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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