Читать книгу Introduction to Fuzzy Logic - James K. Peckol - Страница 57

Learning by discovery is the antithesis of rote learning. In this paradigm, the learner is the initiator in all five phases of learning discussed earlier. There is no new knowledge in the world since all knowledge already exists and is merely waiting some clever individual to discover it.

According to Carbonell, two basic methods of acquiring knowledge by discovery are available: observation and experimentation. Observation is considered to be a passive approach because the learner collects information by watching a particular event and then later forms a theory to explain the phenomenon. In contrast, experimentation is viewed as active. Here, the process generally involves the learner postulating a new theory about the existence of a particular piece of knowledge and verifying that theory by experiment. In neither case is the possibility of serendipitous discovery excluded.

Discovery, Carbonell proposes, is a three‐step process begun by hypothesis formation. The hypothesis may be either data driven, as is the case for observation, or theory driven as with experimentation. The initial step is followed by a refinement process in which partial theories are merged and boundary conditions are established. Finally, what has been learned and created is extended to new instances.

Clearly, any theory or model of human (or machine) learning must include aspects of each member of the established taxonomy. Today, no comprehensive and unified theory of human learning exists. Only partial theories that attempt to explain portions of the whole of human learning have been developed. Looking back over each of the ideas, we can take away the notion that learning and problem solving are effectively used interchangeably.