Definitions or proposed requirements of technological literacy change as technologies and their applications in the workplace and social interaction diffuse and evolve in complex sociotechnical ecologies. An historic problem encountered by technological literacy advocates is this environment of many moving targets, making the specification of technological literacy criteria and objectives in education a very difficult task. Just when the criteria are defined and proposed, the technology evolves and the criteria are rendered obsolete. An example of this challenge can be found in the history of the adoption of computer programming languages. At separate times, it was considered critical that all students in secondary school should be able to program in BASIC, and all undergraduate engineering students be able to write in FORTRAN, and that all business students be able to program in COBOL. These languages are used in only niche environments, if not altogether rare, today, and certainly are not in any way critical skills expected in the common workplace. Some technologies emerge, peak, and whither quickly, i.e., long before the educational need or level can be addressed. Some technologies diffuse over relatively long periods of time, such that it is difficult to target the level and timing of literacy requirements. Still otherwise promising technologies never reach a significant substitution level, and need not be considered, after all, in a literacy criteria study. The establishment of criteria for assessing technological literacy then, now, and in the future, could significantly be better targeted and more effective if trajectories of diffusing technologies and their applications were available. New techniques in forecasting technology change have given fresh perspectives on acceptance criteria and adoption rates of new technology. Quantitative technology forecasting studies have proven reliable in projecting technological and social change using relatively simple models such as logistic growth and substitution patterns, precursor relationships, constant performance improvement rates of change, and identification of anthropologically invariant behaviors. This paper presents quantitative technology forecasts of the emergence, growth and projected future saturation levels of several computationally and numerically intensive analytical technologies - computation fluid dynamics, modeling and simulation, and finite element analysis. The trajectories are compared to the emergence and diffusion of the response of academia to provide curricula and course education in these technologies so that students are technologically literate in the use of these technologies upon graduation to research and industry. The results provide insight into the lead-lag time relationships of these computational technologies and their co-evolved literacy components. General conclusions on the advantages of including technological trajectories in technological literacy criteria development derived from the results of this research are given.
