The Correlation of Reading Preference, Technological Habits, and Multi-tasking with Creative and...

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; [email protected].

THE CORRELATION OF READING PREFERENCE 2

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


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


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,


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


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


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


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


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


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


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


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),


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,


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


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


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) = -


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


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


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.


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


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


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.


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Appendix


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.


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.

*


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.

*


Figure 4. Bar graph depicting the mean number of questions requiring quantitative reasoning

skills successfully completed by both younger (18 – 30 years of age) and older (31 years of age

and older) individuals on a college campus.

*

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