Brian H. Spitzberg is a Professor in the School of Communication, San Diego State University. His research examines the assessment and conceptualization of interpersonal communication skills, as well as topics on the dark side of communication such as jealousy, coercion, violence, stalking, and cyberstalking.
Address: School of Communication, San Diego State University, San Diego, CA, 92182-4561 USA
The rationale for developing a theoretical model of computer-mediated communication (CMC) competence is established through review of social trends in the use of new media technologies. Special attention is paid to the role new media play in the formation and development of personal relationships. A model of CMC competence is then developed along the lines of motivation, knowledge, skills, context, and outcomes as a metaphorical typology for organizing existing CMC research. This research is reviewed as it informs, and is organized by, the model of CMC competence. A sampling of formal propositions resulting from the model is elaborated, and the results of preliminary pilot studies of the model are reviewed. The model is offered as a first step in examining individual differences in the domain of CMC relationships and media choice.
Different media, which provide different sensory information, often produce different effects. Historically, every major innovation in communication technology has demonstrated a complex interplay with social forces to produce transformative effects on human relationships (Cheseboro, 2000; Cochrane, 1995; Inose & Pierce, 1984; Kedzie, 1997; McQuillen, 2003; Meyrowitz, 1985). Both the potential bright (utopian) and dark (dystopian) sides of such technological communications revolutions have been debated at length (e.g., Bargh, 2002; Gergen, 1991; Turkle, 1995), and the objective trends in social diffusion studied at length (e.g., Rideout, Roberts, & Foehr, 2005; U.S. Dept. of Commerce, 1998). If new technologies translate into new effects on society and human relationships, it follows that the competence with which any given person utilizes these new technologies is likely to affect whether this person views the technology as utopian or dystopian. This article formulates a theory of computer-mediated communication (CMC) competence in an attempt to model skill with computer-based interpersonal communication.
At least two caveats to the transformative effects of communication technologies bear consideration. First, from a theoretical perspective, strong effects perspectives toward communication technologies have predominated. There is a tendency, especially in the early stages of theorizing that follow the diffusion of new technologies, to overattribute effects to technology and underattribute effects to the individual and social contexts. For example, early research tended to view mass communication messages as “magic bullets,” unidirectionally producing strong effects in the form of persuasion. This paradigm gave way to a more moderated or interactionist paradigm, which recognized the importance of social and contextual forces in attenuating and accelerating the impact of mass communication. This interactionist paradigm is reflected more in current research trends in CMC (e.g., Hardy & Scheufele, 2005), although some anticipate a comeback by strong effects approaches (Herring, 2004).
The second caveat to the strong effects model of communication technology is that the complexity of technology and human relationships tends to require some degree of hindsight before even the right questions can be asked, much less the most accurate understandings formed (Herring, 2004). Such caveats have only recently begun framing the scholarly understanding of the Internet and its affiliated technological ancillaries (e.g., the world wide web, chat spaces, MUDs, MOOs, blogging, instant messaging or IM, videoconferencing, etc.). Collectively, these various uses of CMC are having transformative effects on human relations, but a full appreciation of the complexity of these effects remains elusive.
This analysis proffers a theory of computer-mediated communication competence to organize the accumulating scholarship on CMC. Before defining CMC competence, we identify some scope conditions. A theory of CMC competence does not directly compete with theories of media effects. For example, measures of CMC competence may provide useful dependent variables for models such as the social identification/deindividuation (SIDE) model (Lea & Spears, 1995; Spears, Postmes, Lea, & Wolbert, 2002), but competence itself is not intended to account for why CMC produces different communication effects from face-to-face (FtF) interaction. Likewise, a theory of CMC competence only partly overlaps with theories of how interaction differs based on the interaction medium. For example, hyperpersonal models (e.g., Walther, 1996) may claim that interaction will be differentially competent based on various parameters such as anticipated future interaction and task orientation, but these are not models of individual differences in competence given such parameters. A comprehensive theory of CMC interaction will eventually need to integrate models across such parameters.
CMC is tentatively defined as any human symbolic text-based interaction conducted or facilitated through digitally-based technologies. This working definition includes the Internet; cellular phone text, instant messaging (IM), and multiuser interactions (MUDs & MOOs); email and listserv interactions; and text-supplemented videoconferencing (e.g., decision support systems). This definition requires actual people engaged in a process of message interchange in which the medium of exchange at some point is computerized. There are some electronically enabled or enhanced, or otherwise mediated, forms of communication that might not qualify as CMC, including use of megaphones, hearing aids, or dedicated analog teletype systems. Furthermore, many media not ordinarily considered computers are included, as more and more media involve digital technologies. This definition intends to draw attention to the role of computer-assisted convergence in the technologically-mediated processes of communication.
The proposed theory is not strictly constrained to online interaction. Instead, it applies to any interpersonal communication process mediated through computer-assisted technologies. For example, when someone elects to IM rather than use vocalized phone or FtF interaction, this choice reflects a set of decisions about the functional value of that medium in that context. The cellular phone is a computer and will increasingly converge with all the various characteristics currently associated exclusively with computers. The cell phone also represents a set of technological constraints and affordances. Some of those constraints can be compensated for and others are more intractable. Consequently, this model is proposed to apply to all interactions that could be considered interpersonal computer-mediated interactions in which there are interdependent message response capabilities. To the extent that the Internet and websites provide a forum for email interaction, they could be within the scope of this model. However, the model is not intended to refer to specific hardware or software expertise, which tends to involve specialized forms of knowledge and skill.
The term text is not confined to linguistic symbols. Instead, it is defined broadly, consistent with cultural studies in which images, architecture, metaphors, and other message forms take on iconographic meaning. Specifically, text is defined as any message form to which patterned meanings are attributed. In this sense, sending advertisements or photographs through a cellular phone represents types of texts intended as messages. As technology converges and evolves, such definitions will also evolve. As technology increasingly permits virtual reality to approximate real life (RL), CMC will increasingly blur the notion of “text,” perhaps to the point of dissolving its technological aspect entirely. Until then, the delimitation to text is a useful working space for analysis (Walther & Parks, 2002).
The Web and its Web of Relations
The geometry of CMC diffusion is astonishing by almost any standard of evaluation. Between 2000 and 2005 Internet usage grew an average of 160% worldwide—North America alone now has 68% of its population using the Internet, representing almost a quarter of worldwide usage (Internet World Stats, 2005). According to the Pew Internet and American Life Project (2000, hereafter “Pew”), every day close to 50 million Americans log onto the Internet, send or read email, and perform some activity on the World Wide Web. According to studies of U.S. youth, about half go online daily, about 85% live in homes with a computer, and one third have used their cellular phones to send text messages (Lenhart, Madden, & Hitlin, 2005; Rideout et al., 2005). While diffusion is far lower in some other countries and cultures, the curve of diffusion is still steep (Cochrane, 1995; Kedzie, 1997). As technological distinctions dissolve between cell phones, television, and the computer, and as costs decrease, it seems inevitable that the reverberations of the communications revolution will be felt for some time into the future.
• .5 to 1% of respondents indicated finding a romantic partner was a goal of Internet use, but 7% reported becoming emotionally involved with someone on the Internet (Knox, Daniels, Sturdivant, & Zusman, 2001)
• 17% of instant messaging “users have asked someone to go out with them with an instant message,” and 13% of instant messaging “users have broken up with someone via an instant message” (Pew, 2001, p. 22).
• 20% of teens have asked someone out using IM, and 19% have broken up with someone using IM (Lenhart et al., 2005)
• 19% of college students have formed a relationship online before meeting in person (Jones, 2002)
• 29% reported “having established new friendships over the Internet/email; the distributions were similar for men and women” (Goodson, McCormack, & Evans, 2001, p. 106)
• 37% of sample have used the Internet to meet someone new, 3.6% have used an Internet dating service, 3.5% responded to an online personal ad, 16.8% have used the Internet to flirt with strangers, 10.6% established a long-distance relationship because of the Internet, and 43.6% have maintained a long-distance relationship because of the Internet (Rumbough, 2001)
• 40% or more of college students sampled state their goal in meeting people on the Internet was friendship (Knox et al., 2001)
• 42% of college students use the Internet primarily to communicate socially (Jones, 2002)
• “48% of Internet users say they can turn to many people for support in a time of need, while just 38% of nonusers report they have a large social network” (Pew, 2000, p. 21)
• “55% of Internet users say their email exchanges have improved their connections to family members” (Pew, 2000, p. 7)
• 60% of college students sampled have met someone via Internet, of which 26% became friendships (Knox et al., 2001)
• 61% of usenet group Ss report developing at least one dyadic personal relationship online, 8% of which were described as a romantic relationship (Parks & Floyd, 1996)
• 63% of newsgroup respondents “had spoken to someone they met via the Internet on the telephone, 56% had exchanged pictures of themselves, 54% had written a letter through the post, and 54% had met with an Internet friend in a face-to-face situation, tending to meet an individual an average of eight times” (McKenna et al., 2002, p. 17)
• “66% of Internet users say email has improved their connections with significant friends, 60% of those who email friends report they communicate with significant friends more often now that they use email” (Pew, 2000, p. 7)
• 72% say most of their online communication is with friends, 11% of whom mention communicating with their boyfriend or girlfriend off campus as their most common email activity (Jones, 2002)
• 81% of women and 53% of men indicated they had started an “in-person” friendship via online Matchmaker services; 57% of women and 30% of men indicated they had established a romantic or sexual relationship through online Matchmaker services (Scharlott & Christ, 1995)
• 94% of MOO users reported forming personal relationships with other MOO users, 26% of which were romantic (Parks & Roberts, 1998)
• 90% of teens using IM use it to “stay in touch” with geographically distant friends or friends not in their own school (Lenhart et al., 2005)
Despite the relational uses of CMC, time invested online may in some way come at the expense of face-to-face (FtF) relationship contact or other important aspects of relationships, such as network size, density, or quality of interaction (Cai, 2004). One of the assumptions underlying this concern is that time spent on the Internet is time away from more social or “real” activities. “Almost two thirds of online teens (62%) think that the Internet does keep young people from doing more important things” (Pew, 2001, p. 31). Discontented youths appear to “spend more time using media than their most highly contented peers” (Rideout et al., 2005, p. 24). A study of chat room users found almost 32% “considered that use of the Internet interferes with other activities” (Peris et al., 2002, p. 47). The trade-off may also occur in certain types of relationships. For example, “64% of online teens say they think use of the Internet takes away from the time young people spend with their families” (Pew, 2001, p. 3). A corollary of this reasoning is that Internet use is positively related to loneliness and depression due to lack of more “social” forms or more “real” contact. Some research has shown slight but significant increases in loneliness and depression over time (Kraut et al., 1998), and decreases in social and familial involvement (Kraut et al., 1998; Nie & Erbring, 2000) with increasing Internet use. Many of these studies indicate that online interactions and relationships are in some significant way, “wanting” relative to more traditional media (Cummings et al., 2002).
These studies are far from uncontested. In the Nie and Erbring (2000) study, the vast majority of Internet users reported no effect of time online with time communicating with friends or family. The negative effects were concentrated among a small percentage of (problematic) users (Caplan, 2002; McKenna et al., 2002; Morahan-Martin & Schumacher, 2000), a finding supported by a Pew (2000) survey in which only 8% of Internet users reported they were socially isolated, although over twice as many nonusers (18%) reported they had “no one or hardly anyone to turn to” (p. 21). Furthermore, when Kraut et al. (2002) resampled the respondents from their original study three years later, they found that depression, which in the original study increased with increasing Internet use, actually significantly decreased with increasing Internet use, and loneliness no longer showed a significant association with increasing Internet use (see also Wästlund, Norlander, & Archer, 2001). Amichai-Hamburger and Ben-Artzi (2003) compared the Nie and Erbring hypothesis that Internet use leads to loneliness with the rival hypothesis that lonelier people are more likely to be drawn to use of the Internet, finding more support for the latter. This is consistent with research on Internet motives that found lonely users were generally more sociable online than offline (Morahan-Martin & Schumacher, 2003, p. 665).
The possibility exists that loneliness and depression are related to Internet and CMC use, but in complex ways. This possibility is suggested by a study that found email and Internet use were unrelated to depression at the bivariate level, but were predictive in a more complex path model (LaRose, Eastin, & Gregg, 2001). Other research indicates that the causal path may be reversed, suggesting that those who are lonely or socially anxious are particularly likely to use, and get the most out of, CMC interaction (cf., Patterson & Gojdycz, 2000). McKenna et al.’s (2002) path analysis showed social anxiety and loneliness facilitating expression of one’s true self online, which predicted intimacy and the speed of developing intimacy, as well as the likelihood of using other modes of communication for relational contact. However, other research suggests that when lonely and socially anxious persons reach out through CMC, they engage people less likely to assuage such loneliness. Gross, Juvonen, and Gable (2002, p. 85) found that teenagers “who, on average, reported feeling more daily loneliness or social anxiety in school were more likely to communicate with a stranger than with a friend or close friend after school.” Finally, based on a large representative sample, Wolak et al., (2002, p. 110) found that “a disproportionate number of adolescents with close online relationships were highly troubled, reported high amounts of conflict with their parents, low communication with parents and engaged in high levels of delinquency.” It is unclear whether (a) these problems result from Internet use, (b) youths attempt to compensate for these problems by developing online relationships, or (c) there is a more complex interplay among these factors.
The preponderance of other simple survey research seems to indicate the net effect of the Internet and CMC technologies is, for the majority of users, to expand and enhance relationship networks, specific relational bonds, and, in many cases, the quality of relational interaction. In a separate study by Kraut et al. (2002), increasing use of the Internet correlated positively with indicators of social network size and familial involvement. In another survey, “59% of those who email family members report they communicate more often with significant family members now that they use email,”“66% of Internet users say email has improved their connections with significant friends,” and “60% of those who email friends report they communicate with significant friends more often now that they use email” (Pew, 2000, p. 7). In a later survey, “48% say their use of the Internet improves their relationship with friends; 32% say Internet tools help them make new friends” (Pew, 2001, p. 3). Rideout et al. (2005, p. 14) found that “those young people who spend the most time using media are also those whose lives are the most full with family, friends, sports, and other interests.” At least a priori, then, the average person seems to view CMC as enabling or empowering in terms of relationship management, at least under certain strategic circumstances.
One theory in particular predicts CMC and “leaner” media actually facilitate development of intimacy because of their hyperpersonal affordances (e.g., Walther, 1996). McKenna et al. (2002) hypothesize that CMC creates greater intimacy because of its (1) anonymity, (2) lack of “gating” barriers (e.g., physical attraction cues), and (3) facilitation of locating those with shared interests. These features are predicted to increase self-disclosure and expression of true self. CMC interactions, compared to FtF interactions, appear to display greater self-disclosure and more depth and breadth of questions (Tidwell & Walther, 2002; Whitty, 2002). One survey found that about one-third of people believe it is easier to disclose “frank and unpleasant” things through email (Pew, 2000), which was generally viewed as an important benefit for openness in family and friend relationships.
It follows that “Internet relationships tend to develop closeness and intimacy more quickly than do real-life relationships” (McKenna et al., 2002, p. 20). Participants who interact via the Internet like one another more than those who interact FtF (Bargh, McKenna, & Fitzsimons, 2002). Other research showed that CMC interaction prior to FtF interaction increased enjoyment of the interaction (Dietz-Uhler & Bishop-Clark, 2001). McKenna et al. (2002) found that the relationship between liking and the processes of uncertainty reduction, depth, and breadth of disclosure was greater in CMC interactions than in FtF interactions (McKenna et al., 2002). Walther (1997) found group members given a longer-term identity perceived one another as more socially attractive than short-term identity members. Long-term members with group identity perceived one another as more physically attractive than short-term members with group identity, despite the fact they had never seen one another. Longer-term horizons of interaction apparently allow CMC to amplify social and relational interaction, especially when identification with the group as a whole rather than individual differences among members is salient. In contrast, Bertacco and Deponte (2005) found that the efficiency benefits of email relative to letter-writing tend to detract from the invocation of references to common relational ground (i.e., relationship memories), although egocentrism of messages did not differ across media.
In summary, research demonstrates CMC has infiltrated, supplemented, and perhaps in some cases supplanted, the arsenal of courtship and relationship pursuit, development, and management (Baym et al., 2004). CMC has become an important resource for developing and maintaining familial, friend, romantic, and coworker relationships (Lea & Spears, 1995). Therefore, a thorough understanding of CMC’s role in relationship management becomes an important priority for scholarly agendas.
Toward a Model of CMC Competence
Theories and models are metaphors (Hawes, 1975; McQuail & Windahl, 1993). Theories and models serve as organizing devices for segmenting the symbolic realm of comprehension in a world that is potentially almost infinitely complex. The price paid in exclusion is ideally made up for through comprehension and research progress (Koutougos, 1989; Lakatos, 1970; Papineau, 1989). The metaphorical aspect of theories and models is all the more apparent in the social sciences, where symbolic practices and theorists self-reflectively comprise both object and observer (Ashmore, 1989). Models at moderate levels of abstraction may offer the most useful level (Turner, 1985, 1990) for organizing conceptions of CMC. Therefore, the value of a relatively comprehensive organizing scheme for the CMC literature is intended to outweigh the limitations imposed by its nascent status.
Borrowing from Goffman’s dramaturgical perspective, Ring and colleagues (Ring, Braginsky, & Brajinsky, 1966; Ring, Brajinsky, Levine, & Braginsky, 1967; Ring & Wallston, 1968) suggested a dramaturgical metaphor for conceptualizing an interactant’s (i.e., “actor’s”) performance quality. An actor needs to be motivated to give a good performance. Being motivated, however, is insufficient if the actor does not know the script which is to be enacted or the context in which the script is to be played out. Even motivation and knowledge are still insufficient unless actors have the acting skills requisite to translate their motivation and knowledge into competent action. This metaphor is mirrored in older metaphors of affective, cognitive, and behavioral factors of action (Havighurst, 1957). This metaphor was later imported as a way of organizing research on communication competence (see Rubin, 1983; Spitzberg, 1983; Spitzberg & Cupach, 1984) and elaborated to include the structure and expectancies comprising interaction contexts (Spitzberg & Brunner, 1991). These basic constructs, often expressed in different terminology, are reflected in current models of CMC processes (e.g., Ramirez, Walther, Burgoon, & Sunnafrank, 2002).
Motivation represents the energizing component of competent performance. Negative motivation is represented by constructs such as social anxiety, apprehension, shyness, and even apathy and disinterest. Positive motivation is reflected both by the antitheses of these constructs (e.g., confidence, comfort, communicator involvement, etc.), proactive CMC attitudes (Richter, Naumann, & Groeben, 2000), and by motivating forces such as goals, perceived benefits, motives, gratifications, and uses. Because motivation has both positive and negative facets, there is the possibility of ambivalence, in which the weight of one overpowers the other. Stage fright may disable an otherwise knowledgeable and skilled actor’s performance, and even frightened actors sometimes manage their fears through sheer determination and skill.
Knowledge is represented primarily by cognitive characteristics reflecting such constructs as planning, uncertainty reduction, familiarity, expertise, and other indicators of comprehension. Knowledge can be highly compartmentalized (Smith, Caputi, Crittenden, Jayasuriya, & Rawstone, 1999; Smith, Caputi, & Rawstone, 2000) or a more general dimension of perceived ability (Potosky & Bobko, 1998). A person may know a lot about hardware and software, yet little or nothing about how to compose a message sensitive to status differential between sender and receiver. Knowledge can be operationalized through such constructs as self-monitoring, planning, cognitive complexity, and experience.
Skills are the repeatable, goal-oriented behavioral tactics and routines that people employ in the service of their motivation and knowledge. Spitzberg and Cupach (2002) identified over 100 distinct skills in the communication competence literatures. However, they also argued that these skills probably reflect a more parsimonious set of skill clusters and dimensions. Specifically, at the microscopic level, interpersonal skills reduce to four basic skill clusters: attentiveness (i.e., displaying concern for, interest in, and attention to the other person or persons in the interaction), composure (i.e., displaying assertiveness, confidence, being in control), coordination (i.e., displaying deft management of timing, initiation and closure of conversations, topic management, etc.), and expressiveness (i.e., displaying vividness and animation in verbal and nonverbal expression). This typology of skills has been confirmed in a variety of measurement studies (Spitzberg, 1994b; Spitzberg, Brookeshire, & Brunner, 1990).
It is axiomatic that communication competence is contextual (Spitzberg, 2000; Spitzberg & Cupach, 2002). However, surprisingly few studies have attempted to specify a theory of context (cf., Argyle, Furnham, & Graham, 1981; Heise, 1979). One of the reasons context has eluded theoretical specification is its complexity, which is illustrated by the manifold ways in which contexts have been conceptualized. Contexts vary by cultural, chronological, relational, environmental, and functional characteristics (Spitzberg, 2000; Spitzberg & Brunner, 1991). Each of these facets affects communication competence in complex ways, and any attempt to formulate a theory of competence that ignores these facets is necessarily incomplete.
Regarding positive motivations, research shows “personal benefit” of CMC usage is predictive of frequency of use and satisfaction with email (Hunter & Allen, 1992) as well as problematic Internet uses (Caplan, 2002). Relative value of information contributed and technology-specific competence appear to increase a person’s motivations to contribute to an organizational information commons (Fulk, Schmitz, & Steinfield, 1990; Yuan et al., 2005). Extroversion, a trait disposed toward communication, moderates the impact of CMC on loneliness and depression (Kraut et al., 2002; Mazur et al., 2000), and is positively related to amount of Internet usage (Wästlund et al., 2001). Hacker and Steiner (2001) found “comfort” with Internet usage correlated with actual usage. “Approach” and goal-oriented traits, such as expressive and instrumental dispositions, predict computer interest (Bozionelos, 2002), and the value of the medium in facilitating such information needs predicts web usage (Ambra & Rice, 2001). Utz (2000) found that whereas sociability was unrelated to relationship development via CMC, skepticism toward CMC as a mode of relationship formation was negatively related to relationship development through CMC. Gratifications, or benefits, sought through web use (e.g., pastime, entertainment, relaxation, escape, excitement, companionship) predict actual web use (Perse & Ferguson, 2000), although they may also represent the rationalized reasons for pathological use or Internet addiction (Morahan-Martin & Schumacher, 2000). Perse and Ferguson (2000) unexpectedly found computer access was negatively related to web use, suggesting motivation is necessary to stimulate actual utilization of CMC. However, Hacker and Steiner (2001) found that opportunities to use the Internet correlated significantly with usage.
Séguin-Levesque, Laliberté, Pelletier, Blanchard, and Vallerand (2003) are among the few to have formulated a dual motivation approach to Internet motivations. They distinguish between intrinsic motivations and extrinsic motivations. Intrinsic motives emerge from one’s own values and self-concept, leading to freely chosen activity, which is labeled harmonious passion. Extrinsic motives emerge from participation in interesting activities that are inconsistent with self, leading to a sense of compulsion rather than freely chosen activity. These motives belong to a cluster of motives considered obsessive passion. Both motives were significantly correlated with hours per week on the Internet (.30, .33, p < .01, respectively), but only obsessive passion was positively correlated with relational conflict (r= .35, p < .01) and negatively correlated with relational satisfaction (r=−.30, p < .01).
Thus, although there are some obvious inconsistencies in the research record, there seems to be a broad cluster of motivational constructs suggesting the important role that motivation plays in predicting the use and success in using CMC technologies. CMC motivation is defined here as the ratio of approach to avoidance attitudes, beliefs, and values in a given CMC context.
In general, it seems reasonable to expect that the more knowledgeable a person is with CMC, the more motivated the person will be to use CMC. Conversely, the more motivated someone is to use CMC, the more knowledgeable the person should become. Therefore, there is a feedback loop between these constructs, despite their distinct conceptual boundaries. CMC self-efficacy reflects this overlap. Computer-Mediated Communication self-efficacy is the belief in one’s ability to use CMC effectively, although it has also been defined as an “expectation of mastery” (Beckers & Schmidt, 2001). Research shows Internet self-efficacy is predictive of Internet use, email use, and Internet experience (Eastin & LaRose, 2000; Fang, 1998; LaRose et al., 2001).
Another intersection of knowledge is with the multidimensional constructs of familiarity, expertise, use, and literacy (LaLomia & Sidowski, 1990; Smith et al., 1999; van den Hooff, Groot, & Jonge, 2005). As CMC technology use increases, the more knowledge and skills should increase. Knowledge consists of both content and procedural forms of knowledge (Greene, 1997). Content knowledge is an understanding of the “what” of communication: topics, rules, concepts, and so forth. Procedural knowledge is comprehension of the “how” of communication; how content knowledge can be applied. It is analogous to the difference between knowing the content of a joke versus knowing how to tell it. CMC use and experience, therefore, represent a confluence of both content and procedural knowledge as well as skills (Smith et al., 1999). It is not surprising, therefore, that computer use is positively related to Internet skill over time (Kraut et al., 2002). Hunter and Allen (1992) likewise found “ease of learning” was positively related to email satisfaction and usage frequency. Perse and Ferguson (2000) found computer expertise and experience predicted web use. Markey and Wells (2002) found that chat room experience predicted judges’ liking of chatroom behavior.
Knowledge of CMC can also be obtained through the use of online information-seeking strategies (Ramirez et al., 2002). Such strategies represent a confluence of knowledge and skills, in that goal-oriented tactics are performed to acquire knowledge that will in turn facilitate knowledge and competence. In short, there is a complex of constructs that index knowledge of CMC that is likely to be a central component of competence in the computer-mediated domain of interaction. CMC knowledge is defined here as the cognitive comprehension of content and procedural processes involved in conducting appropriate and effective interaction in the computer-mediated context.
Conceptualizing CMC competence as a function of motivation and knowledge indicates that CMC motivation provides the impetus for more skilled CMC and that CMC knowledge provides the content and procedures for implementing these motives. Motivation and knowledge may at times be merely summative, but they may also interact in certain ways. That is, a person high in both may be significantly more competent than someone only moderate or low on one or the other. As such, these concepts lead to the following propositions:
1CMC motivation is positively related to CMC knowledge.
a. CMC anxiety is negatively related to CMC knowledge.
b. CMC efficacy is positively related to CMC knowledge.
2CMC motivation and knowledge provide unique and interactive effects in predicting CMC competence.
If structural characteristics of the medium affect the expression of interpersonal skills, it is less understood if such skills are directly translatable to the CMC context (Hutchby, 2001). What is “listening” in regard to e-mail? What is “talk time” in regard to email? Such questions suggest interpersonal skills may be transformed or irrelevant rather than merely moderated by CMC. However, Morreale et al. (2001) speculate that basic interpersonal skills are either directly translatable or have close analogues in the CMC context. Attentiveness, or other-orientation, reflects the extent to which interest, concern, and attention are shown to the other interactant(s).
Attentiveness can be displayed in CMC through a variety of tactics, including the degree to which topics initiated by others are taken up in one’s own CMC message content, use and appropriateness of questions, social support and comforting sophistication of message content, and politeness and appropriateness of message content. Pratt, Wiseman, Cody, and Wendt (1999), for example, found interactants modulated the depth of their questions over the stages of the relationship in CMC interactions, suggesting a sensitivity to the appropriateness of interrogative strategies. Similarly, Bunz and Campbell (2004) found that responders to emails with politeness cues responded more politely, indicating an adaptation to the sender. CMC users also employ questions of greater depth than FtF interactants (Tidwell & Walther, 2002, p. 331), suggesting an adaptation to the medium. Rouse and Haas (2003) found that chatroom use of compliments correlated with observer-rated judgments of extraversion (r= .51, p < .01) and openness to experience (r= .42, p < .01) and conscientiousness (r= .24, p < .05).
Composure is displayed in CMC through avoiding cues of uncertainty such as the use of linguistic qualifiers in message content, the proportion of valenced opinion expression of message content, the use of directives and imperatives relative to inquiries or neutral language content, the use of compliance-gaining tactics, and perhaps task or topical redirection and topic initiations. Many linguistic indicators of gender and power are likely to reflect composure as well (e.g., Herring & Martinson, 2004). Assertiveness could also be viewed as a proxy for composure (see Castellá et al., 2000), presuming it is differentiated from aggressiveness.
Composure, which is more of a self-promotional skill, is likely to be delicately balanced in relation to attentiveness, which is more of an other-promotional skill. Such dialectical tensions do not necessarily represent fundamental incompatibilities (Spitzberg, 1993, 1994a). Yet, to date, there is relatively little research directly relevant to indices of composure in CMC interaction. Rouse and Haas (2003) coded the use of self-denigrating or self-depreciation comments in chat space (e.g., “I really suck at this game”), which might be a proxy, albeit a somewhat ambivalent one, for self-confidence. This behavior predicted judges’ ratings of the communicator’s extraversion (r= .53, p < .01) and openness to experience (r= .56, p < .01).
Coordination, or interaction management, skills can be displayed via CMC through the deft management of the number of messages, the length of messages, the rapidity of response to others’ messages, and the content and task relevance of responses. Coordination is likely to be closely aligned with computer-email-web fluency (Bunz, 2004) and is similar to many of the process effects attributed to the interactivity of media, such as navigation control, pace control, rapidity, and responsiveness (Burgoon et al., 2000; Burgoon et al., 2002; Sohn & Lee, 2005). For example, rapidity of response predicts interpretation of affection depending on task versus socioemotional content and time of day that messages are sent (Walther & Tidwell, 1995). Rouse and Haas’ (2003) study found the number of irrelevant comments made in chat space predicted judges’ ratings of extraversion (r= .45, p < .01), openness to experience (r= .35, p < .01), and conscientiousness (r= .34, p < .01).
Expressiveness skills can be displayed in CMC interactions through the use of emoticons and similar paralinguistic features of message content, the use of humor, and even the depth and breadth of self-disclosure (Castellá et al., 2000; Whitty, 2003). For example, CMC users employ greater proportions of self-disclosure and questions than FtF interactants (Tidwell & Walther, 2002). Emoticons apparently attenuate the perceived hostility of mild-to-moderately antagonistic messages, but increase the perceived hostility of highly antagonistic messages (Thompson & Foulger, 1996). Flaming may reflect a dark side of expressiveness, as well as of attentiveness (O’Sullivan & Flanagin, 2003). The use of paralanguage is correlated to the amount of time spent engaging in MUD interactions, as well as the level of development of online friendships (Utz, 2000). In Rouse and Haas’ (2003) study, the sheer number of contributions made in chat space predicted judges’ ratings of extraversion (r= .57, p < .01) and openness to experience (r= .43, p < .01). Use of humor, another potential indicator of expressiveness, also predicted judges’ ratings of neuroticism (r= .37, p < .01) and extraversion (r= .36, p < .01). A converse to expressiveness is lurking (Preece, Nonnecke, & Andrews, 2004), in which computer users enter a chat space and observe but do not participate.
In summary, it appears that skills in the nonmediated context are relatively translatable to the mediated context, allowing for certain structural constraints of the medium. Burgoon et al. (2002; Burgoon et al., 2000) argue that these constraints merely produce an upper boundary on the principle of interactivity, which further suggests the functional equivalence of FtF skills to the CMC context. Direct comparisons suggest that people find the perceived quality of Internet-based interaction lower than FtF or telephone interaction (Baym et al., 2004). Therefore, it becomes important to identify the skills entailed in compensating for media-based constraints. Extensive research indicates that four clusters represent a relatively comprehensive typology of FtF interpersonal skills: attentiveness, composure, coordination, and expressiveness (Spitzberg, 1994b; Spitzberg & Cupach, 2002).
If CMC competence, like FtF competence, is a function of attentiveness, composure, coordination, and expressiveness skills translated into the mediated context, then the following propositions extend from the motivation, knowledge, and skills model.
1CMC motivation is positively related to CMC skills (i.e., attentiveness, composure, coordination, expressiveness).
2CMC knowledge is positively related to CMC skills (i.e., attentiveness, composure, coordination, expressiveness).
Following the five typological facets of context identified by Spitzberg (2000; Spitzberg & Brunner, 1991), CMC interaction is expected to vary based on cultural, chronological, relational, environmental, and functional features. Culture consists of patterns of behavior, attitude, belief, value, and ritual transmittable across generations. These patterns coalesce in variables of nationality, ethnicity, race, religion, and gender, to name a few. While there has been little research on many of these comparative, intercultural, or cross-cultural foci (cf. Brosnan & Lee, 1998; Hart, 1998; Rice, D’Ambra & More, 1998; Rosen & Weil, 1995), at least one factor has stimulated its share of research: gender.
The chronological facet of context has been studied in a wide variety of ways. At a very macro level, age and developmental changes reflect the influences of time within the individual, as well as cohort effects over time. Thus, for example, teenagers have been found to react to CMC usage somewhat differently from adults. Kraut et al. (2002) found that as Internet use increased, teenagers increased their available social support and family communication, whereas adults increased their FtF interactions with friends and family and their closeness with distant relatives. At the more micro level, the chronological dimension of CMC is concerned with the timing and sequencing of messages. For example, the medium selected for messages is likely to vary based on time pressure (Bertacco & Deponte, 2005; Sitkin et al., 1992; van den Hooff et al., 2005). Walther and Tidwell (2002) found time of day interacted with function (task vs. socioemotional) to influence the attributions people made to email messages. Walther, Anderson, and Park (1994) found that as the time constraint of the CMC interaction “relationship” increases, task orientation of the message exchanges tends to become more prominent, whereas more unrestricted time constraints, in which future relations are contemplated, produce more socio-emotional message exchanges and attraction. Walther (1997) found that short-term groups tended to view their communication as less intimate and less socially attractive than long-term groups. Hollingshead et al. (1993) found that differences between FtF and CMC tend to disappear over time as a group acclimates to the media, but these differences can be reintroduced as changes to the media or group are introduced.
The third facet of contexts is the type of relationship among interactants. One of the standard relational questions of CMC is whether such mediated relationships are somehow different qualitatively from “real life” (RL) relationships. Peris et al. (2002, p. 47) found that chat room users found their “friendly (70.6%) or romantic cyberrelations (55.6%) just as important as face-to-face relations.” A survey by McKenna et al. (2002) found 84% of respondents “reported that their online relationships were as real, as important, and as close as their non-Internet relationships” (p. 22). Indeed, the Internet-formed relationships were as stable over a 2-year period as FtF relationships in comparable studies (McKenna et al., 2002, p. 22). Similarly, Parks and Floyd (1996) and Parks and Roberts (1998) found typical CMC based relationships showed consistent evidence of being above the midpoint of criteria of relationship development and intimacy. Another study found that people in both CMC and FtF relationships “perceived their relationships as satisfying and as offering opportunity for growth, but realspace respondents considered their relationships as more serious and they expressed greater commitment” (Cornwell & Lundren, 2001, p. 205). As CMC relationships evolve over time, attributional confidence regarding online relational partners approaches greater equivalence with FtF, although “CMC participants felt the setting impaired their ability to get to know their partner … more so than did FtF interactants” (Tidwell & Walther, 2002, p. 338). There is, as yet, relatively little research on how message content changes based on relationship other than the status of the sender relative to the recipient (Markus, 1994).
The physical environment, place, or situational facet of CMC interaction is, in a large part, instantiated by the features of the media themselves. O’Sullivan (2000) views the media of communication as a metacommunicative message in itself. That is, the computers are a prominent feature of the physical environment, as well as the physical constraints of the context. However, features of the media can change in important ways. For example, Burgoon et al. (2002) found proximal mediated contexts (i.e., interactants can see one another interacting on computers, but cannot read each others’ screens while interacting) produce a greater sense of relational connection than nonproximal or distal mediated interactions. The “geographical reach” of the medium appears to influence the selection of email as a form of CMC (van den Hooff et al., 2005).
In the case of CMC, the aspects of the physical environment that have received the most attention are the interactivity of the technology. Most current theories concur on at least one central tenet, that the more interactive, rich, or adaptable a medium is, the more it should facilitate socioemotional, personal, complex, and subtle communication processes. Simple “mass communication media” such as listservs, standard websites, electronic bulletin boards, and so forth, are likely to be competent for simple information transfer. In such contexts, efficient media are likely to be preferred. Efficiency here would reflect time and effort required to compose and send messages relative to the number of recipients receiving the message. In contrast, messages calling for sensitivity to individual concerns are likely to be more competently delivered through media that better represent the breadth and depth of natural FtF interaction. As convergence increases, it seems likely that media will increasingly be adaptable to either mode of interaction (i.e., efficient and interactive on demand). Thus, text messaging increasingly can be directed interactively to a single person or mass mailed to distribution lists. Such adaptability of medium is likely to enhance the competent communicator’s ability to adapt the medium to the context.
Another aspect of the physical context is geographic proximity. Some research suggests that communication technologies are used more to compensate for geographic distance in relationships (Baym et al., 2004). Burgoon et al. (2002) found proximal CMC forms of interaction were perceived as higher in perceived sociability, connectedness, and task attraction.
The final contextual facet is function. Conflicts are different contexts from get-acquainted conversations. Running a task-oriented CMC meeting is a different context from flirting on a computer dating service chat-space (Whitty, 2003). Many research findings are merely suggestive of such functional influences. For example, “compared to face-to-face negotiation, email reduces rapport building” and “increases multi-issue offers” (Thompson & Nadler, 2002, p. 116). Interactants tend to select media in part on the basis of the function of the intended message (Kayany et al., 1996; Markus, 1994). Research on youth indicates that over three-fourths of their online interactions serve “social” functions (Baym et al., 2004). There is some evidence of greater flaming and hostility in mediated contexts than FtF interactions (Walther & Parks, 2002, p. 532), although this may depend in part on whether the relationship context is in-group or out-group (Thompson & Nadler, 2002), and the particular construction of the message (Thompson & Foulger, 1996). Finally, people apparently feel that they can reveal their more frank, unpleasant (Pew, 2000), or “true” selves (Bargh et al., 2002; McKenna et al., 2002), even if CMC tends to be more facilitative of task-oriented interaction than FtF interactions (Walther & Parks, 2002).
Thus far, there does not appear to be a theoretical model that would integrate all the various functions of messages via CMC any more than there is a comparable model for nonmediated interactions. Nevertheless, it seems clear that interaction in the service of different functions is likely to interact with the media of CMC in distinct ways, and that contextual function must be accounted for in any comprehensive theory.
There are at least five contextual facets of interaction, whether CMC or FtF. As such, it seems reasonable to extend the logic of the model thus far to propose that the more CMC skills are adapted to these contextual facets, the more competent the interaction will be.
1Media Factor Propositions:
a. Media interactivity is positively related to CMC competence for socioemotionally and relationally focused functions.
b. Media efficiency is positively related to CMC competence for informationally focused functions.
c. Media adaptability is positively related to CMC competence.
2Message Factor Propositions:
a. Congruence of message content and function with personal functional objective is positively related to CMC competence.
b. Congruence of message task-orientation with contextual and media factors is positively related to CMC competence.
c. Congruence of message openness with contextual and media factors is positively related to CMC competence.
3The more CMC skills are adapted or sensitive to cultural, chronemic, relational, environmental, and functional cointeractant positive expectancies, the more competent the CMC interaction.
Coorientation refers to the degree of correspondence between a sender’s intentions and/or message content and the interpretations of the receiver(s). Appropriateness is the perceived legitimacy or fit of a message to the context. It is related but not isomorphic with conformity, because an interactant may negotiate new contextual rules in the process of violating existing rules. Effectiveness is the degree to which preferred objectives are optimized. It is related to but not isomorphic with satisfaction because an effective choice may be relative when there is no satisfactory response, in which case the least punishing response may be considered effective. Satisfaction is the positive affect associated with the fulfillment of positively valenced expectancies (Spitzberg & Hecht, 1984). Efficiency is the relative economy with which preferred outcomes are achieved. The less time, effort, or resources invested to achieve the same outcome, the more efficient the process. Finally, relational development represents the degree of breadth, depth, intimacy, closeness, commitment, and attraction achieved in a relationship.
CMC users vary their media selection based on their impressions of appropriateness and effectiveness (Rice, 1993; Tidwell & Walther, 2002), and these proximal criteria are likely to be supportive of more terminal goals and objectives. Thus, a reasonably generalizable working typology of outcomes of CMC competence is appropriateness, effectiveness (including task achievement and efficiency), coorientation, satisfaction, and relationship development. Generally, these outcomes should be positively related to CMC competence, yet, in any given context, communicators may strategically sacrifice one or more outcomes for others, especially when the outcomes are perceived to be mutually incompatible.
1Competence outcomes (i.e., appropriateness, effectiveness, coorientation, satisfaction, and relational development) are positively related to one another but not isomorphic.
2CMC motivation is positively related to competence outcomes (i.e., appropriateness, effectiveness, coorientation, satisfaction, and relational development).
3CMC knowledge is positively related to competence outcomes (i.e., appropriateness, effectiveness, coorientation, satisfaction, and relational development).
4CMC skills (i.e., attentiveness, composure, coordination, and expressiveness) are positively related to competence outcomes (i.e., appropriateness, effectiveness, co-orientation, satisfaction, and relational development).
A Theory of CMC Competence
The basic elements of the theoretical model of CMC competence are visually represented in Figure 1. This model proposes that motivation represents the initial energizing process of knowledge search and application, which manifest through the selection of skills that are applied to the selection of media and messages. Certain motivations are better served by certain media features (e.g., a shy person may prefer an online dating system that permits more lurking than participating) and messages (e.g., a high status person may prefer efficiency and task-orientation of message content). Knowledge of the most competent messages and media is searched and selected accordingly and subsequently implemented through the skills of CMC. The messages transmitted through the selected media are filtered through the receivers’ expectations for messages in those media. Those expectancies are products of the receivers’ experiences with CMC and of the receivers’ culture, sense of chronemics, relationship, environment, and the anticipated function of the messages. Through ongoing interaction, these expectancies are fulfilled, violated, or renegotiated, and the product of the message exchange and the degree to which expectancies are fulfilled or violated predicts the outcomes of the process for both the original sender and the cointeractant(s).
Obviously, many of the previous propositions are predicated on prior conceptualizations of interpersonal competence (see Spitzberg, 1994c, 2000; Spitzberg & Brunner, 1991; Spitzberg & Cupach, 1984, 2002), although other models have demonstrated the relevance of similar constructs (e.g., Levine & Donitsa-Schmidt, 1998). To this point, the components of the CMC competence model have been conceptualized largely from an individual differences perspective, but in keeping with the reasoning of summative, compensatory, and interactive effects (Spitzberg & Cupach, 1984), it is assumed that, in general, competent interactants can facilitate the competence of cointeractants. While the reverse may be true (i.e., an incompetent interactant can diminish a normally competent cointeractant’s performance), part of the benefit of competence is the ability to compensate for the incompetence of other(s).
One of the component relationships only alluded to thus far is the issue of congruence. Specifically, Spitzberg and Brunner (1991) predict a valence reversal of competence impressions. When positive expectancies are fulfilled, outcomes are generally positive. When negative expectancies are fulfilled, outcomes are generally negative. These commonsense predictions anticipate main effects for congruence. In contrast, if interactants expect negative outcomes, the most competent response is to violate those expectancies appropriately. Conversely, violation of positive expectancies is likely to produce unpleasant or dispreferred outcomes. These predictions anticipate interaction effects between the valence of expectancy and the valence of response. Contrary to the interaction effects, a recent experiment found that positively valenced email responses were viewed as more competent regardless of the valence of expectancy (Ladwig & Spitzberg, 2005). If replicated, such findings will call for the modification of the expectancies components of the theory, although there is sufficient evidence for the role of expectancies in FtF interaction to retain their theoretical role until further research can be conducted. The other propositions follow from the original model of communication competence or from integration of prior CMC research with the model.
1Congruence of CMC messages with prior positively valenced (contextual, message, and media) expectancies is positively related to competence outcomes.
2Incongruence of CMC messages with prior negatively valenced (contextual, message, and media) expectancies is positively related to competence outcomes.
3Congruence of CMC messages with prior negatively valenced (contextual, message, and media) expectancies is negatively related to competence outcomes.
4Incongruence of CMC messages with prior positively valenced (contextual, message, and media) expectancies is negatively related to competence outcomes.
6As interactant (i.e., sender) pursues outcomes that preference personal effectiveness, coorientation, or satisfaction over appropriateness, the lower cointeractant’s (i.e., receiver) perceptions of sender’s CMC competence, and the lower receiver’s outcomes.
7As mutual CMC motivation, knowledge, and skills increase, mutual relationship development increases.
Preliminary Measure and Test
Measurement development efforts in the CMC context are evolving rapidly (e.g., Ambra & Rice, 2001; Caplan, 2002; Gaudron & Vignoli, 2002; Richter et al., 2000). Research on the CMC competence model is nascent. An a priori measure was developed on the basis of the model in Figure 1 and subsequently revised on several occasions. The original measure was used in a study by Harper (1999). Unfortunately, the data were not analyzed in a manner conducive to drawing conclusions regarding the measure’s reliability or validity. Research was subsequently collected and analyzed in projects by Bubaš (2002, 2005), Bunz (2002, 2003), and Van Slooten and Spitzberg (2002). Although the preliminary measure generally revealed promise, at least two important problems reoccurred across these studies. First, the negatively worded items in the subscales of the measure tended to attenuate the reliability of the scales, especially those scales with few items. Second, the various items designed to measure context, message, and media factors were not as multidimensionally complex as originally anticipated. As a result of these findings, the measure was significantly simplified with the objective of increasing the reliability and parsimony of the overall measure. Measures of related constructs are already available (e.g., Burgoon et al., 2002; Parks & Roberts, 1998). The current measure is at present being prepared for data collection. Preliminary results from a study of an online version in Croatia indicate that when all items are factor-analyzed, four reliable factors emerge that roughly parallel motivation, knowledge, skills, and outcomes (Bubaš et al., 2003).
The potential applications of a model and measure of CMC competence are manifold. For example, it seems reasonable to expect that as CMC competence increases, loneliness, depression, and computer-based stresses and hassles will decrease. Given that CMC competence is correlated with use and experience, it may in fact be positively related to overall risk of cyberstalking victimization (Finkelhor, Mitchell, & Wolak, 2000; Spitzberg & Hoobler, 2002; cf. Wolak et al., 2002), but holding such opportunity costs constant, it seems reasonable to expect that more competent CMC users would be less likely to be victimized than less competent users. As a screening device, a model and measure of CMC competence may be useful in diagnosing those in greater need of earlier intervention in schools and organizations. As the digital divide dilates or dissolves, it becomes increasingly important to understand the factors that enhance users’ abilities to navigate and negotiate the divide’s turbulent currents.
In proposing this theory of CMC competence, I have suggested its nature, function, and scope, as well as its research implications. The theory does not have a primary motivational metaphor, such as the naive scientist (attribution theory), investor (social exchange theory), information processor (uncertainty reduction theory), comparator (sociometer theory), and so on. Instead, motivation, knowledge, skills, context, and outcomes serve as metaphorical vessels into which prior and future research can be functionally ensconced. At some level, it is presumed that there are real, reducible parallels that serve as the substance of motivation, the substance of knowledge, and the substance of skills, which are moderated by real contextual factors in their influence on real outcomes. Collectively, the CMC theory is ontologically consistent with both traditional causal and teleological systems perspectives.
Another presumption of the model is that FtF and CMC interaction are more similar than they are different. Both can be explained by the same general model components, and, in most cases, the components of this model require only minor adaptation to the particular technological features of the context. As such, the parameters of the model are that it is proposed presently for all mediated interpersonal types of communication (thereby excluding traditional mass communication types of contexts in which relatively singular messages are distributed to large, relatively undifferentiated groups of individuals). The primary value of the model is in outlining a heuristic schema for reorganizing much disparate literature into a semantic model that can generate coherent hypotheses.
About the Author
Brian H. Spitzberg is a Professor in the School of Communication, San Diego State University. His research examines the assessment and conceptualization of interpersonal communication skills, as well as topics on the dark side of communication such as jealousy, coercion, violence, stalking, and cyberstalking.Address: School of Communication, San Diego State University, San Diego, CA, 92182-4561 USA
Instructions: We are interested in how people use various computer-mediated communication (CMC) technologies for conversing with others. For the purpose of this questionnaire, please consider CMC to include all forms of e-mail and computer-based networks (e.g., instant messaging, world-wide-web, chat rooms, personal data assistant, electronic bulletin boards, terminal-based video-telephony, etc.) for sending and receiving written messages with other people. For this survey, indicate the degree to which each statement regarding your use of various CMC media is true or untrue of you, using the following scale:
1= NOT AT ALL TRUE OF ME
2= MOSTLY NOT TRUE OF ME
3= NEITHER TRUE NOR UNTRUE OF ME; UNDECIDED
4= MOSTLY TRUE OF ME
5= VERY TRUE OF ME
01I enjoy communicating using computer media.
02I am nervous about using the computer to communicate with others. [R]
03I am very motivated to use computers to communicate with others.
04I look forward to sitting down at my computer to write to others.
05Communicating through a computer makes me anxious. [R]
06I am very knowledgeable about how to communicate through computers.
07I am never at a loss for something to say in CMC.
08I am very familiar with how to communicate through email and the internet.
09I always seem to know how to say things the way I mean them using CMC.
10When communicating with someone through a computer, I know how to adapt my messages to the medium.
11I don’t feel very competent in learning and using communication media technology.
12I feel completely capable of using almost all currently available CMCs.
13I am confident I will learn how to use any new CMCs that are due to come out.
14I’m nervous when I have to learn how to use a new communication technology.
15I find changes in technologies very frustrating.
16I quickly figure out how to use new CMC technologies.
17I know I can learn to use new CMC technologies when they come out.
18If a CMC isn’t user friendly, I’m likely not to use it.
19I know when and how to close down a topic of conversation in CMC dialogues.
20I manage the give and take of CMC interactions skillfully.
21I am skilled at timing when I send my responses to people who email me.
22I am skilled at prioritizing (triaging) my email traffic.
23I ask questions of the other person in my CMC.
24I show concern for and interest in the person I’m conversing with in CMC.
25I can show compassion and empathy through the way I write emails.
26I take time to make sure my emails to others are uniquely adapted to the particular receiver I’m sending it to.
27I am very articulate and vivid in my CMC messages.
28I use a lot of the expressive symbols [e.g., ? for “smile”] in my CMC messages.
29I try to use a lot of humor in my CMC messages.
30I am expressive in my CMC conversations.
31I display a lot of certainty in the way I write my CMC messages.
32I use an assertive style in my CMC writing.
33I have no trouble expressing my opinions forcefully on CMC.
34I make sure my objectives are emphasized in my CMC messages.
35My CMC messages are written in a confident style.
36I am skillful at revealing composure and self-confidence in my CMC interactions.
I choose which medium (i.e., computer, phone, face-to-face, etc.) to communicate based on . . .
37how quickly I need to get a message out to people.
38how much benefit there would be to having the other(s) present face-to-face.
39how lively the interaction needs to be.
40how much access the person I need to communicate with has to the medium.
41how much information is involved in the message I need to communicate.
42how much access I have to the channel or medium.
43how long I need people to hang on to or remember the message.
44how many different uses and forms are needed (e.g., hardcopy, image processing, voicemail, computer language, etc.)
45how personal or intimate the information in the message is.
46how quickly the receiver needs to react to the message.
47the extent to which I need to get some “back and forth,”“give and take,” and interchange of ideas.
48the extent to which I need some creative brainstorming.
49I avoid saying things through that might offend someone.
50I pay as much attention to the WAY I say things as WHAT I say.
51I never say things that offend the other person.
52I am careful to make my comments and behaviors appropriate to the situation.
53I generally get what I want out of interactions.
54I consistently achieve my goals in interactions.
55My interactions are effective in accomplishing what I set out to accomplish.
56I am effective in my conversations with others.
57I get my ideas across clearly in conversations with others.
58My comments are consistently accurate and clear.
59My messages are rarely misunderstood.
60I feel understood when I interact with others.
61I am generally satisfied with my communication encounters.
62I enjoy my interactions with others.
63I feel good about my conversations.
64I am generally pleased with my interactions.
65If I can engage someone in conversation, I can usually get them to like me.
66I come across in conversation as someone people would like to get to know.
67I make friends easily.
68People generally enjoy my company when interacting with me.
69I get a tremendous amount accomplished through CMC.
70My CMC interactions are more productive than my face-to-face interactions.
71I am more efficient using CMC than other forms of communication.
72CMC technologies are tremendous time-savers for my work.
73I rely heavily upon my CMCs for getting me through each day.
74I use computer-mediated means of communication almost constantly.
75I can rarely go a week without any CMC interactions.
76I am a heavy user of computer-mediated communication.
77If I can use a computer for communicating, I tend to.