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opic: You will write a three-to-four-page paper (excluding the title page and references) on thetopic of “multitasking” using the two empirical articles you read and summarized in theMultitasking Graphic Organizer Assignment. These articles, Bellur et al. (2015) and Spence etal. (2020) will be discussed in class to ensure that you understand the purpose, method, andfindings. You will be doing a “mini” literature review of these two studies (A partial citation forthe two studies found on the top of the next page). A literature review may serve severalpurposes including (APA, 2020, p.8): Defining and clarify the problem Summarizing previous investigations to inform readers of the state of the research Identifying relations, contradictions, gaps, and inconsistencies in the literature; and Suggesting next steps in solving the problem.Your paper should address what is known about academic multitasking and what future researchon the topic should address. Your papers should draw a conclusion about what the literature saysabout multitasking (e.g. it is harmful, it may be harmful in some situations, there is not enoughknown) and use evidence from the articles to support this position
Your first paragraph should be an introductory paragraph sparking the reader’s interestin the topic. What is meant by “multitasking” in this context? How prevalent is multitasking incollege? Why is it interesting and/or important to study multitasking, specifically in collegestudents? The paragraph should end with a thesis statement presenting the main idea and focus ofyour paper. The thesis statement sets the reader up for what he or she will learn by reading yourpaper. In other words, what do you conclude about multitasking in academic settings based onyour review of these two studies? A strong thesis lets the reader know at the outset what yourpaper will conclude. Your introduction should be approximately half a page.Your body paragraphs should be a review of the two studies. Your literature reviewshould present relevant information in a coherent and organized fashion. For each of the articles,summarize the main question that it addressed, the general methodology, and the overall findings(results). The reader should have enough information about each study to evaluate “the four bigvalidities” (the research design, who participated, the procedure used, the size of the effect, etc.).After describing the studies for the reader identify the relations, contradictions, gaps andinconsistencies between them. When taken together what can and cannot be concluded about theimpact of multitasking on college students? This is where you help the reader understand thesimilarities/differences among the studies with connecting statements (e.g., “In contrast tofindings by Rose et al., (2018), Smith’s (2015) study showed that…”). Strong writing presentsrelevant information in a clear, succinct, organized fashion using straightforward, accurate,unbiased language. Your analysis is where you integrate and interpret the information that waspresented in your literature review. Your analysis should support of your thesis statement.Your conclusion is where you briefly summarize your paper. What were the key points?What should future research examine and why? This direction for future research should berelated to the gaps and inconsistencies you addressed previously. What is a “take home” messageabout multitasking? Does the evidence suggest that multitasking is efficient/effective? Why orwhy not? What is a practical implication from this research (i.e., how could these findings beapplied to real life?)?
First study
Education in many universities consists primarily of classroom
instruction time followed by independent homework consisting
of reading and studying. For this system to work, students must
pay focused attention during class so they can take useful notes
that they can later study. There were issues with attention during
class long before the diffusion of hand held devices and digital
messages provided potential distractions. Today, the media are
filled with reports of young adults continually multitasking, or
being engaged with different media devices at the same time they
are also working, studying, walking, and even driving. Multiple
sources have reported that young adults are being continuously
connected and always ‘‘on,’’ and they are engaged with more than
one task at any given time, including during class (Duggan &
Rainie, 2012; Foehr, 2006; Rideout, Foehr, & Roberts, 2010). In
one study, 38% of students reported they were unable able to go
beyond ten minutes without checking their phones, or other device
(for e.g., laptop, e-reader) (Kessler, 2011).
There is no denying the importance of computer literacy for col-
lege students, and efficacy with technology provides benefits to the
social lives and job opportunities for students familiar with technol-
ogy. While there are pedagogical benefits to technology and stu-
dents may bring a computer to class to allow them to take notes or
look up course related information, the most common activities dur-
ing class include texting, Facebook, tweeting, playing games, watch-
ing videos, and other activities that are not related to class
(Kuznekoff & Titsworth, 2013). The limited in-class time with an
instructor should ideally be a focused time of attention with
minimized distractions to foster greater engagement and learning.
Pew report shows that nearly 64% of students admitted to regularly
texting during class (Lenhart, Ling, Campbell, & Purcell, 2010), and
close to three-fourths of college students surveyed acknowledged
that they engage with some form of technology even while they
are studying.
Parents and educators are increasingly concerned about the costs
of the time and attention given to these devices and what is being
missed during the lack of focus in the classroom. The goal of this
study is to consider the potential impact of this constant technolog-
ical connectedness from a cognitive capacity and information pro-
cessing perspective, and to assess the impact of multitasking both
within and outside the classroom on grades and learningThere are many advantages available to those who can effec-
tively use computers and associated technologies (Albion, 2001;
Compeau, Higgins, & Huff, 1999). The use of digital technologies
in class requires creative and intentional curriculum design by
instructors as well as active involvement from students in the
classroom (Hillman, 2014), making it critical for college students
to use and learn appropriate technology functions to enhance their
learning experience. Constant access to digital devices, ubiquitous
connectivity and high speed Internet teach certain abilities, allow
students to keep in touch with parents and friends from almost
anywhere, and facilitate easy search of and access to information
on any topic. Experience with technology leads to computer skills,
and those without these skills are likely to be left behind, unable to
obtain careers in many fields (Albion, 2001; Compeau et al., 1999).
A majority of careers for college students will require computer
and technology usage (Straubhaar, LaRose, & Davenport, 2014),
so it is important to prepare students for careers that will require
them to effectively use computers and technology. There is no
denying that technology can enhance the presentation of topics,
and engage students more interactively in the learning process
and outcomes, but it must be done correctly, so that it can comple-
ment active learning behaviors.
Furthermore, some believe that the brains and cognitive capac-
ity of those engaged in frequent multitasking will expand and
adapt as a result of the behavior, which may help them become
‘‘nimble, quick-acting multitaskers’’ (Anderson & Rainie, 2012,
p. 2), who are able to manage symbols from multiple sources at
a time and are well prepared for careers in the information indus-
try using technology. This would make them uniquely qualified for
a variety of jobs and develop unique skills. Appropriate use of tech-
nologies in classrooms can be used to enhance instruction by
engaging students with content, allow students to easily look up
reference materials, and record notes for studying. This explains
why institutions of higher learning are placing a large emphasis
on the availability of state-of-the-art technologies in classrooms,
which provide students unlimited access to high speed Internet
during class and while completing homework. There is no doubt
about the numerous advantages of access to technology, but access
alone does not necessarily enhance learning. Hence, this project
asks whether the use of technology interferes with classroom
learning.
1.2. Concerns surrounding technology use in classrooms
There is little debate that students are using various forms of
technology (laptops and mobile phones) within classrooms, and
discussions of the benefits of such technology are plentiful, as
outlined above (Burns & Lohenry, 2010; Ransford, 2009). Even
so, there is some disagreement about the effect of this trend
and the extent to which it should be celebrated, regulated, or
both. There is a growing concern among the press, parents,
and media effects researchers that relentless media multitasking
is distracting adolescents from tasks requiring deep thinking,
taking time away from family, harming their social connections,
cognitive performance, and socio-emotional well-being (Ophir,
Nass, & Wagner, 2009; Pea et al., 2012). It is possible that being
constantly connected through and with technologies results in a
continuous stream of distractions that make it difficult to pay
close attention to complicated topics, as would be expected in
a classroom setting. Studies have shown that students in class-
rooms continuously shift their attention from work to
non-work tasks, diminishing focus on the course specific infor-
mation being presented (Fried, 2008).
1.3. Information processing, multitasking and divided attention
The instructional format in most academic institutions is still
based on a traditional lecture format where students are expected
to pay close attention to the instructor, take active notes and par-
ticipate in classroom discussions (Sana, Weston, & Cepeda, 2013).
Students temporarily ‘‘checking-out’’ to focus on another task
may miss critical information being given in the lecture that will
be difficult to make up. When this set of primary tasks is inter-
rupted via several secondary tasks that are not related (or relevant)
to the primary task, it will hinder the learning process by impairing
the extent to which they pay attention to material presented.
Active attention and processing are required for information to
be transferred from short-term to long-term memory.
Multitasking impairs attention and processing by a phenomenon
described as task-set inertia (Wickens & McCarley, 2008 as cited
in Wei, Wang, & Klausner, 2012). Once attention is diverted from
the primary task, apart from the costs involved (such as greater
response time, more delays) in switching between tasks, there is
also a tendency to remain with the secondary (distraction) task.
In the classroom, this means that the student would take time to
switch focus from the lecture to a text message. They would read
that message, think of a response and then possibly respond.
They may then read or send other messages, possibly checking
Facebook, Twitter, or other social media. By the time they are ready
to return attention back to the primary task, they may have missed
15 min or more of a 50-min lecture. Essentially, when students are
doing things not related to class, they are not paying attention, and
are less likely to learn from the lesson. This will likely require them
to learn the material independently, meaning they have to spend
more time studying outside of class to learn the content and main-
tain their grades.
Wood et al. (2012) define multitasking as ‘‘the inability to
simultaneously perform two or more overlapping tasks when each
requires selecting a response (i.e., a decision task) due to a general
slowing in the performance of the second task’’ (p. 366). This
defines multitasking in terms of the inability to focus on one or
the other task because of the divided attention between two or
more tasks. People can only process information when they pay
attention to it. This means that attention is the main ‘‘gateway’’
(Craik & Lockhart, 1976) or the key ‘‘gatekeeper’’ (Wei et al.,
2012) of the information processing approach. Cognitive theories
based on information-processing (Mayer, 1996) and multimedia
learning (Mayer & Moreno, 2003) argue that for ‘‘meaningful learn-
ing’’ to occur, individuals must actively process information, focus
their attention on new information and actively arrange and inte-
grate new information into preexisting knowledge structures.
These theories would predict that when individuals are constantly
engaged in multiple tasks, or multitasking, they are only partially
engaged with each task as they switch back and forth. This in turn
results in less attention to information and poor performance and
learning outcomes (Bailey & Konstan, 2006; Kraushaar & Novak,
2010).
Use of technological devices within classrooms has been shown
to lower academic performance. Research in education has shown
the importance of attentive listening and active note-taking as
important classroom skills for their contribution to higher
grades/scores in exams (Titsworth & Kiewra, 2004). Activities such
as multitasking on laptops (Sana et al., 2013), texting, and posting
comments to social networking sites, reduce attention to course
content (Wei et al., 2012), the amount and usefulness of notes that
are taken, and generally negatively impact learning when done
during class (Kuznekoff & Titsworth, 2013).
Because information is not learned in class, students would
need to learn it on their own some other time to avoid a negative
influence on their academic performance. Thus, the use of
64 S. Bellur et al. / Computers in Human Behavior 53 (2015) 63–70technology not related to the course information, inadvertently
increases the amount of time students need to spend studying to
retain information, thus decreasing efficiency in studying habits
and decreasing exam performance and overall grades (Kirschner
& Karpinski, 2010). The studies reviewed above which have exam-
ined multitasking behavior within classroom settings lead us to the
following research questions and prediction:
RQ1: How frequently are college students using Facebook and
other technologies in general?
RQ2: How frequently are college students engaging in multi-
tasking during class and while doing homework?
H1a. Multitasking during class will be negatively associated with
current college GPA (CGPA).
Often, young adults tend to dismiss the negative impacts of
multitasking, perceiving it as ‘‘easy,’’ and self-reporting high effi-
cacy (Carrier, Cheever, Rosen, Benitez, & Chang, 2009; Wood
et al., 2012), when compared to older adults. Although young
adults may perceive themselves to be good at multitasking, focus-
ing and sustaining attention on more than one task is challenging
and no one seems to be really good at it. While it seems everyone
multitasks sometimes, there are some people who multitask fre-
quently, or even chronically. A study by Ophir et al. (2009) found
that ‘‘chronic media multitaskers’’ have trouble focusing their
attention, and they are more susceptible to distractions than less
frequent multitaskers even when the stimulus is irrelevant. This
distractability makes them less able to focus on the important
information they need to learn. The performance of these dis-
tractable chronic multitaskers further declines because they do
not exactly switch between tasks. They stay partially engaged with
both tasks and never pay full attention to either one. Ophir et al.
(2009) suggested that because chronic media multitaskers are
always switching attention from one task to another, they are less
capable of ‘‘filtering out’’ irrelevant stimuli or attending to the rel-
evant information, which in turn hampers their learning and per-
formance on a given task. There is evidence to suggest that an
individual’s preference for multitasking is an important determi-
nant of how easily one gets distracted (Rosen, Carrier, & Cheever,
2013). Those who showed higher preference for task-switching
were more likely to go ‘‘off-task,’’ whereas those students who
made use of study strategies (i.e., engaging in school-related tasks
such as looking up additional information) were less likely to be
distracted from their primary task. Rosen et al. (2013) argued that
individuals’ preference of multitasking, combined with emotional
gratifications obtained from constant social media use or texting,
encourage students to saturate their studying environments with
different forms of technology, which in turn heightens the poten-
tial for multitasking and distractibility.
Similarly, outside classroom settings, Junco and Cotten (2011)
observed negative effects of instant messaging (IM) use while
doing homework on students’ overall academic performance. A
fairly high number of students in the sample (approximately
93%) reported engaging in some form of instant message use (such
as AOL, MSN, and Facebook), while doing their homework. The
amount of time engaging in IM use, and frequency of checking in
on Facebook, particularly when combined with other tasks,
decreased student performance and GPAs (Junco & Cotten, 2011;
Rosen et al., 2013). Junco (2012) found that while some Facebook
activities such as checking up on friends or sharing links, turned
out to be a positive predictor of overall GPA, other activities such
as posting status updates and using the chat feature, emerged as
negative predictors of GPA. This is consistent with other studies
that have found a similar inverse relationship between increased
multitasking and decreased efficiency in studying strategies
and practices (Kirschner & Karpinski, 2010; Kraushaar & Novak,
2010).
Further, these self-reported measures of academic impair-
ments suggest that students are aware of (and acknowledge)
the negative impact that technology-induced multitasking has
on their academic performance, but they continue to engage in
multitasking. Thus, based on the studies reviewed above, which
have examined multitasking behavior outside of classroom set-
tings and the impact of Facebook use in particular, we hypothe-
size that:
H1b. Multitasking while doing homework (outside class) will be
negatively associated with current college GPA (CGPA).
H2. Hours spent on Facebook will be negatively associated with
current college GPA (CGPA).
In sum, we examine how the tendency to multitask (in the form
of multitasking efficacy), along with self-reported multitasking
behaviors – both within and outside classroom settings – are likely
to affect academic performance. Further, we examine these rela-
tionships through the lens of additional time spent preparing for
class (studying behaviors outside classroom settings) and students’
perceived multitasking efficacy. While the studies reviewed above
have examined the direct impact of multitasking behaviors on sev-
eral academic performance and learning outcomes, the impact of
the time spent preparing for class and perceived multitasking effi-
cacy variables have not been explored systematically. We address
this as described in the sections below.
2. Method
2.1. Participants
Students (N = 361), male (n = 156) and female (n = 204),
enrolled in a basic communication course at a large northeastern
university were surveyed. Participants ranged in age from 18 to
26 with a mean age of 19.2 years and were predominantly
Caucasian (76.7%), followed by Asian (8.3%), and Hispanic (6.6%).
2.2. Procedure
Data were collected via QuestionPro, an online survey hosting
website. Upon arrival, participants were asked to turn off and relin-
quish their cell phone in order to reduce distraction. Participants
were then given a unique identification number. After being seated
at a computer and answering general demographic questions, par-
ticipants reported their technology use with specific emphasis on
mobile computing using cell phones, social networking behavior,
and multitasking. Participants answered questions concerning
checking and participating in Facebook, multitasking during home-
work and while in university classrooms.
2.3. Measures
All scales were evaluated for acceptable reliability and factor
structure. Item quality was assessed with a series of confirmatory
factor analyses. Three criteria were employed to test item quality.
The first criterion was content validity, or homogeneity of item
content. To be included on a scale, items had to tap into the same
underlying theme. The second criterion was internal consistency,
unidimensionality, was measured with coefficient alpha. The third
criterion was parallelism, also known as external consistency,
which examines the extent to which each item on a scale correlates
with other scales in the study to approximately the same degree
(in the case of equal item quality) or forms a gradient.
S. Bellur et al. / Computers in Human Behavior 53 (2015) 63–70 65
Second study
Increased access to electronic devices over the past twenty years hasresulted in a rapid rise in individuals performing multiple differenttasks simultaneously [27, 32]. Although using electronic devices for“multitasking” (i.e., the parallel use of several media alone or in com-bination with nonmedia activities) has become profoundly more con-venient and accessible to the general public, the availability andwidespread use of electronic devices has also created a mechanism fordistraction from cognitive tasks [27]. Various forms of electronic de-vices such as laptops, tablets, and smart phones are now regularly en-countered in the college classroom [17] and educators are increasinglyconcerned about the impact these devices might have on learning [15,27]. A growing body of literature indicates that the use of electronicdevices in the classroom and multitasking can have a negative impacton learning. For example, a negative correlation has been found be-tween laptop use in a large-lecture course environment and students’performance [15, 49]. Additionally, when students reported what dis-tracted them in class, laptop use by other students represented themajority of distractions [15]. Similarly, students who used laptopcomputers performed poorer on both short-answer and multiple-choicequestions when tested on the material following a lecture presentationcompared to students who did not use laptop computers during lecture[19]. Moreover, the movement and lighting of text and pop-up mes-sages in laptops has been found to reduce performance and increase thenumber of errors [42]. Students’ use of phones in the classroom has alsobeen reported to distract both faculty and other students, resulting ipolicies created by instructors to attempt to reduce cell phone useduring class time [4, 5, 7, 9, 17]. Interestingly, one study found that themere presence of a cell phone, even when participants were not using it,can reduce cognitive capacity [45].Conversely, while multiple studies found a negative impact onlearning associated with the use of technology in the classroom, somegroups report that use of laptops in the classroom can enhance aca-demic achievements and satisfaction of students [8, 39]. The reason forthese discrepancies is unclear, although it is possible that certain dis-tractions may be more engaging (e.g., scrolling a Facebook feed), and,therefore, more distracting than others [48, 49], while other forms ofdistractions (e.g., an open laptop) might provide a subtle unconscioushabitual distraction in the form of attraction towards certain frequentlyvisited websites (e.g., Facebook) but do not cause a large deviation inattention [1]. Additionally, as many modern science, technology, en-gineering, and mathematics (STEM) collegiate classrooms are now in-corporating active learning strategies into lecture‐style classes to in-crease student comprehension and engagement [13, 38], thesestrategies may include electronic devices such as clickers [12]. Clickerscan be used by instructors to ask students questions during class andallow students to respond immediately [12, 27] and have been shownto lead to an increase in student engagement [12, 40]. Clickers may bepurchased devices for polling or polling can be done via web-basedsoftware (e.g., poll everywhere) that can allow students to use a per-sonal electronic device, such as a cell phone. This increase in sanctionedcell phone use for polling purposes has led to increased off‐task cellphone use [26]. In fact, a recent survey of US college students reportedthat on average, each day in class students used a digital device fornon‐academic purposes more than 11 times, spending 20% of class timeon non‐class related activities [26]. Thus, electronic devices may bothhelp and distract from learning in the classroom.While the literature on the impact of technology on cognition isgrowing, studies have long demonstrated the negative impact of variousforms of multitasking on learning and memory. For example, studies ofeighth graders in the Netherlands demonstrated that watching a Dutch-language soap opera while working on a task reduced accuracy andspeed on both a paper-and-pencil task and a memorization task [30].Similarly, background television affects even the youngest childrenduring play; infants have shorter episodes of play and focused attentionwhen background television is present [35]. Studies examining avariety of cognitive domains including episodic memory, attention,task-goal management and long-term memory generally demonstratedeficits in these cognitive tasks in subjects when multitasking (see [43]for a review). Episodic learning and memory (i.e., the learning ofknowledge rather than practice) seems to be particularly suspectable todistractions [43]. However, some studies demonstrate that individualsthat routinely engage in multitasking can demonstrate benefits on testsexamining task-switching abilities [3]. The brains of children andyoung adults are still developing which provides further urgency tobetter understand the relationships between multitasking, memory andlearning [34].There is a similar mixed, albeit much smaller body of literatureexamining the impact of social media use on cognition and learning.Although some evidence suggests that social media may be beneficialfor cognition, particularly memory functioning [21, 28, 44], other re-ports indicate social media use can result in unintended costs tomemory [14]. For example, one study found that on days when socialmedia use was high, individuals reported more memory failures [36].However, this study utilized self-reported social media use which maynot be as accurate as objective measures [20]. Another study found noeffect of either texting or e-mail during class on performance on amultiple-choice assessment compared with a control group, revealingthat only distraction by Facebook resulted in a significant performancedecrement [49]. A separate study found that when students were dis-tracted by social media during a visual and oral presentation, memoryperformance decreased only on examination questions based oninformation presented visually [25]. Collectively, these studies suggestperformance deficits might depend on the type of distraction facing thestudent. These results also indicate social media might result in a dis-traction depending on the timing of its use; however, we are unaware ofany studies examining this directly. The mechanisms underlying theseeffects remain largely unexplored, yet some data suggest that chronicsocial media multitasking is associated with a wider attentional scope/higher attentional impulsivity, which may allow goal-irrelevant in-formation to compete with goal-relevant information [43]. Given thepopularity and use of social media [29] and the increasing prevalenceof electronic devices in the classroom [26], further investigation intothe relationship between social media use and cognition is warranted.In the current study, we examined how the timing of social mediause (Instagram) impacted retention of presented material (i.e., cogni-tive short-term memory) in college students. Students were exposed tosocial media either during or immediately following oral presentationof new material. We hypothesized that exposure to social media during,but not immediately following, presentation of a new set of informationwould decrease a subject’s recall accuracy when compared to subjectsthat were not exposed to social media. In addition to examining howthe timing of social media use impacted memory, we also examined ifthe type or quantity of topics displayed in a subject’s Instagram feedmodulated memory. Our findings may have implications regarding theuse of electronic devices and social media in the classroom.2. Materials and methods2.1. ParticipantsParticipants were college undergraduates (n = 45; 36 women and 9men) at a small liberal arts college in the US, aged 18–24 years whoresponded to in-class recruitment solicitations and were offered extracredit in one of their classes for participation. This particular demo-graphic was chosen because they represent the single largest group ofusers interacting though social networks [29] and previous results havefound conflicting reports regarding the impact of social networks onhealth in this population [6, 14, 21, 28]. All participants reported nochronic or acute illness, no regular medication regimen, and goodhealth prior to study onset. All procedures were approved by the RegisUniversity Institution Review Board.2.2. ProceduresSubjects were asked to refrain from any physical exercise, meals, orany beverages at least 1 hour prior to testing time. Upon arrival at thelab, participants completed an informed consent form, were instructedof the testing procedures and randomly placed into one of three ex-perimental groups (described below).2.3. The logical memory test of the Wechsler memory scale IVThe Wechsler Memory Scale IV (WMS-IV) was administered as de-scribed previously [46]. The WMS-IV consists of seven subtests of whichsubjects completed only the Logical Memory Immediate Recall (LM I)subset. This part of the scale is optimized for testing immediate recall ofinformation presented (common in a classroom setting) and is con-sidered a useful and effective measure of episodic memory as it ad-dresses three processes involved in memory: encoding, storage, andrecall [23]. The LM I is a measure of auditory recognition memorydesigned to test participants ages 16 to 90 and has good test-retest re-liability as well as inter-rater reliability [47]. The test consists of twostories of different lengths (65 words and 85 words), which were pre-sented to subjects orally at a steady pace. Following listening to the firststory, subjects answered a series of 15 true/false recognition questionson paper (Quiz 1). Once the first quiz was complete, subjects were readthe second story and subsequently answered 15 additional true/false.recognition questions on paper (Quiz 2). Each correct question wasawarded one point (15 points/quiz; 30 points total) and overall percentaccuracy was calculated [2].2.4. Experimental groupsSubjects were randomly assigned to one of three experimentalgroups (n = 15 subjects/group; male subjects dispersed evenly betweenthe three groups). This sample size has been determined sufficient toreport significant differences between groups [25]. The control group ofsubjects listened to the first story for one and a half minutes then satquietly for an additional one and a half minutes before completing Quiz#1 (No Instagram). Using the same methods, subjects listened to thesecond story and completed Quiz #2. The second group of subjectslistened to the first story while actively scrolling through their In-stagram feed for one and a half minutes (Instagram During Story).These subjects were then instructed to sit quietly (not using Instagram)for an additional one and a half minutes after which point they com-pleted Quiz #1. Using the same methods, subjects then listened to thesecondary story and completed Quiz #2. The third group of subjectslistened to the first story for one and a half minutes and then wereinstructed to actively scroll through their Instagram feed for one andhalf minutes (Instagram After Story) before completing Quiz #1. Usingthe same methods, subjects then listened to the second story andcompleted Quiz #2. Once subjects completed the second quiz they weasked to complete a short survey on their Instagram usage. The surveyasked subjects to report the type of content displayed on their feed froma list of twelve topics derived from previous results ([29]; Table 1) andthe total categories displayed in a subject’s feed was calculated for eachsubject. Following completion of this survey, subjects were debriefed bythe researchers about the goals of the study.2.5. Statistical analysisTo assess the hypothesis that the type of activity (No Instagram,Instagram During Story, Instagram After Story) to which a subject wasexposed to while listening to a story impacted their memory recallability, we performed one-way analysis of variance (ANOVA). We thenperformed Fischer’s paired least-significant difference (PLSD) post hocanalysis between each of the conditions. To examine subject Instagramuse, separate unpaired t-tests (as only two groups had access toInstagram) and correlation analyses were conducted. Alpha was set at0.05. Figures are shown as mean ± SEM or as individual data.3. Results3.1. Logical memoryLogical memory as assessed through the WMS-IV LM I betweengroups (No Instagram, Instagram During Story, Instagram After Story)using a one-way ANOVA revealed a significant difference, indicatingthat exposure to Instagram decreased memory recall (Fig. 1, F(2,42) = 3.353, p = 0.04). Post hoc analyses demonstrated that logicalmemory was lower in the group that used Instagram during the pre-sentation of the story (71.55% ± 2.6) compared with the control groupthat did not use Instagram at any time (80.89% ± 2.1) (p = 0.01). Anon-statistically significant trend was also observed between the groupthat used Instagram during the presentation of the story(71.55% ± 2.6) compared with the group that used Instagram afterlistening to the story (77.77% ± 2.9) (p = 0.09). A difference was notobserved between the group that used Instagram after the presentationof the story (77.77% ± 2.9) compared with the control group that didnot use Instagram at any time (80.89% ± 2.1) (p = 0.44). No differ-ences were observed in memory recall between female and male par-ticipants (p = 0.31; data not shown). Collectively, these results suggestthat social media use diminished memory recall ability when usedduring presentation of novel audio material.3.2. Instagram useIn order to begin to examine how subjects were using Instagram,after completing the second quiz subjects were asked to complete asurvey indicating the content of their Instagram browsing. The mostpopular Instagram topics browsed were Family/Friends, Humor, andInfluencer/Celebrity, with the least popular topics related to Sports,News, and Science/Tech (Table 1). T-test indicated no differences in theamount of topics appearing in subjects’ Instagram feed when comparingthe two groups with access to Instagram (During and After the story)(Fig. 2, F(1,28) = 1.856, p = 0.18). Correlational analysis revealed norelationship between the logical memory recall ability and the numberof topics appearing on an Instagram feed (Fig. 3; r = −0.03, p = 0.75).Taken together, these results suggest that neither the type of images northe number of topics displayed on a subject’s Instagram modulated thereduction in memory ability observed.4. DiscussionThe current study examined if using social media (Instagram) eitherduring or immediately following presentation of new auditory materialimpacted retention of that material. Our results indicate that exposureto Instagram decreased memory recall (Fig. 1) when subjects wereusing Instagram while listening to a presentation. Subjects that wereusing Instagram during the presentation answered on average 71% ofquiz questions correctly when assessed almost immediately followingcompletion of the presentation, while subjects that did not use In-stagram answered ~9% more answers correctly on average (80%;p = 0.01). In an academic setting this difference in performance isequal to a full letter grade (e.g., C- vs B-). Subjects that listened to thepresentation without distraction and then used Instagram prior totaking the memory quiz performed slightly worse in memory recall(3%) than the group who did not use Instagram at all, although thissmall difference was not statistically significant.The results from this study suggest that individuals may allocateattentional resources to their social media account rather than at-tending to presentation of new material which can result in a reductionin retention of new material. These results are consistent with a recentstudy where participants were instructed to either passively view aseries of paintings, take photographs of the paintings, or use Snapchat(a photo-sharing-based social media platform) to document their ex-perience of the paintings. Participants who used Snapchat demon-strated lower recall for the paintings than the other two groups [37].The results of the current study, however, contrast with previous workthat found student performance on questions from information pre-sented orally was similar when students used social media to that ofcontrols ([25], Elder et al., 2013). A possible explanation for thesedifferences could be the variable amounts of time students weredistracted. In the study by Marone et al. [25], subjects used Facebookfor 40% of the presentation while subjects in the current study scrolledthrough Instagram the entire length of the presentation. However,overall the literature does not support the idea of an inverse relation-ship between academic performance and time spent in distractivemultitasking [10, 13, 16, 22]. Consistent with this body of work, in thecurrent study the length of the distraction was controlled betweengroups (1.5 min), yet only the group that used Instagram during thepresentation demonstrated a large performance deficit. Taken as awhole, these findings suggest that the timing of the distraction may bemore important than total time distracted. In the classroom setting,even a brief distraction occurring at the time important material ispresented could disrupt the learning process.In addition to the timing of social media use, we also found nodifferences in the type or amount of topics appearing in subjects’Instagram feed when comparing the two groups with access toInstagram (During and After the story) (Fig. 2, p = 0.18). Moreover, acorrelation was not found between logical memory recall ability andthe number of topics appearing on an Instagram feed (Fig. 3;r = −0.03, p = 0.75). Taken together, these results suggest that nei-ther the type of images nor the number of topics displayed on a subject’sInstagram modulated the reduction in memory ability observed.College students acknowledge that multitasking can be distractingand disruptive to learning ([41], Elder et al., 2013, [33]) yet manycontinue to use electronic devices in class [18, 33, 41]. Some authorshave suggested that users are unable to stop themselves from usingsocial media even if they are aware use might impact them negatively[1, 31]. Indeed, a recent study reported that social networking siteaddiction resulted in task distraction during a work shift in nurses [24].However, as previously mentioned, some use of electronic devices (e.g.,clickers) has been found to enhance the classroom experience [12]emphasizing that how individuals use electronic devices may also in-fluence whether beneficial or detrimental effects emerge. Prior researchdemonstrates that more passive use (i.e., scrolling through feeds) isassociated with more negative effects on well-being relative to moreactive social media use (i.e., chatting, posting comments) [11]. Overall,the ways in which social media is used likely will determine whether itis beneficial or harmful for memory. Future research should extend theresults of the current study and examine whether short-term memory ismodulated by social media site, motivation for use, and patterns of use.5. LimitationsWe did not control for scholastic aptitude or age in the current studyand had a relatively small sample size. While the randomization of thegroups likely reduced the chance that uneven distribution occurred,future studies should control for these variables and include a largersample size. In addition, the relatively small number of male subjects inFig. 1. Logical memory was assessed by cal-culating average percent correct answers to arecall quiz as part of the WMS-IV LM I. One-way ANOVA was used to compare differencesin logical memory between groups (NoInstagram (No IG), Instagram During Story (IGDuring Story), Instagram After Story (IG AfterStory)). Analyses indicated that exposure toInstagram decreased memory recall(p = 0.04). Fischer’s paired least-significantdifference (PLSD) analyses demonstrated thatlogical memory was lower in the group thatused Instagram during the presentation of thestory (71.55% ± 2.6) compared with the groupthat did not use Instagram at any time(80.89% ± 2.1) (p = 0.01). Alpha was set at0.05. Data are shown with group means ±standard error of the mean.Fig. 2. Subjects reported the number ofInstagram topics appearing in their Instagramfeed. T-test was used to compare differences innumber of Instagram topics between groups(Instagram During Story (IG During Story),Instagram After Story (IG After Story)).Analysis indicated no differences in theamount of topics appearing in subjects’Instagram feed when comparing the twogroups with access to Instagram (p = 0.18).Alpha was set at 0.05. Data are shown withgroup means ± standard error of the mean the study make it difficult to draw any conclusions about potential sexdifferences in episodic memory. Moreover, the small sample size pre-vented control of a variety of factors (e.g., stress levels, distractibility,attention) that can influence memory and should be examined in futurework. Future studies should attempt to recruit a more balanced samplepopulation in order to investigate potential differences based on sex.Finally, this study only examined the short-term effect of social mediause on memory and future longitudinal research is needed to examinethe long-term implications for memory functioning over different spansof time.6. ConclusionsThe results of the current study demonstrate that distraction bysocial media can result in a reduction in short-term memory recall whensocial media use occurs during the presentation of novel information.Furthermore, even short-term passive use of social media (scrollingthrough an Instagram feed) is sufficient to result in reductions inmemory recall. Finally, it appears the timing of social media use, butnot the time spent, the type of content viewed, nor the quantity of to-pics displayed, modulated the observed reductions in memory recallability. The current study only examined one type of social mediaplatform (Instagram) that involves looking at and scrolling throughpictures/comments and our results might not be generalizable to otherplatforms. It remains unclear how the use of other social media plat-forms that require different levels of attention might influence learningand memory. These results have implications regarding the availabilityand/or use of electronic devices and social media in the classroom andare especially important given that more and more young people,whose brains are still developing [34], are engaging in media multi-tasking.