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In higher education, the most successful institutions are mission driven (Kuh, Kinzie, Schuh, Whitt,&Associates, 2005). In many instance, however, the decision to place courses online appears to be revenue driven rather than mission driven ( So many students , 2009). In some instances the prevailing motive underlying these revenue driven decisions appears to be greed, that is, the generation of revenue for its own sake. In other instances, the prevailing motive appears to be fear, that is, the fear that not offering online classes will result in a loss of enrollment to other institutions with online courses (Newman, Coultrier,&Scurry, 2004).

The analysis presented in this paper, a conceptual analysis, is an interpretation of a complex real world phenomenon based upon principles that have been established in previous research. Such analyses are common in science when a real world phenomenon is too large or too complex for direct manipulation, such as ocean tides, the movement of plants, or weather phenomena. A number of calculations are presented as part of the analysis. The numbers used in these calculations represent the best or most recent estimates available. Because the specific numbers will vary from institution to institution, our calculations herein are only for illustrative purposes.

The current situation: the use of benchmarking

The decision to offer courses online

In ours and the opinion of other professionals, organizational decision-makers seldom use sound statistical data to make decisions (Carson, Becker,&Henderson, 1998). Instead, they prefer benchmarking, the process of comparing what an organization is doing with what its competitors are doing. Jayne and Rauschenberger (2000, p. 140) noted that, “Executives are fascinated with comparing practices of their own firms with those of others.” Decision makers in higher education are no exception.

Benchmarking can provide important information to decision-makers. It can yield examples of effective practices. Moreover, keeping informed of what competitors are doing is always of value. Copying them, however, may or may not be the best decision. Followed blindly, benchmarking is simply the adult equivalent of, “everyone else is doing it.” Unfortunately, when this process is given the fancy name, benchmarking, organization members are less likely than your mother was to ask, “If everyone were shooting themselves in the foot, would you do it too?”

Decision-making in higher education regarding online instruction is currently dominated by the fact that the number of institutions offering online courses, and the number of students enrolling in these courses, is increasing rapidly (Ashby, 2002). These raw numbers, however, provide an incomplete picture of the demand for online learning. Although educational researchers have a fondness for straight lines, there will certainly be limits to the demand for online education. Raw numbers on growth do not answer such questions as: To what extent do online students represent a new enrollment pool as opposed to being students who would have enrolled in higher education anyway? If a new pool of students is being tapped, at what rate does this pool replenish itself? If the large enrollment growth primarily reflects students who would have enrolled in on-campus classes, institutions will expend considerable resources with the main effect being to allow students to take courses in their pajamas instead of getting dressed to go to class. If the increases in enrollment tap a new pool that has built up over time but that does not replenish rapidly, the result will be the creation of a large, expensive infrastructure to serve a rapidly dwindling population.

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Source:  OpenStax, Ncpea handbook of online instruction and programs in education leadership. OpenStax CNX. Mar 06, 2012 Download for free at http://cnx.org/content/col11375/1.24
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