Family Microeconomics

180 to learn was reported in 65 cases, to play was reported in
57 cases, to browse in 35 cases, and to communicate in 27 cases. Thus, the five indices of child home Internet use in cluded: 1) the continuous variable years of home Internet access and the dichotomous (report ed-unreported) variables of child home In ternet use to 2) learn, 3) play, 4) browse, and 5) communicate.
Family Socioeconomic Characteristics
The parent questionnaire assessed five family characteris tics commonly used to determine socioeconomic status
(Bradley & Corwyn, 2002; Sirin, 2005). Two items queried father’s and mother’s employment status. Approximately
70% of mothers and 96% of fathers were employed, full-time or part-time. Two questionnaire items
The mean educational level of mothers was 4.79 (SD = 0.95) suggesting that many mothers had post-secondary education; the mean educational level of fa thers was 4.45 (SD = 1.02) suggesting that some fathers had post-secondary education. The final socioeconomic item on the questionnaire asked parents to indicate annual family income by selecting one of the following options: < $20 000 = 1, $20 000 to $40 000 = 2, $40 000 to $60 000
= 3, $60 000 to $80 000 = 4, $80 000 to $100 000 = 5, > $100 000 = 6. Annual income for participating families was approximately $60,000 CD (M = 4.07, SD = 1.48).
Table 2 presents a summary of measured constructs which includes: four tests of children’s cognitive development, five indices of children’s home Internet use, and five fa mily socioeconomic
Indicated by adjusted R
2
, children’s online communication, years of home Internet access, and online learning (as reported by parents) accounted for ap proximately 29% of the varia tion in children’s level of expressive language as measured by the WISC-IV vocabulary subtest. Online learning and communicating (reported- unreported) combined to explain 13.5% of the variation in children’s metacognitive planning. Online learning and playing (reported-unreported) combined to explain 10.9% of the variation in children’s auditory memory. Years of home Internet access explained approximately 3% of the diffe rences in children’s visual perception scores. With the exception of visual perception, indices of home Internet use (elements of the techno-subsystem) were better predictors of children’s cognitive development than were family socioeconomic characteristics (elements of the microsystem). Tab le 4
. Stepwise Regression Analysis: Home Internet Use Predicting Child Cognitive Development
Cognitive Score Predictor/s Beta Weight t value R
2
(adj)