A Constrained Maximization Extension to Incremental Transfer Effectiveness, or, How to Mix Your Training Technologies

Abstract

The incremental transfer effectiveness concept can be extended to a constrained maximization context by replotting the data to form a set of iso-transfer contours and adding constraints to this same graph as binding linear functions. This transformation permits an analytically elegant solution to maximizing transfer of training dynamically constrained by financial, environmental, reliability, or other restricting factors for any number of instructional technologies through application of the Lagrange Multiplier method. Alternatively, the dual problem of finding the minimum value of these constraints can be solved to achieve a specified transfer of training. An example of applying the Lagrange Multiplier method to training is provided and the potential usefulness of mathematical programming techniques noted. This extension is particularly useful in complex training environments involving numerous instructional technologies or frequently changing constraints. In the single instructional technology case, this extension provides additional graphical insight into the trade-offs involved in designing cost-effective training programs.