Complete educational cycle, particular in strategically important SMET (science, math, engineering and technology) domain, should adhere to the three cornerstone principles: learn, practice, apply, or LPA. Online education is capable of implementing the corresponding three components at the same extent as its institutionalized traditional school-centric counterpart. The importance of these educational principles is almost axiomatic: for many of us it’s obvious even at the intuitive level. The quintessential question to answer is: what should be the proper allocation matrix between these three? Some numeric estimates are absolutely necessary in order to achieve the proper balanced STEM educational methodology and practice.
1. The first thing to mention is that the allocation matrix is not like something constant, carved in stone, but rather a function of many variables. In a simplified matrix form it could be presented as a function of school grade (g), subject (s) and individual capabilities (i), i.e. |L,P,A| = f (s,g,i), where: L,P,A stands for a percentage of time spent on “learn, practice, apply” activities, correspondingly.
2. The next important thing to mention is the measured complexity of the subjects, which essentially could be considered as an aggregate of two factors: logical (or reasoning) complexity and memorizing complexity. As an example, logical complexity of math learning process is much higher than, for example, of historical studies or mastering the foreign languages: the latter two are heavily based on memorizing of the huge data sets with corresponding high memorizing complexity level.
3. LPA allocation matrix, pertinent to K-12, would vary substantially between the grades. As the general rule: it’s “apply” component could be near zero at early years, but grow substantially at the later middle and especially high-school periods. In order to preserve and extend the US role as the world technological leader, the early participation of high-school students in a real-life scientific and engineering activity should be considered as a high national priority.
4. And last but not least, in order to be the most effective the educational cycle should have the ability to accommodate to the level of individual cognitive and creative capabilities of the K-12 students. Educational system should be able to early detect and promote the highly-talented students in SMET domain, in particular, by implementing a proper |L,P,A| allocation matrix for such individuals. This should be also considered a high national priority. Let’s acknowledge the fact: super-talented US scientists and engineers with entrepreneurial aptitude, like Bill Gates of Microsoft™, couple of Steves of Apple™ (Wozniak and Jobs), Sergei Brin and Larry Page of Google™ and, going back in time, Wrights Brothers, Alexander G. Bell, Thomas A. Edison, Nicola Tesla and other intellectual/entrepreneurial titans, made an unparalleled contribution to the American prosperity, way of living and techno-economic leadership. In order to achieve the goal of implementing individually adjusted |L,P,A|matrix amd complexity levels, online education could be quite handy as the traditional institutionalized public education system has rather limited ability to accommodate such levels of complexity granularity.
5. Going beyond the |L,P,A| allocation matrix, it’s relevant to mention, that traditional K-12 educational cycle is artificially stretched: majority of the students in the US are able to acquire the necessary knowledge and skills within 11 or even 10 years of systemic school education, thus having the opportunity to enter the US labor market at early stage and getting the competitive advantage against their foreign counterparts. At the later stage, they could refer to the continuous “education on demand” model with online education playing the center role.
In practical sense, the empirically found generalized quasi-optimum |L,P,A| allocation matrix for the high school math and science students could look like “40 – 40 – 20”, though, as stated above, the values could vary dramatically depends on the individual student’s capabilities.
Copyright © 2010 Alexander Bell
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