Transcript online social presence was unrelated to gender in the population

Will Online Social Presence be
Related to Gender?
Chih-Hsiung Tu, Ph.D.
Northern Arizona University
Cherng-Jyh Yen, Ph.D.
George Washington University
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
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 computermediated communication (CMC) to another
intellectual entity (Tu & McIsaac, 2002)
• Online SP not supported physical presence
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)
Interactivity
Social Context
Constructed from the
learners’
characteristics & their
perceptions of the
4 Dimensions of SP
CMC environment.
Collaborative
activities in which
(Tu & McIsaac, 2002)
learners are engaged
& the communication
styles used by CMC
users
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.
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)
Online Gender Communications
•
Women
–
–
•
Men
–
•
more aggressive, argumentative, and power-oriented (Soukup, 1999)
Work alone online
–
•
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).
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.
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%)
Measurements of Variables
•
CMCQ (Yen & Tu, 2006)
–
–
•
Results in the test validation study (Yen & Tu, 2006)
–
–
–
–
•
24 test items
five-point Liker scale (1: strongly disagree; 2: disagree; 3: uncertain; 4: agree;
5: strongly agree)
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
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
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
Histograms: M vs. F
The histograms of online social presence scores for male & female groups
30
50
25
40
Frequency
Frequency
20
15
30
20
10
10
5
Mean = 38.84
Std. Dev. = 5.48834
N = 150
0
30.00
35.00
40.00
Social_Presence
45.00
50.00
Mean = 38.241
Std. Dev. = 5.60198
N = 278
0
20.00
30.00
40.00
Social_Presence
50.00
Normal Q-Q Plot: M vs. F
Normal Q-Q Plot of Social_Presence
Normal Q-Q Plot of Social_Presence
for gender= female
for gender= male
3
4
2
Expected Normal
Expected Normal
2
0
1
0
-1
-2
-2
-3
-4
25
30
35
40
Observed Value
45
50
55
20
30
40
Observed Value
50
60
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
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.
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
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.
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
–
•
Male only groups
–
•
•
described as having high levels of satisfaction because they used more coalition language
self-disclosure, and personal opinion statements
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
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
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.