The study I report on today was one for which I had high hopes.  The topic, digital equity, is near and dear to me as it was the focus of my dissertation and one of my first major academic publications.  However, after reading the article, Digital Equity: New Findings from the Early Childhood Longitudinal Study, by Sharon Judge, Kathleen Puckett and Burcu Cabuk, I had many critiques.  Mostly, I felt like the authors had certain expectations and wanted to write about a digital divide; however, the data did not ultimately support their hypotheses.  Yet, they highlighted very small conclusions and “buried the lead.”  So, with all due respect to the authors, I’m going to use this article to point out some of my critiques and to surface the lead story, which is that, when properly “measured,”  and despite what most people think, students in high poverty schools have equal or greater access to computers in schools than their wealthier counterparts; schools are leveling the playing field that is unbalanced only beyond the bricks-and-mortar school buildings.

My first critique of the article is that the authors make statements of the following sort:

The problem here is that the last sentence invalidates the first two.  That is, if there are no statistically significant differences, it is simply wrong to suggest that one group is higher or lower than the other.  This is a basic rule of inferential statistics.  Where one group appears higher or lower, without statistical significance, those perceived differences may very well be due to chance, especially where the sample size is as large as the one used in this study.

My second major critique is that the authors highlight their conclusion that “…children attending higher poverty schools had significantly fewer computers and software programs available.” They even include this in their abstract. While that conclusion may be accurate based on some dichotomous dependent variable (e.g. are there any computers in your school?), it is not true when considering other better measures. For instance, how could the authors bury these findings?:

• Students in high poverty schools were significantly more likely (23% vs. 18%) to attend a school with a student:computer ratio of 4:1 or better.
• First-grade children attending higher poverty schools had more adequate computer labs than children attending lower poverty schools (t = 1.97, p < .05)…In addition, higher poverty schools employed significantly more full-time computer specialists compared to lower poverty schools (t = 5.76, p < .001).

Those seem like pretty important conclusions, no?

Or, consider this statement, which resonates most with me and, concerns me most:  “In first grade, higher poverty schools used computers for instructional purpose significantly more for read/write/spell, whereas lower poverty schools used computers significantly more for fun.” In first grade? Really?

You see, these authors highlighted one very minimal finding and failed to emphasize that what they found was that schools have done a good job of leveling the digital playing field that is only (and substantially) unbalanced beyond the bricks-and-mortar school buildings. In fact, in many cases, lower income students have greater access to computers in schools than their wealthier counterparts. The research and policy questions that must be asked now relate more to the last finding I highlighted. That is, the REAL digital divide in education may be the one that exists with respect to use; not amounts of use, but types of use. Do low-income students and/or students of color have equal opportunities to learn with more current, more relevant digital applications? That’s the research and policy question I want explored.

Tags: digital equity, education, equity, research, technology