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Nowak, K. L., Watt, J., and Walther, J. B. (2005). The influence of synchrony and sensory modality on the person perception process in computer-mediated groups. Journal of Computer-Mediated Communication, 10(3), article 3. http://jcmc.indiana.edu/vol10/issue3/nowak.html
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The Influence of Synchrony and Sensory Modality on the Person Perception Process in Computer-Mediated Groups
This study examined the effects of synchrony and the number of cues on the person perception process in computer-mediated communication. One hundred and forty-two participants in groups of three or four engaged in collaboration over five weeks to develop oral reports, using alternate versions of communication systems or meeting face-to-face. Consistent with the hyperpersonal model, those using low cue media felt their partners were more credible, and reported more social attraction, less uncertainty, and more involvement in the interaction than those using high cue media. People interacting with synchronous media felt increased social attraction, self-reported involvement, and certainty. They also felt that their conversations were more effective, although this effect appeared mainly in low cue groups. Results of an exploratory path analysis suggest that future research should focus on causal chains rather than direct effects, and that intervening variables (such as involvement) may be central to our understanding of the effects of communication technology systems.
Several theories of computer-mediated communication have argued that computer media that are able to engage more senses facilitate more satisfying interactions. These technologically-deterministic theoretical perspectives include social presence theory, media richness, and the social context cues hypothesis (Daft & Lengel, 1986; Kiesler, Siegel, & McGuire, 1984; Short, Williams, & Christie, 1976). However, this latter position, which states that lean media systems are inherently not well suited for social interactions, has been widely challenged (for a discussion see Walther, 1996).1 The most persuasive evidence that cue lean media can be used for social interactions comes from actual media use. Cue lean media, including text-based systems, have been used to fulfill a variety of interpersonal goals including forming and maintaining meaningful interpersonal relationships (Becker & Mark, 2002; O'Sullivan, 2000; Parks & Floyd, 1996). The Pew Internet and American Life Project (Madden, 2004) recently reported that email is the communication tool of choice and that it enhances people's sense of connection to key family and friends.
Media Affordances: Synchrony and Geography
An essential element required for fulfilling communication goals is the ability of communicators to coordinate content and realize some level of common ground (Clark & Brennan, 1991). It is important to examine how features of various media could be utilized to fulfill, if not augment, people's ability to realize this common ground and fulfill their interaction goals.
The Impact of Synchrony and Cues on Person Perception in Group Work
The above discussion raises a number of questions about the effects of media characteristics and the extent to which people's preferences for cue rich media influence their perceptions of one another. It is possible, as posited by the efficiency framework, that even though people are able to adapt their communication behaviors to meet the features of cue lean media, they maintain a preference for cue rich media. This use of adapted behaviors may require the communicators to expend more effort, for example spending more time typing than speaking (Clark & Brennan, 1991). However, this does not necessarily mean that there will be a negative influence on the communicators' ability to reach common ground, nor would it necessarily negatively affect the person perception process. The need to adapt their communication process and the greater effort users expend in doing so may lead to the hyperpersonal experience described by Walther (1996). This section considers how number of cues and synchrony may influence the person perception process.
RQ1: What is the effect of number of cues on uncertainty?
Social attraction is an important part of person perception (McCroskey & McCain, 1974). Research has shown that people are more attracted to others when uncertainty has been reduced (Clatterbuck, 1979; Infante, Rancer, & Womack, 1997). It is possible that people will like their interaction partners less when they interact using a cue lean interface, as could occur if the predictions of the efficiency framework affect the person perception process. If increased uncertainty leads to less liking, then asynchronous cue lean media would reduce social attraction. On the other hand, the hyperpersonal model predicted that people would like their partners more following cue lean interactions. Neither theory makes direct predictions about synchrony, but it is likely that synchrony will influence social attraction in the same direction. Therefore, we ask:
RQ3: What is the effect of number of cues on social attraction?
The present study also examines how involved in the interaction people perceive their partners to be, which is an important part of people's perception of the quality of their interaction (Burgoon & Hale, 1987). People's own involvement is likely to affect how involved they feel their partners are as well. The hyperpersonal model argues that people will need to be more involved in the interaction when they adapt their communication behaviors to meet the features of the medium than when they are able to use more intuitive methods that come with richer media, or face-to-face interactions. The efficiency framework does not make a prediction about involvement, but the predictions of the hyperpersonal model requiring increased involvement in interactions using lean media are consistent with this position. It is likely that people's perceptions of their teammates' involvement will be highly correlated with their self-reported involvement. Neither model makes direct predictions about synchrony, although the hyperpersonal model mentions that it is likely to be influential. Therefore, the following questions are asked:
RQ5: What is the effect of number of cues on people's self-reported involvement?
Another important consideration is the extent to which people are perceived to be credible. Credibility refers to the judgments made by the perceiver about the knowledge of their partner (McCroskey, 1971; McCroskey, Hamilton, & Weiner, 1974). The lack of social context cues hypothesis predicts that leaner media induce people to focus more on the task. Whether this enhanced task focus leads to enhanced perceptions of credibility, or amorphous partner perceptions, is unclear. However, the increased involvement predicted by the hyperpersonal model should lead to increased perceptions of credibility in a context where credibility is desirable. It is also possible that people who respond immediately are likely to be considered more credible. This is one of synchronous media's affordances that asynchronous media do not allow. Although people are likely to realize on a conscious level that immediate response is not possible in asynchronous channels, this still may influence perceptions of credibility. Alternatively, the efficiency framework predicts a reduction in social attraction following interactions in asynchronous or cue lean media. If this is the case, then it is likely that people will perceive their partners to be less credible following interactions in either asynchronous or cue lean media. Therefore, the following questions are tendered:
RQ9: What is the effect of number of cues on credibility following a task-based
interaction?
The efficiency framework would argue that even though cue lean media facilitate people's ability to fulfill their goals, they would feel that the conversation was less effective. In contrast, the hyperpersonal model's prediction that people will like their partners more and be more involved in the interaction suggests that these factors may increase people's perception of conversational effectiveness. The same rationale would possibly apply to asynchronous media.
RQ11: What is the effect of number of cues on conversational effectiveness?
Participants Participants were 142 students enrolled in a communication course at a large public university in the eastern United States. The students were randomly assigned to 39 groups of three or four members each. These groups, in turn, were assigned to collaborate using one type of communication medium to complete a class project. The Task All participants did the same task, which was part of the course and worth 20% of each student's overall grade. Students were asked to research and prepare a 12-15 minute oral report, as if it were to be presented to the United States Congress, arguing how to balance privacy and national security. The groups met at assigned times once a week for five weeks and were instructed to discuss the issues and to prepare a final, smoothly flowing oral presentation. The final oral report required each group member to present a portion of the arguments, thus preventing "social loafing." In addition to a course grade for the project, the group that gave the best presentation received a $100 prize. Students in all groups were asked not to discuss the project with their partners outside their assigned medium. The final videotaped oral presentations were evaluated by outside raters. Asynchrony and Synchrony All participants were assigned a time and day of the week to come to a computer lab to participate in this project. Each individual came at the same time and day each week for five weeks. With synchronous groups, all group members were participating at the same time (although they may have been in different locations). Each member of the asynchronous groups was assigned distinct days and times of the week for the duration of the project. No two members of the same asynchronous group participated either at the same time, or during adjacent times. An asynchronous participant would download and review his or her teammates' messages and respond as desired, and that would end the session. The participant would return the following week at the assigned time to repeat this procedure. The Media To disentangle the impact of cues and synchrony on group performance, five different group collaboration conditions were used. Seven face-to-face groups (multiple-cue, synchronous) were used as a reference to four factorial combinations of time mode and cue multiplicity as summarized in Table 1.
Table 1. The four factorial combinations of time mode and cue multiplicity
The asynchronous audio video combination was created to fill in the "missing cell" of the full crossing of time mode with cue richness (see Watt et al., 2002). Eight groups completed their task by using an asynchronous audio-visual group collaboration system known as the Time Independent Collaboration system (TIC), development of which is detailed in Watt et al. (2002). The TIC system allowed users to record messages by using a computer equipped with a microphone and Webcam. Messages were stored in a server database, and presented to users via an interface that allowed them to see the date of message creation, author, and a text subject identification. Measures Upon completion of the group project, self-administered paper and pencil measures were used to operationalize the variables described below. The full set of scale items and whether individual or group means were used are shown in Appendix A. Uncertainty Reduction Uncertainty reduction was measured using seven Likert-type items on a 7-point metric from Clatterbuck's (1979) Attributional Confidence Scale, including how comfortable the participants felt about their ability to predict other group members' values, attitudes, feelings, and emotions. These items achieved a unidimensional inter-item Cronbach alpha reliability of .94. Social Attraction Social attraction was measured using eight Likert-type items on a 7-point metric, based on McCroskey and McCain's (1974) scale. The items measured the extent to which participants felt their partner was pleasant or offensive and whether or not the participant desired a future interaction. These items achieved a unidimensional inter-item alpha of .91. Self-Reported Involvement Self-reported involvement was measured using three Likert-type items on a 7-point metric. These items were revised from indicators of involvement (Burgoon & Hale, 1987) to ask the participants to report their level of involvement in the interaction. These items achieved a unidimensional inter-item alpha of .71. Perceived Partner Involvement For perceived partner involvement, all questions were asked about each group member (meaning each person responded to these items for all of his or her group members). Ten Likert-type items on a 7-point metric were selected from a combination of the indicators for involvement and immediacy (Burgoon & Hale, 1987) after conducting tests of internal consistency and reliability. These items achieved a unidimensional inter-item alpha of .91. Credibility Credibility was measured using seven semantic differential items from McCroskey et al. (1974). These items achieved a unidimensional inter-item alpha of .91. Conversational Effectiveness Conversational effectiveness was measured using nine Likert-type items on a 7-point metric from Canary and Spitzberg (1987). These items achieved a unidimensional inter-item alpha reliability of .83. The research questions were tested with 2-way ANOVAs, examining both main effects of number of cues and of synchrony, and their interaction. The analyses were first done with only the mediated groups, excluding the face-to-face groups. The analyses were then repeated with the face-to-face groups included in the synchronous, high cue cell. The results of the latter analysis added to the power of the tests, but the results did not meaningfully differ from those obtained by examining only the four conditions that were mediated. Even the cell means differed by very small amounts. The results reported below exclude the face-to-face groups and include only the four mediated conditions. RQ1 and RQ2: What are the effects of number of cues and synchrony on uncertainty?
There was a significant main effect for number of cues, F(1,116)=5.84, p<.02, partial eta sq.=.05, and for synchrony, F(1,116)=4.09, p<.05, partial eta sq.=.03, on uncertainty. However, these main effects must be qualified, as there was a significant interaction between cues and synchronicity, F(1,116)=15.32, p<.001, partial eta sq.=.12.
RQ3 and RQ4: What are the effects of number of cues and synchrony on social attraction? There was a significant effect of the number of cues on social attraction, F(1,116)=7.54, p<.01, partial eta sq.=.06. High cue media (M=35.71) provided significantly less social attraction than low cue media (M=39.80). There was also a significant effect of synchrony on social attraction. Synchronous media (M=39.43) provided significantly higher social attraction than asynchronous media (M=36.08) F(1,116)=5.04, p<.03, partial eta sq.=.04. There was no significant interaction between synchronicity and cues. RQ5 and RQ6: What are the effects of number of cues and synchrony on people's self- reported involvement? The effect of number of cues on self-reported involvement was not significant F<1 (M=13.53 for high cue and M=13.86 for low cue media). However, the effect of synchronicity on self-reported involvement was significant, F(1,116)=13.30, p<.01, partial eta sq.=.10. Those using synchronous media reported higher self-involvement (M=14.69) than those using asynchronous media (M=12.70). There was no significant interaction effect on self-reported involvement, F<1. RQ7 and RQ8: What are the effects of number of cues and synchrony on people's perceptions of their partners' involvement? There was a significant effect of number of cues on perceived involvement F(1,116)=9.48, p=.003, partial eta sq.=.08. Those using high cue media perceived less involvement (M=51.22) than those using low cue media (M=55.47). There was no significant effect of synchrony on perceived involvement F(1,116)=3.16, p=.08, between those using synchronous (M=54.57) and asynchronous media (M=52.12). There was no significant interaction of cues and synchrony for perceived involvement, F<1. RQ9 and RQ10: What are the effects of number of cues and synchrony on credibility following a task-based interaction?
There was a significant effect of number of cues on credibility, F(1,116)=8.77, p<.005, partial eta sq.=.07. Those using a lean cue medium rated their partners as more credible (M=40.49) than those in a rich cue medium (M=37.38).
RQ11 and RQ12: What are the effects of number of cues and synchrony on conversational effectiveness? There was no significant difference on conversational effectiveness between those using high cue and those using low cue media F(1,109)=3.93, p>.05. Synchrony had a significant effect on conversational effectiveness F (1,109)=11.50, p=.001, partial eta sq.=.10, However, there was a significant interaction between cues and synchrony F(1,109)=9.37, p<.01, partial eta sq.=.08. Subjects using synchronous low cue media rated conversational effectiveness significantly higher (p<.05 by post hoc Scheffe test, M=53.17) than did subjects in all other experimental groups (asynchronous low cue M=43.82; synchronous high cue M=45.86; asynchronous high cue M=45.38), among which the means did not differ.
The present design and results suggest several implications for conventional theories of CMC, and suggest the importance of examining the relationship between communication technology and behavior in terms of its impacts on fundamental processes, rather than examining simple direct effects.
As with any experiment, there are factors that limit the generalizability of these results. For example, the design required people to work on this project at assigned times. As discussed above, this eliminated a potential advantage of asynchronous media that would have come with being able to use the medium whenever and wherever participants felt like discussing the project.
Exploratory Structural Analysis of Results The ANOVA results discussed above imply a direct link between synchrony and cues and the six outcome variables. To test this implicit assumption, a structural analysis using the AMOS package was conducted. In this analysis, synchrony and cues were the independent variables, which were tested against the six separate dependent outcome variables. As Figure 1 shows, the overall chi-square for this structure was large and significant, indicating that this structure of independent effects does not fit the data. There are clearly interdependencies among the outcome variables that are not captured by multiple independent ANOVAs, and that require explanation.
Figure 1. Structural analysis of ANOVA results
To investigate these, the observed correlations table was examined. The pattern of correlations showed fairly strong relationships of the involvement variables with other perception variables. The other perception variables were only moderately or weakly associated with the synchrony and cues variables, while self-involvement was strongly associated with synchrony. Although not perfect, this pattern of correlations suggested a model in which the involvement variables mediated the effect of the technology mode variables (synchrony and cues) on the other perception variables.
Figure Figure 2. Final model including only significant paths
The overall goodness-of-fit of this model, as measured by the Root Mean Square Error of Approximation (RMSEA), is .07, midway between the desirable value of .05 or less and the unacceptable value of .10 or greater (see Arbuckle & Wothke, 1999). The overall model chi-square is 28.7 with 17 d.f., which differs significantly from the original data at p=.04. This is very close to the desirable significance level of .05 or greater. All structural coefficients in the diagram are significant at p<.01 with the exception of the relationship between self-reported involvement and social attraction, p=.056. This path was retained because it improved the overall goodness of fit of the model. On balance, the structure of the final exploratory model appears to be a reasonably good fit with the observed data (see Table 2).
Table 2. Observed correlations compared to implied correlations from final model
Since this model was developed by empirical observation rather than theoretical deduction, it is possible that its structure is partially due to improbable chance covariation, and thus will not replicate in future tests. An independent replication of this study with new subjects would give the definitive test that might exclude this possibility, and should be explored in future research. However, a partial test of replication can be made with a split-sample test. The original data are randomly separated into two subsamples, each with N/2 observations. These subsamples are used to test the structure of the model. If the structure is a good representation of both the subsamples, it is less likely that the model structure capitalized on extreme (and thus improbable) chance variation, as this variation would likely be attenuated in at least one of the subsets.
Figure 3. Model replicated on Sample Subset 1
Figure 4. Model replicated on Sample Subset 2
These exploratory results indicate that both self-reported involvement and the perception of the involvement of the other group members mediate the effects of synchrony and cues on person perception. In other words, technological factors are only indirectly related to perceptions of the credibility of other participants, conversational effectiveness, uncertainty reduction, and social attractiveness of other group members. Instead, synchrony and cues directly affect the experience and perception of involvement, which then subsequently affect the other perceptions.2
Beyond the theoretical contribution of this research, a major issue raised by the results has to do with how best to approach the study of new media effects. Our analyses show connections between technology variations and person perception, but most importantly they show connections between those moderated by technology's effects on technology-independent processes, such as involvement, which in turn affected distal outcomes. Traditional technologically deterministic "cues-filtered-out" hypotheses of CMC such as social presence theory (Short et al., 1976) have posited rather monolithic relationships between the amount of cues and the quality of social outcomes. These positions have garnered inconsistent support and much refutation over the years (see Walther & Parks, 2002). The present results suggest that conversational processes provide the missing link in technology-behavior relations, refocusing theoretical inquiry on the communication processes affected by artifacts, rather than on their assumed characteristics.
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Items for Collaboration Outcome Measures Uncertainty Reduction (Scale: 1=unable to answer; 7=completely confident). The mean for individual evaluations of all other group members was used in these analyses.
Ability to predict behavior
Social Attraction (Scale: 1=strongly disagree; 7=strongly agree). The mean for individual evaluations of all other group members was used in these analyses.
Could be a friend of mine Self-Reported Involvement (Scale: 1=strongly disagree; 7=strongly agree)
Reverse: I was detached during the conversations Perceived Partner Involvement (Scale: 1=strongly disagree; 7=strongly agree). The mean for individual evaluations of all other group members was used in these analyses.
Partner was willing to listen to me Credibility Scale: 1=strongly disagree; 7=strongly agree). The mean for individual evaluations of all other group members was used in these analyses.
Reverse: NOT of very high intelligence interactions Conversational Effectiveness (Scale: 1=strongly disagree; 7=strongly agree)
Our group meetings were very beneficial
(Ph.D., Michigan State University, 2000) is an Assistant Professor in the Communication Science department, and director of the human computer interaction lab, at the University of Connecticut. Her research focuses on the person perception process and user satisfaction in computer-mediated interactions. She is also interested in design and usability issues involving computer media. See http://www.coms.uconn.edu/hcilab/ for more information.
(Ph.D., University of Wisconsin) is Director of the Rensselaer Social and Behavioral Research Laboratory and Chair of the Department of Language, Literature, and Communication at Rensselaer Polytechnic Institute. His research interests include online marketing communication and distance collaboration technologies.
(Ph.D., University of Arizona) is a professor of communication at Cornell University. His research focuses on the use of communication cues in the management of relationships and their effects, with special emphasis on computer-mediated communication in personal, social, and collaborative work settings. http://www.cmcresearch.org/jw/
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