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

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

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.