CMC and FtF Final Paper

Running Head: COMPUTER MEDIATED COMMUNICATION

Transfer of Communication: The Effect of Computer-Mediated Communication on Social Skills

and Face-to-Face Interactions in College Students.

Undergraduate Students/Debut

University of Portland

Computer Mediated Communication 2

Abstract

The purpose of this study was to determine if computer-mediated communication (CMC) effects

individuals social skills when communicating face-to-face (FtF). In order to test this, an online

survey was conducted through a convenience sample using college participants on Facebook,

Twitter, and email. The results from this survey found that there ultimately is no direct

correlation between participants’ use of CMC and its effect on their social skills. Based from

these results, future directions are discussed.


Transfer of Communication: The Effect of Computer-Mediated Communication on Social

Skills and Face-to-Face Interactions in College Students.

In today’s society it seems that technology has a very important role in the lives of

younger adults today. More and more people are engaging in the Internet, cell phones, and other

technology devices to keep up a new way of communication. Computer-mediated

communication (CMC) is changing the way people communicate. Traditionally, Face-to-Face

(FtF) communication was the primary means of communication, whether it is professional or

social.

Before the invention of computers or even telephones, communication was restricted to

whom you were physically in contact with. Letters were an improvement in that you could

communicate with people who lived far away but it took a lot of time for letters to be exchanged

so communication was slow. Eventually telephones boosted the speed of communication; people

were able to instantly communicate with one another over larger distances. In today’s day in age,

with the luxury of the Internet and computers, communication can be achieved around the world

in mere seconds.

The Internet now allows for communication to happen on a broader spectrum. Instead of

just the simple back and forth conversation between two people, everyone is capable of

communicating on public subjects, such as blogs, with other people they have never met. Online

gaming brings people from around the world to play with one another. Businesses benefit

through conference video calls where they can talk relatively FtF but from different countries at

the same time.

With the increase in access to the Internet, researchers have been investigating the effects

of communication offline versus online. Since online communication is a recent phenomenon


and also ever evolving, communication styles online are constantly changing as well. This in turn

could have a positive or negative effect on traditional means of communication when individuals

interact physically. In this study, we want to examine how online communication (CMC) affects

traditional means of communication (FtF) for college students. In this paper, we will (1) review

literature associated with the research, (2) discuss the methods used to collect data, (3) examine

the results and (4) analyze the results.

Literature Review

In this literature review, we will discuss our theories that include Uncertainty Reduction

and Social Cognitive Theory. We will also discuss our variables of CMC and FtF

communication in detail. Finally, we will conclude by stating our research question.

Social Cognitive Theory

Social Cognitive Theory (SCT) is an important theory that helps guide this research

project in understanding social FtF interactions as influenced by online communications (CMC).

SCT was originally called the Social Learning Theory (Stefanone, Lackaff. 2010). There were

two types of learning associated with the original Social Learning Theory. These were

reinforcement learning and vicarious learning (Lam, Kraus, Ahearne. 2010). Reinforcement

learning is a type of learning where individuals learn from the consequences of their actions and

modify their behavior accordingly. Vicarious learning is “observing others before engaging in a

particular behavior because doing so enables them to avoid needless and costly errors” (Lam,

2010. Pg. 62). These types of learning are the premise for the Social Cognitive Theory.

Vicarious learning is an important aspect of SCT. It is important because “by observing

others’ behaviors, one may develop rules to guide one’s own subsequent actions” (Nabi, Clark.

2008. Pg. 409). Through our observations, people will create symbols to follow because


“symbolization provides humans with a powerful tool for comprehending their environment and

creating and regulating environmental events that touch every aspect of their lives” (Bandura,

2001. Pg. 267). Bandura continues from this to say that the majority of our external influences

that affect us do so cognitively instead of directly (Bandura, 2001). This means that we will be

more affected mentally than we are to be physically by external influences. This plays into how

we act behaviorally as well because our decisions will ultimately be affected by these influences

as well.

The use of symbols is important in our cognitive decisions. Symbols are important

because “it is with symbols that people process and transform transient experiences into

cognitive models that serve as guides for judgment and action” (Bandura, 2001. Pg. 267). These

experiences incorporate a large spectrum. This spectrum includes our own experiences, or the

experiences of others that we observe. People have a very wide capacity for learning weather

through direct experiences or through stories told that can teach vital life lessons even if a person

has no part in the story whatsoever. This is true because “people do not have to learn from direct

observation but rather can learn through observing others’ experiences” (Cuillier, 2008. Pg. 522).

All of this means that people are not limited to their learning.

All of this type of observational learning has a powerful effect on how people will

modify their behaviors and actions. There are four basic processes to observational learning.

These four processes include attention to certain models and their behavior, retention is being

able to represent the models behavior and its consequences, production transforms the

representations into action by the observer, and motivational is when behaviors are done because

of the nature or the valance of the reinforcement (Nabi, Clark. 2008). These four processes

describe how observational learning can in fact change the behavior of the recipient to follow


similar behaviors that they observed. According to SCT, “the term modeling to characterize the

process through which individuals observe others, interpret their behavior, and adjust their own

behavior in response” is used to classify this gradual change (Stefanone, Lackaff. 2010. Pg. 512).

Recently, the idea of modeling in SCT is being observed more during recent years. This

is because modeling is capable of happening in many different contexts, particularly wherever a

person is able to observe someone else and their actions (Bandura, 1986). This is primarily true

today with the use of television and other forms of mass media. These creations are able to

influence masses of people. As more and more people are becoming exposed to these various

forms of mass media, there has been an increase in the amount of research to see the effect of

individuals and their behaviors. It is seen that the effects of television on people who watch large

quantities of television do in fact display effects that are regularly seen on television (Nabi,

Clark. 2008). This is proof that SCT is being seen on a mass scale due to inventions like the

television where masses of people are exposed to the same behavior.

Uncertainty Reduction Theory

Uncertainty Reduction Theory (URT) argues that the primary goal of individuals in initial

interactions is to reduce uncertainty and increase the ability to predict behavior of others

(Dawkins, 136). Defined by Berger and Calabrese (1975), who are the leading researchers of

URT, is a primary motivating factor for communication. As such, it can be both proactive and

retroactive. Proactive mechanisms, such as asking others and Googling, are attempts to decrease

uncertainty prior to communication. Retroactive mechanisms, such as discussing an experience

with friends, allow us to make meaning out of events that have already occurred. In either case,

individuals seek to reduce uncertainty and increase predictability (Berger, 1975).


Berger (1979) argues that three prior conditions exist in all situations involving

uncertainty reduction. The first condition is the potential of the other person to reward or punish.

For example, if Erin is a very popular person on campus, then John may see her attention paid to

him as a reward.

The second condition is when the other person’s behavior is contrary to expectations

(Berger, 1979). In the case of Erin and John, Berger assumes that John expects a superficial

response to his negative comment about a class exercise from Erin. As such, he expects Erin to

smile and agree with his assessment of the class activity. However, if Erin disagrees with John’s

opinion about the class activity, John’s expectations would be violated and his desire to reduce

uncertainty would increase (Berger, 1979). In other words, expectancy violation increases one’s

desire to reduce uncertainty.

The third condition is when a person expects future interactions with another (Berger

1979). In Berger’s example with John and Erin, John realizes that he will continue to see Erin in

the same communication class for the rest of the semester. Yet, because she is a math major, he

may feel that he can avoid her in the future. In the first scenario, Berger would expect John’s

desire to increase predictability (i.e., reduce uncertainty) to be high because he knows he will see

Erin weekly. In the second scenario, Berger would expect John’s desire to increase predictability

(i.e., reduce uncertainty) to decrease because Erin has a different major so he can avoid her once

the class ends.

The main premise of URT (Berger & Calabrese 1975) is that individuals use information

seeking strategies to reduce uncertainties about a target individual and predict his/her attitudes

and behaviors in initial encounters. The process of uncertainty reduction enables individuals to

predict another individual’s actions, attitudes and behaviors, which can ease anxiety in initial


social encounters (Berger & Calabrese, 1975). Research has pointed out that various strategies of

URT are used to gather information on new acquaintances met online (Courtois, All, &

Hadewijch, 2012), whereas traditional research involving URT resides primarily in FtF, where

individuals engage in verbal and nonverbal communication to gain knowledge, with expectations

of future interactions (Zhang, 2012).

Gathering online information is a prerequisite in forming and maintaining relationships in

the college setting. Although online communication (CMC) can lack characteristics of traditional

FtF encounters, such as physical proximity and personal appearance, people in online arenas are

still able to reduce uncertainty about individuals they encounter over the web (Zhang, 2012).

They found that individuals apply similar uncertainty reduction strategies in FtF interactions as

they do in CMC. Because of Facebook’s popularity of sharing status’ and photos, it has created

an environment that allows users to reduce their uncertainty of other people and build

connections with them on and of the SNS.

Computer-Mediated Communication (CMC)

Computer-mediated communication (CMC) is a relatively new area over the last two

decades that has been an ever changing and evolving that research is constantly being done to

keep up with it. CMC is the communication that is done through online means like through

telephones, texting, and computers. This is because “the availability of interactive

communication technologies has made the Internet part of everyday life, which people use to

form and maintain personal relationships” (Jiang, Bazarova. Hancock, 2011. Pg. 58). There have

been some very influential observational differences between CMC and FtF interactions. One of

these includes nonverbal communication. In CMC “users are unable to recognize when the pre-

interaction expectances they hold about a conversational partner’s personality are not accurate”


(Walther, Deandrea. Tong, 2010. Pg. 365). In essence, through CMC, people are unaware if the

other user is being sarcastic or not which can lead to errors in communication.

Even without nonverbal communication, which is a very important part of

communication, CMC is becoming more and more of a popular means of communication.

Recently, some of the ways that people have been using online communication (CMC) is to

create and maintain relationships with others (Houser, Fleuriet, Estrada. 2012). CMC has had a

very important part in the continuation of relationships, especially with relationships that are

distanced from each other physically. Since these relationships lack intimacy since there is no

FtF interaction, it does not that they lack substance. It is argued that “relationships developed and

maintained through CMC are as deep as those fostered in a solely FtF context” (Houser, 2012.

Pg. 36). This is beneficial news for people who wish to maintain a relationship with someone

who may live very far away. People “may use CMC to maintain long-distance relationships with

those they have already met FtF” (Houser, 2012. Pg. 37). This is beneficial for people who want

to continue certain relationships.

There are also other advantages to using CMC than just to keep in contact with a person

who is far away. Some of these advantages include an increase in participation by users, it allows

for people to have meaningful conversations, it enhances people’s motivations, and it reduces a

person’s anxiety that may be typical in face-to-face interactions (Saleh, Eddin. 2012). Online

communication (CMC) allows for more “networked exchanges to help all individuals engage

more frequently, with greater confidence, and with greater enthusiasm” (Saleh, 2012. Pg. 76).

All of this has led to the continuing increase of, and the ever evolving, CMC.

As CMC is constantly evolving, so are the users of it. Normally, nonverbal

communication is not available during online communication (CMC). Due to this, many online


users have begun to notice and pay attention to various verbal and textual clues that is in online

messages in order to overcome the lack of nonverbal communication (Walther, Deandrea. 2010).

This kind of accommodation implies that there is more ground to CMC than simple text and that

the text can begin to be perceived to having deeper meanings. As this kind of adaptation

increases, CMC users can get the same understandings, or better understandings, of interpersonal

communication as they could in FtF interactions (Walther, 1996). Favorability that can be seen

as becoming more and more popular as CMC becomes more complex.

For some people, “online relationships tend be more intimate than FtF relationships”

(Jiang, Bazarova, Hancock. 2011. Pg. 60). In online communication (CMC) there are many

variables that play into the fact that people have time to craft their messages before sending it out

and having it being read by someone else. This makes the message deeper and more meaningful

as it has been articulated according to the writer of the message. With this kind of safety check, it

makes it easier for people to share any kind of information about themselves that they might

normally have difficulty of constructing verbally. People become more comfortable with

revealing more about them online than verbally (Jiang, 2011). This kind of phenomena will be

important to understand in order to further study a person’s communication habits.

Face-to-Face (FtF) Communication

In this day in age, many have believed with the increasing number of technological

advances, CMC would soon replace business-related travel. But research by Rhoads (2010)

suggests that many projected growth estimates of telecommuting have been overinflated and that

it may be growing at a slower pace than in previous years.

When humans analyze words that are being spoken, they attempt to imagine and interpret

the communicator’s intention behind them. “Therefore, the nonverbal and paraverbal (tone,


pitch, and inflection) components in a conversation are as important as the verbal” (Rhoads 114).

According to Rhoads (2010), paraverbal and nonverbal cues control conversation flow, turn

taking and mind reading. Any lack of these cue controls for conversation flow can result in

“unregulated and disordered conversation, which can lead to confusion and incoherence”

(Rhoads 114). Like what happens when a person misreads a text message or email on their

computer or Smartphone.

A 2008 study by researchers at the University of Illinois-Urbana-Champaign and George

Mason University put more than 200 students in groups to perform teamwork tasks and found

that those working FtF showed greater cooperation than those communicating through instant

messaging or videoconferencing, who were more likely to lie. Morella (2010) believes digital

messages and phone conversations are better "supplements" than "substitutes" for speaking in

person (Morella, 48). Though online messages can provide a handy written record of

conversations, employees who interact in person also feel more engaged with one another and

the work (Morella, 2010). He says “Only 7 percent of communication that deals with feelings or

attitudes is conveyed in the words used, with the rest of the meaning coming from tone or

nonverbal cues” (Morella, 49). Meaning the importance of nonverbal cues is still just as

important as the actual language being spoken in FtF communication. By reading the message

rather than listening and watching the context can be missed and thus misunderstanding the

communicator.

Important components of such nonverbal communication include space, time, physical

aspects of the environment and eye contact. Rhoads (2010) emphasizes the importance of culture

in understanding communication. Different cultures assume different levels of comfort regarding


proximity to another and different tone, pitches, and degrees of assertiveness when

communicating.

Samar and Alibakhshi (2007) argue that men's discourse has assertive and competitive

features, whereas women's is supportive and relational, leading to the distinction between male

"report talk" and female "rapport talk". They examined email messages and found that emails

from 61 participants contained a higher incidence of features associated with the maintenance of

rapport and intimacy than those from male participants. Samar and Alibakhshi (2007) has also

found that males are more prone to write in an aggressive, competitive style, while women tend

to be far more supportive in their writing (email messages). This connects to Rhoads theory of

assertiveness when communicating cross-culturally.

Anna Banks and Anna Faul (2007) conducted a study to see the impact of reducing the

number of FtF contact hours in a Master’s of Science in Social Work (MSSW) foundation

research course in an urban school of social work on students’ knowledge gained and course

satisfaction. The findings of this study address concerns that web-based and distance learning do

not provide the rigor and quality of the traditional FtF classroom. Their Results suggest that

reducing the number of FtF contact hours in a classroom setting and replacing them with web-

sessions does not negatively affect student learning as both the comparison, and the experimental

group demonstrated an increase in foundation research knowledge (Banks & Faul 2007). In a

classroom setting such as a lecture, having less hours does not affect the students because of their

year of experience of time management and skills in technology.

Rationale

By using the Social Cognitive Theory and the Uncertainty Reduction Theory, we want to

better understand how online communication (CMC) effects FtF communication. It is important


to know if online communication (CMC) is changing how people interact in FtF. By using SCT

and the URT, we want to answer the question that as computer mediated communication use

increases, a person’s social skills with FtF interactions decreases.

RQ1. How does CMC influence/impact the social skills and FtF communication in

college students?

Methods

Participants

There were a total of 88 participants who completed an online survey. Of these

participants, 87 indicated their sex (44 females and 43 males). Half of the total number of

participants indicated that their age was between 20 and 21 years (N=43). The primary language

of the participants was English (N=86) while one participant indicated “other”. Participants

indicated that their primary ethnicity was 59% were Caucasian, 21% were Asian, 12% were

Latino, 6% were Hawaiin/Pacific Islander, and 2% were other. There was a general distribution

of majors between the participants with 30% studying in the college of arts and sciences, 25%

studying business, 10% studying nursing, 11% studying engineering, and 25% studying other.

Following these, participants were asked some general questions about social media use.

Procedures

Participants were recruited using a convenience sample through online means consisting

of Facebook, Twitter, and email. A snowball technique was also used where participants were

asked to ask their friends to participate in the survey as well. The survey was accessed on an

online survey site called Qualtrics. Data and informed consent were collected through this

system. Data was collected through a month long process.


The participants were asked general demographic and social media questions. The

demographic questions were elaborated on in the participants section. Social media questions

asked general questions about the participants use in social media, the duration, and the reasons

for use.

Measures

Questions were developed specifically for this study to assess the effects that online

communication use has on the participant’s social skills when interacting with others in an FtF

environment. This study used a 1-5 Likert scale that was modified from Martha Perry’s (2010)

study where she used a 1-5 Likert scale to study CMC competence. The questions were

modified, some questions changed wording, others were deleted because they were not relevant

to this study, and new ones were added. The questions in this study were focused on specifically

looking at the effects that CMC has on social skills when interacting FtF.

The study was broken down to three sections. The first section focused on questions

regarding CMC. The second section focused on questions regarding FtF. The last section

contained general demographic questions, as well as some general social media use questions.

Some examples from each of these sections include the following: “When communicating with

someone through a computer, I know how to adapt my messages to the medium” in the CMC

section; “I feel it is easier for people to understand what I say in face-to-face interactions” in the

FtF section; “what language do you primarily communicate in?” in the general demographics

section; and “which social media sites do you use?” in the social media general questions. The

CMC and FtF sections used the 1-5 Likert scale, 1 “strongly agree” to 5 “strongly disagree”,

where the participants were asked to gauge truthfully how comfortable they felt with using CMC

and FtF. The general demographics and general social media questions asked more specific


questions regarding the participants. Participants chose one answer, unless the question provided

a multiple answers, regarding this section.

The 1-5 Likert scale was used in this study because it provides the ability to analyze how

comfortable students are with communicating with CMC and FtF. By allowing students to

choose how they feel when communicating with CMC and FtF, there could be a direct

correlation between the amount of CMC use and how comfortable students are when they

interact in FtF situations. The Cronbach’s Alpha reported for this measure is .863 and .815,

respectively.

Results

The research question was how CMC impacts or influences the social skills and FtF

interactions of college students. Focusing on the CMC variable, an independent samples t-test

showed no significant difference (t(84)= -1.56, p= .123) between college males and females.

Both males (M=3.80, SD=.59) and females (M=4.0, SD=.61) reported similar CMC competency.

This result suggests that CMC competency is not distinguishable between college males and

females as both gender groups are comfortable communicating with CMC.

With the same research question, we also focused on the FtF variable using an

independent samples t-test. Using an independent samples t-test showed no significant difference

(t(81)= .73, p= .468) between college males and females. Both males (M=4.01, SD= .48) and

females (M=3.93, SD= .47) reported similar FtF competency. The results between college males

and females on FtF satisfaction are non-distinguishable as both gender groups are competent

when communicating in FtF interactions.

Using the same research question, a One-Way Anova test was conducted to find how

often participants accessed social media sited when using CMC. Focusing on the CMC variable


of this test, the One-Way Anova test showed a significant (F(4.81)=4.35, p= .003) difference

between the different access times. The majority of participants (N=76) indicated that they

access social media sites daily. When participants do access social media sites, 57% of

participants indicated using them for 0-1 hour, 32% said they use it for 1-2 hours, 3% use it for

2-3 hours, and 7% use it for 3+ hours. Based off of this result, participants largely access social

media sites for at most an hour versus longer sessions at a time.

From the same One-Way Anova test, the FtF variable was found to have almost no

significant (F(4.78)= .14, p= .966) between access times of social media sites. Based from this

result, it could be that because participants are communicating FtF they have no need to be

accessing social media sites.

The final test conducted also refers to the same research question. In the final test, a

Pearson Correlation test was conducted to find a correlation between the influences of CMC on

FtF. The Pearson Correlation test showed no correlation (r= -.142, p= .204) between the

influences of CMC on FtF. Based from this result, no matter how competent a participant was

with CMC, it had no direct effect on their FtF satisfaction.

Discussion

Implications

This study was conducted to find out if college students’ use of CMC ultimately effected

their FtF interactions. With more and more people engaging in online communication (CMC), it

was felt that it would be important to understand any potential effect it could have on traditional

means of communication (FtF). In order to better understand these growing phenomena of social

media use and FtF interactions with college students, two theories were applied to the research.


These two theories were the Social Cognitive Theory (SCT) and the Uncertainty

Reduction Theory (URT). SCT is an important theory for this research because it helps to

understand how people gain and apply social teachings. Originally called the Social Learning

Theory by Stefanone and Lackaff (2010), SCT focuses on two styles of learning that people

engage in called reinforcement and vicarious learning. It was important to understand these

learning’s because college students unknowingly engage in these learning’s constantly.

Especially with vicarious learning, where people observe a behavior before engaging in it, plays

a key aspect in social media use (Nabi, Clark. 2008). More college students are willing to engage

with social media use if their colleagues engage in them as well. URT happens when people try

to reduce uncertainty about someone else in order to understand their actions. According to

Berger and Calabrese (1975), this theory is vital to communication. This theory was important to

this study because it would allow us to understand how important reducing the uncertainty is for

college students online when there is a lot of uncertainty online. With this theory, it would be

easier to understand if college students find it easier to reduce uncertainty about someone in FtF

or with CMC.

Based from the results of the study, it was ultimately found that there is almost no

correlation between the influences of CMC on FtF interactions. This tells us that as college

students are becoming more and more competent with online communication (CMC), there is no

direct correlation with their FtF interactions. College students are still just as comfortable

communicating FtF even if they are very active online with social media sites. Based off of this

interpretation, it tells us that no matter how advance technology may become and how active

college students are with it; this does not mean that they will reject traditional methods of


communication. College students are apt at adapting to new means of communication while still

remaining competent with older methods.

This interpretation is true for both male and female college students. This is because the

results of the study found that both male and female college students were essentially equal with

their ability to communicate using CMC, as well as communicating in FtF. The results found that

both gender groups are just as competent communicating with online communication (CMC) and

with FtF interactions.

The final results found in the study focused on how long participants accessed social

media sites when they log in to them. Since it was found that both college males and females

were just as competent communicating online, there was a large difference between how long

they access social media sites. The majority of participants were found to only access social

media sites for around an hour at a time. This observation shows that even though college

students are competent communicating online, they do not show a need to remain online for long

durations.

Limitations

Limitations within the research would include our sample number and the use of a

convenience sampling method. For this type of research, a large number of participants would be

ideal in order to have a greater number of reliability and less room for error. In our study we

collected surveys from 91 college students ranging from 18 to 24 years of age. During the time

of our research, college students are heading towards the end of their summer vacations and

spending time with their friends and family before getting ready to return back to school. It

would be fair to say that many of the requests that were extended to participate in the study were

ignored because of time conflicts, students who were away on vacation, and those who did not


want to participate in the study. This had an effect on the research data due to the low number of

participants, less than was ideal for the research that was conducted.

The use of a convenience sampling method could also be a limitation. The reason this

could be a limitation would be because the sample collected is similar to our personalities and

tendencies. The participants were chosen to participate through requests posted on Facebook and

Twitter as well as email invitations. This means that the survey was sent out to students who are

likely to know each other and possibly be acquainted with each other. The survey also had a

snowball effect where participants also passed on the survey for others to complete. The result

could have an effect on the data collected in the sense that the data received could be similar to

other participants.

Future Directions

For future replication of the present study, it would be useful to use a random sampling

method and to survey a larger amount of participants. The participants in this study were a

homogenous group of college students. By having a different sample method, this present study

can expand from being college students to the differences of age, regardless of education level.

By doing so, the results can show greater levels of significance between age and CMC

competency as well as age and FtF satisfaction. Our study focused on college students ranging

from 18-24 years of age. In today’s society, college students have to be knowledgeable and feel

competent working with computers. And our results suggest that, whereas with a random

sampling method that would include college students and non-college students, there could

possibly be a greater correlation between CMC use and FtF satisfaction in regards to age.


Another possible direction that could be implemented in this study would be collecting a

larger sample pool. By using a convenience sample, we are only capable of reaching out to a

handful of students. Other methods of publicizing or requesting people to participate in the study

would be recommended. By having a larger number of participants, the data collected would

have a smaller area for error and any participants who answer incorrectly in their surveys can be

voided. Due to our number of low number of participants than was originally expected, our area

for error is smaller than it would with a larger pool. By having a larger participant pool,

researchers can better understand the relationship between CMC use and its effect on FtF

communication.


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CMC and FtF Final Paper

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