Do Electronic Technologies Increase or Narrow Differences in Higher Education Quality Between Low- and High-Income Countries?

Abstract

The disruptive technologies of the Internet and computers are changing our world in myriad ways. These technologies are also increasingly being employed in higher education but to what effect? Are the effects on higher education quality measurable, and if so, what is the effect on the traditional gap between high-income and low- to middle-income nations on this score? This theme is pursued in this article, which uses a variety of methods to probe the question. Because great controversy attends the notion of institutional quality, measures differ, and the effect of these technologies on that quality depends to a great extent on the definition being used. Low- to middle-income countries' usage of the Internet and computer technologies lags behind that of high-income countries, but projections indicate they are catching up.

Notes

¹Because a smaller number denotes a higher ranking school.

∗∗∗p = .01.

∗Not statistically significant.

∗∗p = .05.

²Benefits of pursuing a technology follower strategy are addressed in Christensen (2000).

³Not to be confused with the notion of “media richness,” which is a vibrant media and communications research field of its own. See Daft and Lengel (1986) and Trevino, Lengel, and Daft (1987).

⁴Not all lists had more than 50 schools in common, thus it was impossible to calculate a correlation coefficient for this item.

⁵It is interesting that the Gourman listing and the Webometrics listing differ enough on the Top 10 schools to create a negative correlation coefficient, the only one in all of the comparisons that is negative. However, this could happen if the same schools were listed in the Top 10 but their orders were reversed—for example if Harvard is listed as number 1 on one list and number 10 on the other list. Thus, the absolute value of the correlation gives more information about the consensus of the Top 10 than their specific positions.

⁶Reasons for differential long-term adoption levels are discussed in depth in Capshaw (2007).

⁷ Teledensity is defined as the number of phone lines per capita in a country.

⁸As reported by Transparency International's (2004) Corruption Perception Index.

⁹Although these “Course Management Systems” potentially provide a portal for online distance education, they are also often used as a supplement to classroom-based courses at many U.S. institutions.

¹⁰Usually an e-mail address with an institutional tag—such as [email protected] and the ability to access this account through the institutional Web site.

¹¹The process of such Web site development may follow a multitude of models, but one such model that is likely to be prevalent today in some low- to middle-income country institutions is the following: a graduate student or even an undergraduate student who is technologically adept plays a strong role in the initial development of the school's Web site. He or she is limited in this effort in several respects: by the information provided by the institution for inclusion in the Web site, by the hardware and software that he or she uses to initially develop the Web site, by the bandwidth limitations due to the country or institution's infrastructure, by his or her own knowledge and ability, and by his or her eventual departure from the institution through graduation or transfer, often leaving no one to maintain the Web site.