Question Details

(solution) I need help with my paper and help answering question the answers


I need help with my paper and help answering question the answers must be numbered when answered to be sure that they go along with the question that is being asked


EFFECTS OF CLASSROOM CELL PHONE

 

USE ON EXPECTED AND ACTUAL LEARNING

 

ARNOLD D . FROESE

 

CHRISTINA N . CARPENTER

 

DENYSE A . INMAN

 

JESSICA R . SCHOOLEY

 

REBECCA B . BARNES

 

PAUL W . BRECHT

 

JASMIN D . CHACON Sterling College

 

Studies of driving indicate that the conversational aspects of

 

using cell phones generate high risks from divided attention.

 

Prior surveys document high rates at which students carry

 

phones to and use them during class. Some experiments have

 

demonstrated that cell phones distract students from leaming.

 

The present studies combined survey and experimental methods

 

to determine student expectations about and actual performance

 

under cell phone use conditions. On the survey, students estimated the number of questions they could answer out of 10 when

 

texting and when not texting. For the experiment, we used a

 

repeated measures design with simulated classroom presentations and measured performance on a 10-item quiz. Students

 

expected to lose close to 30% on a quiz and actually did lose

 

close to 30% when texting. We discuss implications of our

 

methodology and our findings for improving student leaming. Studies of drivers using cell phones

 

reveal that the cognitive distraction of conversations significantiy increases accident

 

risk. The National Safety Council (2010)

 

published a literature review explaining

 

why cognitive load from cell phones produces inattention blindness for drivers. messages, and manual instead of verbal

 

"talking" as they reply. If conversational

 

cognitive load increases accident risk for

 

drivers, the same cognitive load should

 

increase errors on tests of lesson material

 

presented while students are texting. Strayer and Johnston (2001) showed that Survey Research listening to music or even to a recorded

 

Researchers have explored the disbook did not produce high accident risks, tracting effects of cell phones in classrooms

 

as did conversing on cell phones.

 

using surveys. Many students admit to

 

These findings are important for con- using cell phones for social networking

 

sidering the potential effects of classroom purposes in the classroom (Bayer, Klein,

 

texting on students' ability to leam pre- & Rubinstein, 2009; Besser, 2007;

 

sented material. Texting is conversational, Kennedy & Smith, 2010; Rubinkam,

 

though it involves visual instead of audi- 2010). Some studies documented perceptory "listening" as students read incoming tions of distraction from phone ringing

 

323 324 7 College Student Journal (Campbell, 2006) and from texting or sending instant messages during a class or study

 

session (Besser, 2007; Kennedy & Smith,

 

2010; Levine, Waite, & Bowman, 2007).

 

These studies employed survey responses

 

to evaluate effects.

 

The typical measurement scales for

 

such reports are quandtatively weak. For

 

example. Besser (2007) and Kennedy and

 

Smith (2010) measured student percepdons of the effects of cell phone use on

 

class performance using statements with

 

which respondents either agreed or disagreed. Besser's statement was about

 

texting drawing attendon away from class,

 

and Kennedy and Smith's statement was

 

about these acdvities helping class performance. These nominal measurements

 

do not provide informadon about the quantity of expected information loss. Other

 

researchers (Campbell, 2006; Levin, Waite,

 

& Bowman, 2007) have expanded the number of response options. For example,

 

Campbell (2006) used a 5-point Likert

 

scale ranging from strongly agree to

 

strongly disagree to evaluate student atdtudes about the disruptive effects of ringing

 

phones. Although these scales increase

 

response variability, there is no clear reladonship between level of agreement with

 

a statement such as "when a mobile phone

 

rings during class, it is a serious distraction" and any quandty of informadon loss.

 

The absence of clarity about the expected size of the effect presents addidonal

 

interpredve problems. Some researchers

 

have found a difference between expressed

 

attitudes about phone risks and actual

 

behavior. An American Automobile Association Foundation for Traffic Safety

 

(2008) survey showed that drivers viewed cell phone use as a serious safety risk. Nevertheless, 46% of those claiming that such

 

use was an "extremely serious risk" sdll

 

reported using their phones while driving

 

within 30 days prior to the interview.

 

Kennedy and Smith (2010) reported similar discrepancies in student behavior.

 

Although students generally "agreed" that

 

cell phones disrupted classroom leaming,

 

they persisted in using their cell phones in

 

the classroom. Levels of agreement do not

 

clearly indicate the size of the expected

 

effect. If respondents agree that risk is

 

increased, but perceive that the risk is low,

 

they may feel jusdfied in ignoring the risk.

 

Experimental Research Some researchers have employed experimental techniques to assess actual effects

 

of cell phone activity on classroom-related performance. Bowman, Levine, Waite,

 

and Gendron (2009) and Fox, Rosen, and

 

Crawford (2009) compared comprehension scores for students who were or were

 

not sending instant messages during a nonclass reading task. Neither study revealed

 

differences in comprehension, but completing the reading took significandy longer

 

for those engaged in instant messaging.

 

These results do not generahze to a lecture or discussion-based classroom

 

environment where students do not control the dming of informadon.

 

Other researchers have experimentally

 

explored distracdon from a cell phone ringing in a classroom. In two studies,

 

researchers compared classroom scores for

 

material when no phone was ringing to

 

scores when a phone was ringing (End,

 

Worthman, Mathews, & Wetterau, 2010;

 

Shelton, Elliott, Eaves, & Exner, 2009). In Effects of Cell Phone Use on Learning... / 325 both studies, performance deteriorated significantly for material presented during the

 

ringing condition. Performance decrements

 

ranged from 25-40% during ringing

 

periods. These two studies addressed distraction effects for bystanders and left open

 

the question of distraction for texting performers.

 

Ellis, Daniels, and Jauregui (2010) most

 

directly assessed the effects of texting on

 

performers in a real classroom context.

 

Students in the experimental condition sent

 

three text messages to the instmctor during the lecture. The control group

 

presumably had tumed their phones off.

 

Experimental students scored significantly lower than control students did on a pop

 

quiz at the end of class. Although this

 

experiment comes directly from a classroom setfing, sending a text message to a

 

teacher who does not respond is likely not

 

as distracting as a conversational texting

 

dialogue.

 

Purpose The above studies begin to explore how

 

texting changes classroom leaming. However, their limitations suggested the

 

following research strategies. First, we

 

designed both a survey to assess how much

 

information students thought they would

 

lose if they were texting, and a corresponding experiment to explore the actual

 

loss of information. Second, we generated a survey response scale that had stronger

 

numerical properties than dichotomous or

 

Likert-scale response options. Third, our

 

survey response scale had numerical properties that matched those of our

 

experimental outcome variable. This match

 

allowed us to compare quantity estimates of expected quiz score changes with experimental performance scores. Finally, we

 

designed an experiment that approximated both the classroom environment and

 

students' texting experiences. Hearing a

 

cell phone ringing in a class distracts leamers from lesson content. However, if

 

increased cognitive load explains leaming

 

deficits from texting distraction, the most

 

invasive distraction should occur for

 

students actively engaged in texting conversations during a class. Implementing

 

these developments permitted us to compare expected and actual effects of

 

non-class-related texting on classroom

 

leaming. We expected that students would

 

be aware of leaming decrements produced

 

by texting, and that their actual performance would confirm that expectation.

 

Study 1 This study employed a self-report survey to assess students' cell phone activity

 

in classes and their expectations of the

 

effects of such activity on leaming outcomes. Unlike previous studies using

 

self-report measures, we created a measure of anticipated leaming deficits from

 

texting based on measurements common

 

to classroom settings.

 

Method Participants. We collected surveys

 

from 693 students at seven colleges and

 

universities across the United States during October through December, 2009.

 

Seven teachers at these schools administered the surveys in their classes during

 

class time. Participants' average age was

 

20.5 years. Ninety-nine percent owned cell

 

phones. They had owned cell phones an 326 / College Student Journal

 

Table 1

 

Verbal and Quantitative Comparison of Self-Described Texting How Would

 

You Describe

 

Yourself as a

 

Text User?

 

Total How Often Do You Text in a Day?

 

0 -25 2 6 - 5 0 51 -75 76-100 100+

 

times

 

times

 

times times times

 

0

 

0

 

0

 

0

 

Emergency-only

 

5

 

1

 

1

 

1

 

7

 

53

 

Minimal

 

14

 

46

 

23

 

87

 

84

 

Moderate

 

139

 

76

 

54

 

70

 

21

 

Avid

 

154

 

117

 

100

 

148

 

163 average of 5.4 years and used texting functions an average of 4.1 years.

 

Instrument. Our survey requested

 

demographic information from students

 

(summarized above), and information

 

about frequency of carrying their phones

 

and texting frequency in various daily

 

activity contexts. Participants also estimated their expected learning performance

 

if they texted during class. Our metric for

 

performance was the question, "If you were

 

listening to some information, and someone asked you 10 factual questions about

 

that information, estimate the number of

 

questions you might be able to correctly

 

answer?" Participants answered that question for two conditions?if they were and

 

were not texting while they listened to the

 

information.

 

Procedure. Instructors read an introductory script to their classes that provided

 

instructions and the informed consent

 

option of not completing the survey. Surveys were confidential, and students

 

completed them during a 6-minute time

 

limit. Total

 

5

 

63

 

254

 

360

 

682 Results More than half (52.8%) of our respondents described themselves as "avid users"

 

and 90% described themselves as moderate or avid users. These verbal categories

 

corresponded with reported number of

 

texts sent per day, r^ (682) = .612,p < .01,

 

as shown in Table 1.

 

Most students carry their phones to

 

class. Seventy-five percent reported carrying phones to class "always," and another

 

16.4% said "most ofthe time." These carrying frequencies were lower than when

 

students performed daily errands (87%

 

reported "always"), but higher than when

 

in leisure activity (72% reported "always"),

 

at work (61% reported "always"), or

 

attending church (46% reported "always").

 

Students predicted scoring significantly better if not texting (M = 8.93, SD =

 

1.68) than if texting (M= 6.01, SD = 2.25),

 

i(676) = 31.31,/? < .01, effect size (t/ ^/Ñ)

 

= 1.20. Low-frequency users expected

 

greater decrements from texting (M=4.16,

 

SD = 2.77) than did moderate (M = 3.01,

 

SD = 2.24) or higher-frequency users (M

 

= 2.61, SD = 2.41), F(2, 672) = 12.14, p Effects of Cell Phone Use on Learning... / 327 < .01, effect size (rf) = .035. A Tukey posthoc test indicated that the low-frequency

 

users differed significanüy from both higher-frequency users.

 

Discussion These data confirm prior reports of the

 

ubiquity of cell phones in the classroom

 

(Bayer, Klein, & Rubinstein, 2009; Besser, 2007; Kennedy & Smith, 2010;

 

Rubinkam, 2010). They add contextual

 

informadon to classroom frequency data,

 

indicating that the classroom presents

 

fewer inhibidons to phone use than do

 

church and work setdngs.

 

More importandy, these data present a

 

strong metric for expected leaming effects

 

of phone use in the classroom. Researchers

 

can directly compare expected point losses on a 10-item quiz to actual performance

 

from a classroom experiment.

 

Study 2

 

We designed a simulated classroom in

 

which we manipulated student texdng. Otir

 

goal was to establish actual effects of texdng on quiz performance, and compare

 

this performance with expectadons derived

 

from the survey in Study 1.

 

Method Participants. We randomly selected 82

 

names from a complete college student list,

 

and 40 of these students (21 men and 19

 

women) agreed to pardcipate. We believe

 

this procedure produced a much better

 

sample of students than the typical General Psychology student sample receiving

 

course credit for participadon. Our sample

 

derived from random selecdon, and par- dcipants received no incendves for participation beyond being involved in and

 

receiving informadon about the results of

 

the project.

 

Materials. Pardcipants brought their

 

personal cell phones to a classroom that

 

contained a computer, a projector and

 

screen, and sound connecdvity. Students

 

had access to pencils and blank paper so

 

they could take notes. Another room across

 

the hallway was available for break periods between sessions and for

 

co-experimenters who texted participants

 

during tesdng.

 

We prepared two lessons for participants. Each lesson provided author and

 

content information about the books,

 

"Young Men and Fire" by Norman

 

Maclean (1992), and "Let the Great World

 

Spin" by Colum McCann (2009). No pardcipant indicated any prior knowledge of

 

either book. Each presentadon consisted

 

of a prerecorded narrative and accompanying, self-timed, PowerPoint presentadon

 

that lasted about 6 minutes. The presentations simulated classroom teaching. For

 

each presentadon, we prepared a 10-item

 

multiple-choice quiz. We pretested the

 

quizzes with people who had not read the

 

books and modified them so that pretest

 

scores were close to chance levels.

 

Procedure. We tested all participants

 

twice?once while texdng and once while

 

not texdng. We counterbalanced all story

 

and condition orders, and each story

 

appeared an equal number of dmes in each

 

order condidon. We tested texdng and nontexting pardcipants simultaneously in small

 

groups depending on when pardcipants

 

could attend. Texdng and non-texdng par- 328 / College Student Journal ticipants sat on different sides of the room

 

to reduce distraction. Co-experimenters

 

sat in the room across the hall.

 

We told all participants that they would

 

watch an informational presentation; they

 

could take notes if they desired; and they

 

should try to retain the presented information for a quiz following a 5-minute

 

break. During the break, participants had

 

access to refreshments. They were told not

 

to discuss the content of the presentation.

 

We identified the texting condition for

 

each participant before each presentation.

 

The texting participants set their phones

 

on vibrate, and were free to respond immediately to any texts that arrived. The

 

non-texting participants turned off the

 

vibrate function, placed their phones out

 

of sight and did not use their phones during the presentation. Following the first

 

quiz, the groups switched conditions for

 

the second presentation.

 

The co-experimenters confirmed phone

 

functionality with participants before the

 

experiment began. Following confirmation, the experimenter signaled

 

co-experimenters to begin texting the participants. When all texting participants

 

received their first message, the experimenter started the PowerPoint presentation.

 

Co-experimenters exchanged messages as

 

quickly as possible with assigned participants throughout the presentation. We

 

prepared a list of texting topics involving

 

general introductory information, but

 

allowed texting content to develop spontaneously throughout the interactions. Results Quiz scores were significantly lower

 

when students texted (M = 6.02, SD =

 

2.224) than when they did not text (M =

 

8.25, SD = 1.597), i(39) = 5.34, p < .01,

 

effect size (t/ ^//V) = .84. The difference in

 

scores represented a 27% decline during

 

texting from the non-texting performance.

 

Neither the story during which they texted,

 

nor the order of texting and non-texting,

 

produced different results.

 

For a convenience sample of 15 students, we recorded the time participants

 

actually spent reading or texting on their

 

phone during the texting phase. Participants spent an average of 2.69 minutes

 

engaged in texting during the presentation.

 

The range of texting times was from 1.5 to

 

4.25 minutes. Time engaged in texting was

 

negatively, though not significantly, correlated with quiz score in the texting phase,

 

076

 

Discussion

 


 

Our data support a prior report (Ellis,

 

Daniels, & Jauregui, 2010) of deleterious

 

effects of texting on classroom leaming..

 

Score reductions for texting conditions

 

were greater in our experiment than in the

 

prior experiment. Our methodological

 

addition of conversational texting may

 

account for our greater score reductions.

 

Although the correlation between texting time and texting score was not

 

significant, the direction and size of the

 

correlation leave open possibilities that

 

level of engagement in texting is a factor

 

in losing classroom information.

 

Our method presents a strong tool for

 

evaluating the effects of texting on leam- Effects of Cell Phone Use on Learning... 7 329 ing. The counterbalanced, repeated-measures design controlled subject and order

 

variables. The pre-recorded presentadons

 

equated lesson materials for all pardcipants across tesdng sessions. Nevertheless,

 

due to phone connectivity differences, pardcipants spent widely differing amounts

 

of dme actually engaged in texdng. We

 

expect that methodological refinements

 

could demonstrate even greater loss of

 

informadon than we found.

 

General Discussion

 

Our research successfully implemented a survey measure of students'

 

expectadons about the effects of texdng

 

on leaming that was comparable to typical classroom measures?predicted quiz

 

scores. The measure is quantitatively

 

strong?a rado measurement scale?and

 

easy for respondents to understand. The

 

data confirmed that self-report measures

 

can provide informadon that is verified in

 

experimental outcome studies. One

 

remaining limitadon is that students may

 

fail to account for chance performance levels associated with multiple-choice

 

quesdons. With four response altemadves,

 

that chance level?25%?represents no

 

significant leaming. It is likely that those

 

students who predicted scores lower than

 

chance did not understand this baseline

 

minimum.

 

The texdng manipuladon in the simulated classroom environment more closely

 

approximated texting during real class sessions than previous experiments. Students

 

in the texdng condidon responded to messages from their own friends as well as

 

from co-experimenters. The messages engaged pardcipants in conversadon, a procedure that the driving studies (Nadonal

 

Safety Council, 2010; Strayer & Johnston,

 

2001) suggested as a source of distraction

 

and one that was missing from the Ellis,

 

Daniels, and Jaurgui (2010) study. This

 

engagement likely accounted for more

 

informadon loss in our study than Ellis,

 

Daniels, and Jaurgui (2010) found. Furthermore, the conversations occurred

 

simultaneously with the lesson presentation, unlike the studies reported by

 

Bowman, Levine, Waite, and Gendron

 

(2009) and Fox, Rosen, and Crawford

 

(2009). The differences in informadon loss

 

that we obtained, in contrast to Bowman,

 

Levine, Waite, and Gendron (2009) and

 

Fox, Rosen, and Crawford (2009) support

 

the idea that cognitive load increases when

 

informadon presentadon conflicts with texting communications. One remaining

 

difference between our experimental setting and a real classroom is that some

 

students commented about how different

 

it was to freely text during a classroom

 

presentation.

 

Our data confirm that students expect

 

texdng to dismpt their classroom leaming,

 

and that texting does dismpt leaming. The

 

real score declines (27%) approximated

 

the expected dechnes (33%). The somewhat higher expected declines could have

 

occurred as students failed to account for

 

the 25% chance baseline and from texdng

 

requirements that did not occupy all ofthe

 

lesson dme. The corresponding declines

 

for self-report and experimental measurements suggest that students are aware that

 

using cell phones for personal communication in class compromises classroom 330 / College Student Journal leaming. Thus, our data support the value

 

of self-reports of the effects of using cell

 

phones on leaming, at least as presented

 

with the measurement tools we used.

 

Survey participants varied considerably

 

in their score predictions under texting conditions. Some participants expected no

 

detrimental effects of texting. Similarly,

 

experimental participants varied considerably in their quiz scores under texting

 

conditions. Some texting participants

 

answered all questions correctly. We do

 

not know if each participant's expected

 

and actual performance measures were correlated because different participants

 

completed the survey and the experiment.

 

These data could reflect the same kind of

 

discrepancies reported by the American

 

Automobile Association Foundation for

 

Traffic Safety (2008) between participants'

 

expectations of safety risks for others but

 

false immunity from risk for self. Further

 

research could solicit information loss

 

expectations from experimental participants to determine whether students can

 

accurately predict their own distractibilityStanovich (2009) summarized two

 

aspects of rationality?epistemic and

 

instmmental. Epistemic rationality exists

 

when a person's view ofthe way the world

 

works matches the way it actually works.

 

The correspondence of average expected

 

and actual losses in our studies suggests a

 

degree of epistemic rationality. Participants

 

really do know what happens when students text. Instrumental rationality is

 

evident when a person sets a goal and follows appropriate steps to achieve that goal.

 

Our data suggest deficits in instmmental

 

rationality for students who pay to become educated, yet choose to engage in counterproductive behaviors.

 

Given that students generally expect

 

texting to dismpt their leaming, researchers

 

can reasonably ask why students risk

 

potential failure to maintain social contact? Wei and Wang (2010) recently

 

explored two models of student motivation for classroom texting. They predicted

 

that instmctor immediacy?making eye

 

contact, calling students by name, talking

 

with students outside of class, among other

 

behaviors?could enhance students' motivation to learn and thus reduce texting.

 

Altematively, students' habits and gratifications they receivefi-omthe activity could

 

maintain texting. Their data confirmed that

 

immediacy enhanced motivation to leam,

 

but that motivation did not correlate with

 

texting rates. They concluded that the

 

habits and gratifications model better fits

 

their data. These results raise questions

 

about how phone carrying habits and phone

 

checking impulses relate to instmctional

 

variables. Students may benefit from knowing whether carrying their phones to class

 

increases their impulses to check for messages. Likewise, teachers may want to

 

know if interruptions to lesson flow

 

increase students' urges to check their

 

phones. These possibilities present fertile

 

ground for future research.

 

Finally, faculty variations in handling

 

texting events in classrooms may affect

 

student behaviors in ways that alter leaming. Further research could explore

 

differences between faculty and students

 

in perceptions of the effects of texting as

 

well as of techniques for handling unwanted texting in class. Knowing such

 

perceptions and the effectiveness of inter- Effects of Cell Phone Use on Learning... / 331 venfion techniques in the context of the

 

demonstrated effects of texting could

 

improve classroom environments and

 

enhance student learning. Bowman, L. L., Levine, L. E., Waite, B. M., &

 

Gendron, M. (2009). Can students really multitask? An experimental study of instant

 

messaging while reading. Computers & Education, 54, 927 - 931 .doi : 10.1016/j .compedu 2

 

009.09.024. Author Note

 

Denyse A. Inman is now at the School

 

of Behavioral Sciences, California Baptist

 

University. Christina N. Carpenter is now

 

at Bailey, Colorado. Jasmin D. Chacon is

 

now at the Department of Psychology, Gallaudet University.

 

We thank Brian Allen, Andrea

 

Mehringer, and Jeffi-ey Ropp for assistance

 

in conducting the research, coding data,

 

and discussing our ideas.

 

Address correspondence concerning

 

this article to Arnold D. Froese, Psychology Department, Sterling College, Sterling,

 

KS 67579. E-mail: an-oese46@gmail.com Campbell, S. W. (2006) Perceptions of mobile

 

phones in college classrooms: Ringing, cheating, and classroom policies. Communication

 

Education, 55, 280 - 294. doi: 10.1080/0363

 

4520600748573. References

 

American Automobile Association Foundation for

 

Traffic Safety. (2008). 2008 Traffic Safety Culture Index. Washington, DC: AAA Foundation

 

for Traffic Safety. Downloaded from

 

http://www.aaafoundation.ore/pdf/CellPhone.'i

 

andDrivinpReport.pdf

 

Bayer, J. B., Klein, R. D., & Rubinstei...

 


Solution details:

Pay using PayPal (No PayPal account Required) or your credit card . All your purchases are securely protected by .
SiteLock

About this Question

STATUS

Answered

QUALITY

Approved

DATE ANSWERED

Sep 13, 2020

EXPERT

Tutor

ANSWER RATING

GET INSTANT HELP/h4>

We have top-notch tutors who can do your essay/homework for you at a reasonable cost and then you can simply use that essay as a template to build your own arguments.

You can also use these solutions:

  • As a reference for in-depth understanding of the subject.
  • As a source of ideas / reasoning for your own research (if properly referenced)
  • For editing and paraphrasing (check your institution's definition of plagiarism and recommended paraphrase).
This we believe is a better way of understanding a problem and makes use of the efficiency of time of the student.

NEW ASSIGNMENT HELP?

Order New Solution. Quick Turnaround

Click on the button below in order to Order for a New, Original and High-Quality Essay Solutions. New orders are original solutions and precise to your writing instruction requirements. Place a New Order using the button below.

WE GUARANTEE, THAT YOUR PAPER WILL BE WRITTEN FROM SCRATCH AND WITHIN A DEADLINE.

Order Now