A Mixed-­­Methods Study Investigating the Relationship Between Media Multitasking and
Grade Point Average
Jennifer Lee
University of North Texas
United States
Jennifer.Lee@unt.edu
Abstract: The study examined the relationship between media
multitasking orientation and grade point average. In the quantitative
section of the study, the primary method of statistical analyses was
multiple regression. Three out of four independent variables, namely,
media multitasking orientation, gender and age were statistically
significant predictors of Grade Point Average. In the qualitative section of
the study, seven participants were interviewed to determine how
individual differences in media multitasking orientation manifest
themselves in academic settings.
Introduction
Technology has long been identified as the catalyst that allows us to do more with less
effort. “Today, technologies are no longer tethered to one location and this leads workers to
multitask in work contexts previously not possible” (Kleinman, 2010, p. 15). As a direct result of
new technologies and media in the last fifty years, we have gradually moved away from a linear
work model to one that thrives on multiple tasks. Some researchers described the phenomenon
as media multitasking (Vega, 2009). Others called it task-­ switching (Gopher, Armony, &
Greenspan, 2000; Roger & Monsell, 1995), dual-­ tasking (Meyer & Kieras, 1997), and
interleaving (Salvucci, Taatgen, & Kushleyeva, 2006). For the purpose of the paper, the authors
define multitasking as the act of "engaging in multiple media activities simultaneous, including
multiple windows on a single media platform and/or multiple media” (Vega, 2009, p. 3).
In 2010, the Kaiser Family Foundation conducted a large-­ scale media study in the United
States. Over two thousand youths, ages 8 to 18, participated in the research on media use.
Kaiser researchers found that young people spent an average of 7:38 hours on media
consumption. In terms of media exposure for the 7:38 hours of use, the young people surveyed
packed an average total of 10 hours and 45 minutes of media content daily by using various
media simultaneously. In contrast, when Kaiser Foundation researchers conducted a similar
study in 2006 with six hundred ninety five participants, they found that on the average media
consumption among young adults stood at 6:21 hours a day. In the span of four years (2006-­
2010), we have seen a significant increase in media use. Today, media exposure in this age
group account for forty-­­three and a half percent of the time spent in a day excluding school and
sleep. American youths spent a substantial amount of time pairing audio and/or visual media
with homework, eating, grooming, and traveling (Jeong & Fishbein, 2007).
Questions about how we allocate resources when it comes to handling multiple tasks
simultaneously have been a subject of interests among researchers in many disciplines. Even
though media multitasking is prevalent among teens and college students, few studies have
examined impacts of multitasking on learning habits (e.g. Brasel & Gips, 2011; Fried, 2007;
Gardner, 2008; Hembrooke & Gay, 2003; Ishizaka, Marshall, & Conte, 2001, Lee, Lin, &
Robertson, 2011; Levine, Waite, & Bowman, 2007; Lin, Robertson, & Lee, 2009). Are some
students better at multitasking than others? This study examined the question by analyzing the
relationship between media multitasking orientation and grade point average among college
students.
Literature Review
Various theories on multitasking have been proposed. However, no one theory has been
able to fully explain the nature of media multitasking. In this section, seven major theories on
multitasking and their key ideas are summarized below (Table 1). The theories are (a) early
selection theory (b) late selection theory (c) task switching (d) dual-­ task (e) theory of threaded
cognition (f) limited capacity information processing model (g) cognitive load theory.
Table 1
Summary of the key ideas in each theory
Theory
Key ideas
Early Selection Theory
Broadbent (1956)
Single channel theory. We can only process one task at a
time.
Late Selection Theory
Deutch & Deutch (1963)
We process all incoming information and we select
important signals that require our attention or action. The
selection of these signals depends on our degree of arousal.
Task Switching
Allport, Styles, and Hsieh
(1994); Rogers & Monsell
(1995)
Complete processes associated with a task before the next
task begins. Task switching can either be voluntary or
involuntary.
Dual-­­task
Pashler (1994); Pashler,
Harris, & Nuechterlein (2003)
Classified into two paradigms: (a) stop-­ signal (b) stop-­­
change. The first paradigm involves inhibition of responses
on cue while the second paradigm involves the switch to a
secondary task on cue.
Theory of Threaded Cognition
Salvucci & Taatgen (2008)
Resources can execute only one process at a time
Limited Capacity Information
Processing Model
Lang (2000)
Our ability to process information is limited. We can only
process a limited amount of information before our
cognitive resources are tied up.
Cognitive Load Theory
Sweller, van Merrienboer, &
Pass (1998)
Cognitive load that affect learning: intrinsic, extraneous, and
germane.
Despite the theoretical differences, most theories share the same underlying premise
that humans have limited capacity for processing information. Some researchers believe that
multitasking (such as the use of instant messaging) interfere with academic performance
through (a) displacement of time available for study, (b) direct interference while studying, and
(c) development of a cognitive style of short and shifting attention (Levine, Waite, & Bowman,
2007, p. 6). Little is known about the impact of media multitasking on academic performances
of college students. When it comes to academic performance, Grade Point Average has
become the de facto method of measuring academic performance before and after admission
at the post-­ secondary education level.
Methods, techniques, or modes of inquiry
In this study, two research questions were examined:
1. To what extent do media multitasking orientation, gender, age, employment, income, and
living arrangement affect grade point average?
2. How do individual differences in media multitasking orientation manifest themselves in
academic activities?
Method:
The purpose of the study necessitated the use of a mixed-­­methods approach.
Specifically, quantitative research methods were used to answer the first research question. In
order to strengthen the validity of the quantitative results and provide a richer level of details,
the study utilized qualitative techniques, to offset biases associated with a single method.
Participants:
The data were collected from 212 participants from a major public university in the
Southwest. From a total of 212 participants who responded to the survey invitations, 183
responses were used in the study. Additionally, a total of 7 students from the group
participated in a follow-­ up interview for the qualitative part of the study.
Procedure:
In the first part of the study, 212 participants took the Media Multitasking Index (Ophir,
Nass, & Wagner, 2009). Participants were asked to rate their secondary media consumption
while using a primary medium. Based on the following ratings “Most of the time” (=1), “Some of
the time” (=.67), “A little of the time” (=.33), and “Never” (=0). A total of 12 different media was
used in the study. The media included television, video, music, non-­­musical audio, video games,
cell phone, texting, instant messaging, email, web, computer applications, and print media. The
survey helped identify heavy, moderate, and light media multitaskers. Data collected from the
survey were used to design interview questions for the qualitative portion the study. The
qualitative data provided a deeper understanding of the behaviors of low, moderate, and high
media multitaskers. Using the purposive sampling technique, semi-­ structured interviews of
participants were conducted after quantitative data from the survey has been analyzed. The
interviews were guided by six open-­­ended questions and other information derived from the
survey.
Results and/or conclusions/point of view
The quantitative findings in the study showed that there was statistically significant
relationship the three independent variables: Media Multitasking Orientation, Gender, and Age
and GPA (R2=.160, F(4,183)=11.042, p <.05). Three other independent variables, Employment,
Income, and Living Arrangement were not statistically significant predictors of Grade Point
Average for undergraduate students major public university in the Southwest. The qualitative
interviews provided rich details on how light, moderate, and heavy media multitaskers juggle
their academic commitments in media saturated environments. The interviews revealed
various facets of how media and media multitasking preferences influenced where the students
studied, how they studied, and how well they studied as evidenced by their media use, gender,
age, and grade point averages.
Educational or scientific importance of the study
This study was significant in three ways. First, the study provided a framework and an
understanding of the relationship between multitasking preferences and academic
performance. Little is known about the impact of multitasking on college students. At best, past
findings have been mixed. Second, the study expanded the nascent literature in the areas of
multitasking, new media, and attention in the learning environment. Current literature has not
adequately addressed the impact of multitasking on the scholarship of teaching and learning
(Brooks-­­Gunn & Marx, 2008; Levine, Waite & Bowman, 2007; Lin, Lee, & Robertson, 2009).
Third, the study examined the implications on college students spending so much time on
media. Many experts believe that media multitasking comes at the expense of reading
(Anderson & Hanson, 2009), focused attention (Hallowell, 2005), and even driving fatalities
(Watson & Strayer, 2010).
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