Technical note What is structured learning theory?

Structured Learning Theory is a radical departure from the current Pavlov‐Watson‐Skinner system. The latter represents learning change as a scalar quantity: structured learning represents learning gain as a vector quantity. The vector is the difference of loadings on a series of ability, personality and motivation factors between a pre and a post learning behavioural equation obtained by factor analysis. A glance at the post‐learning factor pattern matrix, which represents the dynamic lattice (Cattell, 1979), is sufficient to show how the learning has affected not only the given attitude strength but the whole dynamic lattice. That is to say, learning is represented by a complete change in the dynamic lattice, including the use of primary abilities. Thus, Structured Learning Theory links up with the equations in the dynamic calculus —equations dealing with conflict, decision theory and the internal readjustments of subsidiations to primary instincts (Murray, 1938). It is obvious that the complete description of an individual change through a learning experience requires not only a change in the loadings but also in the magnitude of the ability, personality and dynamic factors. This latter is obtainable by the usual estimations of factor magnitudes from the magnitudes of variables. The calculation of two vector changes may seem very demanding to experimenters, but this is the truth of what life learning does. It needs the use of matrix calculations because an individual is normally simultaneously experiencing exposure to several life‐path learnings.