CONTINUOUS PARTIAL ATTENTION AS A PROBLEMATIC TECHNOLOGY
USE: A CASE OF EDUCATORS

Mehmet FIRAT

Anadolu University

Abstract

Continuous Partial Attention is a current concept open to research which, besides
multitasking, intensely occupies the agenda of education, communication and cognitive
psychology. The purpose of the present study was to determine educators’ continuous partial
attention. In line with this purpose, the research data were collected from 109 educators inhigher education from different age groups and from four different countries with the use of aquestionnaire made up of two sections and seven questions. The findings obtained in the
study revealed that the educators’ Continuous Partial Attention did not significantly differ
with respect to their technology use efficacies, their ages or their countries. In addition, it was
found out that the educators’ Continuous Partial Attention differed statistically significantly
depending on the fields they worked in. Based on this, it could be stated that educators
working in the field of educational technologies encounter with Continuous Partial Attention
more frequently than educators working in other fields. At the end of the study, several
suggestions were put forward.

Keywords: Educators, Continuous Partial Attention, multitasking

INTRODUCTION

Continuous Partial Attention (CPA), one of the current concepts open to research regarding
interaction with technology, occupies the current agenda of cognitive psychology,
communication and education. This concept, first introduced in 1998 by Linda Stone (2007),
a former manager of Apple and Microsoft, is considered to be one of the important effects oftoday’s information technologies on individuals. Stone defines this concept as trying tofollow and deal with everything while, in fact, failing to focus on anything. According toFriedman (2001), what CPA means is that the individual replies to his or her e-mails while, atthe same time, the phone rings and/or he or she chats with his or her children. As, in such acase, the individual is under a bombardment of interactions, he or she can focus only partiallyon each of these interactions (Virilio, 2003).

In his book titled Everything bad is good for you: How popular culture is making us smarter?
Steven Johnson defines CPA saying, "this generally involves synthesizing superficially thedata obtained, collecting the related information and going on with the following data flow”(2004, p.59). As can be understood from this definition, Johnson regards CPA as a kind of
multitasking. According to Johnson, this situation provides people with a wider network,
while, at the same time, it involves the risk of preventing from learning to fish. In otherwords, the individual has the opportunity to revise a wider range of data in a shorter period oftime, while he or she is likely to lack the knowledge of how to establish connections between
the data. This could prevent the individual from focusing on a certain field.

In related literature, it is seen that multitasking and CPA are frequently confused or discussed
comparatively. In literature, CPA is reported to be a concept related to “multitasking”, or also
known as dual tasking.The concept of multitasking is a real process that requires
simultaneous fulfillment of two or more tasks (talking on the phone and driving)(Appelbaum, Marchionni and Fernandez, 2008). However, CPA is a concept that refers tointeraction and communication with everything while failing to focus on anything in realterms. CPAleads to a high level of stress in an individual’s brain (Small and Vorgan, 2008a).
As a result, the Internet-addicted individual does not have time to respond, to think or makeconscious decisions but constantly experiences conflicts and expects to make new friendswith artificial sincerity and to hear the latest news. Soon, this could become an irresistible
situation.

According to Stone (2007), CPA and multitasking are two different attention strategies: theformer being motivated by the desire for not missing anything and the latter by the desire forbeing more successful and more effective. In other words, in CPA, the individual
permanently watches for an opportunity to meet someone new, to take part in a new activity
or to get the latest news by being in constant connection at any time. Similarly, according toKirsner (2005), CPA is a situation in which the individual places orders via his or her mobile
phone in front of the computer while, at the same time, he or she follows the papers presented
at an on-going conference. This situation is like being aware of a number of things
simultaneously and drawing attention to a newly-received e-mail or to a ringing phone.

In order to emphasize the difference between CPAand multitasking, Small and Vorgan(2008b) pointed out the motivation of multitasking and CPA; accordingly, while theindividual tries to improve the effectiveness and productivity in multitasking and has an
objective for each task, he or she is in a struggle for getting a chance for a connection at any
time when his or her mind is partially stimulated and when this becomes constant. Thismeans being in a partial connection with everything everywhere via CPA. Similarly,
Benbunan-Fich (2012) pointed out that CPA occurs due to the desire for not missing anything
and that multitasking occurs due to the need for being more prolific and more productive.

According to Small andVorgan (2008a),when CPA is maintained, the feelings regarding selfworth and control felt are condemned to be destroyed at some point. One of the reasons isthat our brains are not structured in a way to make such an observation in the long term. On
the other hand, the concept of multitasking behavior should be considered within its own
contexts as a variable developing, at least partially, based on rich information because themultitasking situations contain a natural adaptation of the person to the rich information
environments.

As can be understood from the limited number of studies reported in related literature, CPA isregarded as a concentration problem which is created by current information andcommunication technologies and which is likely to influence almost every moment of
individuals’ daily lives. On the other hand, there is no research conducted directly on CPA inliterature. According to Appelbaum, Marchionni and Fernandez (2008), “there is no refereed
study on continuous partial attention” (p. 1318). In this respect, the present study is thought tobe the first step to fill this gap in literature.

Educators have a wide range of preference for the technological tools that provide learning
experiences. According to Roberts (2009), although there is a high level of resistance inhigher education, technology has now become an indispensable part of daily life. Educators
working in close connection with technology not only have the potential to encounter the
CPA problem, but also are expert both on technology use in education and on the effects ofthis use on individuals. In addition, educators have the responsibility for training individuals
who can constantly follow the technological developments and who have the ability toaccess, produce, share and use information effectively (Akkoyunlu and Kurbanoğlu, 2003).
Educators who are engaged with education technologies as required by their fields of work
have a place which could allow examining CPA. Therefore, it is quite important to determine
educators’ CPA. Thus, the present study could contribute to future studies to be conducted tohelp both educators and students cope with CPA.

Purpose of Study

The main purpose of the present study was to determine educators’ continuous partial
attention. For this purpose, the following research questions were directed:

1. To what extent do educators encounter distractionwith continuous partial attention(CPA)?
2. Is there a significant relationship between educators’ continuous partial attention anda. their countries,
b. their ages,c. their fields andd. their technology use efficacies?

METHOD
This part introduces the participants of the study, the data collection tool used for research
and analysis of the research data. In the study designed with the survey method, quantitative
data were used.
Participants
In order to determine the participants of the study, the purposeful sampling method wasapplied. It was thought that the educators selected for the examination of their CPA, which isa concept related to technology use, were relegated to those who used the Internet. The
questionnaire form developed was transferred into electronic format. The electronicquestionnaire form was sent to seven e-mail accounts created in different fields of education
across 20 countries. In total 140 educators responded to the survey. Because of the missing
data 31 responses were eliminated. As a result, 109 valid returns were utilized for thequestionnaire delivered to educators. The questionnaire was made up of two sections andseven questions. There were four questions related to the demographic backgrounds of theparticipants in the first section and three 5-point Likert-type questions regarding CPA in thesecond section.

The participants of the study were 109 higher education educators from four different
countries and from different age groups. Of all the participants, 42 of them were from USA,63 from Turkey, two from Canada and two from Iran. The age, technology usage efficacy andprofession demographic backgrounds of the participants are presented in Table1below.
Table 1. Demographic Backgrounds of the ParticipantsFrequency (f)Percentage (%)

20-50

64

58.7

50and over

45

41.3

Inefficient

21

19.2

Average14

12.8

Efficient

74

67.9

Educational Technologies

64

58.7

Other Fields (Science, foreign

45

41.3

Age

Technology Use Efficacy

Profession

languages, mathematics, special
education and so on.)As can be seen in Table 1, the ages of 58.7% of the participants ranged between 20and 50.
This demonstrates that most of the participating educators belonged to the middle-age group.
According to the views of the participating educators, they had quite a high level oftechnology use efficacies. Of all the educators, 67.9% of them considered themselves to be“efficient” in terms of technology use efficacy. When the professions of the educators
participating in the study were taken into consideration, it was seen that 58.7% of them

worked in the field of Educational Technologies and 41.3% of them in the others fields ofeducation (science, foreign language, mathematics, special education and others).
Data Collection Tool and Data Collection Process
As the data collection tool in the study, the questionnaire of “Continuous Partial Attention”
developed within the scope of the study was used. The questionnaire was made up of two
sections and seven questions. There were four questions related to the demographic
backgrounds of the participants in the first section and three 5-point Likert-type questions
regarding CPA in the second section.
For the development of the items in the questionnaire, studies reported in related literatureand experts’ views were used. First, for the face and content validity of the questionnairedeveloped in line with the related literature, it was presented to two academicians expert in
the field of Educational Technologies, and the items were revised and corrected based on theexperts’ recommendations. The Continuous Partial Attention Questionnaire was developed in
two languages: Turkish and English. For the translated version of the questionnaire, an
educator from the Department of English Language Teaching was asked for help. In thesecond section of the questionnaire, the translated and original versions of three questions
regarding CPA are presented in Table 2 below.
Table 2: Translated and Original Versions of Three Questions Regarding CPA
English Items

Turkish Items

I constantly follow and get engaged with

Teknolojiylesüreklibirizlemeveuğraşiçerisindeyim.

technology (While following the news on TV, at(TV'denhaberleritakipederkenbirtaraftan e-

the same time, reply to my e-mails, chat with mymaillericevaplamabirtaraftanarkadaşlasohbetisürdürm

friends and answer the phone).

evegelentelefonacevapvermedurumu).

I want to stay in constant connection at any time

Hiçbirşeykaçırmamakiçinherhangibirzamandasüreklib

not to miss anything (I constantly wait for anağlantıhalindeolmakistiyorum. (Yenibirhaberalmak,

opportunity to get the latest news, meet someone

yenibiriyletanışmakveyayenibiretkinliğekatılmakiçins

new or join a new event).

üreklibirkollama/beklentiiçindeolmadurumu).

I pay partial attention to what I'm doing while

Teknolojiylesüreklibirizlemeveuğraşiçerisindeikenger

following and getting engaged with technologyçekteyaptığımşeyedikkatimi tam veremiyorum. (Her(while trying to communicate and interact withşeyleiletişim,everything, I fail to focus on anything in real

etkileşimhalindeolmakisterkengerçekanlamdahiçbirşe

sense).

yeodaklanamamadurumu).

In order to reinforce the comprehensibility of the questionnaire items, a pilot study was
conducted with three teachers, one teacher of Information Technologies, one teacher of
Turkish Language and one teacher of English Language. With the pilot application, thequestionnaire items were revised, and the survey validated.
For the collection of the research data, the e-mail lists that the educators used for sharing
were used. Three international e-mail lists and four national e-mail lists, seven in total, whichwere used in such fields as “Educational Technologies”, “Science”, “Elementary School
Teaching”, “Special Education” and “Mathematics Education”, were used. The online
Continuous Partial Attention Questionnaire was transferred into Google documents anddelivered to the participating educators via the e-mail lists.
Data Analysis
For the analysis of the data collected in the study, qualitative and quantitative analysis
techniques were used. After the Kolmogorov-Smirnov Z normality test it was seen that thedata collected weresignificantly differed from normal distribution [D(109)=1.812, p<.05].
Therefore, Kruskal-Wallis H test was applied instead of a one-way ANOVA, and theMann-Whitney U test was run instead of independent samples two-sample t-test. Thus, in thesecond section of the questionnaire, for the analysis of the scores obtained related to the items
regarding CPA, the Kruskal-Wallis H test and the Mann-Whitney U test were applied.
Descriptive statistics like mean, standart devision and frequenty was used to determine what
extent educators encounter distraction with continuous partial attention (CPA). A MannWhitney U test and Kruskal-Wallis H test were run to examine relationship between
educators’ continuous partial attention and their countries, their ages, their fields and theirtechnology use efficacies. For the analysis of the quantitative data collected in the study, theSPSS 15.0 package software was used.
FINDINGS
In this section, the findings were obtained and summarized under two headings according to
the research questions directed in the study. Data were collected to determine whether thedata collected met the parametric test conditions. The first condition related to the applicationof the parametric tests, whether the data had normal distribution or not, was examined. The
means of the scores assigned to the three items found in the second section of thequestionnaire regarding CPA were taken as CPA scores. Figure 1 below demonstrates thenormal distribution chart regarding the CPA scores.

Figure 1. Normal Distribution Chart
30

20

10

0
0.00

1.00

2.00

3.00

4.00

5.00

6.00

As can be understood from the normal distribution chart and the normal distribution curve,
the data collected within the scope of the study had a left-skewed distribution compared tonormal distribution. As presented in Table 3 below, when the data set was examined, because
the kurtosis was higher than three and because the leptokurtosis and kurtosis were negative,
the measures had a left-skewed distribution.
Table 3: Descriptive StatisticsN

Mean

Standard deviation

Kurtosis

Skewness

Min

Max

109

3.42

.84

.152

-.652

1

5

In order to test whether the data had a normal distribution or not, the Kolmogorov-Smirnov Z
Test was applied. As a result of this test, it was seen that the data with a mean of 3.42 and astandard deviation of .84 significantly differed from normal distribution [D(109)=1.812,
p<.05]. As the data did not have a normal distribution, the first one of the parametric test
conditions was not achieved. Therefore, for the analysis of the data collected, non-parametrictests were used. In this way, for the analysis of the data, the Kruskal-Wallis H testwas appliedinstead of one-way ANOVA, and the Mann-Whitney U test was run instead of independent
samples two-sample t-test.

To what extent do educators encounter CPA?

In order to evaluate the educators’ approaches to CPA, various statistical methods wereapplied. For this purpose, first, the educators’ mean scores regarding CPA were examined.
Table 4 below presents the mean scores for each item.

Table 4: Mean Scores for Each Item
Items

Mean (X)

1. I constantly follow and get engaged with technology.

3.58

2. I want to stay in constant connection at any time not to miss anything.

3.41

3. I pay partial attention to what I'm doing while following and getting 3.26
engaged with technology.
Mean

3.42

As can be seen in Table 4, the mean scores for each item were quite close to one another.
According to the educators’ scorings, the highest mean score (3.58) belonged to the first item
and the lowest mean score (3.26) to the third item. Depending on this finding, it could bestated that all the participating educators experienced CPA (X=3.42). In order to examine theeducators’ mean scores for the three items regarding continuous partial attention with respect
to their demographic backgrounds, Table 5 below was prepared.

Table 5: Participants’ CPA Scores with Respect to their Demographic Backgrounds
Variables

Mean (X)Standard Deviation
(SD)

Age
20-50

3.40

.82

50 and over

3.45

.86

Inefficient

3.57

.81

Average

3.42.85

Efficient

3.19

.86

Educational Technologies

3.68

.62

Other Fields (Elementary School

3.05

.97

USA

3.30

.86

Turkey3.49.81

Technology Use Efficacy

Profession

Teaching, Science, Foreign
Language, Mathematics, Special
Education and so on)
Country

As demonstrated in Table 5, the educators who considered themselvesto be efficient in termsof technology use had higher CPA scores than those who considered themselves to beinefficient. In addition, it was striking that the educators working in the field of Educational
Technologies had higher scores of continuous attention than those working in other fields.

This demonstrates that the educators working in the field of Educational Technologies
encountered with the CPA problem more frequently.

Is there a significant relationship between the educators’ CPA and their countries, ages, fields
and their technology use efficacies?

In order to determine whether the educators’ CPA differed with respect to their fields andtheir countries, the Mann-Whitney U test was applied. Due to the low number of theeducators participating in the study from other countries except for USA and Turkey, thesetwo countries were selected as independent samples. Table 6 below presents the results of theMann-Whitney U test.

Table 6: The Mann-Whitney U Test Results with Respect to the Variables of Country andProfession

Variable GroupsnMean Rank

Country

42

49.52

Field

USA
Turkey63

55.32

Educational

64

63.39

Technologies

Age

Other

45

43.07

20-49

64

53.73

50 and over

45

56.80

M-Whitney U

Z

p

1177

-.964

.333

903

-3.34

.001

1359

-.505

.614

As can be seen in Table 6, there was no significant difference between the educators’ CPA
and their ages or countries. This result demonstrates that there was no significant relationshipbetween the educators’ CPA and their ages or countries. However, when the educators’ CPAs
were examined with respect to their fields of work, a statistically significant difference wasfound (p<.05). Depending on this finding, it could be stated that the educators working in thefield of Educational Technologies encountered CPA more frequently than those working inother fields. The reason for this could be the fact that educators working in the field of
Educational Technologies use technology more frequently as required by their field.

In order to determine whether the educators’ CPA differed depending on their technology use
efficacies, the Kruskal Wallis H test was used. Table 7 below presents the Kruskal Wallis H
test results with respect to the technology use efficacies of the participating educators.

Table 7:Kruskal Wallis H Test Results with Respect to the Variable of Technology Use
Efficacy

VariableGroupsn

Mean Rank

Inefficient

21

58,55

Efficient

72

54,35

Average

1445,39

Chi-Square

p

1177

,455

Technology Use
Efficacy

According to the results presented in Table 7, it is seen that the educators’ CPA did not
significantly differ with respect to their technology use efficacies (p>.05). In other words, thisfinding demonstrates that there was no significant relationship between the educators’ CPA
and their technology use efficacies. The reason for this could be the fact that individuals who
can use technology well consider themselves efficient in technology use.

CONCLUSION

The present study aimed at finding answers to two research questions regarding educators’
CPA. The first research question was related to the extent to which the educators encountered
CPA, and the second one was directed to determine whether the educators’ CPA significantly
differed depending on such independent variables as their countries, ages, fields of work andtheir technology use efficacies. A total of 109 educators from four different countries
participated in the present study conducted to determine the educators’ CPA. The study
focused on the extent to which the participating educators encountered with CPA and onwhether their CPA differed with respect to their countries, ages, fields of work and theirtechnology use efficacies. As the quantitative data collected did not have normal distribution,
the Kruskal-Wallis H and Mann-Whitney U non-parametric tests were applied.

When the demographic backgrounds of the educators were examined, it was seen that theeducators belonged to the middle-age group; that more than half of them worked in the fieldof educational technologies; and that most of them considered themselves to be efficient intechnology use. It was found out that these participants assigned scores with a mean of 3.42
to the three 5-point Likert-type items reflecting CPA. In addition, the item most supported by
the participants with a mean score of 3.58 was the item of “I constantly follow and get
engaged with technology”. Depending on these findings, it could be stated that theparticipants were intensely engaged with technology and that this engagement could result in
CPA.
In order to determine whether there was a significant relationship between the educators’
CPA and their demographic backgrounds, the Kruskal-Wallis H test was applied instead of
ANOVA, and the Mann-Whitney U test was run instead of independent two-sample t-test.
The findings obtained revealed that the educators’ CPA did not significantly differ dependingon their technology use efficacies, their ages or their countries. In addition, it was seen thatthe educators’ CPA statistically differed significantly with respect to their fields of work.
Accordingly, the educators working in the field of educational technologies encountered CPA
more frequently than those working in other fields. In this respect, it could be stated that
educators more intensely engaged with technology encountered the attention problem more
frequently.

Based on the findings obtained, it could be concluded that, considering the limitations in the
study, there is no significant relationship between educators’ CPA and their technology use
efficacies, their ages or their countries. In addition, it was seen that the educators’ CPA
differed with respect to their fields of work. This result is thought to occur as educators
working in the field of information technologies are in more interaction with technology. In
the light of these results, in order to help educators in the field of educational technologies
cope with the CPAproblem, in-service training for appropriate use of technology could be
provided. In this way, not only education technologists, but also the students these education
technologists will guide regarding technology use could avoid the negative influence of CPA.
Because educators in the field of educational technology also are assumed to be role models
in the appropriate use of technology, for this reason, educators in educational technology
should have knowledge and experiences about different technology usage aspects besides theappropriate use of technology as instructional environments. These are;•appropriate use of technology in terms of health (ergonomics, internet addiction,
games, etc.),•

appropriate use of technology in terms of legal points (cyber crimes, etc.) and•appropriate use of technology in terms of social-cultural aspects (misuse of social
media, virtual love, cyber-bullying etc.).

In future studies, teachers and students’ CPA could be examined using qualitative researchmethods; to better determine CPA, a scale-development study could also be designed
employing more participants. For educators in the field of educational technology a study
could be conducted related to determination of CPA status; there could be ways of decreasing
the effects of CPA, determination the effects of CPA, collecting views of educators on theeffects of CPA, and a determination of the relationship between CPA and other variables likemutitasking, cognitive overload or disorientation.

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Appendix