Parallels between machine learning / statistical learning theory and traditional learning theories?

In reading through machine learning / statistical learning theory literature the emphasis seems to be on minimal development of the philosophical justification and maximal focus on the mathematical machinery. Similarly in traditional learning (Behaviorism, Cognitivism, Constructivism, Humanism) literature there's is plenty of focus on the philosophical justification and case studies.

Is there any well know literature drawing parallels between these two camps or for example, extending traditional learning directly to machine learning/statistical learning theory?