In more recent times, though, academic institutions have placed great hope in the possibilities of technology to help cut and lower the rate of rising costs. Such experiments may also help gauge whether pedagogic outcomes merit any cost savings attained. One prominent feature of C-E studies is their intrinsically relative character. If we are to find out whether the use of technology is truly a relevant causal factor in either lowering instructional costs or raising learning outcomes, then such measures must be taken in circumstances that are relevantly similar save for the technology-use intervention. Thus each project requires expertise regarding pedagogic evaluation, costs measurement, and higher education policy studies.
Expertise regarding instructional technology is relevant as well.
A first step in measuring pedagogic outcomes is to decide on the accurate measure of student performance in a course. This requires as broad a range of outcomes measured as is feasible, with a clear vision of performance and behavior domains in the possible outcomes, and a notion of what constitutes a successful outcome. Further, successful project design requires definitions of the total data pool, randomization of selection, and control groups. Finally, before the experiment begins, baseline data is captured on student performances in courses taught without the use of instructional technology. In measuring costs, baseline data is also pertinent.