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Running head: THE CORRELATION OF READING PREFERENCE1
The Correlation of Reading Preference, Technological Habits, and Multi-tasking with Creative
and Higher Order Thinking
Jim Rubin and Ellen H. Williams
Union College
Author Note
Jim Rubin, Ed. D., Department of Education, Union College, and Ellen H. Williams,
Ph.D., Department of Psychology, Union College.
This research was partially funded with a faculty research grant awarded to both authors,
Jim Rubin and Ellen H. Williams.
Correspondence concerning this article should be addressed to Jim Rubin, 118 College
Street Park Drive, apt. #7, Barbourville, Kentucky, 40996; jrubin@unionky.edu.
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Abstract
This article examines relationships between individuals’ abilities to utilize creative and higher
order thinking processes with preferences for using traditional versus digital reading sources and
tendencies to multi-task. Participants were self-selected from faculty and students at a small
private college in Southeast Kentucky. Primary findings indicate that tendencies to multi-task
(engaging in more than two active behaviors simultaneously), degree to which participants use
digital technology, and preference for type of reading material did not impact one’s ability to be
creative or successfully solve higher order reasoning problems. Data also reveal that older
individuals (31 years and above) are less digitally focused, spend more time reading traditional
sources, and are more successful at completing quantitative problems requiring higher order
thinking skills.
Keywords: digital reading, creativity, higher order thinking, multi-tasking, digital learning
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The Correlation of Reading Preference, Technological Habits, and Multi-tasking with Creative
and Higher Order Thinking
With changes in lifestyle brought on by innovations in digital technology, teachers,
administrators, and parents alike are questioning the effect that these habits could have on a
student’s ability to focus. Teachers, especially, are faced with challenges and unknowns in
working with students who have grown up in a digital environment that some researchers warn
could be disabling important systems of brain development that relate to lack of exposure with
traditional reading habits (Wolf, 2007). In addition to the increase in digital resources, today’s
student tends to engage him/herself in numerous activities simultaneously, which may have a
deleterious effect on the capacity to successfully complete academic assignments (Abelson,
Ledeen & Lewis, 2008; Bauerlein, 2008; Carr, 2008; Jackson, 2008; Jacoby, 2008; Keen, 2007;
Postman, 1993; Shaughnessey & And, 1994; Siegel, 2008). The ability to focus on tasks and
assignments for extended periods of time is an important trait that is related to creativity and
higher order thinking (Weisberg, 1993), and it is these skills that are at the forefront of academic
goals. The importance of educating students to think critically and creatively was recognized
over 2000 years ago by Socrates (Plato, 2009), reworked in the 1950’s by Benjamin Bloom
(1956), and addressed in a recent study by Wagner (2010). Updated federal standards reflect this
philosophy, raising the bar for teachers to educate students to think critically and emphasize
creative problem solving (Standards, 2011). Research data show that students’ perceptions of
learning activities as being creative and meaningful are significant indicators of interest for
lessons (Vekiri, 2010). With full agreement on the significance for critical and creative thinking
on the part of administrators, teachers, and students, it is imperative to understand how
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capabilities to execute these skills may be compromised or enhanced as a result of exposure to
digital lifestyles, which is the motivation behind the current study.
There is an abundance of prior research and literature that have painted a dire forecast for
how exposure to modern day technology affects the capacity to learn. However, most of the
focus of the research has been directed to testing skills that are associated with recall of facts and
short term memory operations. The present study explores the correlation of technology use to
the ability to use creative and higher order problem solving skills. The hypothesis of the present
study is that individuals who report increased tendencies to multi-task and strong likelihood to
use modern day technology will not be at a significant disadvantage when confronted with tasks
that involve creative problem solving.
The current study integrates an assessment of creative and higher order thinking skills as
potential correlates with preferred reading text, habits to use digital technologies, and
involvement in multi-tasking behaviors. The present research accomplishes these goals via
quantitative research seeking to establish relationships between individuals’ abilities to use
creative thinking and quantitative/ literal reasoning with tendencies to multi-task and extent of
exposure to traditional reading versus digital sources. One of the primary objectives of this study
was to investigate potential correlations between creativity and higher order thinking skills and
individuals who have divergent digital and multi-tasking habits.
The need to maximize curriculum effectiveness to support creativity and higher order
thinking skills arises from a current state of affairs that worries many educators. One indication
of how well students enrolled in higher education are doing academically stems from opinions of
college professors who work with them on a daily basis. A recent study found that 94 percent of
college professors felt that their students were not prepared to write at a collegiate level (Sanoff,
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2006). In 2005, only 51 percent of high school graduates who took the ACT met the college-
readiness benchmark in reading, while an even more saddening percentage of only 21 percent
met the benchmark in all subjects combined (math, science, English, reading) (Bauerlein, 2008).
There are several aspects of this issue that will benefit from an increased awareness of the effects
that digital technology have on the cognitive ability of youth. One is the extent that technology
is embraced and utilized as a medium in the classroom. There is a current push to include
technology in a wider array of teaching resources, but could this contribute to a dulling of
cognitive potential by overexposure to the medium? Schools and culture alike have taken on the
promise that technology holds for education, out of both a need to improve a system that
constantly struggles to improve itself and a requisite to stay relevant with a generation that will
have it no other way. However, as schools adapt to keep abreast with the fast pace of
technological innovation, there is a need to make decisions concerning how technology is
implemented in the classroom that is based on an awareness of how digital habits are affecting
learning outcomes.
It is difficult for parents to modulate the extent to which technology plays a role in their
children’s lives, but knowledge about how this exposure could be affecting cognitive skills may
influence what actions some guardians decide to take. This may be especially relevant for how
technology is introduced into lives of children who have not yet begun traditional schooling, as
this is an important time period for developing cognitive skills and not influenced as much by
peer pressure. Current research indicates preschoolers are more likely to use a laptop than play
outside (Moses, 2012).
Another aspect concerns the degree to which teacher and parent preconceptions of
negative effects of exposure to technology have on student outcomes. The significance of
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teacher and parent expectations and the degree to which they are positively associated with both
students’ belief in their own abilities and academic outcomes is well documented (Beard, Hoy, &
Hoy, 2010; de Boer, Bosker, & van der Werf, 2010; Hinnant, O'Brien, & Ghazarian, 2009;
Jacobs & Harvey, 2010; Rubie-Davies, Peterson, Irving, Widdowson, & Dixon, 2010; Vekiri,
2010). Negative perceptions on the part of teachers and parents about the learning potential of
youth, due to a vast increase in habitual attention to digital technology, could have a deleterious
impact on student outcomes. In other words, regardless of whether claims about digital habits
impairing cognitive development are true, the negative expectations that result from them could
affect the potential for students to excel.
Reading trends have also been affected by the change in habits brought about with the
evolution of technological innovation, both by what is read (e-books versus traditional books)
and the manner in which reading is done (directed attention versus split attention). Additionally,
reading is morphing into a multi-tasking activity that utilizes the capacity of the internet to
follow any line of thought that may result from studying a particular subject (Wolf, 2007). The
extent to which these newly evolved reading habits may be contributing to a lesser capability to
focus on creative problem solving is of prime concern for all involved in the field of education.
Measuring creativity and the associative component of divergent thinking has been
successful in a number of prior studies (Feldhusen, Treffinger, Van Mondfrans, & Ferris, 1971;
Mumford, Baughman, Costanza, Uhlman, & Connelly, 1993; Plucker & Renzulli, 1999).
However, there is some discussion concerning the correlation of creativity with the ability to
generate superior performance in the context of timed measures, and whether metacognitive
factors are involved without regard to speed that can be used to legitimately characterize degrees
of creative ability (Wickes & Ward, 2006). Creative measures rely on the production of original
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thinking tasks on demand, in a testing environment that is removed from the natural
environment. The fact that some individuals summon the motivation to respond creatively in this
setting has been identified as one of the factors that portray creative functions (Runco, 1987;
Winner, 2000).
Research suggesting negative consequences of digital use.
While there is some hope for enhancing learning through a system that offers a multi-
media approach, several studies reveal that the data do not meet those expectations. In a recent
study college students were tested on ability to recall facts from two different versions of a
newscast. One version reported four stories while info-graphics and textual news ran across the
screen simultaneously. The other newscast ran the same four stories but without the added
material. Subjects that watched the pared down version did a better job of recalling specific facts
and details. Bergen, Grimes, and Potter (2005) concluded that the multi-message format
disrupted the attention capacity and students’ ability to absorb the material, thus impacting
memory retention and learning outcomes. The study tested two groups of students and their
ability to recall information from a lecture. One group was allowed to use laptops during the
lecture while the other group was permitted to use pen and paper, a more traditional note taking
strategy. Data indicate that students who used pen and paper scored significantly better on the
assessment following the lecture. These two studies provide data that suggest the potential for
both multi-tasking and digital use to impair cognition and memory retention.
In 1999, Zhu experimented with the effects of reading comprehension when using digital
sources. The issue was whether the number of web links within the passage would play a
significant role in distracting readers. Results indicated that the number of links correlated
strongly with a condition Zhu termed “cognitive overload.” In other words, the links offered too
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much information for the readers to assimilate concurrently with the task of comprehending and
synthesizing the main ideas of the narrative.
Ophir, Nass, & Wagner (2009) found that individuals who reported high use of digital
resources were more easily distracted and more likely to commit errors when asked to conduct
basic short term memory tasks related to spatial memory, rote memorization, and ability to
successfully complete a simple task. Similar research has focused strictly on short term memory
skills and has inferred comprehension differences solely from eye movement, as the patterns for
internet users tended to be more scattered and haphazard than traditional readers (Nielsen &
Pernice, 2009). More specifically, the eye pattern for reading digital material resembled the
shape of the letter F, indicating that material on the lower right portion of the page tended not to
be read.
In a recent meta-analysis, DeStafano and LeFevre (2007) reviewed 38 studies that
involved reading with digital technology. They reported that the increased potential of enriched
information offered by the internet was more than the human brain could effectively handle (also
see Miall & Dobson, 2001; Sweller, 1999). DeStafano and LeFevre suggested that the evolution
of the information delivery system was expanding at a pace that challenged the brain’s ability to
keep up. Thus, while the internet offers more information at faster intervals, the mind cannot
assimilate and make sense of the data.
Research suggesting positive consequences of digital use.
While not as prevalent as the amount of research suggesting negative consequences for
the integration of technology and education, there is evidence that the digital landscape holds
promise for enhancing the capability to learn in an academic environment. When the internet
was first introduced to the educational community in the 1980’s there was enthusiasm from some
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academic circles, exemplified by the literary theorists George Landow and Paul Delany.
Landow and Delany (2001) expressed the view that the internet provided a model for learning
that was better related to the experience of making associations with the material, while
empowering the reader to take more responsibility to challenge information, make personal
connections to the ideas presented, and follow related lines of questioning.
As mentioned above, early studies testing the ability of readers to answer questions based
on using either digital mediums or traditional material showed cognition problems for the
digitally focused groups (Miall & Dobson, 2001; Sweller, 1999; Zhu, 1999). However, one of
the confounding variables related to these studies involved the relatively new nature of computer
literacy for students that lacked regular exposure to it as a learning resource and the more
demanding task of assimilating a greater variety of material at a faster pace (Rouet & Levonen,
1996). It seemed while the brain had the ability to quickly adapt to the expanding rapid
informational sources available through the internet, there was a lag in the ability of those newly
activated systems of the brain to show gains in knowledge via traditional models of assessment.
A meta-analysis that focused on comparing which educational platforms were most effective
predicted that given additional time, people would become more literate with the digital medium
and the cognition lag would likely diminish.
Studies by multiple researchers (e.g. Kawashima, 2005; Mori, 2002) make an important
distinction between passive and active digital activities. Watching TV, movies, and casual web
browsing do not involve the attention and focus required by some video games and online
interactive activities such as gambling and stock trading. While some research warns that too
much time spent playing video games could cause atrophy in the development of frontal lobe
activity (related to communication and cognitive processes), other studies show a potential for
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regulated time spent at computer games to improve cognitive ability and multi-tasking skills
(Kearny, 2007; Rosser et al., 2007; Small & Vorgan, 2008). Participants who played games for
eight hours each week showed significant gains with an ability to successfully complete multiple
tasks simultaneously (see Kearny, 2007).
James Rosser and associates (2007) discovered an inverse relationship between
laparoscopic surgeons who played video games for more than three hours each week and the
number of errors made during surgical procedures. Specifically, results indicate that video game
playing surgeons made 40 percent fewer procedural errors, compared with surgeons who did not
play video games. Small and Vorgan (2008) recognized that “gaming in moderation could help
develop improved pattern recognition, more systematic thinking, and better executive skill” (p.
39); however, it is believed that the key terms within this statement are “in moderation.”
Small and Vorgan (2008) also report that the daily use of computers stimulated areas of
the brain that were unaffected by reading in the traditional sense. Results show the left side of
the dorsolateral prefrontal cortex, was more highly activated in subjects that were internet-savvy
compared with those that read text in the traditional fashion. However, even after five days of
practice for the subjects who were not heavy internet users, that part of the brain showed a
significant increase in activity. Their findings suggested that the sensitive nature of the brain’s
plasticity and the extent to which a relatively small amount of time spent with the computer
could affect brain function. Further research needs to address the extent to which digital
involvement can facilitate brain function or how much is too much.
From our current vantage point, which lies in the midst of the evolution of these new
cultural trends, it is difficult to cast a substantive verdict on the value or detriment of digital
habits, hence the disparity of results when trying to come to agreement on whether digital use is
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supportive or disruptive to educational outcomes. In an effort to address this disparity and work
toward better understanding of educational consequences, the current study integrates an
assessment of creative and higher order thinking skills as potential correlates with preferred
reading text and involvement in multi-tasking behaviors. In taking a quantitative approach, the
research seeks to establish relationships between individuals’ abilities to use creative thinking,
quantitative reasoning, and literal reasoning with tendencies to multi-task and extent of exposure
to traditional reading versus digital sources. The objectives are to test for potential relationships
that may bring to light the advantages and/or disadvantages of digital use, specifically in regards
to reading material, and how digital use may impact students’ and educators’ abilities to
successfully solve problems involving creative aptitude and higher order thinking processes.
Method
Participants
The sample was drawn from students, faculty, and staff at a private liberal arts institution
in southeastern Kentucky. Participant selection for Phase I of the study was based on email
correspondence to all members of the college community. Responses from this phase of study
involved 151 electronic submissions, 47 males and 104 females, and all participants were at least
18 years of age. Participants in Phase I were compensated for their participation with coupons
from Dairy Queen and a $5.00 gift certificate valid at the college book store. Participants for
Phase II were recruited via both email and telephone requests. Participants in Phase II were
compensated with $10.00 in cash and a coupon to the local Dairy Queen, in addition to their
compensation for participation in Phase I.
For reasons explained below (see discussion section), participants were grouped into two
groups based on age: (1) 18 – 30 years of age, and (2) 31 years of age and older, some greater
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than 60 years of age (NMales 18 – 30 years = 27; NMales 30 and above = 20; NFemales 18 – 30 years = 55; NFemales 30 and above
= 49). Demographic data, specifically age, were collected using bracketed categories (oldest
category was ’60 and above’).
Procedure
During Phase I, participants were asked to complete a survey designed by the researchers
to measure the following variables: (1) reading material preferences (tendency to prefer digital
versus traditional sources), (2) amount of time spent engaged in reading, for either pleasure or
work, and (3) the tendency to multi-task, which was based on the likelihood to engage in
multiple behaviors at the same time. The purpose was to gather data that presented a profile that
documented to what extent participants used technology on a habitual basis, and to what extent
those habits correlated with reading habits. This was an eight question, online, multiple-choice
assessment administered via Survey Monkey©. Based on data collected from the online survey,
participants were ranked based on total number of hours spent reading, preference for type of
reading material, tendencies to multi-task, and total number of hours spent working with digital
media. In order to maximize the differences in the habitual use of technological and reading
habits between the two samples needed for the study, forty-five individuals were chosen from
approximately the upper and lower thirds of the sampling population to participate in Phase II;
13 males and 32 females, ranging in age from 18 to 60 and above (NMales 18 – 30 years = 9; NMales 30 and
above = 4; NFemales 18 – 30 years = 20; NFemales 30 and above = 12).
Participants recruited for Phase II of the study were divided into two primary groups.
Group 1 (N = 20), labeled multi-tasking/digital, consisted of individuals whose data in Phase I
reported high reliance and use of digital resources, a strong tendency to multi-task, and spent less
time reading (either digital or traditional sources) for either pleasure or work. Group 2 (N = 21),
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labeled high read, consisted of individuals who preferred to engage in reading behavior using
more traditional forms, with low reliance on digital sources, tended to multi-task to a lesser
degree, and reported more time spent reading for either pleasure or work. Four individuals,
included in the sample for Phase II, were classified as ‘both,’ such that their reported scores
placed them in both categories. These individuals were digitally-oriented, high multi-taskers, and
spent a lot of time reading traditional as well as digital sources for pleasure and work.
According to the Geneplore model, the process of creativity involves a generation stage
(divergent thinking) and an exploration stage (convergent thinking) (Kaufman, 2012; Korba,
1993). The current study uses a combination of instruments to address both components of the
creative process. The Abbreviated Torrance Test for Adults (ATTA) is a well know measure that
targets divergent thinking and other problem solving skills (Cho, Nijenhuis, van Vianen, Kim, &
Lee, 2010). The Quantitative and Literal Reasoning Assessment (QLRA) is a behavioral
measure created for the purpose of measuring convergent thinking by the authors of the present
study to test critical thinking, quantitative and literal reasoning skills, and creative problem
solving. The QLRA was tested during a pilot study during the fall of 2010 with a group of seven
students and one faculty member. Based on results from the pilot study, decisions were made as
to the reliability and validity of the questions that were eventually used in the study.
During data collection for Phase II, participants were asked to attend a one-hour session
on the college campus where they completed two assessments. The first assessment, titled the
Quantitative and Literal Reasoning Assessment, contained 11 questions. Students were allotted
forty minutes for completion, followed by a five minute break. Participants then completed the
Abbreviated Torrance Test for Adults (ATTA) (Goff & Torrance, 2002; Scholastic Testing
Service, Inc.). This assessment consisted of three questions with three minutes allotted for each,
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totaling nine minutes of testing. These three questions measured individuals’ abilities to think
creatively in verbal and figural contexts, measuring fluency, originality, and flexibility of
thinking. This assessment included a verbal section: "thinking creatively with words," and a
nonverbal or figural section: “thinking creatively with pictures.” Prior research indicated that the
reliability coefficient for assessing both components of the ATTA was greater than 0.90
(Sweetland & Keyser, 1991). According to Treffinger (1985), test-retest reliabilities of the
various sub dimensions commonly lay between 0.60 and 0.70. The ATTA consisted of four
norm-referenced abilities: 1) fluency: the ability to produce quantities of ideas which are relevant
to the task instruction; 2) originality: the ability to produce uncommon ideas or ideas that are
totally new or unique; 3) elaboration: the ability to embellish ideas with details; and 4)
flexibility: the ability to process information or objects in different ways, given the same
stimulus (Abbreviated Torrance Test for Adults: Goff & Torrance, 2002).
All data were collected following strict procedures with the researcher for each session
following a written script and protocol. Data collection for Phase I ran from November 5, 2010
to January 13, 2011. Data collection for Phase II began on February 21, 2011 and ended on
April 16, 2011.
Data analysis
Primary analyses for phase II were conducted between the two sub-groups described
above: (1) multi-tasking/digital and (2) high-read. Secondary analyses involved age
classification and also resulted in two groups, younger (18 – 30 years of age) and older
participants (31 years of age and older).
Scoring of the ATTA followed the procedure outlined in the Abbreviated Torrance Test
for Adults Manual (Goff & Torrance, 2002). Independent samples t-tests, adjusting for groups
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of different size, were used to calculate mean group differences of the cumulative score on the
Quantitative and Literal Reasoning Assessment. Using data collected from the Quantitative and
Literal Reasoning Assessment additional comparisons were made on three dependent variables:
(1) quantitative reasoning: questions measuring mathematical skills and applied math, (2)
creative problem solving: questions that required participants to design creative alternative
solutions to proposed situations, and (3) literary reasoning: questions that required solving word
association problems and recognizing relationships among variables. Inter-rater reliability for
scoring of the ATTA was assessed using Pearson Product Moment Correlation Coefficient.
Independent samples t-tests, adjusting for groups of different size were also used to
compare the two subgroups multi-tasking/digital and high read sub-groups on the ATTA,
specifically, assessing quantitative differences across a variety of mental characteristics relevant
to creativity and higher order thinking. Branching from this analysis, the individual components
of this assessment: fluency, originality, elaboration, and flexibility were compared between
groups. Additional analyses compared participants ranging from 18 to 30 years of age to
participants 31 years of age and older, across various dimensions, including time spent reading,
multi-tasking behaviors, and digital habits, as well as results from the ATTA and the
Quantitative and Literal Reading Assessment.
Results
As described above, the eight question multiple choice survey used in phase I of the study
provided data regarding digital or traditional reading material for pleasure and for academic
purposes, amount of time spent engaged in reading behavior, amount of time spent in a variety of
leisure activities, and amount of time spent performing activities at the same time, i.e. likelihood
to engage in multi-tasking behavior. Twenty participants who reported strongest tendencies to
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multi-task, use digital resources to a greater extent, and read less were placed in the multi-
tasking/digital group and twenty-one participants who reported strongest tendencies to read
traditional material, multi-task less, and spend less time using digital resources were placed in
the high read group. There were four individuals who scored high in both categories. A Pearson
Product Moment Correlation was computed, revealing a significant negative correlation between
the groups, suggesting that the two groups were in fact composed of different individuals who
did not report similar characteristics in regards to reading and multi-tasking behavior. This
strong, negative correlation allowed us to systematically divide our participants into two groups
for additional analyses. Furthermore, this relationship indicates that individuals who read more
tended to multi-task less (r(38) = -0.611, p < 0.001. Seven participants were eliminated from
this statistical test: three participants failed to answer all pertinent questions necessary for
calculation of the multi-tasking index and four participants’ self-reported data met the criteria for
both the multi-tasking/digital and high-read groups; thus, only 38 individuals were included in
this statistical test). Data belonging to these participants was included in the following analyses
where appropriate. Data from only one participant was excluded from analyses as this individual
listed another language as his native language.
There were no significant differences found when comparing the multi-tasking/digital
group to the high-read group in regards to cumulative score on the Quantitative and Literal
Reasoning Assessment (t(39) = -1.42, p > 0.05; MMD = 1.39; MHiR = 1.61; d = 0.46). There was a
trend toward significance when comparing the multi-tasking/digital individuals to those
classified as high readers, revealing higher mean scores in literary reasoning for the individuals
in the high read group (t(39) = -1.73, p = 0.09; MMD = 0.46; MHiR = 0.58; d = 0.55; see figure 1).
The two groups did not differ from one another in regards to quantitative reasoning (t(39) = -
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0.70, p > 0.05; MMD = 0.55; MHiR = 0.62) or creative problem solving (t(39) = -0.44, p > 0.05;
MMD = 0.38; MHiR = 0.41). Four individuals met the criteria for both groups, thus these four
participants were not included in these group level analyses. Additionally, the two groups did
not significantly differ from one another when comparing cumulative scores on the ATTA,
although the mean for the high read group was slightly higher (t(39) = -0.64, p > 0.05; MMD =
68.0; MHiR = 71.1; d = 0.2).
For further analyses, individuals were split into two groups based on age: those aged 18
to 30 years (N = 29) and those 31 years of age and older (N = 16). Before examining the
assessments, it was of interest to see if there were overall differences by age in regards to time
spent reading and one’s tendency to multi-task. Based on data collected from Phase I, older
participants who participated in Phase II, those aged 31 years of age and older, were significantly
more likely to report involvement in reading behavior and spent more time reading for either
work or pleasure when compared to the younger participants, those ranging in age from 18 to 30
years of age (t(43) = -4.31, p < 0.001; M18 – 30 years = 3.45; M31 and above = 4.90; d = 1.37; (see Figure
2). Furthermore, we find that older participants are significantly less likely to engage in multi-
tasking behaviors (t(40) = 4.21, p < 0.001; M18 – 30 years = 2.41; M31 and above = 1.77; d = 1.41; (see
Figure 3). Three participants were eliminated from this statistical test due to pertinent questions
necessary for calculation of the multi-tasking index being left blank or unanswered; thus, only 42
individuals were included in this statistical test. These significant differences by age led to
additional analyses testing for performance differences between the two age groups.
When comparing performance on the Quantitative and Literal Reasoning Assessment,
although not significant, we find that older participants, those aged 31 and above, tend to
perform better (t(43) = -1.79, p = 0.08; M18 – 30 years = 1.38; M31 and above = 1.64; d = 1.04) on this
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assessment. More specifically, older participants out performed younger participants when
asked to complete questions involving quantitative reasoning (t(43) = -2.47, p = 0.018; M18 – 30 years
= 1.00; M31 and above = 1.44; see Figure 4). Using these same groupings, we did not find significant
differences by age on the ATTA, although again we are seeing that older participants are earning
higher scores (t(43) = -0.29, p > 0.05; M18 – 30 years = 68.76; M31 and above = 70.19; d = 0.09). Thus,
with a larger sample to compare differences in higher order thinking abilities according to age,
data may reveal significant results.
Inter-rater reliability was assessed for the calculated scores on the Abbreviated Torrance
Test for Adults. Raters followed the instructions outlined in the Abbreviated Torrance Test for
Adults Manual for grading of all parts of the assessment. Both raters graded 20 completed
assessments, compiling 44.4% of the total sample. Reliability was found to be very high for all
sections of this assessment (r = 0.93, p < 0.001).
Discussion
As evidenced in the literature review, there is ample support to identify an inverse
relationship between individuals who tend to multi-task and respective short term memory skills
(e.g. Ophir et al., 2009). The present study sought to add to the existing literature by examining
potential relationships between multi-tasking, daily use of digital technology, and tendencies to
read on a daily basis, with creative and higher order thinking skills. Results in the present
research indicate no significant differences for the dependent variables, including scores on the
ATTA, scores on the Quantitative and Literal Reasoning Assessment, as well as the individual
sub-dimensions of each instrument. It was hypothesized that creative and higher order thinking
skills may not suffer to the same degree that factual recall and short term memory skills seem to
do as a result of growing up in the digital age, and the data support that contention. One of the
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prime reasons for conducting the present study was the lack of prior research that made a
distinction between short term memory skills and higher order thinking. Given a clear
distinction between the two groups tested (high read and multi-task/digital), and the variety of
instrumentation used, findings indicate that the skill sets necessary for being creative and using
higher order thinking may not be compromised by daily habits that reinforce multi-tasking
behavior and shortened periods of focus on any single topic.
Participants in the two groups (high read and multi-task/digital) were distinguished by a
difference in the use of traditional reading materials, and findings indicated that those with
stronger reading did not score significantly better on the assessment. The habits formed by
reading certainly have a relationship to the development of overall intellect and the exercise of
complex thinking that forms the basis for creative and higher order thinking. Johnson (2006, p.
22) spoke about the mental work involved in processing and storing information when reading,
networking synapses in new patterns that support use of knowledge. Small and Vorgan’s (2008)
research show that use of digital technology activates areas of the brain distinct from those that
are stimulated by traditional reading habits, calling into question how our technological lifestyles
may be detrimental in some ways and advantageous in other ways. Further illustrating this point
is a study in 2001 that compared respondents’ abilities to recall details about plot, setting, and
imagery after reading literature on either traditional or digital sources (Miall & Dobson, 2001).
Results from this research contend that the digital medium was a distraction, contributing to a
diffusion of focus toward recalling information from the reading. A study that sought to measure
respondent’s abilities to extrapolate deeper meaning from the story and create new material
based on their perceptions might not have found similar results.
THE CORRELATION OF READING PREFERENCE 20
Results of the present study reveal a clear distinction between younger participants (those
ranging in age from 18 to 30 years of age) and older participants (those 31 years of age and
older) in terms of their tendency to use traditional reading sources and their tendency to multi-
task. Data reveal that participants aged 31 years and older reported a lower frequency of
technology use during daily life. Additionally, older participants, as defined for the present
study, were more likely to read for pleasure and less likely to multi-task. The motivation to test
for differences between these groups stems from the hypothesis that people who have grown up
with digital technology and have strong multi-tasking habits will be less successful when faced
with quantitative and literary problems to solve, based on recent prior research (Abelson,
Ledeen, & Lewis, 2008; Bauerlein, 2008; Carr, 2008; Jackson, 2008; Jacoby, 2008; Keen, 2007;
Postman, 1993; Shaughnessey & And, 1994; Siegel, 2008). In order to examine digital use in
both college students and educators, division of our participants into two age groups allowed us
to examine preferred reading material, digital use, and creativity in both a traditional age college
student sample and an older sample, representative of most educators. The cut off age of 30
years was both an intuitive and a statistical decision. The differences in multi-tasking
tendencies, time spent reading, and digital habits proved to be significant factors in the analyses
of data during Phase I of the study when using 30 years of age as a defining line. Additionally,
in order to keep parity in the numbers for each group, it was significant not to lower or raise the
cut off age.
In conjunction with recent research, the present study found that younger individuals,
who were significantly more likely to prefer digital media, engage in multi-tasking behaviors,
and spend less time reading traditional sources, scored significantly lower on the quantitative
measure for higher order thinking skills. Research by Prensky (2001) showed a generational gap
THE CORRELATION OF READING PREFERENCE 21
between Digital Immigrants (those born and raised prior to the advent of the computer) and
Digital Natives (those born and raised amidst digital technology) with respect to multi-tasking
skills. To the extent that quantitative reasoning skills depend on a single focus of concentration,
results in the present study may reflect a negative repercussion of exposure to digital media and
the subsequent tendencies to multi-task. This study focused on quantitative skills specifically
associated with higher order thinking, and it is important to note that multi-tasking may not have
negative effects on using more factual based mathematical skills. A further limitation of results
indicating differences in quantitative reasoning stems from the instrument devised for the study.
While pre-tested prior to the actual study, future work in this area would do well to affirm that
questions used in measurement correlate strongly with higher order mathematical reasoning
skills.
A limitation of the present study that will confound anyone trying to measure creativity
and higher order thinking skills with quantitative instruments in a short term testing environment
is the validity of the data, and whether results gained from instruments assess the constructs.
Creativity and higher order thinking manifest in many different forms and contexts; however,
this study chose to focus on those behaviors that are expected within a classroom teaching
environment. The instruments used to measure those variables, as well as the manner in which
the tests were organized, do have close association with original thinking and problem solving
that is expected within a classroom environment, but should not be construed to have
implications for a broader concept of the terms.
It is important to note that the lack of significance found when comparing creativity
scores on the ATTA indicates a need for qualification in passing judgment on the potential
detriment of multi-tasking and using digital sources to a high degree, while favoring traditional
THE CORRELATION OF READING PREFERENCE 22
reading sources as a model for study. While short term memory skills may be at risk for
individuals who exhibit high digital characteristics (Nielsen & Pernice, 2009; Ophir et al., 2009),
it appears that there is no significant effect on creativity and higher order thinking skills. Both
sets of skills are important components for learning, but it is creativity and higher order thinking
which have been viewed as having greater value as end products of the academic experience.
Therefore, it is important for the academic world to also understand the potential benefits that
accompany the use of digital media and to further investigate how these resources may
contribute to helping educators succeed in achieving educational goals and learning outcomes.
THE CORRELATION OF READING PREFERENCE 23
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THE CORRELATION OF READING PREFERENCE 30
Figure 1. Bar graph comparing the multi-tasking/digital group to those classified as high readers
for the mean number of questions requiring literary reasoning that were successfully completed.
THE CORRELATION OF READING PREFERENCE 31
Figure 2. Bar graph depicting the mean amount of time participants on a college campus, aged
18 – 30 years and 31 years of age and older , spent engaged in reading behavior on a daily basis.
Reading refers to active reading of any type of media.
*
THE CORRELATION OF READING PREFERENCE 32
Figure 3. Bar graph depicting the mean amount of time participants on a college campus, aged
18 – 30 years and 31 years of age and older, spent engaged in multi-tasking behavior on a daily
basis.
*