The K-12 educational technology value chain: Apps for kids, tools for teachers and levers for reform

For example, a new generation of younger, computer savvy teachers are now replacing a large cohort of older “baby boom” of teachers; this should lower the costs of technology training than would otherwise be necessary.

According to Gartner Group, Inc., the use of cloud computing is growing, and by 2016 it will increase to become the bulk of new IT spending (Gartner Group Press release October 24, 2013, retrieved August 30, 2014 from http://​www.​gartner.​com/​newsroom/​id/​2613015.

(Major examples of relevant privacy legislation include, the Family Educational Rights and Privacy Act (FERPA) (20 U.S.C. § 1232 g; 34 CFR Part 99, retrieved from (www2.​er.​gov/​policy/​gen/​guid/​fpco/​ferpa) on July 12, 2014; the Federal Trade Commission’s Children’s Online Privacy Protection Act (COPPA), (Title XIII, SEC. 1301–1308) retrieved from (www.​ftc.​gov/​ogc/​coppa1.​htm) on July 12, 2014; and the Federal Communications Commission’s Children’s Internet Protection Act (CIPA) Pub. L. 106–554; Title Xvii--Children's Internet Protection; SEC. 1701–1741) retrieved from www.​fcc.​gov/​guides/​childrens-internet-protection-act on July 12, 4014.

The K-12 system in the United States is very large and diverse and most schools systems are modest sized organizations. In 2007–2008 there were 98,916 public schools, 13,809 public school districts along with an additional 33,740 private schools that made up the K-12 marketplace (Center for Education Reform, K-12 Facts from http://​www.​edreform.​com/​2012/​04/​k-12-facts/​, retrieved August 30, 2014).

Fig. 2 presents a standard version of a diffusion of innovation curve (Bass, 1969; Rogers 2003). It is characterized by a sigmoid function that exhibits very slow growth in during the initial stages of development followed by often rapid increase (depending on the innovation or application) and ending with a leveling off, as the limits of the innovation’s utility are achieved. Concurrent with the diffusion growth curve is a second, inverse sigmoid curve that represents the fiscal and organizational transaction costs associated with introducing and implementing an innovation. In this case, there is a relatively long period where the costs associated with developing a technology’s infrastructure do not decline appreciably. However, as an infrastructure matures, there can follow a relatively rapid decline in the fiscal and transaction costs associated with the innovation. Transaction costs are most likely to decline when a technology is successfully integrated (fully operationalized) into the organizational system(s) it supports, which in this case is the K-12 system. Thus, the slope of the diffusion function is dependent on the financial and transaction cost function, and the slope of the cost function is determined ultimately by how fully the value chain (Fig. 1) is implemented.