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OMG! Texting in Class ¼ U Fail :( Empirical Evidence That Text Messaging During Class Disrupts Comprehension

Amanda C. Gingerich1 and Tara T. Lineweaver1

Abstract In two experiments, we examined the effects of text messaging during lecture on comprehension of lecture material. Students (in Experiment 1) and randomly assigned participants (in Experiment 2) in a text message condition texted a prescribed con- versation while listening to a brief lecture. Students and participants in the no-text condition refrained from texting during the same lecture. Postlecture quiz scores confirmed the hypothesis that texting during lecture would disrupt comprehension and retention of lecture material. In both experiments, the no-text group significantly outscored the text group on the quiz and felt more confident about their performance. The classroom demonstration described in Experiment 1 provides preliminary empiri- cal evidence that texting during class disrupts comprehension in an actual classroom environment. Experiment 2 addressed the selection bias and demand characteristic issues present in Experiment 1 and replicated the main findings. Together, these two experiments clearly illustrate the detrimental effects of texting during class, which could discourage such behavior in students.

Keywords texting, distraction, comprehension, cognitive overload

According to Nielsen, U.S. wireless subscribers between the ages

of 18 and 24 sent an average of 790 text messages per month

between January 2006 and June 2008 (The Nielsen Company,

2008). That equates to more than one text message on average

sent each hour of every day over the entire month. Survey

responses of college students are even more impressive; 95% of students report bringing their phones with them to class every day

and 91% report using their phones to text message during class time (Mayk, 2010). Given that text messaging during class is so

common, the question of how dividing attention between lecture

and text messaging affects students’ comprehension and retention

of classroom material warrants investigation.

Although there is a relative abundance of research showing

the dangers of dividing one’s attention through text messaging

while driving (e.g., Drews, Yazdani, Godfrey, Cooper, &

Strayer, 2009; Hosking, Young, & Regan, 2009; Lee, 2007;

Strayer & Johnston, 2001), to our knowledge, no published

research has addressed the effects of text messaging in the

classroom on comprehension of lecture material. Several

researchers have demonstrated that intrusive noises such as a

cell phone ringing during cognitive tasks impair academic per-

formance (e.g., End, Worthman, Mathews, & Wetterau, 2010;

Hughes & Jones, 2001), but no one has published research

investigating the potentially detrimental effects of text messa-

ging during class on learning. This issue is especially pertinent

given the high prevalence of text messaging among college

students (Mayk, 2010).

Copious research has demonstrated the detrimental cogni-

tive effects of divided attention, although not conducted in a

classroom setting. Rubinstein, Meyer, and Evans (2001), for

example, found that people lost time as they switched from one

cognitive task to another; the amount of time they lost

increased as the task became more complex or unfamiliar.

Given that students rarely (if ever) focus on a lecture while text

messaging, task switching may be a more accurate description

of what texting students are doing in class. Other researchers

have demonstrated that divided attention impairs memory

particularly when attention is divided during the initial learning

and encoding of new information (Fernandes & Moscovitch,

2000). Thus, students trying to learn the typically new, com-

plex, and unfamiliar material introduced during lecture may

be particularly vulnerable to the divided attention associated

with text messaging.

In addition to the scarcity of empirical research addressing

the effects of text messaging on learning in the classroom,

we were motivated to conduct these experiments by the results

of a previous in-class demonstration in which we paired

1 Department of Psychology, Butler University, Indianapolis, IN, USA

Corresponding Author:

Amanda C. Gingerich, Department of Psychology, Butler University, 4600

Sunset Avenue Indianapolis, IN 46208, USA.

Email: [email protected]

Teaching of Psychology 2014, Vol 41(1) 44-51 ª The Author(s) 2013 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0098628313514177 top.sagepub.com

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students with someone sitting near them. Half of the pairs com-

prised a ‘‘text-first’’ group, who completed an entire prescribed

text-messaging conversation before reading a research article

describing neurological evidence that divided attention modu-

lates the extent to which declarative memory or habit learning

contributes to solving a complex problem (Foerde, Knowlton,

Poldrack, & Smith, 2006). The remaining pairs comprised a

‘‘text-while-reading’’ group, who began reading the article

immediately and completed the same text-messaging conversa-

tion while they read. As such, the ‘‘text-first’’ group focused on

only one task at a time, while the ‘‘text-while-reading’’ group

engaged in frequent task switching. All students took a quiz

over the article as soon as they finished reading it.

After 15 min, 70% of the ‘‘text-first’’ group had started the quiz compared to only 40% in the ‘‘text-while-reading’’ group, despite the time delay that occurred before beginning the read-

ing in the ‘‘text-first’’ group. After another 10 min, 40% in the ‘‘text-first’’ group had finished the quiz, compared to only 20% in the ‘‘text-while-reading’’ group. Finally, scores on the quiz

revealed that the students who texted while simultaneously

reading the article earned an average of 3.6 points, which was

notably lower than the 5.6 points earned by the ‘‘text-first’’

group. Based on these findings, we designed a pair of experi-

ments to more rigorously test the deleterious effects of text

messaging on learning in a classroom environment.

Experiment 1

Method

Participants

A total of 67 students across three consecutive semesters of an

upper-level cognitive processes class at Butler University

participated in this experiment. Participation was voluntary,

and we did not compensate students, as the experiment was

conducted as part of an in-class demonstration.

Materials and Procedure

During a lecture on attention and time management, we asked

for volunteers who had unlimited text-messaging plans on their

mobile devices and who had their device with them to partici-

pate in a demonstration. We selected a subset of these volun-

teers equal to approximately half of the students in the class

to be in the text condition of the experiment. Those in the text

condition (n ¼ 35) submitted their mobile phone numbers, which we shuffled and redistributed to one other text-condition

student. During the lecture, students in the text condition began

and sustained a prescribed conversation via text message with

both the person whose phone number they received and the

person who received their phone number. The remaining stu-

dents in the class (those who did not volunteer or whom we did

not select for the text condition) were in the no-text control

condition (n ¼ 32).

All participants heard a brief lecture on time management

strategies and took a quiz (announced before the lecture) on the

material from the lecture. We projected the text conversation

(see Appendix) on the screen at the front of the room and began

the lecture, which lasted approximately 12 min. After a 5- to

7-min delay, participants completed a multiple-choice quiz

on the time management material. After taking the quiz but

before seeing their grade, participants also assessed their per-

formance by indicating what percentage of the questions they

believed they had answered correctly (1 ¼ 0–49%, 2 ¼ 50– 59%, 3 ¼ 60–69%, 4 ¼ 70–79%, 5 ¼ 80–89%, 6 ¼ 90–99%, 7 ¼ 100%). We then collected the experimental materials and resumed the class lecture on divided attention.

Results

Figure 1 displays the mean percentage of correctly answered

quiz items as a function of text-messaging condition. A two-

way analysis of variance (ANOVA) with condition (text vs.

no-text) and semester (Spring 2010 vs. Fall 2010 vs. Spring

2011) as between-participants independent variables revealed

a main effect of condition, F (1, 61)¼ 14.24, mean square error (MSE) ¼ 427.51, p < .001, Z2 ¼ .189. Participants in the text condition (M ¼ 60.14%, SD ¼ 23.81%) answered significantly fewer quiz items correctly than did participants in the no-text

condition (M ¼ 79.22%, SD ¼ 15.56%). Neither the main effect of semester nor the condition by semester interaction

reached significance, both Fs (2, 61) < 1, suggesting that the

effect of condition was consistent across time.

Figure 2 displays the mean performance self-assessments of

participants in the text condition and participants in the no-text

condition. A two-way ANOVA with condition (text vs. no-text)

and semester (Spring 2010 vs. Fall 2010 vs. Spring 2011) as

between-participants factors revealed a main effect of text con-

dition, F(1, 61) ¼ 31.35, MSE ¼ 1.32, p < .001, Z2 ¼ .339.

Figure 1. Mean percentage of correctly answered quiz items as a function of text-messaging condition in Experiment 1.

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Participants in the text condition (M¼ 3.83, SD¼ 1.38) did not believe they answered as many items correctly on the quiz as

did those in the no-text condition (M ¼ 5.53, SD ¼ .84). This indicates that participants who texted during the lecture were

aware that their performance on the quiz was compromised.

The main effect of semester, F(2, 61) ¼ 1.56, MSE ¼ 1.32, p ¼ .218, Z2 ¼ .049, and the condition by semester interaction, F(2, 61) ¼ 0.72, MSE ¼ 1.32, p ¼ .493, Z2 ¼ .023, failed to reach significance. Thus, the lower confidence that the text

group had in their quiz scores relative to the no-text group was

consistent across all three semesters.

Discussion

The demonstration described in Experiment 1 effectively illus-

trates how texting during class impairs comprehension and

retention of lecture material as measured by quiz scores. The

results of Experiment 1 also provide preliminary empirical

evidence that text messaging during lecture interferes with

mastery of lecture material. However, our findings are limited

by a number of factors. Our study did not utilize a true experi-

mental design. We did not randomly assign our students to the

text or the no-text condition. Instead, students who had mobile

phone plans with unlimited text messaging volunteered for the

text condition so that students would not incur any monetary

expense as a result of their participation. As such, a selection

bias may have influenced our results. Specifically, students

who are heavy media multitaskers may be more likely to have

phone plans with unlimited text messaging. Previous research

has shown that, compared to light media multitaskers, heavy

media multitaskers are more likely to experience interference

from irrelevant stimuli in the environment and from irrelevant

memory representations (Ophir, Nass, & Wagner, 2009). Thus,

if heavy media multitaskers were overrepresented in our text

group and light media multitaskers were overrepresented in our

no-text group, the group differences we documented in quiz

scores may be attributable to a differential vulnerability to

interference from irrelevant stimuli.

Another potential scientific limitation of Experiment 1 is

that we conducted it as part of an in-class demonstration of the

effects of divided attention. Although students were aware that

they would take a quiz on the information, which, presumably,

motivated their best effort, they were also aware of the intended

outcome of the demonstration, which may have introduced

demand characteristics.

To control both of these potential confounds, we designed

Experiment 2 to replicate the results of Experiment 1 in a con-

trolled laboratory setting. We excluded students who did not

have unlimited texting as part of their mobile phone plans and

randomly assigned students who did have unlimited texting to

the text or the no-text condition. We lectured over material

unrelated to divided attention and included participants who

were not enrolled in a cognitive processes class in order to

reduce these possible biases.

We also used Experiment 2 to follow up on our somewhat

surprising results that demonstrated that students in the text

group accurately judged their performance on the quiz to be

lower than that of the no-text group. Our students made this

judgment after they took the quiz, but before they received their

score. One possibility is that students do not realize that text

messaging during class is distracting to their learning until after

they are faced with a quiz on which they do not know several of

the answers. In a typical classroom setting, quizzes may follow

lectures by several days to several weeks. In this case, a number

of intervening events occur between the lecture and the quiz,

and students who are seeking explanations for a poor quiz score

may be unlikely to attribute their poor retention of lecture

material to texting during class. In addition, students who

recognize their learning deficit only after taking a quiz may

be too late to adjust their study habits in order to overcome

it. In other words, students may not feel that their learning is

impaired after text messaging during a lecture, but they may

realize this impairment after attempting to retrieve the material

later. If this is the case, text messaging during class may have

an even greater detrimental effect on students’ grades than we

were able to demonstrate in our study. Students may not recog-

nize their lower mastery of the lecture material covered while

they were texting until they take a quiz or exam, when it is too

late for them to compensate for their decreased initial learning

by increasing the time and effort they dedicate to studying that

information in preparation for the graded assessment.

Because the design of Experiment 1 did not allow us to

determine at what point in time students became aware of how

texting during lecture affected their learning, we gathered

students’ predictions about their performance at several time

points in Experiment 2 to investigate whether students who text

message during lecture recognize that their comprehension has

been compromised even before they take a quiz. Including

additional measures of students’ learning confidence also

allowed us to investigate whether the accuracy of students’

metacognitive judgments are affected by their being distracted

Figure 2. Mean performance self-assessment as a function of text- messaging condition in Experiment 1.

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by text messaging while learning new material in class. Some

researchers have found that dividing participants’ attention

while they encode a word list results in less accurate judgments

of their own learning than allowing participants to focus their

attention (e.g., Barnes & Dougherty, 2010). Experiment 2

allowed us to investigate whether this is also true when applied

to learning lecture material in a classroom-like setting.

Experiment 2

In order to address the selection bias and demand characteristics

present in Experiment 1, we designed and conducted a more con-

trolled experiment, one that did not take place in the context of a

class on divided attention and one in which participants were

randomly assigned to text or not to text during the ‘‘lecture.’’

Method

Participants

Fifty-six undergraduate students (40 women and 16 men) at

Butler University participated in this experiment. Participants

either received extra credit in a psychology course or a

US$10 gift card to a fast-food restaurant in return for their par-

ticipation. Participants were recruited from psychology courses

through an online participant management program.

Materials and Procedure

Participation occurred in group testing sessions that ranged in

size from 1 person to 15 people. After obtaining informed

consent, we told participants that the purpose of the study was

to investigate how classmates communicate about lecture

material and how their communication affects learning. We

randomly assigned each participant to the ‘‘text’’ or ‘‘no-text’’

condition. However, in order to minimize participants’ expec-

tations regarding their performance in this experiment, we told

participants that they were assigned to one of three conditions:

a no-text group, a text about lecture content group, or a text

about unrelated content group. In reality, no participants texted

about lecture content. Participants were told that they would

listen to a lecture about the effectiveness of various study

strategies before taking a quiz on the lecture content. All

participants were told to take notes on the lecture material as

though they were in class. Participants then received a packet

containing their assigned condition and a text conversation

between two people. Those assigned to the text condition

received the phone number of one other participant and were

instructed to skim the conversation and to begin texting that

conversation when the ‘‘lecture’’ began. Those assigned to the

no-text condition were instructed to read the text conversation,

which had occurred between two students recently. After learn-

ing what the quiz would involve but before the lecture began,

participants predicted how well they would perform on the quiz

by indicating how many of the nine quiz questions they

expected to answer correctly. After they made their prediction,

the experimenter began the lecture on how people learn.

Participants in the text condition sustained the prescribed con-

versation via text message with another student in the room

during the lecture, whereas those in the no-text condition did

not. At the end of the approximately 30-min lecture, partici-

pants again predicted how well they would perform on the quiz.

In order to prevent participants from rehearsing lecture

content, we instituted a distractor phase, in which participants

watched an episode of ‘‘SpongeBob Squarepants’’ for approx-

imately 10 min. They then rated the extent to which the episode

portrayed feelings in SpongeBob such as excitement, fear, and

nervousness. After the distractor phase, participants completed

a multiple-choice quiz about the lecture content and offered a

final estimate of their performance on the quiz. We then

thanked and fully debriefed participants.

Results

Figure 3 displays the mean percentage of correctly answered

quiz items as a function of text-messaging condition. A one-

way ANOVA with condition (text vs. no-text) as a between-

participants independent variable revealed a main effect of

condition, F(1, 54) ¼ 4.33, MSE ¼ 0.03, p < .05, Z2 ¼ .074. As hypothesized, participants in the text condition (M ¼ 73.41%, SD ¼ 16.95%) answered significantly fewer quiz items correctly than did participants in the no-text condition

(M ¼ 83.00%, SD ¼ 17.26%). Figure 4 contains students’ judgments of learning (JoLs) as

a function of condition and time of judgment. A multivariate

ANOVA with condition (text vs. no-text) as a between-

participants independent variable and time of judgment (pre-

lecture, postlecture, postquiz) as a within-participants variable

revealed a significant effect of condition such that those in the

text condition (M ¼ 57.50%, SD ¼ 21.09%) gave significantly lower JoLs than did those in the no-text condition (M ¼ 80.07%, SD ¼ 14.05%), F(1, 54) ¼ 29.66, MSE ¼ 0.07, p <

Figure 3. Mean percentage of correctly answered quiz items as a function of text-messaging condition in Experiment 2.

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.001, Z2 ¼ .355. There was also a significant effect of time of judgment, F(2, 53) ¼ 4.75, Wilks’ l ¼ .85, p < .05, Z2 ¼ .152. Post-hoc paired samples t-tests indicated that JoLs made

before the lecture began (M ¼ 70.70%, SD ¼ 18.53%) were significantly higher than those made after the lecture but

before the quiz (M ¼ 64.07%, SD ¼ 23.09%), t(55) ¼ 3.33, MSE ¼ .02, p < .001. Post-lecture JoLs did not statistically differ from those made after the quiz (M ¼ 66.75%, SD ¼ 22.85%), t(55) ¼ 1.10, MSE ¼ .02, p ¼ .274. There was also not a statistically significant difference between JoLs made

before the lecture and those made after the quiz, t(55) ¼ 1.44, MSE¼ .03, p¼ .155. The Time of Judgment� Condition interaction was not significant indicating that changes in JoLs

across time were consistent regardless of whether participants

were in the text or the no-text group, F(2, 53) ¼ 1.87, Wilks’ l ¼ .93, p ¼ .164, Z2 ¼ .066.

To investigate the consistency between participants’ JoLs and

their actual performance, we ran a two-way ANOVA with actual

versus expected quiz scores as a within-participants variable and

text condition as a between-participants variable. Because we

were interested in the extent to which texting during lecture

affects participants’ ability to accurately monitor the extent to

which they have learned just-presented information, ‘‘Expected’’

quiz scores refer to the JoLs that participants made after the

lecture, but before taking the quiz.1 As shown in Figure 5, parti-

cipants in both conditions underestimated the percentage of quiz

items that they would get correct (MPercentCorrect ¼ 77.52%, SDPercentCorrect ¼ 17.59%; MJoL ¼ 64.07%, SDJoL ¼ 23.09%, F(1, 54) ¼ 12.66, MSE ¼ 325.40, p < .005, Z2 ¼ .190). More importantly, the Expected versus Actual quiz performance

� Text Condition interaction was significant, F(1, 54) ¼ 5.86, MSE ¼ 325.40, p < .05, Z2 ¼ .098. Specifically, participants in the no-text condition showed much higher con-

sistency between their expected (MJoL ¼ 79.08%, SDJoL ¼ 12.86%) and actual (MPercentCorrect ¼ 83.00%, SDPercentCorrect ¼ 17.26%) quiz scores than did participants in the text condi- tion (MJoL ¼ 52.81%, SDJoL ¼ 22.76%; MPercentCorrect ¼ 73.41%, SDPercentCorrect ¼ 16.95%). This suggests that text messaging during lecture disrupts the cognitive processes

associated with learning as well as those involved in judging

how well material is learned. Interestingly, although Barnes

and Dougherty (2010) found that dividing attention results

in overconfidence, our results suggest that, in the case of

dividing attention via text messaging, individuals recognize

the potentially detrimental effects and overadjust for them

when formulating their performance expectations.

Discussion

Consistent with the results of Experiment 1, the results of

Experiment 2 provide evidence that text messaging during

lecture impairs comprehension and retention of lecture content.

When we took steps to reduce the demand characteristics asso-

ciated with performing the demonstration within the context of

a class on divided attention, the impaired performance among

those who text messaged during lecture remained. Likewise,

the effect persisted when participants were randomly assigned

Figure 5. Expected performance (postlecture JoLs) and actual performance (mean percentage of correctly answered quiz items) as a function of text-messaging condition in Experiment 2. JoLs ¼ Judgments of learning.

Figure 4. Judgments of learning (JoLs) as a function of text-messaging condition and time of judgment in Experiment 2.

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to text-messaging conditions, thereby eliminating selection

biases.

Also consistent with the results of Experiment 1 was the

finding that JoLs of those in the text condition were lower than

those of participants in the no-text condition. To some extent,

participants seemed to realize that their performance would

be impaired, even before they had their attention divided during

lecture. Even more remarkable is the finding that those who did

not text had more accurate expectations about their quiz perfor-

mance than those who did text. This implies that, in addition to

actual attention and comprehension processes, the monitoring

involved in metacomprehension processes may be impaired

by text messaging during lecture.

Although we attempted to eliminate demand characteristics

in Experiment 2, the finding that students in the text condition

anticipated performing worse on the quiz than those in the no-

text condition even before they heard the lecture suggests that

participant expectations could have still contributed to perfor-

mance differences on the quiz. We hoped to mitigate the effects

of this expectation by telling all participants that there were two

texting groups—one who texted about lecture material and

one who texted about unrelated content. Our rationale was that

participants in the no-text condition might also lower their

expectations about their quiz scores if they believed texting

about the lecture content would improve retention of the lecture

material, making the no-text and text group more comparable

in their prelecture expectations. Because we did not actually

include a group who texted about the lecture material, we

cannot address how this cover story affected either expecta-

tions or performance. Perhaps future replications of this study

could investigate this issue directly or could directly examine

whether telling participants that texting actually improves quiz

scores would yield the same effects on performance.

In summary, the results of Experiment 2 provide additional

evidence that text messaging during a lecture results in lower

scores on a subsequent quiz assessing comprehension of lecture

material. Even when the methodological limitations present in

conducting the classroom demonstration described in Experi-

ment 1 were addressed, the effect of text messaging during

lecture was apparent.

General Discussion

Although the results of these two studies may confirm what

many college instructors already know, or at least suspect to

be true, students in our classes often seem surprised by how

detrimental texting during class is to their learning when it is

demonstrated to them. Many students may believe that they can

listen to a lecture while also engaging in a text message conver-

sation because one task is primarily auditory and the other pri-

marily visual in nature. The results of our two experiments

showed that, on average, students who text during class can

decrease their initial learning from a B level (i.e., 81.11%) to a D level (i.e., 66.78%). In many courses, this would mean the difference between passing and not passing. The results were

consistent across each of the three semesters of Experiment 1

as well as in the more controlled environment of Experiment

2, suggesting that the effect is likely to be reliable with future

students in other classes and other disciplines.

We did the Experiment 1 demonstration in a cognitive

processes class as part of a lecture about divided attention, but

college instructors could easily incorporate it into their courses

at any point in the semester. Because the demonstration can

occur during a lecture, it requires very little extra class time

other than that needed to administer a short quiz, grade it, and

graph the scores. As students’ text messaging in college class-

rooms has become more prominent (Mayk, 2010), some

instructors have responded by limiting or forbidding the use

of cell phones during class (cf. Gilroy, 2004). Perhaps an in-

class demonstration like the one we describe in Experiment 1

would more effectively convince students that dividing their

attention during class (whether via text messaging or other

means) is not in their best interest academically and would have

a greater potential to generalize to other classes or to other

settings where divided attention or task switching can interfere

with students’ cognitive efficiency.

Unexpectedly, our results indicate that students are aware

that texting during lecture impairs their learning, at least when

they are explicitly told that they will be text messaging during a

lecture on which they will later be quizzed. Given the preva-

lence of texting during our classes, we were surprised to find

that students who knew that they would be texting during lec-

ture expected to learn less. This raises at least three important

questions that may warrant additional research. (1) If students

are aware that text messaging will damage their ability to com-

prehend lecture material, then why do so many students insist

upon text messaging during class? Future research investigat-

ing this question may help to disambiguate the relationship

between students’ metacognitive beliefs and their behaviors.

Relatedly, (2) Could students’ behavior in the classroom be

aligned with their understanding of the ‘‘dangers’’ of text

messaging during lecture simply by reminding those who are

texting of their task and asking them to consider how well they

will learn class material while they are texting? Perhaps this

exercise in predicting learning and performance could

enhance students’ ability to calibrate their confidence in their

learning with their accuracy. Finally, (3) Could it be the case

that texting reduces initial learning of material but does not

necessarily affect performance on typical classroom assess-

ments? If, as seems to be the case in our study, students realize

that texting has negatively affected their initial learning, they

could potentially compensate for this through increased

studying between the time of the lecture and the time they

take a quiz or exam.2 In fact, given that the JoLs of students

who text during lecture actually underestimate their mastery

of the lecture material, they may instead overcompensate for

their perceived lack of learning by studying more than neces-

sary to close the achievement gap, putting them at an advan-

tage relative to students who do not text during class.

Incorporating announced delayed assessments into future

studies of the effects of texting during lecture could investi-

gate this interesting possibility.

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Future research could also address how utilizing a pre-

scribed text message conversation impacted the external valid-

ity of our study. In order to increase experimental control, we

dictated the content of the text messages that participants

exchanged. It is possible, though, that this made the text condi-

tion even more demanding of attention. Maintaining one’s

place in the conversation and ensuring proper punctuation and

spelling may have made completing the task more difficult than

text messaging in ‘‘real life.’’ Under ‘‘normal’’ texting circum-

stances, individuals can minimize the attentional impact of

dividing their attention by using ‘‘text-speak’’ and shortening

phrases and words, an option that was not available to the par-

ticipants of this experiment. On the other hand, having the text

message prescribed may have reduced the cognitive demands

of the texting task. It is possible that generating appropriate

responses to a spontaneous text conversation would require

more cognitive resources than simply copying a scripted

response (see Strayer & Johnston, 2001). If this is the case, our

results may actually underestimate the cognitive cost involved

with texting during lecture. Replicating the design of Experi-

ment 2 while permitting participants to compose a unique text

conversation would more directly address this issue.

Future studies could also replicate our study using alternative

types of assessments. The quizzes that students took in both of

our experiments were fairly basic multiple-choice quizzes that

asked students simply to recognize the information from the lec-

ture. Although the quiz in Experiment 2 required more thorough

understanding and critical analysis of lecture material than the

quiz in Experiment 1, neither quiz required recall of lecture

content, open-ended comparison of theories or evaluation of evi-

dence, or creation of unique ideas. Many formal assessments in

college classrooms do ask students to critically appraise and

apply lecture material to new situations. We suspect that the

decreased ability of the text group to demonstrate a basic under-

standing of lecture material compared to our no-text group sug-

gests that they would also struggle (and perhaps more so) with

questions evaluating their learning at a more complex level of

understanding, having even stronger implications for the ways

in which instructors handle text messaging in the classroom.

Appendix

Text Conversation—Experiment 1

� ‘‘Hi. Im txting u from Cog.’’ � ‘‘Hi. Who’s this?’’ � ‘‘It’s [your name]. Who’s this?’’ � ‘‘It’s [your name]. Did u watch the Superbowl on

Sunday?’’

� ‘‘[Answer Yes or No]. Did u?’’ � ‘‘[Answer Yes or No].’’ � ‘‘I couldn’t wait 2 come 2 class today.’’ � ‘‘I know. Dr. G rocks. This is my fave class.’’ � ‘‘Mine too. Psych is the best subject ever!’’ � ‘‘I know! :) I tell my fam that all the time.’’ � ‘‘So do I! I’m so glad I study Psych @ Butler.’’

� ‘‘Me too. Learning about psych is the highlight of my day.’’

� ‘‘The highlight of my day is sharing what I learn with my friends!’’

� ‘‘Yeah, they’re always impressed by the demos.’’ � ‘‘This conversation is cheesy.’’ � ‘‘Yeah, peace out.’’

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to

the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship,

and/or publication of this article.

Notes

1. Analyses conducted on all three judgments of learning (JoLs)

combined yielded the same results.

2. We thank an anonymous reviewer for this suggestion.

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