Living in an age where technology governs humans in almost every aspect of life, concern over the gap in internet usage in relation to economic and racial differences have consumed policymakers. This is merely because of the conspicuous digital divide where despite the universal benefit resulting from advancement in technology, there are several sectors that are still at a distance from this blessing. One such example is the public schools which is a place reflecting equality, learning and education without disparity on the basis of sex, race and status. In this regard, in order to serve every student, the government started subsidizing the internet rates and school lunch in accordance with the Telecommunications Act of 1996.
Consequently, a study conducted by Goolsbee and Guryan (2003) analyzed the impact of E Rate program in California public schools. Started in 1998, The E-Rate program provides approximately $2.25 billion annual subsidies to schools and libraries to invest upon computers and technology. Goolsbee and Guryan (2003) aimed at finding the extent to which the E-Rate subsidy affected an increase in the rate of internet usage and schools by also examining the way in which spending was being subsidized. Also, they aimed at looking at the widely debated issue of the influence of technology and computers on student performance. For this reason, the following table would provide a brief about the correlation between the variables focused upon in this study:
Correlation is a tool for statistical analysis in order to determine the relationship between two variables. Dependant variable is the one which is of greatest interest for the researcher as independent variables causes a change in the dependant variable. In this regard, the correlation is measured on a scale from -1 to +1 where +1 denotes the strongest positive correlation between the variables. In other words, a positive high correlation means that an increase/decrease in one variable results in a significant increase/decrease in the other. Similarly, a correlation of with a negative sign such as -1 shows an inverse relationship between the two variables which means that an increase in one variable would result in a decrease in the other and vice versa. However, a correlation value between 0 to -.5 or 0 to +.5 depicts a weak and a moderate relationship between the variables. In contrast a value ranging from +/- .5- +/- 1 shows a strong significant correlation between the variables (Johnson & Bhattacharyya, 2006).
For instance, since the main of the article by Goolsbee and Guryan (2003) was to analyze the impact of government subsidy on internet usage in public schools, there is a positive correlation between the two variables as according to the findings, the increase in government subsidies enabled public schools to invest more in information technology. Hence there was an increase in internet usage in the Californian public schools. In contrast, there is a negative correlation between family income and government subsidies for school lunch. This is because of the underlying fact that government provides free/subsidized lunches to only those students who belong to a lower income group. Therefore, a low income background would result in higher school lunch subsidy. This is also important to take into consideration because the federal and state related education programs are made available only for the students who are eligible for subsidized/free lunch. On the contrary, since Goolsbee and Guryan (2003) also evaluated the impact of school investment in information technology on student performance. Results show a minimal correlation between the two variables evident from the test scores of the students. The increase in the subsidies to school for investment in the information technology in classrooms did not result in an increase or improvement in student performance. One reason for this minimal relationship was the low level of teacher comfort level with computer usage. However, Goolsbee and Guryan (2003) were of the opinion that there was a dire need for another future research that would focus upon exploring other reasons such as incorporating technology in curriculum and the qualification of teachers in public schools.
Thus, the digital divide arising because of racial and status difference can be minimized in public schools via government subsidies which will not only provide free lunch to deserving students but will also provide schools with a budget to invest in information technology. However, the research conducted by Goolsbee and Guryan (2003) revealed that internet usage/ information technology in the classroom did not improve student performance because of which there is a need to further explore the issue in depth.
REFERENCES
Goolsbee, D. A., & Guryan, J. (2003). Closing the Digital Divide: Internet subsidies in public schools. Capital Ideas, 5(1), 1-4.
Johnson, A. R., & Bhattacharyya, G. K. (2006). Statistics: Principles and Methods. USA: John Wiley & Sons
