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Beyond Access: Digital divide, Internet Use and Gratifications Gained
Unformatted Document Text:  R ETHINKING THE D IGITAL D IVIDE 13 subgroup representing the low socio-economic and young. Thus, the significant relationship between comsumptive use and connection gratification ( β = .06, p < .001) in the whole sample analysis is driven by this particular subgroup. Learning Gratification. For the whole sample model, learning gratification was explained by both surveillance use ( β = .27, p < .001) and interaction over the Internet ( β = .07, p < .001). These two types of Internet use explained 8 percent of variance in connection gratification with demographics and basic pattern of Internet use controlled. For the subgroup representing low socio-economic and young people, both surveillance ( β = .23, p < .001) and interactive uses of the Internet ( β = .13, p < .001) were positive predictors of learning gratification with 9 percent of total variance in learning gratification explained. Almost identical pattern was found in the low socio-economic and old subgroup: learning gratification was explained by both surveillance ( β = .28, p < .001) and interactive use of the Internet ( β = .12, p < .001) with 10 percent of total variance explained. In contrast, for the subgroup for high socio- economic and young respondents, surveillance ( β = .30, p < .001) was a single predictor of learning gratification. In this model, 9 percent of variance in learning gratification was uniquely explained by this single factor. Similarly, for the high socio-economic and old subgroup, learning gratification was explained by only surveillance use ( β = .27, p < .001). A total of 8 percent of variance in learning gratification was explained by this factor. Overall, surveillance use of the Internet was the most important predictor of learning gratification across all subgroups. However, interactive uses of the Internet were also significantly related with learning for low socio-economic subgroups, regardless of age. Acquisition Gratification. For the whole sample model, acquisition gratification was explained by both consumptive use ( β = .31, p < .001) and surveillance use of the Internet ( β

Authors: Cho, Jaeho., Zuniga, Homero Gil de., Nah, Seungahn., Humane, Abhiyan., Hwang, Hyunseo., Rojas, Hernando. and Shah, Dhavan.
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background image
R
ETHINKING THE
D
IGITAL
D
IVIDE
13
subgroup representing the low socio-economic and young. Thus, the significant relationship
between comsumptive use and connection gratification (
β
= .06, p < .001) in the whole sample
analysis is driven by this particular subgroup.
Learning Gratification. For the whole sample model, learning gratification was explained
by both surveillance use (
β
= .27, p < .001) and interaction over the Internet (
β
= .07, p < .001).
These two types of Internet use explained 8 percent of variance in connection gratification with
demographics and basic pattern of Internet use controlled.
For the subgroup representing low socio-economic and young people, both surveillance (
β
= .23, p < .001) and interactive uses of the Internet (
β
= .13, p < .001) were positive predictors of
learning gratification with 9 percent of total variance in learning gratification explained. Almost
identical pattern was found in the low socio-economic and old subgroup: learning gratification was
explained by both surveillance (
β
= .28, p < .001) and interactive use of the Internet (
β
= .12, p <
.001) with 10 percent of total variance explained. In contrast, for the subgroup for high socio-
economic and young respondents, surveillance (
β
= .30, p < .001) was a single predictor of
learning gratification. In this model, 9 percent of variance in learning gratification was uniquely
explained by this single factor. Similarly, for the high socio-economic and old subgroup, learning
gratification was explained by only surveillance use (
β
= .27, p < .001). A total of 8 percent of
variance in learning gratification was explained by this factor.
Overall, surveillance use of the Internet was the most important predictor of learning
gratification across all subgroups. However, interactive uses of the Internet were also
significantly related with learning for low socio-economic subgroups, regardless of age.
Acquisition Gratification. For the whole sample model, acquisition gratification was
explained by both consumptive use (
β
= .31, p < .001) and surveillance use of the Internet (
β


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