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Will Online Social Presence be Related to Gender?
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  1. Will Online Social Presence be Related to Gender? Chih-Hsiung Tu, Ph.D. Northern Arizona University Cherng-Jyh Yen, Ph.D. George Washington University

  2. Purposes • Assess the relationship between gender & online social presence empirically • Conclude • Online social presence is not related to gender • Gender cannot serve as an effective predictor of online social presence

  3. Online Social Presence • A vital affective learning factor that influences online interaction (Gunawardena & McIsaac, 2003) • The degree of Feeling, Perception, & Reaction of being connected by computer-mediated communication (CMC) to another intellectual entity (Tu & McIsaac, 2002) • Online SP not supported physical presence

  4. Impacts • High degree of SP will initiate & maintain a greater quantity of interactions & promote deeper interactions (Polhemus, Shih, & Swan, 2001) • SP has positive impacts on cognitive contents (Rourke et al., 2002 & Stacey, 2002) • Lack of SP leads to • a high level of frustration, an attitude critical of the instructor's effectiveness (Rifkind, 1992) • a lower level of affective learning (Hample & Dallinger, 1995)

  5. Interactivity • Collaborative activities in which learners are engaged & the communication styles used by CMC users • Social Context • Constructed from the learners’ characteristics & their perceptions of the CMC environment. 4 Dimensions of SP(Tu & McIsaac, 2002) Social Presence • Online Communication • Refers to the attributes, application, & perception of the language used online. • Privacy • Quality and sense of being secluded from the presence or view of others.

  6. Online Gender Communications • Men tend to dominate the communications in FTF encounters at the expense lower social presence for women • Similar phenomena between men and women were observed in the CMC environment (Blocher & Tu, in press)

  7. Online Gender Communications • Women • Seek harmonious social relationships, social networks, and support to build intimacy and rapport through more social-orientated processes in the social context dimension • Use non-verbal cues to deliver their meaning in online communications & are more adept at decoding non-verbal cues (Briton, & Hall, (1995). • Men • more aggressive, argumentative, and power-oriented (Soukup, 1999) • Work alone online • may conflict with the social communication customary for women • CMC • less able or incapable of delivering non-verbal cues, rendering interactivity between gender communications more complicated.

  8. Participants • Participants: N = 395 • Graduate programs, two four-year universities • Respond to the Computer-Mediated Communication Questionnaire (CMCQ) on a voluntary basis • Female students (n = 278, 70.4%) • Males students (n = 117, 29.6%)

  9. Measurements of Variables • CMCQ (Yen & Tu, 2006) • 24 test items • five-point Liker scale (1: strongly disagree; 2: disagree; 3: uncertain; 4: agree; 5: strongly agree) • Results in the test validation study (Yen & Tu, 2006) • 12 test items were selected to indicate 4 first-order factors • Social context, privacy, interactivity, & online communication • Each respondent would be assigned a total score, ranging from 12 to 60 • Support to the score internal consistency, content validity • The predictor variable, gender, was measured by the test item in the second part of the CMCQ asking explicitly of the gender of the respondent

  10. Data Analysis • Histograms, & descriptive statistics of means, and standard deviations (Hinkle, Wiersma & Jurs, 2003) • A simple regression analysis with the categorical predictor variable (Pedhazur, 1997) • A two-tailed t test of the regression coefficient • Squared multiple correlation coefficient (R2) (Pedhazur, 1997) • Adjusted squared multiple correlation • Assumption of normality was assessed by the normal Q-Q plots • Levene’s test of equality of variance and the scatterplot for the standardized residual scores and the predicted scores of the criterion variable checked

  11. Descriptive Statistics • Online social presence scores male & female groups • Male (n = 117) M 39.230 SD 4.938 • Female (n = 278) M 38.241 SD 5.602

  12. Histograms: M vs. F The histograms of online social presence scores for male & female groups

  13. Normal Q-Q Plot: M vs. F

  14. Homogeneity of variances • Supported by the statistically nonsignificant result in • Levene’s test of equality of variance, F(1, .393) = 1.636, p = .202, & • Configuration of the data points in the scatterplot for the standardized residual scores and the predicted scores

  15. Simple Regression • With Dummy Coding for the Categorical Predictor Variable • Group membership of different gender groups were not statistically significant at the .05 level, t(393) = 1.659, p = .098. • Observed differences between the means of online social presence scores for those two gender groups • not large enough to be deemed as nonzero differences in the population. Accordingly, online social presence was not predictable by gender.

  16. Simple Regression • Squared multiple correlation coefficient, .007 • indicated that there was less than 1% of variation • Value of adjusted squared multiple correlation coefficient: .004. • The results suggested • online social presence was unrelated to gender in the population and were consistent with the results of the aforementioned t test. • Gender couldn’t serve as an effective predictor of online social presence

  17. Discussions • Levels of social presence between genders are not significantly different. • Women perceive online SP equally to men • Gender-related communication style differences indicated that the current “lean” text-based electronic communication systems tend to promote a more direct “report” communication style. • Despite male communication styles may dominate & overpower a women’s ability to communicate, women perceived their online communication styles equally as comfortable as men in this study.

  18. Discussions • Women’s communication styles • may be even more effective than men’s in the CMC venue in certain specific online communication environments (Savicki, Kelley, & Lingenfelter, 1996; Savicki,, Kelley, & Oesterreich, 1998) • Female only groups • described as having high levels of satisfaction because they used more coalition language self-disclosure, and personal opinion statements • Male only groups • demonstrated the opposite style and were labeled “low group development • Both genders to be aware of, monitor, & perhaps strategically utilize communication styles that increase social presence. • Both gender should be empowered & be able to apply different communication styles for different communication purposes

  19. Discussions • Illogical that both genders utilize the same CMC strategies since SP is measured by the perception of the learners. • Additional critical variables should be examined & compared • computer aptitudes, CMC experience, age, & ethnicity • before declaring that gender is an insignificant factor in online communication. • Future studies examine • the multiple relationships between/among these additional variables to attain comprehensive understanding of social presence

  20. Conclusions • Technology may shape human learning in online learning in both genders; however, • Online learners can be empowered by effective online instructional communication to further shape online communication technologies.