Technology and Today’s Learners

Resources and equity

Finally, there is some evidence that the level at which students have access to technology and the ways in which technology is used differ with the SES make-up of the student body. Often you will see that the issue of socio-economic status (SES), which is theoretically a function of family income, education and occupation, operationalized in education as a function of whether or not students qualify for “free or reduced” lunches. Eligibility is a function of family income and thus schools with a high proportion of students who qualify for this subsidy are different from schools in which a low proportion of students qualify.

New technologies have the potential to both ease and aggravate existing inequalities. If distributed equally and used well, technology provides opportunities to overcome some disadvantages. For example, access to the Internet provides some relief from an inadequate library. Unequal access and differences in patterns of use can also magnify existing inequities. For example, expecting students to search for Internet resources outside of class and after school places those students without home computers at a significant disadvantage.

The Department of Education data we have been reporting offers the opportunity to compare activity based on differences in the proportion of students who qualify for free or reduced lunches. The extreme categories involve schools in which more than 75% qualify and school in which less than 35% qualify. When reporting on level of use, we have been focusing on what for our perspective would be a negative; I.e., teachers saying students rarely or never use technology. Here, teachers in schools with more low income students report 24% rarely or never use technology while teachers in schools with fewer low income students report 34% rarely or never use technology. You will likely have to read the previous sentence carefully to interpret it correctly. This may seem counter intuitive if you assumed schools with more low income students would make less use of technology.

Some interesting patterns also emerge if the data on categories of classroom use are examined. In the table that follows, we include several of the categories we have already described in this case comparing higher levels of use (sometimes or often) between the two extreme categories of most and fewest students qualifying for a lunch subsidy.

Income Level Typical of Student Body (% receiving subsidy)

The one difference that stands out is the focus on learning or practicing basic skills. There seems to be a clear difference in using technology to focus on the development of basic skills in schools with a higher proportion of students from low income families. It is not possible to say from these data whether this is a general focus of instruction within these schools or whether this is something unique to the way technology resources are used. We might suggest that there is possibly a type of trade-off demonstrated here. The trade-off might be described as technology as tutor (the learn/practice emphasis) and technology as tool (tasks in which students create content based on what they have learned). An emphasis in one area may mean less time is spent in the other area. Again, this is not the only time we will address equity issues, but it would seem there are differences here that should raise some interesting questions. Are the differences in experiences a function of what students need to learn? Are the differences in experiences a function of what we are able to provide different learners?