W. D. (2013). E-textbooks at what cost? Performance and use of
electronic v. print texts. Computers & Education, 62, 18-23.
DIGITAL TEXTS 26
Delello, J. A., Reichard, C. A., & Mokhtari, K. (2016). Multitasking among college students: Are
freshmen more distracted? International Journal of Cyber Behavior, Psychology and
Learning, 6(4), 1-12.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.4018/IJCBPL.2016100101
Doyle, M., & Furnham, A. (2012). The distracting effects of music on the cognitive test
performance of creative and non-creative individuals. Thinking Skills and Creativity,
7(1), 1-7. doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1016/j.tsc.2011.09.002
Dubois, M., Poeppel, D., & Pelli, D. G. (2013). Seeing and hearing a word: combining eye and
ear is more efficient than combining the parts of a word. PloS one, 8(5), e64803.
Eden, S., & Eshet‐Alkalai, Y. (2013). The effect of format on performance: Editing text in print
versus digital formats. British Journal of Educational Technology, 44(5), 846-856.
Feng, S., D'Mello, S., & Graesser, A. C. (2013). Mind wandering while reading easy and
difficult texts. Psychonomic Bulletin & Review, 20(3), 586-592.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.3758/s13423-012-0367-y
Furnham, A., Gunter, B., & Green, A. (1990). Remembering science: The recall of factual
information as a function of the presentation mode. Applied Cognitive Psychology, 4(3),
203-212. doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1002/acp.2350040305
Goh, C. C. (2000). A cognitive perspective on language learners' listening comprehension
problems. System, 28(1), 55-75.
Gurung, R. A. (2017). Predicting learning: Comparing an open educational resource and
Standard textbooks. Scholarship of Teaching and Learning in Psychology, 3(3), 233.
Gray, H. J., Davis, P., & Liu, X. (2011). Keeping up with the technologically savvy student:
Student perceptions of audio books. Schole, 26(2).
DIGITAL TEXTS 27
Hackshaw, R. (2001). Effects of an audible distractor on fixation variability during a silent
reading of narrative text (Order No. AAI9989274). Available from PsycINFO.
(619711554; 2001-95006-477). Retrieved from
http://login.ezproxy1.lib.asu.edu/login?url=http://search.proquest.com.ezproxy1.lib.asu.e
du/docview/619711554?accountid=4485
Henningsen, A. (2011). censReg: Censored Regression (Tobit) Models. R package version 0.5,
http://CRAN.R-project.org/package=censReg.
Henrich J., Heine S. J., Norenzayan A. (2010). The weirdest people in the world? Behav. Brain
Sci. 33, 61–83. 10.1017/S0140525X0999152X
Hinrichs, A. F. (2014). Instructional design implications about comprehension of listening to
music before and during reading (Order No. AAI3589242). Available from PsycINFO.
(1528895109; 2014-99091-307). Retrieved from
http://login.ezproxy1.lib.asu.edu/login?url=http://search.proquest.com.ezproxy1.lib.asu.e
du/docview/1528895109?accountid=4485
Hispanic Association of Colleges and Universities (retrieved 2017):
http://www.hacu.net/hacu/HACU_101.asp
Johnson, J. W. (2013). A comparison study of the use of paper versus digital textbooks by
undergraduate students (Order No. 3589517). Available from ProQuest Dissertations &
Theses Global: Social Sciences. (1430910308). Retrieved from
http://login.ezproxy1.lib.asu.edu/login?url=http://search.proquest.com.ezproxy1.lib.asu.e
du/docview/1430910308?accountid=4485
Joseph, R. (2015). Higher education book publishing – from print to digital: A review of the
literature. Publishing Research Quarterly, 31(4), 264-274.
DIGITAL TEXTS 28
Judd, T. (2013). Making sense of multitasking: Key behaviours. Computers & Education, 63,
358-367. doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1016/j.compedu.2012.12.01
Junco, R. (2013). Comparing actual and self-reported measures of Facebook use. Computers in
Human Behavior, 29(3), 626-631.
Larson, L. C. (2015). E‐Books and Audiobooks. The Reading Teacher, 69(2), 169-177.
Lin, C. C. (2016). Learning English with electronic textbooks on tablet PCs. Interactive Learning
Environments, 1-13.
Lund, R. J. (1991). A comparison of second language listening and reading comprehension. The
Modern Language Journal, 75(2), 196-204.
Marin, A. J., & Hock, R. (2016). Psychology. Boston, MA: Pearson.
McKinney, K., Atkinson, M., & Flockhart, T. (2017). A sampling of what psychologists engaged
in SoTL might learn from sociology. Scholarship of Teaching and Learning in
Psychology, 3(2), 178-190. http://dx.doi.org/10.1037/stl0000080
McVay, J. C., & Kane, M. J. (2012). Why does working memory capacity predict variation in
reading comprehension? On the influence of mind wandering and executive attention.
Journal of experimental psychology: general, 141(2), 302.
Medina, C. A., & Posadas, C. E. (2012). Hispanic student experiences at a hispanic-serving
institution: Strong voices, key message. Journal of Latinos and Education, 11(3), 182-
188. doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1080/15348431.2012.686358
Molen, J. H. W. v. d., & Voort, T. H. A. v. d. (2000). The impact of television, print, and audio
on children's recall of the news: A study of three alternatives explanations for the dual-
coding hypothesis. Human Communication Research, 26(1), 3-26.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1093/hcr/26.1.3
DIGITAL TEXTS 29
Moyer, J. (2011). “Teens today don’t read books anymore”: A study of differences in
comprehension and interest across formats (Doctoral dissertation, University of
Minnesota, MN). Retrieved from
http://readingformatchoicesdissertation.pbworks.com/f/ReadingFormatsFinalJuly27.pdf
National Clearinghouse for English Language Acquisition (2017). Langauge spoken by English
learners (ELs). Retrieved April 24, 2017 from
http://www.ncela.us/files/fast_facts/FastFactsAllLanguagesFebruary2017.pdf
Pachai, A. A., Acai, A., LoGiudice, A. B., & Kim, J. A. (2016). The mind that wanders:
Challenges and potential benefits of mind wandering in education. Scholarship of
Teaching and Learning in Psychology, 2(2), 134.
Patterson, M. C. (2017). A naturalistic investigation of media multitasking while studying and
the effects on exam performance. Teaching of Psychology, 44(1), 51-57.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1177/0098628316677913.
Perham, N., & Currie, H. (2014). Does listening to preferred music improve reading
comprehension performance? Applied Cognitive Psychology, 28(2), 279-284.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1002/acp.2994
Roberts, K. C. (2017). Electronic versus traditional print textbooks: An evaluation of student
achievement and instructor levels of use of the innovation in a community college (Order
No. AAI10127873). Available from PsycINFO. (1883362017; 2016-53063-146).
Retrieved from
http://login.ezproxy1.lib.asu.edu/login?url=http://search.proquest.com.ezproxy1.lib.asu.e
du/docview/1883362017?accountid=4485
Rockinson-Szapkiw, A. J., Courduff, J., Carter, K., & Bennett, D. (2013). Electronic versus
DIGITAL TEXTS 30
traditional print textbooks: A comparison study on the influence of university students'
learning. Computers & Education, 63, 259-266.
Roche, R. A., Commins, S., Agnew, F., Cassidy, S., Corapi, K., Leibbrand, S., ... & O’Mara, S.
M. (2007). Concurrent task performance enhances low-level visuomotor learning.
Perception & psychophysics, 69(4), 513-522.
Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2015). Matching learning style to instructional
method: Effects on comprehension. Journal of Educational Psychology, 107(1), 64.
Rood, A. N. (2009). Minorities in the majority: College adjustment of latinas and latinos at a
hispanic serving institution (Order No. AAI3323784). Available from PsycINFO.
(622042639; 2009-99020-547). Retrieved from
http://login.ezproxy1.lib.asu.edu/login?url=https://search-proquest-
com.ezproxy1.lib.asu.edu/docview/622042639?accountid=4485
Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013). Facebook and texting made me do it:
Media-induced task-switching while studying. Computers in Human Behavior, 29(3),
948-958.
Schinske, J. N., Balke, V. L., Bangera, M. G., Bonney, K. M., Brownell, S. E., Carter, R. S., ... &
Gonzalez, B. (2017). Broadening Participation in Biology Education Research: Engaging
Community College Students and Faculty.
Singh, T., & Kashyap, N. (2015). Does doodling effect performance: Comparison across
retrieval strategies. Psychological Studies, 60(1), 7-11.
Sousa, T. L. V., Carriere, J. S., & Smilek, D. (2013). The way we encounter reading material
influences how frequently we mind wander. Frontiers in psychology, 4.
Sugden, N. A., & Moulson, M. C. (2015). Recruitment strategies should not be randomly
DIGITAL TEXTS 31
selected: Empirically improving recruitment success and diversity in developmental
psychology research. Frontiers in Psychology, 6, 11. Retrieved from
http://login.ezproxy1.lib.asu.edu/login?url=https://search-proquest-
com.ezproxy1.lib.asu.edu/docview/1751226214?accountid=4485
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive
Science, 12(2), 257-285.
Taylor, A. K. (2011). Students learn equally well from digital as from paperbound texts.
Teaching of Psychology, 38(4), 278-281.
Terry, C. A., Mishra, P., & Roseth, C. J. (2016). Preference for multitasking, technological
dependency, student metacognition, & pervasive technology use: An experimental
intervention. Computers in Human Behavior, 65, 241-251.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1016/j.chb.2016.08.009
US Congress. National Institutes of Health Revitalization Act of 1993: Act to Amend the Public
Health Service Act to Revise and Extend the Programs of the National Institutes of
Health, and for Other Purposes. Public Law 103-43. Washington, DC: US Congress;
June 20, 1993.
Yancey A. K., Ortega A. N., Kumanyika S. K. (2006). Effective recruitment and retention of
minority research participants. Annu. Rev. Public Health 27, 1–28.
10.1146/annurev.publhealth.27.021405.102113
Ylias, G., & Heaven, P. C. L. (2003). The influence of distraction on reading comprehension: A
big five analysis. Personality and Individual Differences, 34(6), 1069-1079.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1016/S0191-8869(02)00096-X
DIGITAL TEXTS 32
Young, J. (2013, January). The object formerly known as the textbook. The Chronicle of
Higher Education Retrieved April 24, 2015 from: http://chronicle.com/article/Dont-
Call-Them-Textbooks/136835/
Van Norman, T. L. (2014). The effects of media multitasking while studying: Students'
performance and perceptions (Order No. AAI3556371). Available from PsycINFO.
(1501840668; 2014-99011-060). Retrieved from
http://login.ezproxy1.lib.asu.edu/login?url=http://search.proquest.com.ezproxy1.lib.asu.e
du/docview/1501840668?accountid=4485
Wammes, J. D., Boucher, P. O., Seli, P., Cheyne, J. A., & Smilek, D. (2016). Mind wandering
during lectures I: Changes in rates across an entire semester. Scholarship of Teaching and
Learning in Psychology, 2(1), 13-32.
doi:http://dx.doi.org.ezproxy1.lib.asu.edu/10.1037/stl0000053
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